diff --git a/.claude/settings.local.json b/.claude/settings.local.json new file mode 100644 index 00000000..ce8473a3 --- /dev/null +++ b/.claude/settings.local.json @@ -0,0 +1,19 @@ +{ + "permissions": { + "allow": [ + "Bash(git remote *)", + "Read(//Applications/**)", + "Read(//Users/alspenceramitojr/Applications/**)", + "Bash(pip3 list *)", + "Bash(python3 -c \"import cv2; print\\('opencv ok'\\)\")", + "Bash(python3 -c \"import pyttsx3; print\\('pyttsx3 ok'\\)\")", + "Bash(pip3 install *)", + "Bash(python3 -c \"import cv2, pyttsx3; print\\('deps ok'\\)\")", + "Bash(say -v '?')", + "Bash(pip show *)", + "Bash(pip install *)", + "Bash(python *)", + "Bash(python3 *)" + ] + } +} diff --git a/.cursor/plans/cactus_disk_file_resolution_9ec40360.plan.md b/.cursor/plans/cactus_disk_file_resolution_9ec40360.plan.md new file mode 100644 index 00000000..b47cb4f8 --- /dev/null +++ b/.cursor/plans/cactus_disk_file_resolution_9ec40360.plan.md @@ -0,0 +1,221 @@ +--- +name: Cactus disk file resolution +overview: Fast, local-only file resolution — Gemma 4 via Cactus proposes Spotlight (mdfind) predicates, rule-based gating, bounded refine rounds, then path pick when needed. Structured `[file-resolve]` logging (timings, branch, counts, outcome—no raw transcripts or full paths by default) supports tuning latency and accuracy after the prototype ships. Output merges into intent.slots. +todos: + - id: settings-env + content: Add FILE_SEARCH_*, SPOTLIGHT limits, tight defaults (e.g. max 2 Cactus rounds, small mdfind cap) in config/settings.py + status: pending + - id: mdfind-runner + content: Safe mdfind subprocess helper (no shell, -onlyin from allowlisted roots, -0 parse, cap count); optional predicate sanitization/validation + status: pending + - id: cactus-predicate-loop + content: "intent/file_resolve.py: rules-first loop — Cactus predicate/refine only when rules say refine; avoid optional Cactus judge; minimal prompts" + status: pending + - id: cactus-final-pick + content: Cactus pick only when ambiguous; else deterministic (single hit) or rules; validate against allowed_paths + status: pending + - id: walk-fallback + content: Bounded pathlib walk when mdfind empty, errors, or loop exhausts without confidence + status: pending + - id: wire-main-debug + content: Call enrich after parse_intent in main.py and scripts/debug_local_flow.py + status: pending + - id: tests + content: Unit tests for predicate validation, path validation, mock Cactus/mdfind; walk fallback on temp dirs + status: pending + - id: observability-logging + content: "[file-resolve] structured logs — exit_reason, timings (cactus_ms, mdfind_ms, walk_ms), round counts, result counts; optional VOICE_AGENT_FILE_RESOLVE_DEBUG for predicates" + status: pending +isProject: false +--- + +# Local disk resolution — Cactus-built Spotlight predicates + iteration + +## Current behavior + +- Paths come from [`config/resources.py`](config/resources.py) `FILE_ALIASES` and [`executors/local/filesystem.py`](executors/local/filesystem.py) `find_by_alias`. +- [`orchestrator/orchestrator.py`](orchestrator/orchestrator.py) uses `collected_data.get("resume_path")` first, then `find_by_alias("resume")`. **`resume_path` in `intent.slots` flows through** to `collected_data`. + +## Goal of this iteration + +- **No fixed “resume PDF” predicates only**: **Gemma 4 / Cactus** proposes **Metadata query predicates** (and optional scope) from natural language + structured intent so the agent can target **arbitrary** file-finding tasks (resumes, decks, contracts, images named in the transcript, etc.). +- **Closed loop**: If the first search is empty, too large, or **not promising**, Cactus **refines the predicate** (broader, narrower, different metadata, different `-onlyin` from the allowlist) and **retries**, up to a **small max iteration** count—mirroring “agentic” search without hardcoding per-task recipes. + +## Phasing: prototype first, then tune + +**Recommendation: ship a working end-to-end prototype, then iterate on latency and accuracy with measurements—not the other way around.** + +- **Why prototype first**: Predicate quality, “promising” thresholds, and real `mdfind` behavior on messy disks are **empirical**. You learn faster from a thin vertical slice (resolver + wiring + debug script + a few logs) than from designing advanced optimizations before you know which step dominates (Cactus vs Spotlight vs walk) or where mistakes cluster (bad predicates vs bad picks vs indexing gaps). +- **What to bake in from day one (cheap, not premature optimization)**: Local-only policy, allowlisted `-onlyin`, predicate validation, rules-first gating, caps, and **light timing logs** (`[file-resolve] cactus_ms=… mdfind_ms=…`) so the second phase is data-driven. +- **Second phase**: Tighten prompts, adjust thresholds, merge Cactus calls, template predicates, caching, or different refine strategies—using traces from real transcripts and real machines. + +## Iteration workflow (generic template) + +Use the same rhythm for **any** component you want to improve with an agent: spec → thin slice → measurable logs → golden inputs → change one lever → lock tests. + +**Template (copy for vision planner, STT, orchestrator, etc.)** + +1. **Spec anchor**: One plan or ticket lists scope, non-goals, and exit criteria; update it when you learn something material. +2. **Vertical slice**: End-to-end path that runs on your machine (even if dumb), plus a single debug entrypoint (`scripts/debug_…`, unit test, or `main` flag)—before edge-case completeness. +3. **Stable log prefix + timings**: Choose a grep-friendly prefix (e.g. `[vision-planner]`, `[stt]`) and log `event`, `exit_reason` or outcome, and `timings_ms` for expensive steps so bottlenecks are visible without PII. +4. **Golden inputs**: A short, fixed list of inputs you replay after each change (transcripts, WAV paths, URLs—whatever the component consumes). Same inputs → compare logs and behavior. +5. **One variable per iteration**: When tuning, change one of prompts, thresholds, model choice, or data scope per cycle so regressions are attributable. +6. **Feedback packet for the agent**: What you paste in chat—redacted log lines + expected vs actual + which golden input—without dumping secrets; optional debug env only when needed. +7. **Lock with tests**: Add or extend tests when behavior is correct so refactors do not silently regress; optional branch/commit per iteration. + +**How to “enable” this for another component** + +- Add the log prefix and timing lines when you **start** that work (not after). +- Add a subsection to the relevant plan file, or promote this template once to a repo-wide doc (e.g. `.cursor/rules/iteration_workflow.md` or a short section in `AGENTS.md`) and link to it from feature plans. +- For a given feature, name the golden inputs file or list in the plan so runs are reproducible. + +**Applied here (file resolution)** + +- Prefix `[file-resolve]`; golden transcripts; grep `exit_reason` / `timings_ms`; `VOICE_AGENT_FILE_RESOLVE_DEBUG` for predicates; tests in `tests/test_file_resolve.py` when stable. + +## Latency and local-only policy (fast + private) + +- **No cloud for file resolution**: This stage must **not** call Gemini or any remote API. Use **Cactus CLI only** for text JSON steps (same as [`intent/parser.py`](intent/parser.py) Cactus path). If Cactus is unavailable, fall back to **aliases + rules + walk**, not Gemini. +- **Early exits (microseconds–milliseconds)**: + - If `intent.slots` already contains a valid absolute `resume_path` (or equivalent) and the file exists, **skip** the whole resolver. + - If `FILE_ALIASES` / `find_by_alias` resolves and the user intent clearly maps to a known alias, **use it** before any `mdfind` (configurable: `VOICE_AGENT_FILE_RESOLVER_ALIAS_FIRST=1` default on). +- **Minimize Cactus round-trips** (each `cactus run` is the dominant cost on CPU/ANE): + - **Default `VOICE_AGENT_FILE_PREDICATE_MAX_ROUNDS` to 2** (not 3+) so typical flows do at most **initial predicate + one refine**. + - **Rule-based “promising” gate** first: empty → refine; count above high-water → too broad → refine; count 1 → **done** (no picker); count 2–8 in “sweet spot” → **one** Cactus **pick** if needed; **no** separate Cactus “judge” call—rules decide refine vs pick vs give up (saves one full model pass per iteration). + - **Tiny prompts**: fixed short MD cheat sheet; candidate lists as **basename + parent dir** only; truncate to `FILE_INDEX_MAX_CHARS`; **no** full paths repeated in refine prompts beyond what’s required. + - **Combine operations where possible**: the **refine** prompt can also return the **final choice** if the model returns both `next_predicate` and `chosen_path` when the candidate set is already small—implementation detail to avoid back-to-back Cactus calls on the same round. +- **Spotlight is already fast**: `mdfind` hits the index; keep **per-query result caps** small (e.g. 30–50) so post-processing and prompts stay bounded. +- **Walk fallback is last and bounded**: depth/ignore caps; only run when `mdfind` fails or exhausts rounds—avoid doubling work when Spotlight already returned enough signal. + +## Why Spotlight remains the execution engine + +- **`mdfind`** evaluates predicates against the **Spotlight index** (metadata and often content). The **model does not** need a full directory listing first; it outputs **query strings** the runtime executes safely. + +## Safety and control + +- **Allowlisted search roots only**: Config lists directories (e.g. `~/Desktop`, `~/Documents`, `~/Downloads`). Each `mdfind` invocation uses **`-onlyin `** so results cannot drift to arbitrary volumes unless explicitly configured. +- **No shell interpolation**: Run `subprocess` with `shell=False`, predicate as a **single argv** to `mdfind` (after validation). +- **Predicate validation**: Reject or strip dangerous patterns (newlines, backticks, `;`, subshell risk). Enforce **max length**. Optionally restrict to a **character class** compatible with MDQuery syntax, or use a **two-phase** approach: model picks from **enum buckets** (e.g. “PDF + name contains”, “image + last 7 days”) mapped to **templates**—trade-off between flexibility and safety. **Default in plan: validated free-form predicate** with strict length and charset checks; if too brittle in practice, narrow to template mapping in a follow-up. +- **Caps**: Max **N** iterations (default **2**), max **M** paths per query (e.g. 40–50), max chars for prompts. + +## Proposed pipeline + +### 1. Settings ([`config/settings.py`](config/settings.py)) + +- `VOICE_AGENT_FILE_SEARCH_ROOTS` — comma-separated; each used as `-onlyin` (resolved, must exist or skip). +- `VOICE_AGENT_FILE_PREDICATE_MAX_ROUNDS` — max Cactus refine loops (**default 2** for latency). +- `VOICE_AGENT_FILE_RESOLVER_ALIAS_FIRST` — try `FILE_ALIASES` before Spotlight when applicable (default on). +- `VOICE_AGENT_FILE_MDFIND_MAX_RESULTS` — per-query cap. +- `VOICE_AGENT_FILE_INDEX_MAX_CHARS` — cap for candidate lists in prompts. +- `VOICE_AGENT_FILE_RESOLVER` — master enable/disable. +- `VOICE_AGENT_USE_SPOTLIGHT` — allow disabling `mdfind` (walk-only). + +### 2. `mdfind` runner ([`executors/local/file_index.py`](executors/local/file_index.py) or `spotlight.py`) + +- `run_mdfind(predicate: str, only_in: Path, limit: int) -> list[Path]` +- Use `-0` and split on NUL for paths; truncate to `limit`. +- On non-zero exit or missing `mdfind` binary: return empty and signal failure for fallback. + +### 3. Cactus predicate loop ([`intent/file_resolve.py`](intent/file_resolve.py)) + +**Round 1 — generate initial predicate** + +- **Input**: `raw_transcript`, `IntentObject` (goal, slots, `uses_local_data`), short **cheat sheet** of common MD attributes (`kMDItemContentTypeTree`, `kMDItemDisplayName`, `kMDItemFSName`, `kMDItemFSCreationDate`, etc.) and logical operators allowed in Spotlight queries. +- **Output JSON** (strict): e.g. `{ "predicate": "...", "only_in_root_index": 0, "rationale": "..." }` where `only_in_root_index` picks from the **ordered allowlisted roots** (never a raw path from the model). + +**Execute** `mdfind` for that root + validated predicate. + +**Assess “promising” (rules only — no model)** + +- Empty → refine (if rounds remain) or walk fallback. +- Count above `HIGH_WATER` (e.g. 40) → too broad → one **Cactus refine** only if rounds remain. +- Count 1 → **deterministic**: use that path (validate under root); **no Cactus pick**. +- Count in sweet spot (e.g. 2–15) → **one Cactus pick** prompt with **basenames + parent only**; if over token budget, **random/sample** down to 12 lines before calling Cactus. + +**Refine rounds 2..K** + +- If rules say `refine` and round `< max_rounds`: **one** Cactus call with **previous predicate**, **counts**, **short basename sample** → revised predicate JSON. +- Repeat until rules say stop, `give_up`, or max rounds. + +**Final path selection** + +- **0 Cactus** when exactly one candidate after rules; otherwise **one** Cactus JSON: `{ "chosen_path": "...", ... }` with path ∈ **allowed set** only. + +**If still stuck**: run **bounded walk** under the same roots (depth/ignore caps), pass that list into the same **final picker** prompt, or second predicate attempt with simpler predicate. + +**Aliases**: If everything fails, fall back to `FILE_ALIASES` / `find_by_alias` as today. + +### 4. Wiring + +- After `parse_intent` in [`main.py`](main.py) and [`scripts/debug_local_flow.py`](scripts/debug_local_flow.py): `await enrich_intent_with_resolved_files(intent, transcript)`. +- Populate e.g. `resume_path` for apply flows; generalize slot keys as needed for other `uses_local_data` entries. + +### 5. Tests + +- **Predicate validation**: reject unsafe strings. +- **Path validation**: chosen path ∈ allowed set and exists. +- **Mock**: fake `mdfind` stdout to test loop without macOS. +- **Walk fallback**: temp directory tree. + +### 6. Logging and observability (for iteration after prototype) + +Implement from the first prototype so tuning is evidence-based. Use a single prefix: **`[file-resolve]`** (or `logging.getLogger("yc_voice_agent.file_resolve")` with a handler that keeps the same visible prefix). + +**Always log (structured key=value or JSON lines on one line per event)** + +- **`event`**: `start` | `exit` | `round` | `mdfind` | `cactus` | `walk` | `fallback` +- **`exit_reason`**: `skipped_slot_path` | `alias_hit` | `alias_miss` | `disabled` | `no_cactus` | `single_hit` | `picked` | `refine` | `max_rounds` | `walk_only` | `validation_failed` | `error` (and short human `detail` only when needed) +- **`timings_ms`**: `cactus_total`, `mdfind_total`, `walk_total`, `resolver_wall` (per invocation) +- **`counts`**: `predicate_rounds_used`, `mdfind_calls`, `last_result_count`, `walk_file_count` +- **`outcome`**: `success` | `partial` | `failure` and which slot was set (e.g. `resume_path`) without logging full path unless debug + +**Privacy defaults** + +- Do **not** log full user **transcripts** or **full absolute paths** at INFO. Log **basename** and **root index** (e.g. `root_index=0`) for debugging. +- Log **predicate strings** and **full paths** only when **`VOICE_AGENT_FILE_RESOLVE_DEBUG=1`** (or similar) is set. + +**Per-round `round` event (when iterating)** + +- `round_index`, `predicate_chars` (length only at INFO), `only_in_root_index`, `mdfind_result_count`, `rule_decision` (`refine` | `pick` | `single` | `give_up`) + +**Implementation note** + +- Wrap each `cactus run` and `mdfind` / walk in `time.perf_counter()` deltas; emit one line after each phase so traces are easy to grep. + +**Settings** + +- `VOICE_AGENT_FILE_RESOLVE_DEBUG` — default off; enables predicate text and fuller paths in logs. + +## Data flow (mermaid) + +```mermaid +flowchart TD + parse[parse_intent] + alias[alias_or_valid_slot_path] + c1[Cactus: predicate_JSON] + mdf[mdfind -onlyin] + rules[rules: promising] + c2[Cactus: refine_predicate] + pick[Cactus: pick_if_ambiguous] + walk[bounded_walk_fallback] + slots[intent.slots] + + parse --> alias + alias -->|hit| slots + alias -->|miss| c1 + c1 --> mdf + mdf --> rules + rules -->|refine| c2 + c2 --> mdf + rules -->|one_hit| slots + rules -->|multi_hit| pick + rules -->|give_up| walk + walk --> pick + pick --> slots +``` + +## Optional follow-ups + +- **Template-only mode** for high-security deployments: map Cactus output to a fixed set of predicate templates (less universal, safer). +- **User confirmation** when confidence is low ([`ui/confirmation.py`](ui/confirmation.py)). +- **Aggregate metrics**: if you later add a small on-disk JSONL of `exit_reason` + timings (opt-in), use it to compare prompt/threshold changes across versions. diff --git a/.cursor/plans/disk_layer_orchestrator_integration_2aac001c.plan.md b/.cursor/plans/disk_layer_orchestrator_integration_2aac001c.plan.md new file mode 100644 index 00000000..a4398919 --- /dev/null +++ b/.cursor/plans/disk_layer_orchestrator_integration_2aac001c.plan.md @@ -0,0 +1,106 @@ +--- +name: Disk layer orchestrator integration +overview: Generalize the Spotlight+Cactus file resolver from a single `resume_path` into a role-based `resolved_local_files` map, run resolution at orchestrator startup (or keep a thin duplicate in `main` for clarity), and wire the visual planner plus executor so browser/local actions consume the right paths by key—enabling contextual disk access for multiple goals without hardcoding task-specific layout. +todos: + - id: model-resolved-map + content: Introduce resolved_local_files (role→path), keep resume_path derived for YC compatibility; adjust file_resolve for multi-role + FIND_FILE key + status: completed + - id: orchestrator-hook + content: Call resolver at start of Orchestrator.run; merge into collected_data; upload_file resolves via file_role helper + status: completed + - id: planner-disk-context + content: Add disk_context to visual_planner prompt; document file_role in params for upload_file + status: completed + - id: optional-reveal + content: Add reveal_in_finder action + FilesystemExecutor helper (Phase B) + status: completed + - id: tests + content: Tests for multi-role resolution and orchestrator path selection + status: completed +isProject: false +--- + +# Connect disk resolution to the orchestrator + +## Current state + +```mermaid +flowchart LR + main[main.py] --> parse[parse_intent] + parse --> enrich[enrich_intent_with_resolved_files] + enrich --> slots["intent.slots resume_path only"] + slots --> orch[Orchestrator.run] + orch --> planner[visual_planner.choose_next_action] + orch --> exec["_execute_action upload_file"] + exec -->|"resume_path"| browser[yc_apply_fill] +``` + +- [`intent/file_resolve.py`](intent/file_resolve.py) is **resume-centric**: it gates on `_needs_resume_path()` and always writes `intent.slots["resume_path"]` (even for `FIND_FILE`, which is semantically wrong). +- [`orchestrator/orchestrator.py`](orchestrator/orchestrator.py) never calls the resolver; it assumes upstream filled `resume_path` for `upload_file`. +- [`orchestrator/visual_planner.py`](orchestrator/visual_planner.py) passes `intent_slots` + `collected_data` in JSON to Cactus but has **no explicit "disk summary"** field—paths are easy to miss or conflate. + +## Target shape + +**Single source of truth for resolved paths:** a small map on the intent (or merged into `collected_data` at orchestrator start): + +- `resolved_local_files: dict[str, str]` — **role → absolute path** (e.g. `"resume"`, `"attachment"`, `"deck"`, `"target"`). +- Legacy **`resume_path`** can remain as a **derived convenience**: if `"resume"` exists in the map, set `slots["resume_path"]` for older YC browser code paths, or migrate call sites to `resolved_local_files["resume"]`. + +**Resolver behavior:** + +- Replace `_needs_resume_path` / single output with **file roles to resolve**, derived from: + - `intent.goal`, + - `intent.uses_local_data` (extend usage of tags like `resume`, `attachment`, `document`, …), + - optional parser slots such as `file_hints: list[{"role", "description"}]` (future-friendly). +- For each role, run the **same** pipeline (Spotlight + predicate rounds + pick + refine on low confidence) with a **role-specific transcript hint** (e.g. append `"Role: attachment — user asked: …"`). +- **FIND_FILE**: resolve the user’s query into one path and store under `resolved_local_files["found"]` (or `target`) instead of overloading `resume_path`. + +## Where to hook resolution (orchestrator connection) + +**Recommended:** call resolution **inside** [`Orchestrator.run`](orchestrator/orchestrator.py) **before** the first `choose_next_action`, e.g. `await resolve_local_paths_for_intent(intent, transcript)` which: + +1. Mutates `intent.slots` / attaches `resolved_local_files`. +2. **`state.collected_data.update(...)`** so every planner step sees stable keys: `resolved_local_files`, plus backward-compatible `resume_path` if present. + +**Optional:** keep [`main.py`](main.py) calling the same function for logging UX ("parsed → resolved → execute") or remove duplicate and rely only on orchestrator—pick one to avoid double resolution (guard with `if "resolved_local_files" not in intent.slots` or idempotent resolver). + +## Visual planner: contextual disk access + +- Extend [`_build_prompt`](orchestrator/visual_planner.py) with a **compact, non-huge** block, e.g. `disk_context`: + - list of `{role, basename, parent_folder, age_hint}` — **not** full paths if you want safer logs; full paths stay in `collected_data` for execution only. +- Update the instructions so Cactus knows **`upload_file` must reference which role** (`params.file_role: "resume"`) and the orchestrator resolves to a real path. +- Extend [`ALLOWED_ACTION_TYPES`](orchestrator/visual_planner.py) / `_execute_action` minimally for general tasks: + - **`reveal_in_finder`** (macOS `open -R path`) — safe, useful after FIND_FILE. + - Later: **`attach_to_mail`** or pass `resolved_local_files` into existing Mail flows—only if you add AppleScript support. + +## Executor wiring + +- [`_execute_action`](orchestrator/orchestrator.py): change `upload_file` to resolve path as: + - `params.get("file_role")` → `data["resolved_local_files"][role]`, else fall back to `resume_path` / `resolved_local_files["resume"]`. +- Add small helper `_path_for_file_action(collected_data, params) -> str`. +- [`_run_local`](orchestrator/orchestrator.py) `find_file`: prefer `resolved_local_files` over raw `find_by_alias` when alias map is empty. +- [`executors/local/filesystem.py`](executors/local/filesystem.py) (or `applescript.py`): add `reveal_in_finder(path: str)` using `subprocess` / `open -R`. + +## Parser and schema (light touch) + +- [`intent/schema.py`](intent/schema.py): document `slots` keys for `resolved_local_files` (no strict TypedDict required initially). +- [`intent/parser.py`](intent/parser.py) / rules: optionally emit **file role hints** in `slots` when user says "attach my deck" (e.g. `uses_local_data` includes `document` and `slots["file_query"]` text)—feeds resolver prompts without new goals. + +## Tests + +- Unit: resolver writes multiple keys when mocked; orchestrator `upload_file` picks path by `file_role`. +- Contract: `test_core_contracts` / smoke: intent with `resolved_local_files` only—no crash. + +## Phasing + +| Phase | Scope | +|-------|--------| +| **A** | Data model `resolved_local_files`, refactor `file_resolve` to multi-role, FIND_FILE uses `found` key, orchestrator calls resolver once + merges into `collected_data`, `upload_file` uses `file_role`. | +| **B** | Visual planner `disk_context` block + prompt text + optional `reveal_in_finder` action + executor. | +| **C** | Parser hints + Mail/Calendar attachments (if desired). | + +## Risks / constraints + +- **Token size:** keep planner `disk_context` summarized (basenames + age), not full directory dumps. +- **Double work:** ensure resolver runs once per command (orchestrator-only vs main-only). +- **Privacy:** logs should prefer basename over full path unless `FILE_RESOLVE_DEBUG`. diff --git a/Ali/.gitignore b/Ali/.gitignore new file mode 100644 index 00000000..ec86c3ae --- /dev/null +++ b/Ali/.gitignore @@ -0,0 +1,31 @@ +__pycache__/ +*.py[cod] +*.egg-info/ +.venv/ +venv/ +dist/ +build/ +.env +*.log +.DS_Store +*.wav +*.tmp + +# Node (vendored browser sub-agent) +node_modules/ +package-lock.json.bak +executors/browser/agent/server/dist/ +executors/browser/agent/dist/ + +# Laptop-wide disk index (built locally, never committed) +# Default location is ~/.cache/ali/ which is outside the repo, but protect +# against relative ALI_INDEX_DIR overrides too. +.cache/ +ali-index/ +index.db +index.db-wal +index.db-shm +vectors.bin +vectors_meta.json +profile.json +manifest.json diff --git a/Ali/PLAN.md b/Ali/PLAN.md new file mode 100644 index 00000000..3692c699 --- /dev/null +++ b/Ali/PLAN.md @@ -0,0 +1,138 @@ +# Build Plan — YC Voice Agent +Hackathon: April 18–19, 2026 | Submissions close: 11am Sunday + +--- + +## Timeline + +### Saturday (Day 1) +| Time | What | +|---|---| +| 10am–1pm | Setup, permissions, Cactus orientation, skeleton | +| 1pm–6pm | Core loop: voice → intent → orchestrator → executor | +| 6pm–10pm | Site adapters (YC Apply first), confirmation gate | +| 10pm–2am | Polish demo flow, error handling, recovery | + +### Sunday (Day 2) +| Time | What | +|---|---| +| 9am–11am | Full demo run-throughs, fix blockers | +| 11am | Submissions close | +| 1pm–2pm | Demo presentation | + +--- + +## Build Sequence + +### Phase 0 — Saturday morning (before lunch) +- [ ] All 4 teammates clone repo, confirm Python env works +- [ ] Run `bash scripts/setup_macos_perms.sh` on the demo machine +- [ ] Get Cactus installed, confirm Gemma 4 loads +- [ ] Confirm Chrome persistent context opens to a logged-in session +- [ ] Confirm `osascript` can send a test iMessage + +### Phase 1 — Voice capture (Layer 1) +- [ ] `voice/capture.py` — hold Option key → start recording, release → stop +- [ ] Raw audio bytes written to temp file +- [ ] `voice/transcribe.py` — pipe audio to Cactus/Gemma 4 STT +- [ ] Fallback path: if Cactus STT fails, use `faster-whisper` locally +- [ ] Test: speak "apply to YC" → get transcript string + +### Phase 2 — Intent parsing (Layer 2) +- [ ] `intent/schema.py` — define `IntentObject` dataclass and `KnownGoal` enum +- [ ] `intent/parser.py` — prompt Gemma 4 with transcript, parse JSON response +- [ ] Prompt design: classify goal, extract slots, flag resource needs +- [ ] Test: transcript "apply to YC Fall 2026 using my resume" → correct intent object +- [ ] Fallback: if parse fails, ask user to rephrase (don't crash) + +### Phase 3 — Orchestrator (Layer 3) +- [ ] `orchestrator/state.py` — TaskState object: goal, plan, step_index, collected_data, status +- [ ] `orchestrator/plans.py` — hardcoded plan for `apply_to_job`, `send_message`, `add_calendar_event` +- [ ] `orchestrator/router.py` — given intent, return ordered list of executor calls +- [ ] `orchestrator/orchestrator.py` — run plan, handle step failures, emit state updates +- [ ] Test: intent object → correct plan selected → first step executed + +### Phase 4A — Local executor (Layer 4A) +- [ ] `executors/local/filesystem.py` — named alias lookup (resume, cover letter, etc.) +- [ ] `executors/local/applescript.py` — send iMessage, send Mail, create Calendar event +- [ ] `executors/local/shell.py` — gated shell with allowlist +- [ ] Test: "text Hanzi I'll be late" → iMessage sends (to test number first!) + +### Phase 4B — Browser executor (Layer 4B) +- [ ] `executors/browser/browser.py` — Playwright persistent context, Chrome profile path +- [ ] `executors/browser/adapters/yc_apply.py` — **primary demo adapter** + - Navigate to apply.ycombinator.com + - Map intent slots to form fields + - Upload resume PDF + - Pause before submit → confirmation gate +- [ ] `executors/browser/adapters/linkedin.py` — Easy Apply flow (stretch) +- [ ] `executors/browser/dom_agent.py` — general fallback (stretch/v2) +- [ ] Test: run YC adapter on staging/personal account, confirm form fills correctly + +### Phase 5 — Confirmation gate (Layer 5) +- [ ] `ui/confirmation.py` — modal dialog: show pending action text + Yes/No buttons +- [ ] Voice confirmation: "yes" or "send it" → approve; "no" or "cancel" → abort +- [ ] Wire into orchestrator: all write actions pause here before executing +- [ ] `ui/menu_bar.py` — macOS menu bar icon, push-to-talk button, status indicator + +### Phase 6 — Integration + demo polish +- [ ] `main.py` wires all layers in a loop +- [ ] Full demo flow works end-to-end: voice → YC form filled → confirmation → submit +- [ ] Second demo flow: voice → iMessage sent +- [ ] Error states handled gracefully (no crashes on stage) +- [ ] Status display shows current step in orchestrator + +--- + +## Demo Script (rehearse this) + +1. "Watch — I'm going to apply to YC using just my voice." +2. Hold Option key. Say: *"Apply to the YC Fall 2026 batch using my resume."* Release. +3. Show transcript appears. Show intent object parsed locally. +4. Browser opens, navigates to apply.ycombinator.com, fields start filling. +5. Confirmation dialog: "I'm about to submit your YC application with resume.pdf. Send it?" +6. Say "yes" → submits (or cancel on stage to not actually submit). +7. "Everything that just happened — the parsing, the intent extraction — ran on my laptop. Nothing left my machine." + +--- + +## Risk Register + +| Risk | Likelihood | Mitigation | +|---|---|---| +| Cactus STT unstable | Medium | Whisper fallback ready Day 1 | +| Gemma 4 intent parsing unreliable | Medium | Hardcode 3 demo intents with fallback JSON | +| YC Apply form changes | Low | Test adapter Saturday afternoon | +| Chrome profile path wrong | Low | Config file, test Sunday 9am | +| macOS permission dialogs during demo | High | Grant all permissions Saturday, test reboot | +| Orchestrator infinite loop | Medium | Max steps limit + hard timeout | +| Demo machine ≠ dev machine | Low | All run on single MacBook, no server deps | + +--- + +## Division of Labor (suggestion) + +| Person | Layer | +|---|---| +| Alspencer | Orchestrator + main loop | +| Hanzi | Browser executor + YC Apply adapter | +| Ethan | Voice capture + Cactus/Gemma 4 integration | +| Korin | UI (menu bar, confirmation gate) + demo polish | + +Overlap: everyone can touch intent/schema.py and plans.py — they're the connective tissue. + +--- + +## Key Decisions + +**Push-to-talk over wake word** — wake word is flaky and will die on stage. Option key hold is legible, demonstrable, and debuggable. + +**State machine over agent loop** — every step is inspectable and interruptible. No runaway agents on stage. + +**Site adapters over general DOM agent** — 50-100 lines of Playwright per site is unbeatable for demo reliability. General agent is v2. + +**Hardcoded plans for known flows** — the LLM fills in slots, not the whole recipe. This is what makes v1 reliable. + +**Persistent Chrome context** — no re-login, no cookie setup, no OAuth dance. You drive the browser you're already logged into. + +**Confirmation gate on all writes** — this is not a limitation. It's the feature that makes the agent trustable and makes the demo pauseable. diff --git a/Ali/README.md b/Ali/README.md new file mode 100644 index 00000000..6d1ae5bb --- /dev/null +++ b/Ali/README.md @@ -0,0 +1,353 @@ +# YC Voice Agent + +> "Tell your computer what to do." + +A local-first voice agent that gives your computer hands — in your files *and* in your browser. Built for the [Cactus × YC Gemma 4 Voice Agents Hackathon](https://github.com/cactus-compute/cactus), April 18–19, 2026. + +--- + +## What it does + +You hold a key, speak a command, release. The agent: + +1. Transcribes your voice on-device (Gemma 4 via Cactus, fallback: Whisper) +2. Parses your intent locally — your words never leave your laptop +3. Captures an initial on-device screen observation (screenshot + context), then routes the task to local tools (iMessage, Mail, Calendar, files) and/or the browser (LinkedIn, YC Apply, Gmail) +4. Iterates observe → decide → act → verify with Cactus-assisted action selection +5. Shows you exactly what it's about to do and waits for confirmation for irreversible actions +6. Executes — using your real browser session, your real resume, your real contacts + +**Demo flow:** "Apply to a YC Fall 2026 batch company using my resume" +→ Finds `resume.pdf` on disk → Opens apply.yccompanyx.com → Fills the form → Pauses for your approval → Submits. + +--- + +## Why local-first matters + +The intent layer — the layer that sees your transcribed voice, your resume, your contacts — runs on-device via Cactus + Gemma 4. Your PII never hits a cloud server. + +--- + +## Architecture (Vision-First) + +``` +┌─────────────────────────────────────────────────────────────────┐ +│ User (voice) │ +└───────────────────────────┬─────────────────────────────────────┘ + │ hold Right Shift / menu bar button + ▼ +┌─────────────────────────────────────────────────────────────────┐ +│ Layer 1 — Voice Input │ +│ Push-to-talk audio capture → speech-to-text │ +│ Primary: Gemma 4 voice via Cactus │ +│ Fallback: whisper.cpp / faster-whisper (local) │ +└───────────────────────────┬─────────────────────────────────────┘ + │ raw transcript + ▼ +┌─────────────────────────────────────────────────────────────────┐ +│ Layer 2 — Intent Layer [ON-DEVICE, Gemma 4 via Cactus] │ +│ Input: raw transcript │ +│ Output: structured intent object │ +│ { goal, target, uses_local_data, requires_browser, ... } │ +│ Jobs: classify goal | extract slots | flag required resources │ +│ Does NOT: write Playwright scripts, reason about DOM │ +└───────────────────────────┬─────────────────────────────────────┘ + │ intent object + ▼ +┌─────────────────────────────────────────────────────────────────┐ +│ Layer 3 — Orchestrator [State Machine] │ +│ 0. Observe — always capture initial screenshot/context │ +│ 1. Decide — Cactus visual planner proposes next atomic action │ +│ 2. Act — execute exactly one action │ +│ 3. Verify — re-observe and continue until complete │ +│ 4. Recover — retry | ask user | fallback | abort │ +└──────────────┬────────────────────────────────┬─────────────────┘ + │ local tasks │ browser tasks + ▼ ▼ +┌──────────────────────────┐ ┌───────────────────────────────┐ +│ Layer 4A — Local │ │ Layer 4B — Browser │ +│ Executor │ │ Executor (Playwright) │ +│ • AppleScript / JXA │ │ • Persistent Chrome context │ +│ iMessage, Mail, │ │ (user's real sessions) │ +│ Calendar, Contacts │ │ • Site adapters: YC Apply, │ +│ • Filesystem (resume, │ │ LinkedIn, Gmail, ... │ +│ cover letters, docs) │ │ • General DOM agent fallback │ +│ • Shell (gated) │ │ (accessibility tree) │ +└──────────────┬───────────┘ └───────────────┬───────────────┘ + │ │ + └────────────────┬───────────────┘ + ▼ +┌─────────────────────────────────────────────────────────────────┐ +│ Layer 5 — Confirmation Gate │ +│ Surface pending action → voice or click approval → execute │ +│ "I'm about to submit your YC app with resume.pdf. Send it?" │ +└─────────────────────────────────────────────────────────────────┘ +``` + +--- + +## Project Structure + +``` +YC_Voice_Agent/ +├── voice/ # Layer 1 — audio capture + STT +│ ├── capture.py # Push-to-talk hotkey + mic recording +│ ├── transcribe.py # Cactus/Gemma 4 STT, Whisper fallback +│ └── __init__.py +├── intent/ # Layer 2 — on-device intent parsing +│ ├── parser.py # Gemma 4 via Cactus → intent object +│ ├── schema.py # IntentObject dataclass + known goals +│ └── __init__.py +├── orchestrator/ # Layer 3 — state machine + routing +│ ├── orchestrator.py # Main orchestrator class +│ ├── plans.py # Hardcoded plans for known flows +│ ├── state.py # Task state object +│ ├── router.py # local / browser / hybrid routing +│ └── __init__.py +├── executors/ +│ ├── local/ # Layer 4A — macOS native tools +│ │ ├── applescript.py # iMessage, Mail, Calendar, Contacts +│ │ ├── filesystem.py # Resume/doc lookup by alias +│ │ ├── shell.py # Gated shell executor +│ │ └── __init__.py +│ └── browser/ # Layer 4B — Playwright browser +│ ├── browser.py # Persistent Chrome context setup +│ ├── adapters/ # Site-specific Playwright flows +│ │ ├── yc_apply.py +│ │ ├── linkedin.py +│ │ └── gmail.py +│ ├── dom_agent.py # General DOM agent fallback +│ └── __init__.py +├── ui/ # Layer 5 — confirmation gate + status +│ ├── menu_bar.py # macOS menu bar button (push-to-talk) +│ ├── confirmation.py # Pre-action confirmation dialog +│ └── __init__.py +├── config/ +│ ├── settings.py # Paths, hotkeys, Chrome profile, etc. +│ ├── resources.py # Named file aliases (resume, cover letter) +│ └── known_intents.py # Enumeration of supported goals +├── scripts/ +│ ├── setup_macos_perms.sh # Grant macOS permissions checklist +│ ├── debug_local_flow.py # Parse/plan/execute from transcript or WAV +│ └── test_demo_flow.py # End-to-end demo smoke test +├── main.py # Entry point — ties all layers together +├── requirements.txt +├── .gitignore +└── README.md +``` + +--- + +## Demo Flows (v1) + +| Voice Command | Route | Tools Used | +|---|---|---| +| "Apply to YC Fall 2026 using my resume" | browser | yc_apply adapter + filesystem | +| "Text Hanzi I'll be 10 minutes late" | local | AppleScript → Messages | +| "Send my resume to the job I have open in Chrome" | browser | LinkedIn adapter | +| "Add a meeting with Ethan tomorrow at 3pm" | local | AppleScript → Calendar | +| "Draft a cover letter for the Stripe job and save it" | local | filesystem + shell | + +--- + +## Setup + +### 1. Install dependencies + +```bash +pip install -r requirements.txt +playwright install chromium +``` + +### 2. Configure paths + +Edit `config/settings.py`: +- `CHROME_PROFILE_PATH` — your real Chrome profile directory +- `RESUME_PATH` — path to your resume PDF +- `CACTUS_MODEL` — Gemma 4 model identifier + +### 3. macOS permissions (do this Saturday afternoon before the demo) + +```bash +bash scripts/setup_macos_perms.sh +``` + +Permissions required: +- Accessibility (for hotkey capture) +- Full Disk Access (for file reads) +- Automation: Messages, Mail, Calendar, Contacts + +### 4. Run + +```bash +python main.py +``` + +Hold **Option** (or click the menu bar button) and speak your command. + +On **first launch**, Ali builds a focused content index. The default scope is: + +- `~/Documents`, `~/Downloads`, `~/Desktop` +- `/Applications` (so "open Slack" works) +- **Contacts** (via Contacts.app — the running terminal needs Contacts + permission) +- **Calendar** (reads `.ics` files under `~/Library/Calendars/` — needs Full + Disk Access) +- **Messages** (reads `~/Library/Messages/chat.db` — needs Full Disk Access, + last 365 days by default) + +To widen the filesystem scope to the full home directory: + +```bash +python main.py --full-disk +# or: +ALI_INDEX_FULL_DISK=1 python main.py +``` + +The index lives at `~/.cache/ali/index/` and is reused on subsequent runs +(incrementally — unchanged files are skipped, only new/modified files get +re-embedded). To force a clean rebuild: + +```bash +python main.py --rebuild-index +``` + +…or click **Rebuild Index…** in the menu bar. + +To tune which non-filesystem sources are pulled in: + +```bash +# disable messages only +ALI_INDEX_SOURCES="contacts,calendar" python main.py + +# index none of them +ALI_INDEX_SOURCES="" python main.py + +# shorter history for Messages/Calendar +ALI_INDEX_SOURCE_HISTORY_DAYS=30 python main.py +``` + +With the index in place Ali can answer questions grounded in your files, +entirely on-device via Gemma 4 (Cactus): + +- "Who am I?" → answered from your macOS user info + Contacts Me card. +- "What's my email?" +- "When did I last update my resume?" +- "What does my contract say about termination?" +- "Summarize my notes about OKRs." + +Cloud fallback (Gemini) is opt-in: + +```bash +export ALI_ALLOW_CLOUD_FALLBACK=1 +``` + +--- + +## Safety / Dry Run + +To rehearse the full flow without performing irreversible actions, run: + +```bash +export VOICE_AGENT_DRY_RUN=1 +python main.py +``` + +In dry-run mode, the agent still transcribes, parses, plans, and executes safe steps, +but skips final write actions like sending iMessages, creating calendar events, and +submitting YC applications. + +--- + +## Debugging Without Hotkey + +Use `scripts/debug_local_flow.py` to test transcription + intent parsing + visual +execution loop without running the menu bar listener. + +```bash +# 1) Record from your mic, save WAV, then transcribe + parse +python scripts/debug_local_flow.py --audio --record-seconds 6 + +# 2) Reuse a saved WAV file later +python scripts/debug_local_flow.py --audio debug_recordings/debug_YYYYMMDD_HHMMSS.wav + +# 3) Optionally run the orchestrator too (recommended with dry run) +VOICE_AGENT_DRY_RUN=1 python scripts/debug_local_flow.py --audio --execute --auto-approve + +# 4) Save visual observation artifacts from each observe loop +python scripts/debug_local_flow.py --transcript "Apply to YC using my resume" --execute --observe-dir debug_observations +``` + +By default, microphone recordings are saved under `debug_recordings/`, so you can share +the exact file path when debugging STT/intent behavior. + +--- + +## Local Troubleshooting + +### 1) "This process is not trusted! Input event monitoring will not be possible" + +`pynput` needs macOS Accessibility permission to listen for the push-to-talk key. + +- Open System Settings → Privacy & Security → Accessibility +- Add and enable your terminal app (Terminal / iTerm / VS Code) +- Restart the terminal and rerun `python main.py` + +If you want to debug without hotkey capture first, use: + +```bash +python scripts/debug_local_flow.py --transcript "Text Hanzi I'll be 10 minutes late" +``` + +### 2) Very short captures ("Captured 0.0s", "Too short — ignored") + +- Hold Right Shift a bit longer before speaking +- Verify the active mic line printed at startup, for example: + `[voice] Active mic: #4 "MacBook Air Microphone" (48000 Hz)` +- Switch your macOS input device if the wrong mic is active + +### 3) Cactus intent parse error (`unrecognized arguments: --max-tokens ...`) + +This is a Cactus CLI version mismatch. The code now uses a compatible fallback +invocation, but if you still see this: + +- update cactus to a recent version, or +- use the debug runner to isolate parser behavior: + +```bash +python scripts/debug_local_flow.py --transcript "Apply to YC using my resume" +``` + +### 4) Missing local file alias warnings at startup + +If preflight warns about missing files (resume, cover letter, linkedin export), +update alias paths in `config/resources.py` to real local files. + +--- + +## Tech Stack + +| Layer | Technology | +|---|---| +| Voice STT | Gemma 4 via [Cactus](https://github.com/cactus-compute/cactus) / whisper.cpp fallback | +| Intent Parsing | Gemma 4 on-device (Cactus) | +| Browser Automation | Playwright + persistent Chrome context | +| macOS Integration | AppleScript / JXA via osascript | +| UI | Rumps (macOS menu bar) + tkinter dialogs | +| Language | Python 3.11+ | + +--- + +## Team + +- **Alspencer Omondi** +- **Hanzi Li** +- **Korin Aldam-Tajima** + +Built at the Cactus × YC Gemma 4 Voice Agents Hackathon, San Francisco, April 18–19 2026. + +--- + +## Privacy + +The intent layer runs entirely on-device. Your voice transcript, resume content, and personal data are processed locally by Gemma 4 via Cactus. Nothing leaves your laptop unless you explicitly trigger a browser action you have approved. diff --git a/Ali/config/index_bootstrap.py b/Ali/config/index_bootstrap.py new file mode 100644 index 00000000..f6e382f4 --- /dev/null +++ b/Ali/config/index_bootstrap.py @@ -0,0 +1,368 @@ +""" +Startup bootstrap for the disk index. + +Invoked once from `main.py` right after preflight. If the index is missing +(or the user asked for a rebuild), we spawn `scripts/build_index.py` as a +subprocess so the heavyweight embedding step runs in a clean interpreter +and doesn't share state with the agent's asyncio loop. + +Default behaviour is **background**: the build runs in a subprocess while +main.py continues to bring up the UI and agent loop. Because the index is a +SQLite WAL DB with commits every ~2s, queries against it immediately return +whatever has been indexed so far. Semantic (vector) search and the user +profile aren't available until the build's final step. + +Progress protocol: + The build script writes tqdm output to **stderr** (inherited by this + process so the user sees it in the terminal) and structured progress + events to **stdout** as lines prefixed with ``PROGRESS `` followed by a + JSON object. We capture stdout, parse those events, and forward them + to the caller-supplied callback (typically the menu bar / overlay). +""" + +from __future__ import annotations + +import atexit +import json +import os +import signal +import subprocess +import sys +import threading +import time +from pathlib import Path +from typing import Callable + + +ProgressCallback = Callable[[str, dict], None] + + +_HERE = Path(__file__).resolve() +_ROOT = _HERE.parent.parent +_BUILD_SCRIPT = _ROOT / "scripts" / "build_index.py" + + +_active_proc: subprocess.Popen | None = None +_active_lock = threading.Lock() + + +def ensure_index( + *, + force_rebuild: bool = False, + skip: bool = False, + background: bool = True, + on_progress: ProgressCallback | None = None, + on_complete: Callable[[bool], None] | None = None, +) -> None: + """Ensure the disk index exists and is up-to-date. + + Default behaviour (`python main.py`): + * no index yet → build one in the background + * partial index on disk → **resume** the incremental build in the + background (picks up exactly where the last run left off, reusing + already-embedded chunks) + * fully-built index → skip; use as-is + + Parameters + ---------- + force_rebuild + Wipe the existing index and rebuild from scratch (`--rebuild-index`). + skip + Bypass the auto-resume behaviour entirely (`--skip-index`). Useful + when you just want to launch the UI against whatever is on disk. + background + If True (default), spawn the build as a detached Popen and return + immediately so the caller can bring up the UI. If False, block until + the build finishes. + on_progress, on_complete + Optional callbacks; see docstring on the watcher thread. + """ + from executors.local.disk_index import ( + index_exists, + index_is_complete, + index_stats, + reset_handle, + ) + + complete = index_is_complete() if not force_rebuild else False + + if skip and not force_rebuild: + stats = index_stats() + state = ( + "complete" + if complete + else ("partial — resume skipped" if index_exists() else "absent") + ) + if stats is not None: + print( + f"[index] --skip-index → {state} ({stats.files} files, " + f"{stats.chunks} chunks, built {stats.age}).", + flush=True, + ) + else: + print(f"[index] --skip-index → {state}.", flush=True) + return + + if not force_rebuild and complete: + stats = index_stats() + if stats is not None: + print( + f"[index] ready — {stats.files} files, {stats.chunks} chunks, " + f"built {stats.age}", + flush=True, + ) + return + + if force_rebuild: + print( + "[index] --rebuild-index — wiping existing index and rebuilding " + "from scratch.", + flush=True, + ) + elif index_exists(): + stats = index_stats() + detail = "" + if stats is not None: + detail = ( + f" ({stats.files} files already indexed, " + f"{stats.chunks} chunks)" + ) + print( + f"[index] partial index detected — resuming incremental build " + f"in background{detail}. Already-indexed files are skipped; " + "embedding reuses existing vectors.", + flush=True, + ) + else: + print( + "[index] indexing your laptop in the background (incremental: " + "already-indexed files are skipped, so resuming an interrupted " + "build is fast). You can start asking questions right away.", + flush=True, + ) + print( + "[index] semantic search and the \"who am I\" profile activate " + "once the build completes (tip: set ALI_INDEX_EMBEDDINGS=0 for a " + "much faster build with filename + content search only).", + flush=True, + ) + + if background: + _spawn_background_build( + on_progress=on_progress, + on_complete=on_complete, + reset_handle=reset_handle, + force_rebuild=force_rebuild, + ) + return + + # Blocking path: stream output through to the terminal and parse progress + # so the caller's on_progress callback still fires. + _blocking_build( + on_progress=on_progress, + reset_handle=reset_handle, + force_rebuild=force_rebuild, + ) + + +def _blocking_build( + *, + on_progress: ProgressCallback | None, + reset_handle: Callable[[], None], + force_rebuild: bool, +) -> None: + from executors.local.disk_index import index_stats + + cmd = [sys.executable, "-u", str(_BUILD_SCRIPT)] + if force_rebuild: + cmd.append("--full") + proc = subprocess.Popen( + cmd, + cwd=str(_ROOT), + stdout=subprocess.PIPE, + stderr=None, # inherit — tqdm bar goes straight to the terminal + bufsize=1, + text=True, + ) + + final_summary: dict | None = None + assert proc.stdout is not None + for raw_line in proc.stdout: + line = raw_line.rstrip("\n") + event = _parse_progress_line(line) + if event is not None: + if on_progress is not None: + try: + on_progress(event["event"], event) + except Exception: + pass + elif line.startswith("{") and line.endswith("}"): + try: + final_summary = json.loads(line) + except json.JSONDecodeError: + pass + + rc = proc.wait() + if rc != 0 or (final_summary and not final_summary.get("ok")): + print( + "[index][warn] build failed; continuing with whatever partial " + "index exists (you can retry later from the menu bar).", + flush=True, + ) + return + + reset_handle() + stats = index_stats() + if stats is not None: + print( + f"[index] built — {stats.files} files, {stats.chunks} chunks.", + flush=True, + ) + + +def _spawn_background_build( + *, + on_progress: ProgressCallback | None, + on_complete: Callable[[bool], None] | None, + reset_handle: Callable[[], None], + force_rebuild: bool, +) -> None: + """Launch the build script as a detached subprocess and start a watcher.""" + global _active_proc + with _active_lock: + if _active_proc is not None and _active_proc.poll() is None: + print( + "[index] build already running (pid=%d); ignoring new request" + % _active_proc.pid, + flush=True, + ) + return + cmd = [sys.executable, "-u", str(_BUILD_SCRIPT)] + if force_rebuild: + cmd.append("--full") + proc = subprocess.Popen( + cmd, + cwd=str(_ROOT), + stdout=subprocess.PIPE, + stderr=None, # inherit so the terminal shows the tqdm bar + bufsize=1, + text=True, + ) + _active_proc = proc + mode = "full rebuild" if force_rebuild else "incremental" + print( + f"[index] {mode} pid={proc.pid} running in background…", + flush=True, + ) + + atexit.register(_terminate_active_build) + + def _watch() -> None: + started = time.time() + final_summary: dict | None = None + assert proc.stdout is not None + try: + for raw_line in proc.stdout: + line = raw_line.rstrip("\n") + event = _parse_progress_line(line) + if event is not None: + if on_progress is not None: + try: + on_progress(event["event"], event) + except Exception: + pass + continue + if line.startswith("{") and line.endswith("}"): + try: + final_summary = json.loads(line) + except json.JSONDecodeError: + pass + continue + print(line, flush=True) + except Exception as exc: + print(f"[index][warn] stdout watcher error: {exc}", flush=True) + + rc = proc.wait() + duration = int(time.time() - started) + ok = rc == 0 + if ok: + print( + f"[index] build complete in {duration}s — reopening handles.", + flush=True, + ) + try: + reset_handle() + except Exception as exc: + print(f"[index][warn] handle reset failed: {exc}", flush=True) + else: + err = "" + if isinstance(final_summary, dict): + err = str(final_summary.get("error") or "") + print( + f"[index][warn] build exited with rc={rc} after {duration}s" + + (f": {err}" if err else "") + + " — see traceback on stderr above.", + flush=True, + ) + if on_complete is not None: + try: + on_complete(ok) + except Exception: + pass + with _active_lock: + global _active_proc + if _active_proc is proc: + _active_proc = None + + threading.Thread(target=_watch, daemon=True, name="index-build-watcher").start() + + +def _parse_progress_line(line: str) -> dict | None: + """Decode a ``PROGRESS {...}`` line emitted by the build subprocess.""" + if not line.startswith("PROGRESS "): + return None + raw = line[len("PROGRESS ") :].strip() + if not raw: + return None + try: + data = json.loads(raw) + except json.JSONDecodeError: + return None + if not isinstance(data, dict) or "event" not in data: + return None + return data + + +def _terminate_active_build() -> None: + """Kill a still-running build when the parent process exits.""" + with _active_lock: + proc = _active_proc + if proc is None: + return + if proc.poll() is not None: + return + try: + proc.send_signal(signal.SIGTERM) + try: + proc.wait(timeout=2) + except subprocess.TimeoutExpired: + proc.kill() + except Exception: + pass + + +def parse_build_summary(stdout: bytes | str) -> dict | None: + """Pull the final JSON line the build script emits (for callers that + capture stdout instead of streaming it).""" + if isinstance(stdout, bytes): + stdout = stdout.decode("utf-8", errors="ignore") + for line in reversed(stdout.strip().splitlines()): + line = line.strip() + if line.startswith("PROGRESS "): + continue + if line.startswith("{") and line.endswith("}"): + try: + return json.loads(line) + except json.JSONDecodeError: + continue + return None diff --git a/Ali/config/index_progress_hub.py b/Ali/config/index_progress_hub.py new file mode 100644 index 00000000..ad186d82 --- /dev/null +++ b/Ali/config/index_progress_hub.py @@ -0,0 +1,67 @@ +""" +Tiny pub/sub hub that buffers disk-index progress events between the +bootstrap subprocess (which starts early, from main thread) and downstream +UI consumers (menu bar, overlay) that come online later on other threads. + +Thread-safe and dependency-free. +""" + +from __future__ import annotations + +import threading +from collections import deque +from typing import Callable + +Listener = Callable[[str, dict], None] + +_lock = threading.Lock() +_listeners: list[Listener] = [] +_buffer: deque[tuple[str, dict]] = deque(maxlen=256) +_last_event: tuple[str, dict] | None = None + + +def publish(event: str, data: dict) -> None: + """Called by the bootstrap watcher thread for every build event.""" + snapshot = dict(data) + global _last_event + with _lock: + _last_event = (event, snapshot) + _buffer.append((event, snapshot)) + listeners = list(_listeners) + for listener in listeners: + try: + listener(event, snapshot) + except Exception: + # Never let a broken consumer break the build pipeline. + pass + + +def subscribe(listener: Listener, *, replay: bool = True) -> Callable[[], None]: + """Register a consumer; returns an unsubscribe callable. + + If ``replay`` is True (default), the listener is immediately invoked with + every buffered event so late arrivals catch up on progress already made. + """ + with _lock: + _listeners.append(listener) + to_replay = list(_buffer) if replay else [] + + for event, data in to_replay: + try: + listener(event, data) + except Exception: + pass + + def _unsubscribe() -> None: + with _lock: + try: + _listeners.remove(listener) + except ValueError: + pass + + return _unsubscribe + + +def last_event() -> tuple[str, dict] | None: + with _lock: + return _last_event diff --git a/Ali/config/known_intents.py b/Ali/config/known_intents.py new file mode 100644 index 00000000..3148fadc --- /dev/null +++ b/Ali/config/known_intents.py @@ -0,0 +1,16 @@ +""" +Human-readable descriptions of each supported goal. +Used in prompts and UI copy. +""" + +from intent.schema import KnownGoal + +INTENT_DESCRIPTIONS = { + KnownGoal.APPLY_TO_JOB: "Apply to a job or program using your resume", + KnownGoal.SEND_MESSAGE: "Send an iMessage to a contact", + KnownGoal.SEND_EMAIL: "Compose and send an email via Mail", + KnownGoal.ADD_CALENDAR_EVENT: "Add an event to your Calendar", + KnownGoal.OPEN_URL: "Open a URL in the browser", + KnownGoal.FIND_FILE: "Find a file on disk by name or alias", + KnownGoal.UNKNOWN: "Unknown intent — ask user to rephrase", +} diff --git a/Ali/config/preflight.py b/Ali/config/preflight.py new file mode 100644 index 00000000..9e1f9a58 --- /dev/null +++ b/Ali/config/preflight.py @@ -0,0 +1,91 @@ +"""Startup preflight checks for demo reliability.""" + +from __future__ import annotations + +import importlib.util +import os +import shutil +from pathlib import Path + +from config.resources import FILE_ALIASES +from config.settings import CHROME_PROFILE_PATH, GEMINI_API_KEY, VISION_ARTIFACT_DIR + + +def run_preflight_checks() -> None: + """Validate key runtime prerequisites before starting the loop.""" + print("[preflight] running startup checks…", flush=True) + errors: list[str] = [] + warnings: list[str] = [] + + # Browser session profile path should be configured to a real directory. + chrome_profile = Path(os.path.expanduser(CHROME_PROFILE_PATH)) + if not chrome_profile.exists(): + warnings.append( + f"CHROME_PROFILE_PATH does not exist: {chrome_profile}. " + "Browser automation may fail." + ) + + # Local file aliases should point at existing files for demo flows. + for alias, raw_path in FILE_ALIASES.items(): + resolved = Path(os.path.expanduser(raw_path)) + if not resolved.exists(): + warnings.append( + f"Alias '{alias}' points to missing file: {resolved}. " + "Update config/resources.py." + ) + + # At least one STT backend is required. + has_whisper = _module_available("faster_whisper") + has_cactus = shutil.which("cactus") is not None + if not (has_whisper or has_cactus): + errors.append( + "No STT backend found. Install faster-whisper or cactus CLI." + ) + + # Optional but recommended for non-rule intent handling. + if not GEMINI_API_KEY and not has_cactus: + warnings.append( + "Neither GEMINI_API_KEY nor cactus intent fallback is available. " + "Only rule-based intents will work." + ) + + artifact_dir = Path(os.path.expanduser(VISION_ARTIFACT_DIR)) + try: + artifact_dir.mkdir(parents=True, exist_ok=True) + except Exception as exc: + errors.append(f"Unable to create VISION_ARTIFACT_DIR '{artifact_dir}': {exc}") + + if shutil.which("screencapture") is None: + warnings.append( + "screencapture command not found. Desktop observation snapshots may fail." + ) + + _print_diagnostics(errors, warnings) + if errors: + raise RuntimeError("Preflight failed. Resolve errors before running.") + + +def _module_available(module_name: str) -> bool: + """Check whether `module_name` can be imported, WITHOUT actually importing it. + + We previously used `__import__(module_name)` which fully loads the module + and its native deps. For `faster_whisper` that cascade alone cost 5-10s + at startup (ctranslate2 + tokenizers + numpy), all of which the agent + thread imports again later anyway. `find_spec` just looks up the module + on sys.path and returns metadata — microseconds. + """ + try: + return importlib.util.find_spec(module_name) is not None + except (ImportError, ValueError): + return False + + +def _print_diagnostics(errors: list[str], warnings: list[str]) -> None: + if not errors and not warnings: + print("[preflight] all checks passed.", flush=True) + return + + for warning in warnings: + print(f"[preflight][warn] {warning}", flush=True) + for error in errors: + print(f"[preflight][error] {error}", flush=True) diff --git a/Ali/config/resources.py b/Ali/config/resources.py new file mode 100644 index 00000000..d85cd5f3 --- /dev/null +++ b/Ali/config/resources.py @@ -0,0 +1,25 @@ +""" +Named file aliases and known contacts. +Edit KNOWN_CONTACTS with real phone numbers or iMessage emails before the demo. +""" + +import os + +FILE_ALIASES: dict[str, str] = { + "resume": "~/Desktop/Omondi, Alspencer 03.03.2026.pdf", +} + +# Hardcoded contacts — checked before querying Contacts.app. +# Keys are lowercase name variants Whisper might produce. +# Values are phone numbers (+1XXXXXXXXXX) or iMessage emails. +# --- Alspencer --- a lot of hardcoded shit here. +KNOWN_CONTACTS: dict[str, str] = { + "hanzi": "hanzili0217@gmail.com", + "hanzi li": "hanzili0217@gmail.com", + "ethan": "etsandoval@hmc.edu", + "ethan sandoval": "etsandoval@hmc.edu", + "korin": "korintajima@gmail.com", + "corin": "korintajima@gmail.com", # common Whisper mishearing + "corinne": "korintajima@gmail.com", # another common mishearing + "korin tajima": "korintajima@gmail.com", +} diff --git a/Ali/config/settings.py b/Ali/config/settings.py new file mode 100644 index 00000000..9ed6da99 --- /dev/null +++ b/Ali/config/settings.py @@ -0,0 +1,168 @@ +""" +Global configuration. +API keys are loaded from .env in the project root (never commit that file --- Alspencer --- I know claude--- don't leak your source code next time). +""" + +import os +from pathlib import Path + +# Load .env from project root (silently ignored if file doesn't exist) +try: + from dotenv import load_dotenv # type: ignore + load_dotenv(Path(__file__).resolve().parent.parent / ".env") +except ImportError: + pass # dotenv not installed — fall back to environment variables only + +# ── Gemini API (for fast text intent parsing) ───────────────────────────────── +GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY", "") + +# ── Deepgram API (real-time streaming STT for meeting capture) ──────────────── +DEEPGRAM_API_KEY = os.environ.get("DEEPGRAM_API_KEY", "") + +# ── Cactus Cloud API ────────────────────────────────────────────────────────── +CACTUS_API_KEY = os.environ.get("CACTUS_API_KEY", "") + +# ── Cactus / Gemma 4 ───────────────────────────────────────────────────────── +CACTUS_GEMMA4_MODEL = "google/gemma-4-E2B-it" +# CACTUS_GEMMA4_MODEL = "google/functiongemma-270m-it" + +# ── Cactus VL (browser sub-agent) ──────────────────────────────────────────── +# The browser sub-agent runs inside a Chrome extension whose LLM is configured +# via chrome.storage.local. scripts/cactus_server.py is the HTTP sidecar the +# extension talks to when provider='cactus'; the AI Studio path (default) is +# used when provider='google'. +CACTUS_VL_MODEL = os.getenv("CACTUS_VL_MODEL", "google/gemma-4-E2B-it") +CACTUS_SIDECAR_URL = os.getenv("CACTUS_SIDECAR_URL", "http://127.0.0.1:8765") +AGENT_NODE_BIN = os.getenv("AGENT_NODE_BIN", "node") + +# ── Whisper fallback ────────────────────────────────────────────────────────── +WHISPER_MODEL_SIZE = "base.en" # tiny.en | base.en | small.en + +# ── Chrome persistent context ───────────────────────────────────────────────── +# macOS default Chrome profile. Change "Default" if you use a different profile. +CHROME_PROFILE_PATH = os.path.expanduser( + "~/Library/Application Support/Google/Chrome/Default" +) + +# ── Push-to-talk hotkey ─────────────────────────────────────────────────────── +# Configured in voice/capture.py — keyboard.Key.alt = Option key + +# ── Demo safety ──────────────────────────────────────────────────────────────── +# When set (1/true/yes), irreversible actions are skipped. +DRY_RUN = os.environ.get("VOICE_AGENT_DRY_RUN", "").lower() in {"1", "true", "yes"} + +# ── Vision-first orchestration ───────────────────────────────────────────────── +VISION_FIRST_ENABLED = os.environ.get("VOICE_AGENT_VISION_FIRST", "1").lower() in {"1", "true", "yes"} +VISION_MAX_ACTION_STEPS = int(os.environ.get("VOICE_AGENT_VISION_MAX_ACTION_STEPS", "8")) +VISION_ARTIFACT_DIR = os.path.expanduser( + os.environ.get("VOICE_AGENT_VISION_ARTIFACT_DIR", "~/tmp/yc_voice_agent_observations") +) + +# ── macOS app names ─────────────────────────────────────────────────────────── +MESSAGES_APP = "Messages" +MAIL_APP = "Mail" +CALENDAR_APP = "Calendar" +CONTACTS_APP = "Contacts" + +# ── File resolver ───────────────────────────────────────────────────────────── +# Local-only resolver that turns natural-language transcripts into concrete +# file paths using Spotlight (mdfind) + Cactus-proposed predicates. + +def _env_bool(name: str, default: bool) -> bool: + raw = os.environ.get(name, "1" if default else "0") + return raw.lower() in {"1", "true", "yes", "on"} + + +def _env_int(name: str, default: int) -> int: + try: + return int(os.environ.get(name, str(default))) + except ValueError: + return default + + +def _parse_search_roots(raw: str) -> list[Path]: + roots: list[Path] = [] + seen: set[str] = set() + for chunk in raw.split(","): + item = chunk.strip() + if not item: + continue + try: + resolved = Path(item).expanduser().resolve() + except OSError: + continue + key = str(resolved) + if key in seen: + continue + if not resolved.exists() or not resolved.is_dir(): + continue + seen.add(key) + roots.append(resolved) + return roots + + +FILE_RESOLVER_ENABLED = _env_bool("VOICE_AGENT_FILE_RESOLVER", True) +FILE_RESOLVER_ALIAS_FIRST = _env_bool("VOICE_AGENT_FILE_RESOLVER_ALIAS_FIRST", True) +FILE_RESOLVER_USE_SPOTLIGHT = _env_bool("VOICE_AGENT_USE_SPOTLIGHT", True) + +FILE_SEARCH_ROOTS: list[Path] = _parse_search_roots( + os.environ.get( + "VOICE_AGENT_FILE_SEARCH_ROOTS", + "~/Desktop,~/Documents,~/Downloads", + ) +) + +FILE_PREDICATE_MAX_ROUNDS = _env_int("VOICE_AGENT_FILE_PREDICATE_MAX_ROUNDS", 2) +FILE_MDFIND_MAX_RESULTS = _env_int("VOICE_AGENT_FILE_MDFIND_MAX_RESULTS", 40) +FILE_INDEX_MAX_CHARS = _env_int("VOICE_AGENT_FILE_INDEX_MAX_CHARS", 2000) +FILE_WALK_MAX_FILES = _env_int("VOICE_AGENT_FILE_WALK_MAX_FILES", 500) +FILE_WALK_MAX_DEPTH = _env_int("VOICE_AGENT_FILE_WALK_MAX_DEPTH", 4) + +FILE_RESOLVE_DEBUG = _env_bool("VOICE_AGENT_FILE_RESOLVE_DEBUG", False) + +# ── Disk index (laptop-wide content + embeddings) ──────────────────────────── +# Local-first retrieval-augmented Q&A over the user's files + macOS data. +# Default is a focused scope: the three docs folders, /Applications, plus +# Contacts / Calendar / Messages. Set ALI_INDEX_FULL_DISK=1 (or pass +# `--full-disk` on the CLI) for a full home-directory scan. + +INDEX_DIR: Path = Path(os.path.expanduser( + os.environ.get("ALI_INDEX_DIR", "~/.cache/ali/index") +)) + +INDEX_FULL_DISK = _env_bool("ALI_INDEX_FULL_DISK", False) + +_DEFAULT_SCAN_ROOTS = "~/Documents,~/Downloads,~/Desktop,/Applications" +_FULL_DISK_ROOTS = "~,/Applications" + +INDEX_SCAN_ROOTS: list[Path] = _parse_search_roots( + os.environ.get( + "ALI_INDEX_SCAN_ROOTS", + _FULL_DISK_ROOTS if INDEX_FULL_DISK else _DEFAULT_SCAN_ROOTS, + ) +) + +INDEX_MAX_FILE_BYTES = _env_int("ALI_INDEX_MAX_FILE_BYTES", 5_000_000) +INDEX_EMBED_MODEL = os.environ.get( + "ALI_INDEX_EMBED_MODEL", "sentence-transformers/all-MiniLM-L6-v2" +) +INDEX_CHUNK_TOKENS = _env_int("ALI_INDEX_CHUNK_TOKENS", 400) +INDEX_ENABLE_EMBEDDINGS = _env_bool("ALI_INDEX_EMBEDDINGS", True) + +# Comma-separated list of non-filesystem data sources to index alongside the +# filesystem walk. Each entry names a module under +# `executors/local/disk_index/sources/`. Set to "" to disable all of them. +INDEX_SOURCES: list[str] = [ + name.strip().lower() + for name in os.environ.get( + "ALI_INDEX_SOURCES", "contacts,calendar,messages" + ).split(",") + if name.strip() +] + +# How far back to go when indexing time-ordered sources (Messages, Calendar). +INDEX_SOURCE_HISTORY_DAYS = _env_int("ALI_INDEX_SOURCE_HISTORY_DAYS", 365) + +# Local-first RAG. Default: 100% on-device via Cactus/Gemma 4. Set to 1 to +# allow falling back to Gemini if Cactus is unavailable for answer generation. +ALI_ALLOW_CLOUD_FALLBACK = _env_bool("ALI_ALLOW_CLOUD_FALLBACK", False) diff --git a/Ali/demo/__init__.py b/Ali/demo/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/Ali/demo/wake.py b/Ali/demo/wake.py new file mode 100644 index 00000000..1cf00a97 --- /dev/null +++ b/Ali/demo/wake.py @@ -0,0 +1,117 @@ +""" +Demo Step 1 — Wake Detection +Press F8 (or run directly) to open the camera. +When Ali sees a face she greets Alspencer by name via TTS, +then calls the optional on_wake() callback so the rest of the +demo can chain from here. +""" + +from __future__ import annotations + +import threading +import time +from typing import Callable + +import cv2 # type: ignore[reportMissingImports] +import pyttsx3 # type: ignore[reportMissingImports] + +USER_NAME = "Alspencer" + +# How long (seconds) a face must be visible before triggering +FACE_HOLD_SECONDS = 1.2 + +# OpenCV's built-in face detector — no model download needed +_CASCADE = cv2.CascadeClassifier( + cv2.data.haarcascades + "haarcascade_frontalface_default.xml" +) + + +def _speak(text: str) -> None: + """Blocking TTS on a background thread so it doesn't stall the camera loop.""" + engine = pyttsx3.init() + # Slightly slower, warmer rate + engine.setProperty("rate", 165) + # Pick the best available voice (prefer Siri/Alex on macOS) + voices = engine.getProperty("voices") + for v in voices: + if "samantha" in v.name.lower() or "alex" in v.name.lower(): + engine.setProperty("voice", v.id) + break + engine.say(text) + engine.runAndWait() + + +def _speak_async(text: str) -> None: + threading.Thread(target=_speak, args=(text,), daemon=True).start() + + +def run_wake(on_wake: Callable[[], None] | None = None) -> None: + """ + Open the camera, wait for a face, greet the user, fire on_wake(). + Blocks until the greeting fires or the user presses Q to quit. + """ + cap = cv2.VideoCapture(0) + if not cap.isOpened(): + print("[wake] Could not open camera") + return + + print("[wake] Camera open — watching for a face...") + print("[wake] Press Q in the camera window to cancel") + + face_first_seen: float | None = None + greeted = False + + try: + while True: + ok, frame = cap.read() + if not ok: + break + + grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + faces = _CASCADE.detectMultiScale(grey, scaleFactor=1.1, minNeighbors=5, minSize=(80, 80)) + + if len(faces) > 0: + # Draw box around first face + x, y, w, h = faces[0] + cv2.rectangle(frame, (x, y), (x + w, y + h), (80, 200, 120), 2) + + if face_first_seen is None: + face_first_seen = time.time() + + held = time.time() - face_first_seen + bar_w = int((held / FACE_HOLD_SECONDS) * w) + cv2.rectangle(frame, (x, y + h + 6), (x + bar_w, y + h + 14), (80, 200, 120), -1) + + if not greeted and held >= FACE_HOLD_SECONDS: + greeted = True + greeting = ( + f"Good morning, {USER_NAME}. " + "While you were asleep, I've been busy. " + "I found some great opportunities and took care of a few things — " + "let me walk you through them." + ) + print(f"[wake] Face held {held:.1f}s → greeting") + _speak_async(greeting) + cv2.destroyAllWindows() + cap.release() + if on_wake: + on_wake() + return + else: + face_first_seen = None + + cv2.putText( + frame, "Ali is watching...", (12, 28), + cv2.FONT_HERSHEY_SIMPLEX, 0.7, (80, 200, 120), 2, + ) + cv2.imshow("Ali — Wake Detection", frame) + + if cv2.waitKey(1) & 0xFF == ord("q"): + break + finally: + cap.release() + cv2.destroyAllWindows() + + +if __name__ == "__main__": + run_wake(on_wake=lambda: print("\n[demo] Wake fired — next step would start here")) diff --git a/Ali/demo/wake_ui.py b/Ali/demo/wake_ui.py new file mode 100644 index 00000000..1b299e00 --- /dev/null +++ b/Ali/demo/wake_ui.py @@ -0,0 +1,264 @@ +""" +Demo Step 1 — Wake UI +Video-call style Qt window: shows live camera feed, detects face, +greets the user by name with a time-appropriate message. +Press backtick ` to launch from main.py. +""" + +from __future__ import annotations + +import datetime +import threading +import time +from typing import Callable + +import cv2 # type: ignore[reportMissingImports] +import pyttsx3 # type: ignore[reportMissingImports] + +from PySide6.QtCore import QPoint, QRect, Qt, QTimer, Signal, QObject # type: ignore[reportMissingImports] +from PySide6.QtGui import ( # type: ignore[reportMissingImports] + QBrush, QColor, QFont, QImage, QLinearGradient, + QPainter, QPainterPath, QPen, QPixmap, +) +from PySide6.QtWidgets import QApplication, QLabel, QWidget # type: ignore[reportMissingImports] + +USER_NAME = "Alspencer" +FACE_HOLD_SEC = 1.2 +CASCADE = cv2.CascadeClassifier( + cv2.data.haarcascades + "haarcascade_frontalface_default.xml" +) + +W, H = 480, 360 +RADIUS = 24 +CAM_W = W - 32 +CAM_H = H - 120 + + +def _greeting() -> str: + hour = datetime.datetime.now().hour + if hour < 12: + tod = "Good morning" + elif hour < 17: + tod = "Good afternoon" + else: + tod = "Good evening" + return ( + f"{tod}, {USER_NAME}. " + "While you were asleep I've been busy — " + "I found some great opportunities and took care of a few things. " + "Let me walk you through them." + ) + + +def _speak_async(text: str) -> None: + def _go(): + engine = pyttsx3.init() + engine.setProperty("rate", 165) + for v in engine.getProperty("voices"): + if "samantha" in v.name.lower() or "alex" in v.name.lower(): + engine.setProperty("voice", v.id) + break + engine.say(text) + engine.runAndWait() + threading.Thread(target=_go, daemon=True).start() + + +# ── Signal bridge (camera thread → Qt main thread) ─────────────────────────── + +class _Bridge(QObject): + frame_ready = Signal(QImage) + face_greeted = Signal(str) + + +class WakeWindow(QWidget): + def __init__(self, on_wake: Callable[[], None] | None = None) -> None: + super().__init__() + self._on_wake = on_wake + self._bridge = _Bridge() + self._greeted = False + self._greeting = "" + self._pixmap = QPixmap() + self._face_rect: tuple[int,int,int,int] | None = None + self._progress = 0.0 # 0‥1 hold progress + + self._font_name = QFont(".AppleSystemUIFont", 18, QFont.Weight.Bold) + self._font_sub = QFont(".AppleSystemUIFont", 13) + self._font_greet= QFont(".AppleSystemUIFont", 14) + + self.setWindowFlags( + Qt.WindowType.FramelessWindowHint + | Qt.WindowType.WindowStaysOnTopHint + | Qt.WindowType.Tool + ) + self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground, True) + self.resize(W, H) + self._center() + + self._bridge.frame_ready.connect(self._on_frame) + self._bridge.face_greeted.connect(self._on_greeted) + + # Start camera capture thread + self._running = True + threading.Thread(target=self._capture_loop, daemon=True).start() + + self.show() + self.raise_() + + def _center(self) -> None: + from PySide6.QtGui import QGuiApplication # type: ignore[reportMissingImports] + screen = QGuiApplication.primaryScreen() + if screen: + geo = screen.availableGeometry() + self.move(geo.center().x() - W // 2, geo.top() + 60) + + # ── Camera thread ───────────────────────────────────────────────────────── + + def _capture_loop(self) -> None: + cap = cv2.VideoCapture(0) + if not cap.isOpened(): + print("[wake] Camera unavailable") + return + + face_first: float | None = None + + while self._running: + ok, frame = cap.read() + if not ok: + break + + frame = cv2.flip(frame, 1) # mirror + grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + faces = CASCADE.detectMultiScale( + grey, scaleFactor=1.1, minNeighbors=5, minSize=(70, 70) + ) + + if len(faces) > 0 and not self._greeted: + x, y, w, h = faces[0] + self._face_rect = (x, y, w, h) + if face_first is None: + face_first = time.time() + self._progress = min(1.0, (time.time() - face_first) / FACE_HOLD_SEC) + if self._progress >= 1.0: + greeting = _greeting() + self._greeted = True + _speak_async(greeting) + self._bridge.face_greeted.emit(greeting) + else: + if not self._greeted: + face_first = None + self._progress = 0.0 + self._face_rect = None + + # Convert BGR → RGB → QImage + rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + h, w = rgb.shape[:2] + img = QImage(rgb.data, w, h, w * 3, QImage.Format.Format_RGB888).copy() + self._bridge.frame_ready.emit(img) + + cap.release() + + def _on_frame(self, img: QImage) -> None: + self._pixmap = QPixmap.fromImage(img) + self.update() + + def _on_greeted(self, text: str) -> None: + self._greeting = text + self.update() + # Close window after 6 s and fire callback + QTimer.singleShot(6000, self._finish) + + def _finish(self) -> None: + self._running = False + self.close() + if self._on_wake: + self._on_wake() + + # ── Paint ───────────────────────────────────────────────────────────────── + + def paintEvent(self, _event) -> None: # type: ignore[override] + p = QPainter(self) + p.setRenderHints( + QPainter.RenderHint.Antialiasing | + QPainter.RenderHint.SmoothPixmapTransform + ) + + shell = QPainterPath() + shell.addRoundedRect(QRect(0, 0, W, H), RADIUS, RADIUS) + p.setClipPath(shell) + + # ── Camera feed ─────────────────────────────────────────────────────── + if not self._pixmap.isNull(): + scaled = self._pixmap.scaled( + W, H, + Qt.AspectRatioMode.KeepAspectRatioByExpanding, + Qt.TransformationMode.SmoothTransformation, + ) + x_off = (scaled.width() - W) // 2 + y_off = (scaled.height() - H) // 2 + p.drawPixmap(-x_off, -y_off, scaled) + else: + p.fillPath(shell, QColor(20, 20, 24)) + + # ── Dark gradient overlay (bottom) ──────────────────────────────────── + grad = QLinearGradient(0, H // 2, 0, H) + grad.setColorAt(0.0, QColor(0, 0, 0, 0)) + grad.setColorAt(1.0, QColor(0, 0, 0, 200)) + p.fillPath(shell, grad) + + p.setClipping(False) + + # ── Face hold progress bar ──────────────────────────────────────────── + if self._progress > 0 and not self._greeted: + bar_w = int(W * self._progress) + p.setPen(Qt.PenStyle.NoPen) + p.setBrush(QColor(80, 220, 120, 180)) + p.drawRoundedRect(QRect(0, H - 5, bar_w, 5), 2, 2) + + # ── Name plate (bottom left) ────────────────────────────────────────── + p.setPen(QColor(255, 255, 255)) + p.setFont(self._font_name) + p.drawText(QRect(20, H - 72, W - 40, 28), + Qt.AlignmentFlag.AlignLeft | Qt.AlignmentFlag.AlignVCenter, + USER_NAME) + + p.setPen(QColor(180, 220, 180)) + p.setFont(self._font_sub) + status = "Ali is watching..." if not self._greeted else "✓ Greeted" + p.drawText(QRect(20, H - 46, W - 40, 22), + Qt.AlignmentFlag.AlignLeft | Qt.AlignmentFlag.AlignVCenter, + status) + + # ── Greeting text (centre, after detection) ─────────────────────────── + if self._greeting: + p.setPen(QColor(255, 255, 255, 220)) + p.setFont(self._font_greet) + p.drawText( + QRect(20, 20, W - 40, H - 100), + Qt.TextFlag.TextWordWrap | Qt.AlignmentFlag.AlignTop, + self._greeting, + ) + + # ── Glass border ────────────────────────────────────────────────────── + border = QLinearGradient(0, 0, 0, H) + border.setColorAt(0.0, QColor(255, 255, 255, 80)) + border.setColorAt(1.0, QColor(255, 255, 255, 20)) + p.setPen(QPen(QBrush(border), 1.5)) + p.drawPath(shell) + + # ── Drag to move ────────────────────────────────────────────────────────── + + def mousePressEvent(self, e) -> None: # type: ignore[override] + if e.button() == Qt.MouseButton.LeftButton: + self._drag = e.globalPosition().toPoint() - self.frameGeometry().topLeft() + + def mouseMoveEvent(self, e) -> None: # type: ignore[override] + if hasattr(self, "_drag") and (e.buttons() & Qt.MouseButton.LeftButton): + self.move(e.globalPosition().toPoint() - self._drag) + + def mouseReleaseEvent(self, e) -> None: # type: ignore[override] + if e.button() == Qt.MouseButton.LeftButton: + self._drag = QPoint() + + def closeEvent(self, e) -> None: # type: ignore[override] + self._running = False + super().closeEvent(e) diff --git a/Ali/docs/cactus-findings.md b/Ali/docs/cactus-findings.md new file mode 100644 index 00000000..2191a44d --- /dev/null +++ b/Ali/docs/cactus-findings.md @@ -0,0 +1,319 @@ +# Cactus integration findings + +**Date:** 2026-04-18 (YC × Cactus Gemma-4 Voice Agents Hackathon) +**Scope:** One day of hands-on integration on an Apple Silicon Mac. Brew-installed Cactus 1.14. Hackathon project: a local-first voice agent with a browser-agent sub-tool. +**Audience:** hackathon team, judges, and whoever picks this project up next. + +This document is a plain-spoken log of what we found, not a review. Where we had to work around something, we say what the workaround was. Where Cactus is genuinely strong, we say that too. + +--- + +## TL;DR + +- **Install + Python bindings work** after one path workaround (Homebrew puts the dylib at a different path than the Python shim expects). +- **Python SDK takes JSON strings, not kwarg dicts.** The integration guide floating around has the wrong call signature — we lost an hour to it. Real API: `cactus_complete(model, messages_json, options_json, tools_json, callback)`. +- **Short-prompt performance is excellent.** gemma-3-1b returned "Four" for "What is 2+2?" in 160 ms. `gemma-4-E2B-it` returned `navigate({url})` as a structured `function_call` on a 1.3 K-token prompt in 22 s (190 tok/s prefill, 10 tok/s decode). +- **Long-prompt performance falls off a cliff on CPU.** gemma-4-E2B @ 6.7 K-token prompt → 35–63 s/step. @ 23 K tokens (LinkedIn rendered DOM) → 120 s+ timeout. gemma-4-E4B @ 6.7 K → **6 tok/s** — the `model.mlpackage` for Apple NPU isn't shipped yet in Cactus 1.14, so prefill stays on CPU. +- **Small models need heavy prompting to use the tool-call grammar.** Default gemma-4-E2B emitted `navigate({"url":"..."})` as plain text. A 4-line "structured-call only" preamble in the system prompt fixed it. +- **`cloud_handoff` is half-finished.** `auto_handoff: true` calls a hardcoded `104.198.76.3` GCP IP with self-signed TLS. We (and the integration guide) recommend `auto_handoff: false` and managing the fallback yourself. +- **For this project, Cactus fits in the intent layer, not the browser agent.** We switched the browser path to Gemini Flash after hitting the LinkedIn-DOM cliff. Cactus's right home here is short-text, privacy-critical operations on the critical path: intent classification + pre-cloud sanitisation. + +--- + +## 1. Installation + +### What works + +```bash +brew install cactus-compute/cactus/cactus +``` + +Installs the CLI at `/opt/homebrew/bin/cactus`, the dylib at `/opt/homebrew/opt/cactus/lib/libcactus.dylib`, and the Python FFI wrapper into Homebrew Python 3.14 (`/opt/homebrew/lib/python3.14/site-packages/cactus.py`). + +### What broke + +`cactus.py` hardcodes the dylib path at `/../../cactus/build/libcactus.dylib`, which **does not match** where Homebrew put the dylib. First `import cactus` raises: + +``` +RuntimeError: Cactus library not found at /opt/homebrew/lib/cactus/build/libcactus.dylib +Please build first: cactus build --python +``` + +The install-time README says "For other Python versions, point to the shared library: `export CACTUS_LIB_PATH=...`" — but the installed `cactus.py` **doesn't read `CACTUS_LIB_PATH`**. The env-var hint is wishful documentation. + +### Workaround + +```bash +mkdir -p /opt/homebrew/lib/cactus/build +ln -sf /opt/homebrew/opt/cactus/lib/libcactus.dylib \ + /opt/homebrew/lib/cactus/build/libcactus.dylib +``` + +One symlink. No code changes needed. This should be in the brew formula post-install step or the `cactus.py` shim should be taught to honour `CACTUS_LIB_PATH`. + +--- + +## 2. Python API: what the bindings actually look like + +The integration guide we were given showed this call pattern: + +```python +# NOT how it actually works +cactus_complete( + MODEL, req.messages, + tools=tools_wrapped, + max_tokens=req.max_tokens, + confidence_threshold=0.7, + auto_handoff=False, + tool_rag_top_k=0, + force_tools=False, +) +``` + +The real signature in `/opt/homebrew/lib/python3.14/site-packages/cactus.py`: + +```python +def cactus_init(model_path, corpus_dir, cache_index): # three args, not one + ... + +def cactus_complete(model, messages_json, options_json, tools_json, + callback, pcm_data=None): # JSON STRINGS, not kwargs + ... +``` + +So the actual usage is: + +```python +model = cactus_init("/opt/homebrew/opt/cactus/libexec/weights/gemma-4-E2B-it", + None, False) + +options = { + "max_tokens": 2048, + "temperature": 0.0, + "tool_rag_top_k": 0, + "force_tools": False, + "confidence_threshold": 0.7, + "auto_handoff": False, +} +tools = [{"type": "function", "function": {...}}] +messages = [{"role": "system", "content": "..."}, ...] + +raw = cactus_complete( + model, + json.dumps(messages), + json.dumps(options), + json.dumps(tools), + None, # no streaming callback +) +result = json.loads(raw) +``` + +The response shape (from `docs/cactus_engine.md` and verified empirically) is: + +```json +{ + "success": true, + "error": null, + "cloud_handoff": false, + "response": "I am an AI assistant.", + "function_calls": [{"name": "click", "arguments": {"ref": "42"}}], + "segments": [], + "confidence": 0.85, + "time_to_first_token_ms": 150.5, + "total_time_ms": 1250.3, + "prefill_tps": 166.1, + "decode_tps": 45.2, + "ram_usage_mb": 245.67, + "prefill_tokens": 25, + "decode_tokens": 8, + "total_tokens": 33 +} +``` + +### Our sidecar wrapper + +Because hitting the bare ctypes API is painful and we had a Node agent loop to integrate with, we built a small FastAPI sidecar at `scripts/cactus_server.py` that exposes: + +- `GET /healthz` — `{"ok": true, "model": "..."}` +- `POST /v1/complete` — accepts `{messages, tools?, max_tokens?, confidence_threshold?, auto_handoff?}`, does the JSON encoding + lazy Cactus import + tempfile handling for images, returns the raw Cactus response dict. + +Recommended as a pattern for anyone embedding Cactus into a multi-language stack. ~200 LOC. + +--- + +## 3. Performance measurements (Apple Silicon Mac, CPU prefill) + +All runs on the same machine, uvicorn + Cactus 1.14 + INT4 weights. + +### Loading + trivial prompt + +| Model | Weights on disk | Cold load | 11-tok prompt, 1-tok output | +|---|---|---|---| +| gemma-3-1b-it | 727 MB | 0.7 s | **160 ms** | +| gemma-4-E2B-it | 6.3 GB | ~30 s | **253 ms** (11 tok @ 50 tok/s prefill) | +| gemma-4-E4B-it | 8.2 GB | ~40 s | **1.84 s** (11 tok @ 6 tok/s prefill) | +| Qwen3.5-2B | ~3 GB | 0.7 s | 0.6 s | + +### Agent-shaped prompt (~1,300 tokens system + 13 tool defs) + +| Model | Prefill tok/s | Decode tok/s | Total | Tool call format? | +|---|---|---|---|---| +| gemma-4-E2B-it | **190** | 10 | **8 s** | ❌ emitted as text until prompt nudged | +| Qwen3.5-2B | 88 | 20 | 22 s | ✅ structured function_call, but wrong tool picked | + +### Real-world prompt (~6,700 tokens — agent system + 13 tool defs, via our extension) + +| Model | Turn duration | Tokens in | Notes | +|---|---|---|---| +| gemma-4-E2B-it | 58–65 s | 6.7 K | 3-step example.com task → **completed correctly** in 187 s. | +| gemma-4-E4B-it | **154 s** | 6.7 K | 6 tok/s CPU prefill — same task would need ~7 min/step. Unusable. | + +### Pathological prompt (~23,000 tokens — LinkedIn rendered DOM in tool_result) + +| Model | Result | +|---|---| +| gemma-4-E2B-it | **Extension 120 s timeout fired.** Prefill of 23 K @ 190 tok/s = ~120 s; model never got to generate. | + +### Why E4B is much slower than E2B + +`[WARN] [npu] [gemma4] model.mlpackage not found; using CPU prefill` + +Cactus 1.14 ships `vision_encoder.mlpackage` + `audio_encoder.mlpackage` (Apple NPU-optimised) for the encoders, but **does not ship `model.mlpackage`** for the LLM body of the gemma-4 family. So even with `--weights-variant apple`, the text decoder runs on CPU. On CPU, E4B at ~6 tok/s prefill is ~32× slower than E2B at ~190 tok/s — the NPU is doing most of the advertised "apple-npu" speedup. + +The integration guide's 660 tok/s M5+ANE number is accurate for when the mlpackage ships; it just isn't shipped yet for E4B. When it does, E4B should be the right default. + +--- + +## 4. Tool-call format failures on small models + +Our first gemma-4-E2B agent run on example.com produced this in the saved log: + +```json +{ + "stop_reason": "end_turn", + "textContent": "navigate({\"url\": \"https://www.example.com\"})", + "toolCalls": [] +} +``` + +The model knew what to do. It just emitted the tool call as plain text in the response field instead of as a structured `function_calls[]`. Cactus's grammar didn't pick it up. `confidence: 0.98` — the model was confident; the protocol was wrong. + +### Fix + +Four lines at the top of the system prompt: + +> **HOW TO INVOKE TOOLS — READ THIS FIRST** +> When you decide to use a tool, you MUST emit it through the structured function-calling mechanism. NEVER write a tool invocation as plain text — text like `navigate({"url": "..."})` is treated as your final answer and the tool will not execute. + +After this nudge, the same task ran in 187 s and correctly called `navigate → read_page → finish`. Output: "The page title is Example Domain." 3 turns, 3 structured tool calls, 0 format errors. + +### Takeaway + +Small (~2B) generalist models like gemma-4-E2B know what to do but don't reliably follow the tool-call grammar without explicit prompt-level pressure. Specialist models (FunctionGemma, Qwen3.5) emit structured calls more reliably but are less intelligent about which tool to pick. For this project we went with gemma-4-E2B + the prompt nudge. + +--- + +## 5. "Hybrid Router" / `cloud_handoff` — what it actually is + +From the integration guide: + +> Passing `auto_handoff: true` to `cactus_complete` makes the engine **itself** call Cactus's cloud endpoint when it decides to hand off. That endpoint: +> - Default URL: `https://104.198.76.3/api/v1` (hardcoded in `ffi/cactus_cloud.cpp:297`). +> - GCP VM. TLS cert is self-signed. +> - Backend model: hardcoded `gemini-2.5-flash`. + +We did not exercise the built-in handoff. We followed the guide's "Option B" — run with `auto_handoff: false`, catch `cloud_handoff: true` in our wrapper, throw a sentinel error, and route the caller to whichever cloud provider it wants (Gemini via AI Studio, Anthropic, Vertex, etc.). + +Also: the handoff trigger is purely **token-distribution confidence**. Default threshold 0.7. It doesn't measure "did the model solve the user's problem." A confidently hallucinating small model cruises past the threshold. In our tests gemma-4-E2B returned `confidence: 0.98+` on every single call including the ones where it emitted plain-text tool calls. Handoff never would have fired. + +**Recommendation:** treat `cloud_handoff` as "model isn't sure about its next token," not "model isn't sure about the answer." It's useful for catching obvious failures (gibberish, generation stuck), not for quality routing. Real quality routing is an application-level decision. + +--- + +## 6. Where Cactus actually fits in *this* project + +We tried Cactus in two places: + +### 6a. Browser agent LLM (the hard mode) — *doesn't fit* + +- System prompt alone is 6.7 K tokens (agent behavior + 13 tool defs). +- A single `read_page` on a real site (LinkedIn, Gmail) adds 15–25 K tokens to the conversation. +- At 190 tok/s prefill, each agent step is 35–60 s; hitting 120 s timeout on big-DOM turns is routine. +- Extension's `api.js` has a 120 s per-call timeout; we can't raise it without risk. + +We switched the browser path to Gemini 2.5 Flash via AI Studio. Same pipeline, ~4 s per task. Confirmed working. + +### 6b. Intent layer + voice STT (the natural fit) — *fits, but not load-bearing today* + +Current state: Cactus is a *cold fallback* on both legs. It only runs if Whisper or Gemini errors out. + +Better state for the hackathon narrative: **Cactus primary on both, cloud only as escalation.** + +- **Voice STT**: flip `voice/transcribe.py` — Cactus Parakeet primary, Whisper fallback. Parakeet's per-call inference is 0.03 s; the cold-start dominates if you don't pre-warm at startup (`warmup()` is already the pattern for Whisper). +- **Intent parser**: flip `intent/parser.py` — Cactus primary via sidecar (keeps model warm, ~200 ms/call), Gemini only when `confidence < 0.7` or JSON parse fails. This is the Hybrid Router pattern the integration guide pitched, done application-side. + +### 6c. PII / privacy gate (the killer app) — *fits best, not built* + +Before the browser task string leaves the laptop for a cloud LLM, run it through Cactus: classify whether it contains PII (salary, SSN-ish, credentials), and either redact or surface approval. This is: + +- Short prompt (a few hundred tokens). +- Pure classification — gemma-4-E2B wheelhouse. +- **Cannot be done in cloud** — the cloud is what we're protecting the data from. +- Demo-legible: "only sanitised task descriptions reach Gemini; your resume contents, contact names, and salary numbers stay on the laptop." + +Scope: ~90 min. Would make Cactus load-bearing on every command. + +--- + +## 7. Cactus strengths and weaknesses, one-liners + +### Good at + +- Short-context (<2 K tokens) text classification and structured extraction. +- Function calling when tools fit in one-shot prompts and the model is big enough. +- On-device voice (Parakeet via `cactus transcribe`). +- Mobile-first (their React Native / Swift / Kotlin SDKs are first-class). +- Tight control over decoding (tool RAG filtering, force_tools, stop_sequences) for protocol-sensitive tasks. + +### Bad at + +- Prefill on big prompts without the NPU mlpackage. CPU at ~190 tok/s on E2B, ~6 tok/s on E4B. +- Quality ceiling at 2B params for multi-step planning (confident hallucinations). +- Developer ergonomics: bare ctypes Python API, JSON-string arguments, schemas documented only in the engine repo. +- The hybrid handoff promise in its current form (`auto_handoff: true`) — hardcoded GCP IP, self-signed TLS, not production-usable. +- Competing with OS-baked models (Apple Intelligence, Gemini Nano in Chrome) on "zero-integration-cost on-device LLM" — those are coming. + +--- + +## 8. Recommendations + +### For Cactus + +1. **Ship the `model.mlpackage` for the full gemma-4 family.** Without it, the "Apple NPU" pitch is encoder-only. With it, E4B becomes the reasonable default. +2. **Teach `cactus.py` to honour `CACTUS_LIB_PATH`.** Or have the brew formula symlink to where the shim looks. The current mismatch is the first pothole new developers hit. +3. **Update or retract the integration guide in circulation** — the `cactus_complete` kwargs example doesn't match the shipping Python API. Reached by more than one team today. +4. **Document `options_json` schema in the Python SDK docstring**, not only in `docs/cactus_engine.md`. Python devs expect the signature to be on the function. +5. **Reframe `cloud_handoff`**. In the pitch it sounds like quality routing; in reality it's token-distribution uncertainty. That's a useful signal for stuck-generation detection, not quality control. Different docs. +6. **Publish OpenAI-compatible endpoints from the Python SDK** — a `chat.completions.create`-shaped wrapper would let most existing agent code drop Cactus in with no changes. + +### For this project (post-hackathon, if continued) + +1. **Move intent parsing and voice STT to Cactus-primary.** They're the natural fits and they're almost-already wired. +2. **Build the PII gate (§6c).** This is where Cactus does work no cloud model can do for this product. +3. **Leave the browser agent on Gemini** until `gemma-4-E4B-it` with NPU prefill is available. Then re-evaluate. +4. **Keep the sidecar pattern.** The FastAPI wrapper solved the JSON-API / bindings / tempfile / lazy-import problem cleanly and is portable across languages. +5. **Wire the `await_confirmation` tool in the extension.** It's currently unwired, so the "pauses for your approval" line in the README is aspirational. Without it the confirmation gate never fires. + +--- + +## 9. Files to read, in this branch + +- `scripts/cactus_server.py` — sidecar wrapping the bare Python FFI. +- `executors/browser/agent/src/background/modules/providers/cactus-provider.js` — extension-side translator (Anthropic content blocks ↔ Cactus wire format with sentinel-token tool calls). +- `executors/browser/agent/server/src/llm/cactus.ts` — Node-side provider (used by the server-side agent loop; only the side-channel `mcp_get_info` / `mcp_escalate` path). +- `executors/browser/agent/src/background/modules/system-prompt.js` — the "HOW TO INVOKE TOOLS" preamble that fixed gemma's format failures. +- `~/Downloads/browser-agent/2026-04-19T*/log.json` — turn-by-turn logs from every real run, including the ones that failed. Useful for comparing gemma vs gemini behaviour on the same task. + +--- + +Written at the end of day-1 of the hackathon, in good faith, from an engineer who wanted Cactus to work harder than it did today and still thinks there are genuine wins here — just narrower than the first pass suggested. diff --git a/Ali/executors/browser/__init__.py b/Ali/executors/browser/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/Ali/executors/browser/agent/UPSTREAM.md b/Ali/executors/browser/agent/UPSTREAM.md new file mode 100644 index 00000000..3853b33e --- /dev/null +++ b/Ali/executors/browser/agent/UPSTREAM.md @@ -0,0 +1,27 @@ +# Upstream pin + +Vendored from: https://github.com/cactus-compute/llm-in-chrome (or local copy at /Users/apple/Dev/llm-in-chrome) +Commit SHA: 401364575626c4daa5db3eefbe565374cfecd130 +Vendored on: 2026-04-18T22:59:12Z + +## Files we modified after copy + +- `server/src/llm/client.ts` — replaced multi-provider routing with single Cactus branch +- `server/src/llm/cactus.ts` — NEW; Cactus provider +- `server/src/index.ts` — stripped imports for deleted modules (managed, license, telemetry, credentials) + +## Files we deleted from the copy + +- `server/src/managed/` (entire dir) +- `server/src/license/` (entire dir) +- `server/src/native-host/` (entire dir) +- `server/src/cli/{managed-client,setup,doctor,detect-credentials}.ts` and detect-credentials.test.ts +- `server/src/relay/api-proxy.ts` +- `server/src/telemetry.ts` +- `server/src/llm/{vertex,credentials}.ts` + +## Re-sync + +To rebase on a newer upstream, repeat the `cp` commands in +`docs/superpowers/plans/2026-04-18-cactus-browse-swap.md` Task 1 then re-apply +the modifications listed above. diff --git a/Ali/executors/browser/agent/icons/icon-128.png b/Ali/executors/browser/agent/icons/icon-128.png new file mode 100644 index 00000000..b85461c7 Binary files /dev/null and b/Ali/executors/browser/agent/icons/icon-128.png differ diff --git a/Ali/executors/browser/agent/icons/icon-16.png b/Ali/executors/browser/agent/icons/icon-16.png new file mode 100644 index 00000000..249479c8 Binary files /dev/null and b/Ali/executors/browser/agent/icons/icon-16.png differ diff --git a/Ali/executors/browser/agent/icons/icon-32.png b/Ali/executors/browser/agent/icons/icon-32.png new file mode 100644 index 00000000..fb80a841 Binary files /dev/null and b/Ali/executors/browser/agent/icons/icon-32.png differ diff --git a/Ali/executors/browser/agent/icons/icon-48.png b/Ali/executors/browser/agent/icons/icon-48.png new file mode 100644 index 00000000..1cc5c532 Binary files /dev/null and b/Ali/executors/browser/agent/icons/icon-48.png differ diff --git a/Ali/executors/browser/agent/manifest.json b/Ali/executors/browser/agent/manifest.json new file mode 100644 index 00000000..efd0a154 --- /dev/null +++ b/Ali/executors/browser/agent/manifest.json @@ -0,0 +1,69 @@ +{ + "manifest_version": 3, + "name": "YC Voice Agent — Browser", + "version": "0.1.0", + "description": "Browser arm of the YC Voice Agent.", + + "icons": { + "16": "icons/icon-16.png", + "32": "icons/icon-32.png", + "48": "icons/icon-48.png", + "128": "icons/icon-128.png" + }, + + "permissions": [ + "activeTab", + "scripting", + "storage", + "debugger", + "tabs", + "tabGroups", + "sidePanel", + "downloads", + "identity", + "nativeMessaging", + "alarms" + ], + + "host_permissions": [ + "" + ], + + "action": { + "default_title": "YC Voice Agent — Browser", + "default_icon": { + "16": "icons/icon-16.png", + "32": "icons/icon-32.png", + "48": "icons/icon-48.png" + } + }, + + "side_panel": { + "default_path": "sidepanel.html" + }, + + "background": { + "service_worker": "src/background/service-worker.js", + "type": "module" + }, + + "content_scripts": [ + { + "matches": [""], + "js": [ + "src/content/accessibility-tree.js" + ], + "run_at": "document_start", + "all_frames": true + }, + { + "matches": [""], + "js": [ + "src/content/content.js", + 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|| ^4" + } + } + } +} diff --git a/Ali/executors/browser/agent/server/package.json b/Ali/executors/browser/agent/server/package.json new file mode 100644 index 00000000..878589e5 --- /dev/null +++ b/Ali/executors/browser/agent/server/package.json @@ -0,0 +1,69 @@ +{ + "name": "hanzi-browse", + "version": "2.4.0", + "description": "Give your AI agent a real browser — click, type, fill forms, test workflows, post content, and read authenticated pages", + "license": "PolyForm-Noncommercial-1.0.0", + "author": "hanzili", + "repository": { + "type": "git", + "url": "https://github.com/hanzili/hanzi-browse.git" + }, + "type": "module", + "bin": { + "hanzi-browse": "./dist/index.js", + "hanzi-browser": "./dist/cli.js", + "hanzi-relay": "./dist/relay/server.js" + }, + "files": [ + "dist", + "skills", + "README.md" + ], + "scripts": { + "build": "tsc && rm -rf dist/managed/templates && cp -r src/managed/templates dist/managed/templates && cp src/agent/domain-skills.json dist/agent/domain-skills.json && cd dashboard && npm run build", + "build:server": "tsc", + "build:dashboard": "cd dashboard && npm run build", + "dev": "tsc --watch", + "start": "node dist/index.js", + "cli": "node dist/cli.js", + "test": "vitest run", + "test:live": "npx tsx test/test-live.ts", + "test:followup": "npx tsx test/test-followup.ts", + "eval:domain": "tsx evals/domain-runner.ts", + "eval:domain:managed": "tsx evals/domain-runner-managed.ts", + "eval:skill-recall": "tsx evals/skill-recall.ts" + }, + "dependencies": { + "@modelcontextprotocol/sdk": "^1.25.3", + "@sentry/node": "^10.46.0", + "better-auth": "^1.5.5", + "cron-parser": "^5.5.0", + "pg": "^8.11.3", + "posthog-node": "^5.21.2", + "stripe": "^20.4.1", + "undici": "^7.24.5", + "ws": "^8.19.0" + }, + "devDependencies": { + "@types/node": "^20.11.0", + "@types/pg": "^8.18.0", + "@types/ws": "^8.18.1", + "tsx": "^4.21.0", + "typescript": "^5.3.0", + "vitest": "^4.1.1", + "yaml": "^2.8.3" + }, + "engines": { + "node": ">=18.0.0" + }, + "keywords": [ + "mcp", + "browser", + "chrome", + "automation", + "claude", + "model-context-protocol", + "browser-automation", + "web-agent" + ] +} diff --git a/Ali/executors/browser/agent/server/src/agent/domain-knowledge.test.ts b/Ali/executors/browser/agent/server/src/agent/domain-knowledge.test.ts new file mode 100644 index 00000000..e6124222 --- /dev/null +++ b/Ali/executors/browser/agent/server/src/agent/domain-knowledge.test.ts @@ -0,0 +1,36 @@ +import { describe, it, expect } from "vitest"; +import { getDomainSkill, getAllDomainSkills } from "./domain-knowledge.js"; + +describe("getDomainSkill", () => { + it("matches exact hostname", () => { + const e = getDomainSkill("https://x.com/home"); + expect(e?.domain).toBe("x.com"); + }); + + it("matches subdomain via endsWith", () => { + const e = getDomainSkill("https://www.linkedin.com/in/me"); + expect(e?.domain).toBe("linkedin.com"); + }); + + it("returns null for unknown domain", () => { + expect(getDomainSkill("https://unknown-site-xyz.test/")).toBeNull(); + }); +}); + +describe("getAllDomainSkills", () => { + it("exposes lastVerified and goldenTasks fields on seeded entries", () => { + const all = getAllDomainSkills(); + const seeded = all.find(e => typeof e.lastVerified === "string"); + expect(seeded).toBeDefined(); + expect(typeof seeded!.goldenTasks).toBe("string"); + }); + + it("loads all 21 entries including unseeded ones (nullable new fields)", () => { + const all = getAllDomainSkills(); + expect(all.length).toBeGreaterThan(10); + for (const e of all) { + expect(typeof e.domain).toBe("string"); + expect(typeof e.skill).toBe("string"); + } + }); +}); diff --git a/Ali/executors/browser/agent/server/src/agent/domain-knowledge.ts b/Ali/executors/browser/agent/server/src/agent/domain-knowledge.ts new file mode 100644 index 00000000..1cbe5f59 --- /dev/null +++ b/Ali/executors/browser/agent/server/src/agent/domain-knowledge.ts @@ -0,0 +1,54 @@ +/** + * Domain-specific knowledge for the agent loop. + * Single source of truth — shared between server (managed API, MCP) + * and extension (via import at build time). + */ + +import { readFileSync } from "fs"; +import { fileURLToPath } from "url"; +import { dirname, join } from "path"; + +interface DomainEntry { + domain: string; + antiBot?: boolean; + /** ISO date (YYYY-MM-DD) the golden tasks last passed. */ + lastVerified?: string | null; + /** Path (relative to server/) to the YAML of golden tasks for this domain. */ + goldenTasks?: string | null; + skill: string; +} + +export type { DomainEntry }; + +// Load from shared JSON file +const __filename = fileURLToPath(import.meta.url); +const __dirname = dirname(__filename); +const DOMAIN_SKILLS: DomainEntry[] = JSON.parse( + readFileSync(join(__dirname, "domain-skills.json"), "utf-8") +); + +/** + * Look up domain knowledge for a URL. + * Returns the first matching entry, or null. + */ +export function getDomainSkill(url: string): DomainEntry | null { + try { + const hostname = new URL(url).hostname.toLowerCase(); + return DOMAIN_SKILLS.find( + (d) => hostname === d.domain || hostname.endsWith("." + d.domain) + ) || null; + } catch { + // URL might not be a full URL — try matching as a bare domain + const lower = url.toLowerCase(); + return DOMAIN_SKILLS.find( + (d) => lower.includes(d.domain) + ) || null; + } +} + +/** + * Get all domain skills. Used by extension to import the full list. + */ +export function getAllDomainSkills(): DomainEntry[] { + return DOMAIN_SKILLS; +} diff --git a/Ali/executors/browser/agent/server/src/agent/domain-skills.json b/Ali/executors/browser/agent/server/src/agent/domain-skills.json new file mode 100644 index 00000000..925ecb5e --- /dev/null +++ b/Ali/executors/browser/agent/server/src/agent/domain-skills.json @@ -0,0 +1,160 @@ +[ + { + "domain": "mail.google.com", + "skill": "Gmail best practices:\n- To open an email, click directly on the email subject/preview text, NOT the checkbox or star\n- Use keyboard shortcuts: 'c' to compose, 'r' to reply, 'a' to reply all, 'f' to forward, 'e' to archive\n- To search, use the search bar at the top with operators like 'from:', 'to:', 'subject:', 'is:unread'\n- Reading pane may be on the right or below depending on user settings - check which layout is active\n- Verification codes are often in emails from 'noreply@' addresses with subjects containing 'verification', 'code', or 'confirm'", + "lastVerified": "2026-04-17", + "goldenTasks": "evals/domain/mail.google.com.yaml" + }, + { + "domain": "docs.google.com", + "skill": "Google Docs best practices:\n- This is a canvas-based application - use screenshots to see content, read_page may not capture all text\n- Use keyboard shortcuts: Cmd/Ctrl+B for bold, Cmd/Ctrl+I for italic, Cmd/Ctrl+K for links\n- To navigate, use Cmd/Ctrl+F to find text, then click on the result\n- For editing, click to place cursor then type - triple-click to select a paragraph\n- Access menus via the menu bar at the top (File, Edit, View, Insert, Format, etc.)", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "sheets.google.com", + "skill": "Google Sheets best practices:\n- Click on cells to select them, double-click to edit cell content\n- Use Tab to move right, Enter to move down, arrow keys to navigate\n- Formulas start with '=' - e.g., =SUM(A1:A10), =VLOOKUP(), =IF()\n- Use Cmd/Ctrl+C and Cmd/Ctrl+V for copy/paste\n- Select ranges by clicking and dragging, or Shift+click for range selection", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "github.com", + "skill": "GitHub best practices:\n- Repository navigation: Code tab for files, Issues for bug tracking, Pull requests for code review\n- To view a file, click on the filename in the file tree\n- Use 't' to open file finder, 'l' to jump to a line\n- In PRs: 'Files changed' tab shows diffs, 'Conversation' tab shows comments\n- Use the search bar with qualifiers: 'is:open is:pr', 'is:issue label:bug'", + "lastVerified": "2026-04-17", + "goldenTasks": "evals/domain/github.com.yaml" + }, + { + "domain": "reddit.com", + "antiBot": true, + "skill": "Reddit UI patterns:\n- Posts are listed in a feed - click on post title to view full post and comments\n- Comments are nested/threaded - each comment has its own reply button underneath\n- Upvote (up arrow) and downvote (down arrow) buttons are to the left of each post/comment\n- To comment, scroll to comment box at top of comments section, or click reply under a specific comment\n- Use the search bar at top to find subreddits or posts\n- r/subredditname format for community names", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "linkedin.com", + "antiBot": true, + "skill": "LinkedIn UI patterns:\n\n## Messaging & Connections\n- To message someone: first check if you're connected (1st degree) - if not, send a connection request first\n- Connection request: go to their profile, click 'Connect' button, optionally add a note\n- Once connected, use the 'Message' button on their profile or go to Messaging tab\n- InMail (messaging non-connections) requires Premium subscription\n\n## Easy Apply Forms\n- Contact Info page is pre-filled from LinkedIn profile - don't try to modify, just click Next\n- Modal forms may need scrolling to see all content and buttons\n- Use screenshots over read_page for modals - accessibility tree often misses modal content\n\n## Navigation\n- Main tabs: Home (feed), My Network, Jobs, Messaging, Notifications\n- Job search: Jobs tab → filter by location, experience level, date posted\n- 'Easy Apply' = apply within LinkedIn; 'Apply' = external site\n- Profile sections are collapsible - click 'Show all' to expand", + "lastVerified": "2026-04-17", + "goldenTasks": "evals/domain/linkedin.com.yaml" + }, + { + "domain": "indeed.com", + "skill": "Indeed best practices:\n- Search for jobs using the 'What' and 'Where' fields at the top\n- Filter results by date posted, salary, job type, experience level\n- Click job title to view full description\n- 'Apply now' or 'Apply on company site' buttons are typically on the right panel\n- Sign in to save jobs and track applications", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "calendar.google.com", + "skill": "Google Calendar best practices:\n- Click on a time slot to create a new event\n- Drag events to reschedule them\n- Click on an event to view details, edit, or delete\n- Use the mini calendar on the left to navigate to different dates\n- Keyboard: 'c' to create event, 't' to go to today, arrow keys to navigate", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "drive.google.com", + "skill": "Google Drive best practices:\n- Double-click files to open them, single-click to select\n- Right-click for context menu (download, share, rename, etc.)\n- Use the search bar to find files by name or content\n- Create new items with the '+ New' button on the left\n- Drag and drop to move files between folders", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "notion.so", + "skill": "Notion best practices:\n- Click to place cursor, type '/' to open command menu\n- Drag blocks using the ⋮⋮ handle on the left\n- Use sidebar for navigation between pages\n- Toggle blocks expand/collapse on click\n- Databases can be viewed as table, board, calendar, etc.", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "figma.com", + "skill": "Figma best practices:\n- This is a canvas-based design tool - always use screenshots to see content\n- Use 'V' for select tool, 'R' for rectangle, 'T' for text\n- Zoom with Cmd/Ctrl+scroll or Cmd/Ctrl++ and Cmd/Ctrl+-\n- Navigate frames in the left sidebar\n- Right-click for context menus and additional options", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "slack.com", + "skill": "Slack best practices:\n- Channels listed in left sidebar - click to switch\n- Cmd/Ctrl+K to quickly switch channels/DMs\n- @ mentions notify users, # references channels\n- Thread replies keep conversations organized\n- Use the search bar to find messages, files, and people", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "twitter.com", + "antiBot": true, + "skill": "See x.com — twitter.com redirects to x.com.", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "x.com", + "antiBot": true, + "skill": "X/Twitter — verified patterns (updated 2026-03-30)\n\n## Reading pages (CRITICAL)\n- X loads content asynchronously — page looks empty for 3-5 seconds after navigation.\n- read_page often returns ONLY \"To view keyboard shortcuts\" — tweets haven't loaded yet.\n- DO NOT re-navigate to the same URL. That resets loading and makes it worse.\n- Instead: wait 5 seconds, then use get_page_text — it reads visible text and is more reliable.\n- If get_page_text returns nothing, scroll down once and try again.\n\n## Search\n- URL: x.com/search?q={encoded_query}&src=typed_query&f=live\n- After navigating, wait 5 seconds, then get_page_text (NOT read_page).\n- Scroll down once to load more tweets, then get_page_text again.\n- Tweet URLs in page text follow pattern: /status/{id}\n\n## Text input (CRITICAL — Draft.js)\n- form_input DOES NOT WORK — Draft.js ignores programmatic input.\n- computer type action GARBLES TEXT.\n- ONLY RELIABLE METHOD — use javascript_tool:\n document.querySelector('[data-testid=\"tweetTextarea_0\"]').focus();\n document.execCommand('insertText', false, 'your reply text here');\n- Always verify text appeared by reading after insertion.\n\n## Replying to a tweet\n1. Navigate to tweet URL (x.com/{handle}/status/{id})\n2. Wait 3 seconds, read the page\n3. Click the reply/comment icon (speech bubble) in the action bar\n4. Use javascript_tool to insert text (see above)\n5. Verify text appeared, then click blue \"Reply\" button\n6. Wait 2 seconds to confirm reply posted\n\n## Known traps\n- DO NOT scroll looking for \"Post your reply\" — reply box appears after clicking comment icon\n- x.com/compose/post may open — that's fine, type and click Reply there\n- \"Leave site?\" dialog — ALWAYS click Cancel, finish posting first\n- Reply button is disabled until text is entered — verify first\n- Space replies 15+ seconds apart (rate limiting)\n- NEVER navigate to the same URL you're already on", + "lastVerified": "2026-04-17", + "goldenTasks": "evals/domain/x.com.yaml" + }, + { + "domain": "apply.ycombinator.com", + "skill": "YC application form patterns:\n- Sections are progressive: company info, founders, idea, traction, submit.\n- Resume upload: the 'Upload resume' button opens a native macOS file dialog. After clicking, wait 1.5s, then call computer_os with action='drive_file_picker' and the provided file path.\n- Verify upload by re-reading the page and confirming the filename appears near the upload button.\n- Company name is a plain text input. Founder emails are plain text (not tag-based).\n- The final submit button says 'Submit application'. If the task explicitly asks to submit, click it. Otherwise, STOP BEFORE the submit button and report that the form is ready for review.\n- Batch selection: the target batch (e.g., Fall 2026) is usually a dropdown with text like 'W26' or 'F26' or the human-readable batch name. Read all options before selecting.", + "lastVerified": "2026-04-18", + "goldenTasks": null + }, + { + "domain": "amazon.com", + "skill": "Amazon UI patterns:\n- Prefer the top search bar or a direct search URL for product discovery\n- The first fold may be dominated by sponsored modules or Amazon brand carousels before standard results\n- Result cards can show total price, unit price, ratings, delivery promises, variation links, and inline Add to Cart buttons all at once\n- Watch carefully for subtle labels such as 'Sponsored' or 'Featured from Amazon brands'\n- Location/shipping prompts can change delivery wording and result context, so verify destination-sensitive text before extracting prices", + "lastVerified": "2026-04-17", + "goldenTasks": "evals/domain/amazon.com.yaml" + }, + { + "domain": "ebay.com", + "skill": "eBay UI patterns:\n- Search results usually show title, condition, price, shipping, and location directly on the card\n- Headline price is often incomplete until you also check shipping cost, coupon text, and 'Best Offer' language\n- Sponsored placements and featured carousels can interrupt the organic result list\n- Use condition and shipping origin early to filter out weak matches\n- Be cautious with range prices and urgency labels like 'Last one' or watcher counts; they do not guarantee a clean fixed-price purchase path", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "walmart.ca", + "antiBot": true, + "skill": "Walmart.ca UI patterns:\n- Search results often expose enough information to compare products before opening a product page\n- Cards commonly include brand, title, price, ratings, fulfillment messaging, and promo details such as Subscribe to Save or pickup thresholds\n- Walmart.com may first present a storefront or region-selection step and later a human-verification blocker ('Press & Hold' challenge); validation was more reliable on Walmart.ca\n- On Walmart.ca product pages, verify one-time price separately from Subscribe to Save pricing and check pickup, express delivery, and standard delivery messages individually\n- Treat promo labels, fulfillment thresholds, and returns messaging as separate signals and verify them individually\n- If you hit a 'Press & Hold' or 'verify you are human' challenge, STOP and tell the user — never attempt to bypass", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "target.com", + "skill": "Target UI patterns:\n- Result cards usually include title, review count, price, promo messaging, and a persistent Add to Cart button\n- Price formatting can mix ranges, sale pricing, regular pricing, and per-unit math, so read the full price block carefully\n- Promo text such as Target gift card offers or 'Highly rated' badges appears frequently and can distract from the base price\n- Fulfillment filters are easy to see near the top, but card-level availability may still need a deeper click\n- Search results can include adjacent-category items, so confirm the exact product type from the title before acting", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "zillow.com", + "antiBot": true, + "skill": "Zillow UI patterns (rentals):\n- Sign in first for full contact info and saved searches; anonymous users see degraded data\n- Use 'For Rent' in the top nav, then refine by price, beds, and 'Move-in Date'\n- Results have a split map + list view — switch to list view for cleaner data extraction\n- Listing cards include price, beds/baths, address, and 'Apply' or 'Request a tour' buttons\n- 'Request a tour' and 'Contact' buttons submit forms — draft the message and wait for explicit user approval before clicking submit\n- Never enter SSN, payment info, or background check data without confirming the user is on an official Zillow Application flow\n- Zillow frequently serves a CAPTCHA / 'Press & Hold' challenge for automated traffic — if you hit one, STOP and tell the user, do not bypass", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "apartments.com", + "skill": "Apartments.com UI patterns:\n- Top filter bar: location, price, beds, move-in date, amenities — apply them before reading results\n- Listing cards include price range, beds/baths, address, and a 'Send Message' or 'Contact' button\n- Many listings have a built-in multi-step application flow — each step is clearly labeled; stop before 'Submit Application' and confirm with the user\n- 'Send Message' opens an inline form — draft the message, show it to the user, wait for approval before submitting\n- Pricing is often shown as a range ($X-$Y) because individual units vary; click into the listing for per-unit prices\n- Response times for large property managers are usually fast (hours); individual landlords slower\n- Do not enter SSN, credit-card, or bank info without explicit user confirmation that they want to proceed with a real application", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "craigslist.org", + "skill": "Craigslist UI patterns (apartments / housing):\n- URL pattern: https://[city].craigslist.org/search/apa?minAsk={min}&maxAsk={max}&bedrooms={n}\n- Sort by 'newest' to avoid stale listings — older listings are frequently scams or already rented\n- Listings may or may not have photos; listings without photos are higher risk, flag them\n- Contact is always via an anonymized email relay — no built-in application flow\n- Scam flags to warn the user about: price >25% below market, 'owner overseas', 'send deposit to hold', asks to text/WhatsApp before viewing, generic stock photos\n- Never follow links off craigslist for a 'verified listings site' — those are almost always phishing\n- Show the user any inquiry message before sending, and wait for explicit approval", + "lastVerified": null, + "goldenTasks": null + }, + { + "domain": "chatgpt.com", + "antiBot": true, + "skill": "ChatGPT (chatgpt.com) — composer is a ProseMirror contenteditable, NOT a + +
+ + +
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+ + + + diff --git a/Ali/executors/browser/agent/src/sidepanel/sidepanel.js b/Ali/executors/browser/agent/src/sidepanel/sidepanel.js new file mode 100644 index 00000000..8f42f095 --- /dev/null +++ b/Ali/executors/browser/agent/src/sidepanel/sidepanel.js @@ -0,0 +1,1475 @@ +/** + * Side Panel - browser sub-agent chat + */ + +// Provider configurations +const PROVIDERS = { + anthropic: { + name: 'Anthropic', + baseUrl: 'https://api.anthropic.com/v1/messages', + models: [ + { id: 'claude-opus-4-5-20251101', name: 'Opus 4.5' }, + { id: 'claude-opus-4-20250514', name: 'Opus 4' }, + { id: 'claude-sonnet-4-20250514', name: 'Sonnet 4' }, + { id: 'claude-haiku-4-5-20251001', name: 'Haiku 4.5' }, + ], + }, + openai: { + name: 'OpenAI', + baseUrl: 'https://api.openai.com/v1/chat/completions', + models: [ + { id: 'gpt-4o', name: 'GPT-4o' }, + { id: 'gpt-5', name: 'GPT-5' }, + { id: 'gpt-5-mini', name: 'GPT-5 Mini' }, + { id: 'gpt-4.1', name: 'GPT-4.1' }, + { id: 'o3', name: 'o3' }, + { id: 'o4-mini', name: 'o4-mini' }, + ], + }, + google: { + name: 'Google', + baseUrl: 'https://generativelanguage.googleapis.com/v1beta/models', + models: [ + { id: 'gemini-3-pro-preview', name: 'Gemini 3 Pro (Preview)' }, + { id: 'gemini-2.5-flash', name: 'Gemini 2.5 Flash' }, + { id: 'gemini-2.5-pro', name: 'Gemini 2.5 Pro' }, + ], + }, + openrouter: { + name: 'OpenRouter', + baseUrl: 'https://openrouter.ai/api/v1/chat/completions', + models: [ + { id: 'qwen/qwen3-vl-235b-a22b-thinking', name: 'Qwen3 VL 235B (Reasoning)' }, + { id: 'moonshotai/kimi-k2.5', name: 'Kimi K2.5 (Reasoning)' }, + { id: 'mistralai/mistral-large-2512', name: 'Mistral Large 3' }, + ], + }, +}; + +// Elements +const messagesEl = document.getElementById('messages'); +const inputEl = document.getElementById('input'); +const sendBtn = document.getElementById('send-btn'); +const modelSelector = document.getElementById('model-selector'); +const modelSelectorBtn = document.getElementById('model-selector-btn'); +const modelDropdown = document.getElementById('model-dropdown'); +const modelList = document.getElementById('model-list'); +const currentModelNameEl = document.getElementById('current-model-name'); +const newChatBtn = document.getElementById('new-chat-btn'); +const settingsBtn = document.getElementById('settings-btn'); +const settingsModal = document.getElementById('settings-modal'); +const settingsSave = document.getElementById('settings-save'); +const settingsClose = document.getElementById('settings-close'); +const planModal = document.getElementById('plan-modal'); +const planDomains = document.getElementById('plan-domains'); +const planSteps = document.getElementById('plan-steps'); +const planApprove = document.getElementById('plan-approve'); +const planCancel = document.getElementById('plan-cancel'); +const askToggle = document.getElementById('ask-toggle'); +const stopBtn = document.getElementById('stop-btn'); +const inputContainer = document.getElementById('input-container'); +const imagePreview = document.getElementById('image-preview'); + +// State +let isRunning = false; +let askBeforeActing = true; +let currentToolIndicator = null; +let currentStreamingMessage = null; +let completedSteps = []; // Array of { tool, input, result, description } +let pendingStep = null; // Current executing step +let stepsSection = null; +let attachedImages = []; // Array of base64 data URLs + +// Session state - managed by UI +let sessionTabGroupId = null; // Tab group for current session + +// Config state +let providerKeys = {}; // { anthropic: 'sk-...', openai: 'sk-...', ... } +let customModels = []; // [{ name, baseUrl, modelId, apiKey }, ...] +let availableModels = []; // Combined list of { name, provider, modelId, baseUrl, apiKey } +let currentModelIndex = 0; +let selectedProvider = null; + +// Domain skills state +let userSkills = []; // [{ domain: 'example.com', skill: '...' }, ...] +let builtInSkills = []; // Loaded from service worker +let editingSkillIndex = -1; // -1 = adding new, >= 0 = editing existing + +// Initialize +document.addEventListener('DOMContentLoaded', async () => { + // Load saved config + await loadConfig(); + + // Auto-resize textarea + inputEl.addEventListener('input', () => { + inputEl.style.height = 'auto'; + inputEl.style.height = Math.min(inputEl.scrollHeight, 150) + 'px'; + }); + + // Handle Enter to send + inputEl.addEventListener('keydown', (e) => { + if (e.key === 'Enter' && !e.shiftKey) { + e.preventDefault(); + sendMessage(); + } + }); + + // Send button + sendBtn.addEventListener('click', sendMessage); + + // Model selector + modelSelectorBtn.addEventListener('click', toggleModelDropdown); + document.addEventListener('click', (e) => { + if (!modelSelector.contains(e.target)) { + closeModelDropdown(); + } + }); + + // New chat + newChatBtn.addEventListener('click', clearChat); + + // Settings + settingsBtn.addEventListener('click', openSettings); + settingsClose.addEventListener('click', closeSettings); + settingsSave.addEventListener('click', saveSettings); + + // Settings tabs + document.querySelectorAll('.tab').forEach(tab => { + tab.addEventListener('click', () => { + document.querySelectorAll('.tab').forEach(t => t.classList.remove('active')); + document.querySelectorAll('.tab-content').forEach(c => c.classList.remove('active')); + tab.classList.add('active'); + document.getElementById(`tab-${tab.dataset.tab}`).classList.add('active'); + }); + }); + + // Provider cards + document.querySelectorAll('.provider-card').forEach(card => { + card.addEventListener('click', () => selectProvider(card.dataset.provider)); + }); + + // Add custom model + document.getElementById('add-custom-btn').addEventListener('click', addCustomModel); + + // Domain skills UI + document.getElementById('add-skill-btn').addEventListener('click', addOrUpdateSkill); + document.getElementById('add-skill-toggle').addEventListener('click', () => showSkillForm(true)); + document.getElementById('skill-form-close').addEventListener('click', hideSkillForm); + document.getElementById('skill-form-cancel').addEventListener('click', hideSkillForm); + + // CLI import/logout (Claude Code Plan) + document.getElementById('import-cli-btn').addEventListener('click', handleImportCLI); + document.getElementById('cli-logout-btn').addEventListener('click', handleCLILogout); + + // Codex import/logout (Codex Plan) + document.getElementById('import-codex-btn').addEventListener('click', handleImportCodex); + document.getElementById('codex-logout-btn').addEventListener('click', handleCodexLogout); + + // Ask before acting toggle + askToggle.addEventListener('click', () => { + askBeforeActing = !askBeforeActing; + askToggle.classList.toggle('active', askBeforeActing); + }); + + // Plan approval + planApprove.addEventListener('click', () => { + chrome.runtime.sendMessage({ type: 'PLAN_APPROVAL_RESPONSE', payload: { approved: true } }).catch(() => {}); + planModal.classList.add('hidden'); + }); + planCancel.addEventListener('click', () => { + chrome.runtime.sendMessage({ type: 'PLAN_APPROVAL_RESPONSE', payload: { approved: false } }).catch(() => {}); + planModal.classList.add('hidden'); + }); + + // Stop button + stopBtn.addEventListener('click', stopTask); + + // Image drag & drop + inputContainer.addEventListener('dragover', (e) => { + e.preventDefault(); + inputContainer.classList.add('drag-over'); + }); + + inputContainer.addEventListener('dragleave', (e) => { + e.preventDefault(); + inputContainer.classList.remove('drag-over'); + }); + + inputContainer.addEventListener('drop', (e) => { + e.preventDefault(); + inputContainer.classList.remove('drag-over'); + handleImageDrop(e.dataTransfer); + }); + + // Paste image + inputEl.addEventListener('paste', (e) => { + const items = e.clipboardData?.items; + if (items) { + for (const item of items) { + if (item.type.startsWith('image/')) { + e.preventDefault(); + const file = item.getAsFile(); + if (file) readImageFile(file); + break; + } + } + } + }); +}); + +// Listen for messages from service worker +chrome.runtime.onMessage.addListener((message) => { + switch (message.type) { + case 'TASK_UPDATE': handleTaskUpdate(message.update); break; + case 'TASK_COMPLETE': handleTaskComplete(message.result); break; + case 'TASK_ERROR': handleTaskError(message.error); break; + case 'PLAN_APPROVAL_REQUIRED': showPlanApproval(message.plan); break; + case 'SESSION_GROUP_UPDATE': + // Service worker informs us of tab group changes + sessionTabGroupId = message.tabGroupId; + break; + } +}); + +// ============================================ +// CONFIG +// ============================================ + +async function loadConfig() { + const config = await chrome.runtime.sendMessage({ type: 'GET_CONFIG' }); + providerKeys = config.providerKeys || {}; + customModels = config.customModels || []; + currentModelIndex = config.currentModelIndex || 0; + userSkills = config.userSkills || []; + builtInSkills = config.builtInSkills || []; + + await updateCLIStatus(); + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + await updateProviderStatuses(); + renderCustomModelsList(); + renderSkillsList(); +} + +async function buildAvailableModels() { + availableModels = []; + + // Check if Claude OAuth is enabled + const oauthStatus = await chrome.runtime.sendMessage({ type: 'GET_OAUTH_STATUS' }); + const hasOAuth = oauthStatus && oauthStatus.isOAuthEnabled && oauthStatus.isAuthenticated; + + // Check if Codex OAuth is enabled + const codexStatus = await chrome.runtime.sendMessage({ type: 'GET_CODEX_STATUS' }); + const hasCodexOAuth = codexStatus && codexStatus.isAuthenticated; + + // Add Codex Plan models if connected (ChatGPT Pro plan via Codex CLI) + if (hasCodexOAuth) { + const codexModels = [ + { id: 'gpt-5.1-codex-max', name: 'GPT-5.1 Codex Max' }, + { id: 'gpt-5.2-codex', name: 'GPT-5.2 Codex' }, + { id: 'gpt-5.1-codex-mini', name: 'GPT-5.1 Codex Mini' }, + { id: 'gpt-5.1-codex', name: 'GPT-5.1 Codex' }, + { id: 'gpt-5-codex', name: 'GPT-5 Codex' }, + ]; + for (const model of codexModels) { + availableModels.push({ + name: `${model.name} (Codex Plan)`, + provider: 'codex', + modelId: model.id, + baseUrl: 'https://chatgpt.com/backend-api/codex/responses', + apiKey: null, + authMethod: 'codex_oauth', + }); + } + } + + // Add models from configured providers + for (const [providerId, provider] of Object.entries(PROVIDERS)) { + const hasApiKey = providerKeys[providerId]; + + // Special handling for Anthropic: show separate entries for OAuth and API key + if (providerId === 'anthropic') { + // Add OAuth models (Claude Code Plan) if connected + if (hasOAuth) { + for (const model of provider.models) { + availableModels.push({ + name: `${model.name} (Claude Code)`, + provider: providerId, + modelId: model.id, + baseUrl: provider.baseUrl, + apiKey: null, + authMethod: 'oauth', + }); + } + } + + // Add API key models if configured + if (hasApiKey) { + for (const model of provider.models) { + availableModels.push({ + name: `${model.name} (API)`, + provider: providerId, + modelId: model.id, + baseUrl: provider.baseUrl, + apiKey: providerKeys[providerId], + authMethod: 'apikey', + }); + } + } + } else if (providerId === 'openai') { + // OpenAI: label as API to distinguish from Codex Plan + if (hasApiKey) { + for (const model of provider.models) { + availableModels.push({ + name: `${model.name} (API)`, + provider: providerId, + modelId: model.id, + baseUrl: provider.baseUrl, + apiKey: providerKeys[providerId], + }); + } + } + } else { + // Other providers (Google, OpenRouter): just check for API key + if (hasApiKey) { + for (const model of provider.models) { + availableModels.push({ + name: model.name, + provider: providerId, + modelId: model.id, + baseUrl: provider.baseUrl, + apiKey: providerKeys[providerId], + }); + } + } + } + } + + // Add custom models + for (const custom of customModels) { + availableModels.push({ + name: custom.name, + provider: 'custom', + modelId: custom.modelId, + baseUrl: custom.baseUrl, + apiKey: custom.apiKey, + }); + } + + // Ensure index is valid + if (currentModelIndex >= availableModels.length) { + currentModelIndex = 0; + } +} + +async function saveConfig() { + const currentModel = availableModels[currentModelIndex]; + await chrome.runtime.sendMessage({ + type: 'SAVE_CONFIG', + payload: { + providerKeys, + customModels, + currentModelIndex, + userSkills, + // Also set the active model config for the service worker + ...(currentModel ? { + model: currentModel.modelId, + apiBaseUrl: currentModel.baseUrl, + apiKey: currentModel.apiKey, + authMethod: currentModel.authMethod || null, + } : {}), + }, + }); +} + +// ============================================ +// MODEL SELECTOR +// ============================================ + +function toggleModelDropdown() { + if (modelDropdown.classList.contains('hidden')) { + modelDropdown.classList.remove('hidden'); + modelSelector.classList.add('open'); + } else { + closeModelDropdown(); + } +} + +function closeModelDropdown() { + modelDropdown.classList.add('hidden'); + modelSelector.classList.remove('open'); +} + +function updateModelDisplay() { + if (availableModels.length === 0) { + currentModelNameEl.textContent = 'No models'; + return; + } + currentModelNameEl.textContent = availableModels[currentModelIndex]?.name || 'Select model'; +} + +function renderModelList() { + if (availableModels.length === 0) { + modelList.innerHTML = ` +
+ No models configured.
Open Settings to add. +
+ `; + return; + } + + modelList.innerHTML = availableModels.map((model, i) => ` +
+ + + + ${model.name} +
+ `).join(''); + + modelList.querySelectorAll('.model-item').forEach(item => { + item.addEventListener('click', () => { + currentModelIndex = parseInt(item.dataset.index); + updateModelDisplay(); + renderModelList(); + closeModelDropdown(); + saveConfig(); + }); + }); +} + +// ============================================ +// SETTINGS +// ============================================ + +async function openSettings() { + settingsModal.classList.remove('hidden'); + selectedProvider = null; + document.getElementById('provider-config').style.display = 'none'; + document.querySelectorAll('.provider-card').forEach(c => c.classList.remove('active')); + renderCustomModelsList(); + renderSkillsList(); + hideSkillForm(); // Hide and reset skill form when opening + await updateCLIStatus(); // Check OAuth login status +} + +function closeSettings() { + settingsModal.classList.add('hidden'); +} + +function selectProvider(providerId) { + selectedProvider = providerId; + document.querySelectorAll('.provider-card').forEach(c => { + c.classList.toggle('active', c.dataset.provider === providerId); + }); + + const configEl = document.getElementById('provider-config'); + const apiKeyInput = document.getElementById('provider-api-key'); + apiKeyInput.value = providerKeys[providerId] || ''; + configEl.style.display = 'block'; + apiKeyInput.focus(); +} + +async function updateProviderStatuses() { + // Check OAuth status + const oauthStatus = await chrome.runtime.sendMessage({ type: 'GET_OAUTH_STATUS' }); + const hasOAuth = oauthStatus && oauthStatus.isOAuthEnabled && oauthStatus.isAuthenticated; + + for (const providerId of Object.keys(PROVIDERS)) { + const statusEl = document.getElementById(`${providerId}-status`); + + // For Anthropic, show OAuth status + if (providerId === 'anthropic' && hasOAuth) { + statusEl.textContent = 'OAuth Active'; + statusEl.classList.add('configured'); + } else if (providerKeys[providerId]) { + statusEl.textContent = 'Configured'; + statusEl.classList.add('configured'); + } else { + statusEl.textContent = 'Not configured'; + statusEl.classList.remove('configured'); + } + } +} + +async function saveSettings() { + // Save provider key if one is selected + if (selectedProvider) { + const apiKey = document.getElementById('provider-api-key').value.trim(); + if (apiKey) { + providerKeys[selectedProvider] = apiKey; + } else { + delete providerKeys[selectedProvider]; + } + } + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + await updateProviderStatuses(); + await saveConfig(); + closeSettings(); +} + +// CLI import handlers +async function handleImportCLI() { + const btn = document.getElementById('import-cli-btn'); + const statusEl = document.getElementById('cli-status'); + + btn.disabled = true; + document.getElementById('import-cli-btn-text').textContent = 'Connecting...'; + + try { + const response = await chrome.runtime.sendMessage({ type: 'IMPORT_CLI_CREDENTIALS' }); + + if (response.success) { + // Update UI + btn.style.display = 'none'; + document.getElementById('cli-logout-btn').style.display = 'block'; + document.getElementById('cli-status-badge').style.display = 'inline'; + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + } else { + throw new Error(response.error || 'Import failed'); + } + } catch (error) { + statusEl.textContent = error.message; + statusEl.style.display = 'block'; + statusEl.style.color = '#ff6b6b'; + btn.disabled = false; + document.getElementById('import-cli-btn-text').textContent = 'Connect'; + } +} + +async function handleCLILogout() { + try { + await chrome.runtime.sendMessage({ type: 'OAUTH_LOGOUT' }); + + document.getElementById('import-cli-btn').style.display = 'block'; + document.getElementById('import-cli-btn').disabled = false; + document.getElementById('import-cli-btn-text').textContent = 'Connect'; + document.getElementById('cli-logout-btn').style.display = 'none'; + document.getElementById('cli-status-badge').style.display = 'none'; + document.getElementById('cli-status').style.display = 'none'; + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + await updateProviderStatuses(); + } catch (error) { + const statusEl = document.getElementById('cli-status'); + statusEl.textContent = error.message; + statusEl.style.color = '#ff6b6b'; + } +} + +async function updateCLIStatus() { + const response = await chrome.runtime.sendMessage({ type: 'GET_OAUTH_STATUS' }); + + if (response && response.isAuthenticated) { + document.getElementById('import-cli-btn').style.display = 'none'; + document.getElementById('cli-logout-btn').style.display = 'block'; + document.getElementById('cli-status-badge').style.display = 'inline'; + document.getElementById('cli-status').style.display = 'none'; + } else { + document.getElementById('import-cli-btn').style.display = 'block'; + document.getElementById('cli-logout-btn').style.display = 'none'; + document.getElementById('cli-status-badge').style.display = 'none'; + document.getElementById('cli-status').style.display = 'none'; + } + + // Update Codex status too + await updateCodexStatus(); +} + +// Codex import handlers +async function handleImportCodex() { + const btn = document.getElementById('import-codex-btn'); + const statusEl = document.getElementById('codex-status'); + + btn.disabled = true; + document.getElementById('import-codex-btn-text').textContent = 'Connecting...'; + + try { + const response = await chrome.runtime.sendMessage({ type: 'IMPORT_CODEX_CREDENTIALS' }); + + if (!response) { + throw new Error('No response from service worker'); + } + + if (response.success) { + // Update UI + btn.style.display = 'none'; + document.getElementById('codex-logout-btn').style.display = 'block'; + document.getElementById('codex-status-badge').style.display = 'inline'; + statusEl.style.display = 'none'; + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + } else { + throw new Error(response.error || 'Import failed'); + } + } catch (error) { + statusEl.textContent = error.message; + statusEl.style.display = 'block'; + statusEl.style.color = '#ff6b6b'; + btn.disabled = false; + document.getElementById('import-codex-btn-text').textContent = 'Connect'; + } +} + +async function handleCodexLogout() { + try { + await chrome.runtime.sendMessage({ type: 'CODEX_LOGOUT' }); + + document.getElementById('import-codex-btn').style.display = 'block'; + document.getElementById('import-codex-btn').disabled = false; + document.getElementById('import-codex-btn-text').textContent = 'Connect'; + document.getElementById('codex-logout-btn').style.display = 'none'; + document.getElementById('codex-status-badge').style.display = 'none'; + document.getElementById('codex-status').style.display = 'none'; + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + } catch (error) { + const statusEl = document.getElementById('codex-status'); + statusEl.textContent = error.message; + statusEl.style.color = '#ff6b6b'; + } +} + +async function updateCodexStatus() { + const response = await chrome.runtime.sendMessage({ type: 'GET_CODEX_STATUS' }); + + if (response && response.isAuthenticated) { + document.getElementById('import-codex-btn').style.display = 'none'; + document.getElementById('codex-logout-btn').style.display = 'block'; + document.getElementById('codex-status-badge').style.display = 'inline'; + document.getElementById('codex-status').style.display = 'none'; + } else { + document.getElementById('import-codex-btn').style.display = 'block'; + document.getElementById('codex-logout-btn').style.display = 'none'; + document.getElementById('codex-status-badge').style.display = 'none'; + document.getElementById('codex-status').style.display = 'none'; + } +} + +async function addCustomModel() { + const name = document.getElementById('custom-display-name').value.trim(); + const baseUrl = document.getElementById('custom-base-url').value.trim(); + const modelId = document.getElementById('custom-model-id').value.trim(); + const apiKey = document.getElementById('custom-api-key').value.trim(); + + if (!name || !baseUrl || !modelId) { + alert('Please fill in Display Name, Base URL, and Model ID'); + return; + } + + customModels.push({ name, baseUrl, modelId, apiKey }); + + // Clear form + document.getElementById('custom-display-name').value = ''; + document.getElementById('custom-base-url').value = ''; + document.getElementById('custom-model-id').value = ''; + document.getElementById('custom-api-key').value = ''; + + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + renderCustomModelsList(); + await saveConfig(); + + // Switch to the new model + currentModelIndex = availableModels.length - 1; + updateModelDisplay(); + renderModelList(); + await saveConfig(); +} + +function renderCustomModelsList() { + const listEl = document.getElementById('custom-models-list'); + if (!listEl) return; + + if (customModels.length === 0) { + listEl.innerHTML = '
No custom models added yet.
'; + return; + } + + listEl.innerHTML = customModels.map((model, i) => ` +
+
+
${model.name}
+
${model.baseUrl}
+
+ +
+ `).join(''); + + // Attach delete handlers + listEl.querySelectorAll('.delete-btn').forEach(btn => { + btn.addEventListener('click', async (e) => { + e.stopPropagation(); + const index = parseInt(btn.dataset.index); + const modelName = customModels[index].name; + if (confirm(`Delete "${modelName}"?`)) { + customModels.splice(index, 1); + await buildAvailableModels(); + updateModelDisplay(); + renderModelList(); + renderCustomModelsList(); + await saveConfig(); + } + }); + }); +} + +// ============================================ +// DOMAIN SKILLS +// ============================================ + +function renderSkillsList() { + const listEl = document.getElementById('skills-list'); + if (!listEl) return; + + // Combine built-in and user skills for display + const allSkills = []; + + // Add built-in skills first (with flag) + for (const skill of builtInSkills) { + allSkills.push({ ...skill, isBuiltIn: true }); + } + + // Add user skills (may override built-in) + for (const skill of userSkills) { + // Check if this overrides a built-in skill + const builtInIndex = allSkills.findIndex(s => s.domain === skill.domain && s.isBuiltIn); + if (builtInIndex >= 0) { + // Replace built-in with user version + allSkills[builtInIndex] = { ...skill, isBuiltIn: false, overridesBuiltIn: true }; + } else { + allSkills.push({ ...skill, isBuiltIn: false }); + } + } + + if (allSkills.length === 0) { + listEl.innerHTML = '
No domain skills yet.
Click + to add one.
'; + return; + } + + listEl.innerHTML = allSkills.map((skill) => { + const preview = skill.skill.substring(0, 80).replace(/\n/g, ' ') + (skill.skill.length > 80 ? '...' : ''); + const icon = skill.isBuiltIn ? '📦' : '✏️'; + const userIndex = userSkills.findIndex(s => s.domain === skill.domain); + + return ` +
+ ${icon} +
+
+ ${skill.domain} + ${skill.isBuiltIn ? 'Built-in' : ''} + ${skill.overridesBuiltIn ? 'Custom' : ''} +
+
${preview}
+
+
+ + ${!skill.isBuiltIn ? `` : ''} +
+
+ `; + }).join(''); + + // Attach event handlers - click anywhere on item to edit + listEl.querySelectorAll('.skill-item').forEach(item => { + const editBtn = item.querySelector('.edit-btn'); + const deleteBtn = item.querySelector('.delete-btn'); + + const handleEdit = (e) => { + e.stopPropagation(); + const domain = item.dataset.domain; + const isBuiltIn = item.dataset.isBuiltin === 'true'; + const userIndex = parseInt(item.dataset.userIndex); + + if (isBuiltIn) { + // Edit built-in: pre-fill with built-in content, will create user override + const builtIn = builtInSkills.find(s => s.domain === domain); + if (builtIn) { + editingSkillIndex = -1; // New skill (override) + document.getElementById('skill-domain').value = builtIn.domain; + document.getElementById('skill-content').value = builtIn.skill; + document.getElementById('skill-form-title').textContent = 'Customize Built-in Skill'; + document.getElementById('add-skill-btn').textContent = 'Save Override'; + showSkillForm(); + } + } else { + // Edit user skill + editingSkillIndex = userIndex; + const skill = userSkills[userIndex]; + document.getElementById('skill-domain').value = skill.domain; + document.getElementById('skill-content').value = skill.skill; + document.getElementById('skill-form-title').textContent = 'Edit Skill'; + document.getElementById('add-skill-btn').textContent = 'Save Changes'; + showSkillForm(); + } + }; + + editBtn.addEventListener('click', handleEdit); + + if (deleteBtn) { + deleteBtn.addEventListener('click', async (e) => { + e.stopPropagation(); + const userIndex = parseInt(item.dataset.userIndex); + if (confirm(`Delete skill for "${userSkills[userIndex].domain}"?`)) { + userSkills.splice(userIndex, 1); + renderSkillsList(); + await saveConfig(); + } + }); + } + }); +} + +function showSkillForm(isNew = false) { + if (isNew) { + editingSkillIndex = -1; + document.getElementById('skill-domain').value = ''; + document.getElementById('skill-content').value = ''; + document.getElementById('skill-form-title').textContent = 'Add New Skill'; + document.getElementById('add-skill-btn').textContent = 'Save Skill'; + } + document.getElementById('skill-form').classList.remove('hidden'); +} + +function hideSkillForm() { + document.getElementById('skill-form').classList.add('hidden'); + cancelSkillEdit(); +} + +async function addOrUpdateSkill() { + const domain = document.getElementById('skill-domain').value.trim().toLowerCase(); + const skill = document.getElementById('skill-content').value.trim(); + + if (!domain || !skill) { + alert('Please fill in both domain and tips/guidance'); + return; + } + + if (editingSkillIndex >= 0) { + // Update existing + userSkills[editingSkillIndex] = { domain, skill }; + } else { + // Check for duplicate user skill + const existingIndex = userSkills.findIndex(s => s.domain === domain); + if (existingIndex >= 0) { + userSkills[existingIndex] = { domain, skill }; + } else { + userSkills.push({ domain, skill }); + } + } + + hideSkillForm(); + renderSkillsList(); + await saveConfig(); +} + +function cancelSkillEdit() { + editingSkillIndex = -1; + document.getElementById('skill-domain').value = ''; + document.getElementById('skill-content').value = ''; + document.getElementById('skill-form-title').textContent = 'Add New Skill'; + document.getElementById('add-skill-btn').textContent = 'Save Skill'; +} + +// ============================================ +// MESSAGES +// ============================================ + +async function sendMessage() { + const text = inputEl.value.trim(); + if (!text || isRunning) return; + + if (availableModels.length === 0) { + alert('Please configure a model in Settings first'); + return; + } + + // Hide empty state (get fresh reference in case it was recreated) + const emptyState = document.getElementById('empty-state'); + if (emptyState) emptyState.style.display = 'none'; + completedSteps = []; + stepsSection = null; + + // Capture images before clearing + const imagesToSend = [...attachedImages]; + + addUserMessage(text, imagesToSend); + inputEl.value = ''; + inputEl.style.height = 'auto'; + clearAttachedImages(); + + const [tab] = await chrome.tabs.query({ active: true, currentWindow: true }); + if (!tab) { + addErrorMessage('No active tab found'); + return; + } + + isRunning = true; + sendBtn.classList.add('hidden'); + stopBtn.classList.remove('hidden'); + + try { + await chrome.runtime.sendMessage({ + type: 'START_TASK', + payload: { + tabId: tab.id, + task: text, + askBeforeActing, + images: imagesToSend, + tabGroupId: sessionTabGroupId, // Send current tab group ID (or null) + }, + }); + } catch (error) { + addErrorMessage(`Error: ${error.message}`); + resetRunningState(); + } +} + +function stopTask() { + chrome.runtime.sendMessage({ type: 'STOP_TASK' }).catch(() => {}); + // Message will be shown by handleTaskComplete when service worker responds + resetRunningState(); +} + +function resetRunningState() { + isRunning = false; + sendBtn.classList.remove('hidden'); + stopBtn.classList.add('hidden'); +} + +// ============================================ +// IMAGE HANDLING +// ============================================ + +function handleImageDrop(dataTransfer) { + const files = dataTransfer.files; + for (const file of files) { + if (file.type.startsWith('image/')) { + readImageFile(file); + } + } +} + +function readImageFile(file) { + const reader = new FileReader(); + reader.onload = (e) => { + attachedImages.push(e.target.result); + renderImagePreviews(); + }; + reader.readAsDataURL(file); +} + +function removeAttachedImage(index) { + attachedImages.splice(index, 1); + renderImagePreviews(); +} + +function clearAttachedImages() { + attachedImages = []; + renderImagePreviews(); +} + +function renderImagePreviews() { + if (attachedImages.length === 0) { + imagePreview.classList.add('hidden'); + imagePreview.innerHTML = ''; + return; + } + + imagePreview.classList.remove('hidden'); + imagePreview.innerHTML = attachedImages.map((img, i) => ` +
+ Preview ${i + 1} + +
+ `).join(''); + + // Attach remove handlers + imagePreview.querySelectorAll('.remove-image-btn').forEach(btn => { + btn.addEventListener('click', (e) => { + e.stopPropagation(); + removeAttachedImage(parseInt(btn.dataset.index)); + }); + }); +} + +function addUserMessage(text, images = []) { + const el = document.createElement('div'); + el.className = 'message user'; + + if (images.length > 0) { + const imagesContainer = document.createElement('div'); + imagesContainer.style.display = 'flex'; + imagesContainer.style.flexWrap = 'wrap'; + imagesContainer.style.gap = '8px'; + imagesContainer.style.marginBottom = '8px'; + + for (const imgSrc of images) { + const img = document.createElement('img'); + img.src = imgSrc; + img.style.maxWidth = '150px'; + img.style.maxHeight = '100px'; + img.style.borderRadius = '8px'; + img.style.objectFit = 'cover'; + imagesContainer.appendChild(img); + } + el.appendChild(imagesContainer); + } + + if (text) { + const textEl = document.createElement('span'); + textEl.textContent = text; + el.appendChild(textEl); + } + + messagesEl.appendChild(el); + scrollToBottom(); +} + +function addAssistantMessage(text) { + const el = document.createElement('div'); + el.className = 'message assistant'; + el.innerHTML = `
${formatMarkdown(text)}
`; + messagesEl.appendChild(el); + scrollToBottom(); + return el; +} + +function addErrorMessage(text) { + const el = document.createElement('div'); + el.className = 'message error'; + el.textContent = text; + messagesEl.appendChild(el); + scrollToBottom(); +} + +function addSystemMessage(text) { + const el = document.createElement('div'); + el.className = 'message system'; + el.textContent = text; + messagesEl.appendChild(el); + scrollToBottom(); +} + +// eslint-disable-next-line sonarjs/cognitive-complexity +function formatMarkdown(text) { + const lines = text.split('\n'); + let result = []; + let inList = false; + let listType = null; + + for (const line of lines) { + const ulMatch = line.match(/^[-*]\s+(.+)$/); + const olMatch = line.match(/^(\d+)\.\s+(.+)$/); + + if (ulMatch) { + if (!inList || listType !== 'ul') { + if (inList) result.push(listType === 'ol' ? '' : ''); + result.push('
    '); + inList = true; + listType = 'ul'; + } + result.push(`
  • ${formatInline(ulMatch[1])}
    • `); + } else if (olMatch) { + if (!inList || listType !== 'ol') { + if (inList) result.push(listType === 'ol' ? '' : '
'); + result.push('
    '); + inList = true; + listType = 'ol'; + } + result.push(`
  1. ${formatInline(olMatch[2])}
    2. `); + } else { + if (inList) { + result.push(listType === 'ol' ? '
' : ''); + inList = false; + listType = null; + } + if (line.trim() === '') { + result.push('
'); + } else { + result.push(`

${formatInline(line)}

`); + } + } + } + if (inList) result.push(listType === 'ol' ? '' : ''); + return result.join(''); +} + +function formatInline(text) { + return text + .replace(/\*\*(.+?)\*\*/g, '$1') + .replace(/\*(.+?)\*/g, '$1') + .replace(/`(.+?)`/g, '$1'); +} + +// ============================================ +// TASK UPDATES +// ============================================ + +function handleTaskUpdate(update) { + if (update.status === 'thinking') { + showThinkingIndicator(); + if (currentStreamingMessage) { + currentStreamingMessage.classList.remove('streaming'); + currentStreamingMessage = null; + } + } else if (update.status === 'streaming' && update.text) { + hideToolIndicator(); + if (!currentStreamingMessage) { + currentStreamingMessage = addAssistantMessage(update.text); + currentStreamingMessage.classList.add('streaming'); + } else { + currentStreamingMessage.querySelector('.content').innerHTML = formatMarkdown(update.text); + } + scrollToBottom(); + } else if (update.status === 'executing') { + if (currentStreamingMessage) { + currentStreamingMessage.classList.remove('streaming'); + currentStreamingMessage = null; + } + // Store pending step with input for rich display + pendingStep = { tool: update.tool, input: update.input }; + const actionDesc = getActionDescription(update.tool, update.input); + showToolIndicator(actionDesc, update.tool); + } else if (update.status === 'executed') { + hideToolIndicator(); + // Complete the step with result (use update.input as fallback if pendingStep is null) + addCompletedStep(update.tool, pendingStep?.input || update.input, update.result); + pendingStep = null; + } else if (update.status === 'message' && update.text) { + hideToolIndicator(); + if (currentStreamingMessage) { + currentStreamingMessage.querySelector('.content').innerHTML = formatMarkdown(update.text); + currentStreamingMessage.classList.remove('streaming'); + currentStreamingMessage = null; + } else { + addAssistantMessage(update.text); + } + } +} + +function handleTaskComplete(result) { + hideToolIndicator(); + if (currentStreamingMessage) { + currentStreamingMessage.classList.remove('streaming'); + currentStreamingMessage = null; + } + resetRunningState(); + if (result.message && !result.success) { + addSystemMessage(result.message); + } +} + +function handleTaskError(error) { + hideToolIndicator(); + if (currentStreamingMessage) { + currentStreamingMessage.classList.remove('streaming'); + currentStreamingMessage = null; + } + resetRunningState(); + addErrorMessage(`Error: ${error}`); +} + +function showToolIndicator(label, toolName = null) { + hideToolIndicator(); + const el = document.createElement('div'); + el.className = 'tool-indicator'; + + // Use tool-specific icon or generic spinner + const icon = toolName ? getToolIcon(toolName) : + ''; + + el.innerHTML = ` +
${icon}
+ ${label} + `; + messagesEl.appendChild(el); + currentToolIndicator = el; + scrollToBottom(); +} + +function hideToolIndicator() { + if (currentToolIndicator) { + currentToolIndicator.remove(); + currentToolIndicator = null; + } +} + +function showThinkingIndicator() { + hideToolIndicator(); + const el = document.createElement('div'); + el.className = 'tool-indicator'; + el.innerHTML = ` +
+ + + + +
+ Thinking + `; + messagesEl.appendChild(el); + currentToolIndicator = el; + scrollToBottom(); +} + +// Tool metadata: labels and icons +const TOOL_META = { + read_page: { + label: 'Reading page', + icon: '' + }, + find: { + label: 'Finding elements', + icon: '' + }, + form_input: { + label: 'Filling form', + icon: '' + }, + computer: { + label: 'Interacting', + icon: '' + }, + navigate: { + label: 'Navigating', + icon: '' + }, + get_page_text: { + label: 'Extracting text', + icon: '' + }, + update_plan: { + label: 'Planning', + icon: '' + }, + tabs_create: { + label: 'Creating tab', + icon: '' + }, + tabs_context: { + label: 'Getting tabs', + icon: '' + }, + javascript_tool: { + label: 'Running script', + icon: '' + }, + upload_image: { + label: 'Uploading image', + icon: '' + }, +}; + +function getToolLabel(toolName) { + return TOOL_META[toolName]?.label || toolName.replace(/_/g, ' '); +} + +function getToolIcon(toolName) { + return TOOL_META[toolName]?.icon || ''; +} + +/** + * Generate human-readable action description from tool input + */ +function getActionDescription(toolName, input) { + if (!input) return getToolLabel(toolName); + + switch (toolName) { + case 'computer': { + const action = input.action; + if (action === 'click' || action === 'left_click') { + if (input.ref) return `Clicking element ref_${input.ref}`; + if (input.coordinate) return `Clicking at (${input.coordinate[0]}, ${input.coordinate[1]})`; + return 'Clicking'; + } + if (action === 'type') { + const text = input.text?.substring(0, 30) || ''; + return `Typing "${text}${input.text?.length > 30 ? '...' : ''}"`; + } + if (action === 'key') return `Pressing ${input.key}`; + if (action === 'scroll') return `Scrolling ${input.direction || 'down'}`; + if (action === 'screenshot') return 'Taking screenshot'; + if (action === 'drag') return 'Dragging element'; + return `${action || 'Interacting'}`; + } + case 'form_input': { + const value = input.value?.substring(0, 25) || ''; + if (input.ref) return `Filling ref_${input.ref} with "${value}${input.value?.length > 25 ? '...' : ''}"`; + return `Filling form field`; + } + case 'navigate': { + try { + const url = new URL(input.url); + return `Navigating to ${url.hostname}`; + } catch { + return `Navigating to ${input.url?.substring(0, 30) || 'URL'}`; + } + } + case 'find': { + const query = input.query?.substring(0, 30) || ''; + return `Finding "${query}${input.query?.length > 30 ? '...' : ''}"`; + } + case 'read_page': + return input.filter === 'interactive' ? 'Reading interactive elements' : 'Reading full page'; + case 'get_page_text': + return 'Extracting page text'; + case 'tabs_create': + return `Opening new tab`; + case 'tabs_context': + return 'Getting tab info'; + case 'javascript_tool': + return 'Running JavaScript'; + case 'update_plan': + return 'Updating plan'; + default: + return getToolLabel(toolName); + } +} + +/** + * Format step result for display + */ +function formatStepResult(result) { + if (!result || result === 'done') return null; + if (typeof result !== 'string') return null; + // Truncate long results + if (result.length > 100) return result.substring(0, 100) + '...'; + return result; +} + +function addCompletedStep(toolName, input = null, result = null) { + const description = getActionDescription(toolName, input); + const step = { tool: toolName, input, result, description }; + completedSteps.push(step); + + // Incremental update: just append the new step + appendStepElement(step); + updateStepCount(); +} + +function createStepsSection() { + stepsSection = document.createElement('div'); + stepsSection.className = 'steps-section'; + stepsSection.innerHTML = ` +
+
+ +
+ 0 steps completed + +
+
+ `; + + // Toggle expand/collapse + // IMPORTANT: Capture local references to avoid closure bug when multiple steps sections exist + const thisSection = stepsSection; + thisSection.querySelector('.steps-toggle').addEventListener('click', () => { + const toggle = thisSection.querySelector('.steps-toggle'); + const list = thisSection.querySelector('.steps-list'); + toggle.classList.toggle('expanded'); + list.classList.toggle('visible'); + }); + + messagesEl.appendChild(stepsSection); +} + +function appendStepElement(step) { + // Create steps section if it doesn't exist + if (!stepsSection) { + createStepsSection(); + } + + const list = stepsSection.querySelector('.steps-list'); + const stepEl = createStepElement(step); + list.appendChild(stepEl); + + // Only auto-scroll if user is already near bottom + if (isScrolledToBottom()) { + scrollToBottom(); + } +} + +function createStepElement(step) { + const div = document.createElement('div'); + div.className = 'step-item'; + + const resultText = formatStepResult(step.result); + div.innerHTML = ` +
${getToolIcon(step.tool)}
+
+
${escapeHtml(step.description)}
+ ${resultText ? `
${escapeHtml(resultText)}
` : ''} +
+
✓
+ `; + + return div; +} + +function updateStepCount() { + if (!stepsSection) return; + + const toggle = stepsSection.querySelector('.toggle-text'); + const count = completedSteps.length; + toggle.textContent = `${count} step${count !== 1 ? 's' : ''} completed`; +} + +function isScrolledToBottom() { + const threshold = 50; // px from bottom + return messagesEl.scrollHeight - messagesEl.scrollTop - messagesEl.clientHeight < threshold; +} + +function escapeHtml(text) { + const div = document.createElement('div'); + div.textContent = text; + return div.innerHTML; +} + +function showPlanApproval(plan) { + planDomains.innerHTML = plan.domains.map(d => `${d}`).join(''); + planSteps.innerHTML = plan.approach.map(s => `
  • ${s}
    • `).join(''); + planModal.classList.remove('hidden'); +} + +function scrollToBottom() { + messagesEl.scrollTop = messagesEl.scrollHeight; +} + +function clearChat() { + messagesEl.innerHTML = ''; + const emptyState = document.createElement('div'); + emptyState.className = 'empty-state'; + emptyState.id = 'empty-state'; + emptyState.innerHTML = `

    What can I help with?

    I can browse the web, fill forms, click buttons, and automate tasks in your browser.

    `; + messagesEl.appendChild(emptyState); + completedSteps = []; + pendingStep = null; + stepsSection = null; + currentStreamingMessage = null; + currentToolIndicator = null; + isRunning = false; + sendBtn.disabled = false; + sessionTabGroupId = null; // Reset tab group on new chat + chrome.runtime.sendMessage({ type: 'CLEAR_CONVERSATION' }).catch(() => {}); +} diff --git a/Ali/executors/browser/agent/src/tools/definitions.js b/Ali/executors/browser/agent/src/tools/definitions.js new file mode 100644 index 00000000..92bf484a --- /dev/null +++ b/Ali/executors/browser/agent/src/tools/definitions.js @@ -0,0 +1,561 @@ +/** + * Tool Definitions for Browser Automation + */ + +/** + * Tools that only work with Claude models. + * These should be filtered out for other providers (OpenAI, Codex, etc.) + * - turn_answer_start: Claude signals before responding + * - update_plan: Claude's "ask before acting" planning tool + */ +export const CLAUDE_ONLY_TOOLS = ['turn_answer_start', 'update_plan']; + +export const TOOL_DEFINITIONS = [ + { + name: 'read_page', + description: `Get a rich DOM tree of the page via Chrome DevTools Protocol. Returns interactive elements with numeric backendNodeId references (e.g., [42]). IMPORTANT: Only use element IDs from the CURRENT output — IDs change between calls. Pierces shadow DOM and iframes automatically. tabId is optional — if omitted, the active tab is used automatically.`, + input_schema: { + type: 'object', + properties: { + tabId: { + type: 'number', + description: 'Tab ID to target. Optional — if omitted, uses the active tab in your window.', + }, + max_chars: { + type: 'number', + description: 'Maximum characters for output (default: 50000). Set to a higher value if your client can handle large outputs.', + }, + }, + required: [], + }, + }, + + { + name: 'find', + description: `Find elements on the page using natural language. Can search for elements by their purpose (e.g., "search bar", "login button") or by text content (e.g., "organic mango product"). Returns up to 20 matching elements with references that can be used with other tools. If more than 20 matches exist, you'll be notified to use a more specific query. tabId is optional — if omitted, the active tab in your window is used automatically.`, + input_schema: { + type: 'object', + properties: { + query: { + type: 'string', + description: 'Natural language description of what to find (e.g., "search bar", "add to cart button", "product title containing organic")', + }, + tabId: { + type: 'number', + description: 'Tab ID to search in. Optional — if omitted, uses the active tab in your window.', + }, + }, + required: ['query'], + }, + }, + + { + name: 'form_input', + description: `Set values in ANY form element — text inputs, textareas, native + + + + + + ); +} + +export default App; diff --git a/Ali/ui-app/src/main.tsx b/Ali/ui-app/src/main.tsx new file mode 100644 index 00000000..16958a20 --- /dev/null +++ b/Ali/ui-app/src/main.tsx @@ -0,0 +1,10 @@ +import React from "react"; +import ReactDOM from "react-dom/client"; +import App from "./App"; +import "./styles.css"; + +ReactDOM.createRoot(document.getElementById("root")!).render( + + + +); diff --git a/Ali/ui-app/src/styles.css b/Ali/ui-app/src/styles.css new file mode 100644 index 00000000..96e997ef --- /dev/null +++ b/Ali/ui-app/src/styles.css @@ -0,0 +1,189 @@ +:root { + color-scheme: dark; + font-family: "SF Pro Display", "Inter", -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; +} + +* { + box-sizing: border-box; +} + +html, +body, +#root { + margin: 0; + width: 100%; + height: 100%; +} + +.viewport { + width: 100%; + height: 100%; + padding: 18px; + background: transparent; +} + +.shell { + width: 100%; + height: 100%; + border-radius: 34px; + border: 1px solid rgba(198, 182, 160, 0.45); + background: linear-gradient(145deg, rgba(60, 45, 31, 0.72), rgba(39, 41, 35, 0.75)); + backdrop-filter: blur(22px); + -webkit-backdrop-filter: blur(22px); + box-shadow: 0 10px 36px rgba(0, 0, 0, 0.28); + padding: 18px 18px 16px; + display: grid; + grid-template-rows: auto 1fr; + gap: 12px; +} + +.close-btn { + position: absolute; + top: 24px; + left: 26px; + width: 30px; + height: 30px; + border: 0; + border-radius: 999px; + color: #d8d1c8; + background: rgba(90, 83, 74, 0.62); + font-size: 20px; + cursor: default; +} + +.header { + text-align: center; + color: #f2eee7; + margin-top: 4px; +} + +.header h1 { + margin: 0; + font-size: 34px; + font-weight: 700; + letter-spacing: -0.02em; +} + +.subtitle-row { + margin-top: 4px; + display: inline-flex; + align-items: center; + gap: 10px; +} + +.subtitle-row h2 { + margin: 0; + font-size: 28px; + font-weight: 700; +} + +.chip { + border-radius: 10px; + background: rgba(255, 255, 255, 0.15); + padding: 4px 10px; + font-size: 16px; + color: #f0ece3; +} + +.panel { + border-radius: 30px; + border: 1px solid rgba(125, 120, 110, 0.65); + background: rgba(29, 31, 28, 0.45); + padding: 20px 24px 22px; + display: grid; + grid-template-rows: auto 1fr auto; + min-height: 420px; +} + +.panel-top { + display: flex; + align-items: center; + justify-content: space-between; +} + +.panel-title { + font-size: 52px; + font-weight: 700; + color: #d7d2ca; + text-transform: lowercase; +} + +.esc { + border-radius: 12px; + padding: 6px 16px; + background: rgba(255, 255, 255, 0.18); + font-size: 32px; + font-weight: 700; + color: #e9e6df; +} + +.bubbles { + display: flex; + flex-direction: column; + gap: 12px; + padding: 10px 0 14px; + overflow: hidden; +} + +.bubble { + border-radius: 18px; + padding: 16px 18px; + font-size: 35px; + line-height: 1.15; + font-weight: 700; + max-width: 100%; + word-break: break-word; +} + +.bubble.user { + background: rgba(255, 255, 255, 0.12); + color: #ffffff; +} + +.bubble.assistant { + background: rgba(255, 255, 255, 0.08); + color: #f8f7f3; +} + +.bubble.status { + background: rgba(255, 255, 255, 0.06); + color: #e8e4dc; + font-size: 30px; +} + +.bubble.error { + background: rgba(255, 107, 107, 0.14); + color: #ffb7b7; +} + +.composer { + display: grid; + grid-template-columns: 1fr auto; + gap: 12px; + align-items: center; +} + +.composer input { + border: 0; + border-radius: 20px; + background: rgba(255, 255, 255, 0.14); + color: #e6e0d5; + font-size: 34px; + font-weight: 700; + padding: 18px 24px; +} + +.composer input:focus { + outline: none; +} + +.send-btn { + width: 62px; + height: 62px; + border-radius: 999px; + border: 0; + font-size: 36px; + font-weight: 700; + color: #2d2b28; + background: rgba(216, 204, 183, 0.88); +} diff --git a/Ali/ui-app/tsconfig.json b/Ali/ui-app/tsconfig.json new file mode 100644 index 00000000..1801a464 --- /dev/null +++ b/Ali/ui-app/tsconfig.json @@ -0,0 +1,18 @@ +{ + "compilerOptions": { + "target": "ES2020", + "useDefineForClassFields": true, + "lib": ["ES2020", "DOM", "DOM.Iterable"], + "module": "ESNext", + "skipLibCheck": true, + "moduleResolution": "Bundler", + "allowImportingTsExtensions": true, + "resolveJsonModule": true, + "isolatedModules": true, + "noEmit": true, + "jsx": "react-jsx", + "strict": true + }, + "include": ["src"], + "references": [{ "path": "./tsconfig.node.json" }] +} diff --git a/Ali/ui-app/tsconfig.node.json b/Ali/ui-app/tsconfig.node.json new file mode 100644 index 00000000..16dfedc6 --- /dev/null +++ b/Ali/ui-app/tsconfig.node.json @@ -0,0 +1,9 @@ +{ + "compilerOptions": { + "composite": true, + "module": "ESNext", + "moduleResolution": "Bundler", + "allowSyntheticDefaultImports": true + }, + "include": ["vite.config.ts"] +} diff --git a/Ali/ui-app/vite.config.ts b/Ali/ui-app/vite.config.ts new file mode 100644 index 00000000..cbfc338a --- /dev/null +++ b/Ali/ui-app/vite.config.ts @@ -0,0 +1,18 @@ +import { defineConfig } from "vite"; +import react from "@vitejs/plugin-react"; + +export default defineConfig({ + plugins: [react()], + clearScreen: false, + server: { + port: 1420, + strictPort: true + }, + envPrefix: ["VITE_", "TAURI_"], + build: { + target: process.env.TAURI_PLATFORM === "windows" ? "chrome105" : "safari13", + minify: !process.env.TAURI_DEBUG ? "esbuild" : false, + sourcemap: !!process.env.TAURI_DEBUG + } + +}); diff --git a/Ali/ui/__init__.py b/Ali/ui/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/Ali/ui/confirmation.py b/Ali/ui/confirmation.py new file mode 100644 index 00000000..756d209a --- /dev/null +++ b/Ali/ui/confirmation.py @@ -0,0 +1,40 @@ +""" +Layer 5 — Confirmation Gate +Shows a native macOS dialog via osascript. +Thread-safe — no main-thread requirement unlike tkinter. +""" + +import asyncio +import os +import subprocess + + +async def ask_confirmation(message: str) -> bool: + """ + Show a native macOS confirmation dialog via osascript. + Returns True if user clicks OK, False if Cancel or error. + """ + # Default to non-interactive auto-approve for voice-first UX. + # Set VOICE_AGENT_REQUIRE_CONFIRM=1 to re-enable native dialogs. + require_confirm = os.environ.get("VOICE_AGENT_REQUIRE_CONFIRM", "").lower() in {"1", "true", "yes"} + if not require_confirm: + return True + loop = asyncio.get_event_loop() + return await loop.run_in_executor(None, _show_dialog, message) + + +def _show_dialog(message: str) -> bool: + # Escape any double quotes in the message + safe = message.replace('"', '\\"').replace("'", "\\'") + script = ( + f'display dialog "{safe}" ' + f'buttons {{"Cancel", "Send it"}} ' + f'default button "Send it" ' + f'with title "Voice Agent"' + ) + result = subprocess.run( + ["osascript", "-e", script], + capture_output=True, + text=True, + ) + return result.returncode == 0 diff --git a/Ali/ui/menu_bar.py b/Ali/ui/menu_bar.py new file mode 100644 index 00000000..78f9d888 --- /dev/null +++ b/Ali/ui/menu_bar.py @@ -0,0 +1,94 @@ +""" +Layer 5 — macOS Menu Bar + +Minimal status indicator + "Rebuild Index…" menu item. Uses rumps +(macOS-only). Falls back to a no-op stub on other platforms. + +Indexing progress is intentionally *not* surfaced in the menu bar title — +the terminal already shows a tqdm bar and the per-event log. The menu bar +only toggles between the coarse agent states (ready / transcribing / +parsing / running / indexing / error). +""" + +from __future__ import annotations + +import subprocess +import sys +import threading +from pathlib import Path + +try: + import rumps # type: ignore + RUMPS_AVAILABLE = True +except ImportError: + RUMPS_AVAILABLE = False + +STATUS_ICONS = { + "ready": "🎙", + "transcribing": "⏳", + "parsing intent": "🧠", + "running": "⚙️", + "indexing": "📚", + "error": "⚠️", +} + + +_BUILD_SCRIPT = Path(__file__).resolve().parent.parent / "scripts" / "build_index.py" + + +class MenuBar: + def __init__(self): + if RUMPS_AVAILABLE: + self._app = _MenuBarApp(on_rebuild=self._rebuild_index) + else: + self._app = None + self._rebuild_thread: threading.Thread | None = None + + def set_status(self, status: str): + icon = STATUS_ICONS.get(status, "●") + label = f"{icon} {status.capitalize()}" + if self._app is not None: + self._app.title = label + else: + print(f"[menu_bar] {label}") + + def _rebuild_index(self) -> None: + """Run scripts/build_index.py in a background thread so the UI stays + responsive. Only one rebuild may be in flight at a time.""" + if self._rebuild_thread is not None and self._rebuild_thread.is_alive(): + print("[menu_bar] rebuild already in progress, ignoring click") + return + + def _worker() -> None: + self.set_status("indexing") + try: + from config.index_bootstrap import ensure_index + + ensure_index(force_rebuild=True, background=False) + except Exception as exc: + print(f"[menu_bar] rebuild failed: {exc}") + finally: + self.set_status("ready") + + self._rebuild_thread = threading.Thread( + target=_worker, daemon=True, name="index-rebuild" + ) + self._rebuild_thread.start() + + +if RUMPS_AVAILABLE: + class _MenuBarApp(rumps.App): + def __init__(self, *, on_rebuild): + super().__init__("🎙 Ready", quit_button=None) + self._on_rebuild = on_rebuild + self.menu = [ + rumps.MenuItem("Rebuild Index…", callback=self._handle_rebuild), + None, + rumps.MenuItem("Quit", callback=self._handle_quit), + ] + + def _handle_rebuild(self, _sender) -> None: + self._on_rebuild() + + def _handle_quit(self, _sender) -> None: + rumps.quit_application() diff --git a/Ali/ui/overlay.py b/Ali/ui/overlay.py new file mode 100644 index 00000000..e6cc9183 --- /dev/null +++ b/Ali/ui/overlay.py @@ -0,0 +1,1256 @@ +""" +Liquid glass overlay — Apple-style frosted pill, top-center, expands downward. +""" + +from __future__ import annotations + +import datetime +import os +import queue +import subprocess +import sys +import threading +from typing import Callable + +from PySide6.QtCore import QPoint, QRect, Qt, QObject, QTimer, Signal, Slot # pyright: ignore[reportMissingImports] +from PySide6.QtGui import ( # pyright: ignore[reportMissingImports] + QBrush, QColor, QCursor, QFont, QGuiApplication, QImage, QLinearGradient, + QPainter, QPainterPath, QPen, QPixmap, +) +from PySide6.QtWidgets import QApplication, QWidget # pyright: ignore[reportMissingImports] + +# #region agent log +def _dlog(loc: str, msg: str, data: dict, hid: str = "H2") -> None: + try: + import json as _j, os as _o, time as _t + _p = "/Users/alspenceramitojr/Desktop/Ali/.cursor/debug-4ea166.log" + _o.makedirs(_o.path.dirname(_p), exist_ok=True) + with open(_p, "a") as _f: + _f.write(_j.dumps({"sessionId":"4ea166","hypothesisId":hid,"location":loc, + "message":msg,"data":data,"timestamp":int(_t.time()*1000)})+"\n") + _f.flush() + except Exception: + pass +# #endregion + +# NOTE: `cv2` is deliberately NOT imported at module load time. +# `faster-whisper` pulls in PyAV, which bundles its own `libavdevice.dylib` +# registering `AVFFrameReceiver` / `AVFAudioReceiver`. `cv2` bundles the same +# classes. Having both loaded in the same process causes macOS to SIGTRAP +# ("zsh: trace trap") on the next AVFoundation call (even indirect ones from +# PyAudio/CoreAudio). Import cv2 lazily, only when the wake-scene actually +# opens the webcam. + +W_WAKE = 560 +H_WAKE = 200 +CAM_W = 160 +CAM_H = 160 +USER_NAME = "Alspencer" + +# ── Meeting mode geometry ───────────────────────────────────────────────────── +W_MEETING = 560 +H_MEETING_BASE = 200 # height before any action items +H_ACTION_ROW = 34 # height per action item row +MAX_ACTIONS_SHOWN = 5 +MAX_TRANSCRIPT_CHARS = 320 # chars of rolling transcript shown + + +def _time_greeting() -> str: + h = datetime.datetime.now().hour + if h < 12: return "Good morning" + if h < 17: return "Good afternoon" + return "Good evening" + + +class _CamBridge(QObject): + frame_ready = Signal(QImage) + greeted = Signal() + + +class _MacGlobalHotkeyBridge(QObject): + """Marshals AppKit global key events to the Qt main thread.""" + + backtick = Signal() + right_option_down = Signal() + right_option_up = Signal() + +# ── Colors ──────────────────────────────────────────────────────────────────── +CITATION_ROW_H = 26 +CITATION_CHIP_PAD_X = 10 +CITATION_CHIP_GAP = 8 + +FG = QColor(246, 246, 250) # primary text on liquid glass +DIM = QColor(196, 194, 202) # secondary text +RED = QColor("#E8342E") +YELLOW = QColor("#F3C84B") +BLUE = QColor("#64D2FF") +GREEN = QColor("#3CD07A") +ERR = QColor("#FF6B6B") + +# ── Geometry ────────────────────────────────────────────────────────────────── +W_PILL = 340 +W_FULL = 560 +H_PILL = 58 +R = 29 # large radius → pill shape +MARGIN = 8 # gap from top (below menu bar) +MARGIN_RIGHT = 16 # gap from right edge when docked-right +MAX_H = 540 +MAX_HIST = 8 + +# ── Docking ─────────────────────────────────────────────────────────────────── +DOCK_TOP = "top" +DOCK_RIGHT = "right" + +# ── Timing ──────────────────────────────────────────────────────────────────── +PULSE_MS = 500 +POLL_MS = 40 +AUTOHIDE_MS = 5_000 + + +def _apply_macos_overlay(win: QWidget) -> None: + win._vibrancy_active = False # type: ignore[attr-defined] + try: + from AppKit import NSApplication, NSColor, NSVisualEffectView # type: ignore[reportMissingImports] + + marker = "__ali_overlay__" + win.setWindowTitle(marker) + QApplication.processEvents() + + ns_app = NSApplication.sharedApplication() + ns_win = None + for candidate in ns_app.windows(): + try: + if candidate.title() == marker: + ns_win = candidate + break + except Exception: + continue + + if ns_win is not None: + # NSPopUpMenuWindowLevel (101) sits above any normal app window + # including Finder + Mail, so our overlay stays on top regardless + # of which app is active. + ns_win.setLevel_(101) + # 1=CanJoinAllSpaces 8=Transient (no Mission Control card) + # 64=IgnoresCycle (no Cmd+Tab entry) 256=FullScreenAuxiliary + ns_win.setCollectionBehavior_(1 | 8 | 64 | 256) + # Keep the overlay visible when our Python app deactivates + # (Finder / Mail take focus). Without this, Qt.Tool windows + # auto-hide on deactivation and the user has to click the Dock + # icon to bring it back. + try: + ns_win.setHidesOnDeactivate_(False) + except Exception: + pass + ns_win.setOpaque_(False) + ns_win.setBackgroundColor_(NSColor.clearColor()) + + qt_view = ns_win.contentView() # QNSView — Qt renders here + # Add the blur view BEHIND Qt's content view (as sibling in frame view) + # so Qt text renders on top of the vibrancy, not underneath it. + try: + frame_view = qt_view.superview() # NSThemeFrame (window frame) + if frame_view is None: + raise ValueError("no frame_view") + effect = NSVisualEffectView.alloc().initWithFrame_(qt_view.frame()) + effect.setMaterial_(21) # UnderWindowBackground — subtle + effect.setBlendingMode_(0) # BehindWindow + effect.setState_(1) # Active + effect.setAutoresizingMask_(18) + # Insert behind Qt's view so Qt text is always on top + frame_view.addSubview_positioned_relativeTo_(effect, -1, qt_view) + win._ns_window = ns_win # type: ignore[attr-defined] + win._ns_effect = effect # type: ignore[attr-defined] + win._vibrancy_active = True # type: ignore[attr-defined] + print("[overlay] liquid glass vibrancy active") + except Exception as ve: + # Vibrancy positioning failed — fall back to Qt-painted glass + win._ns_window = ns_win # type: ignore[attr-defined] + win._vibrancy_active = False # type: ignore[attr-defined] + print(f"[overlay] vibrancy positioning skipped ({ve}) — using solid glass") + + win.setWindowTitle("") + except Exception as e: + print(f"[overlay] vibrancy skipped: {e}") + + +def _open_citation_target(path: str) -> None: + """Open a cited source when the user clicks its chip. + + * Filesystem paths open with macOS `open ` (uses the file's + default app). + * `ali://contacts/…` / `ali://calendar/…` / `ali://messages/…` open + the matching macOS app. We can't easily deep-link to a specific + contact or event through `open`, so we settle for opening the app + itself — good enough as a jumping-off point. + """ + if not path: + return + try: + if path.startswith("ali://"): + rest = path[len("ali://") :] + source = rest.split("/", 1)[0] + app_name = { + "contacts": "Contacts", + "calendar": "Calendar", + "messages": "Messages", + }.get(source) + if app_name: + subprocess.Popen( + ["open", "-a", app_name], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + return + subprocess.Popen( + ["open", path], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + _dlog( + "overlay:open_citation", + "opened cited file", + {"path": path}, + "H2", + ) + except Exception as exc: + _dlog( + "overlay:open_citation:error", + "failed to open cited target", + {"path": path, "err": str(exc)[:200]}, + "H2", + ) + + +def _paint_citation_chips( + p: "QPainter", + *, + citations: list[dict], + font: "QFont", + pad_left: int, + y: int, + max_width: int, +) -> list[tuple["QRect", str]]: + """Draw citation chips in a single row and return their hit rects. + + Each chip renders as an underlined blue label so it reads as a link. + Returns a list of ``(chip_rect, path)`` pairs — mousePressEvent uses + this to route clicks to the correct file. + """ + p.save() + p.setFont(font) + fm = p.fontMetrics() + hit_rects: list[tuple[QRect, str]] = [] + x = pad_left + chip_h = 20 + chip_y = y + (CITATION_ROW_H - chip_h) // 2 + right_edge = pad_left + max_width + for entry in citations: + label = str(entry.get("label") or "").strip() or "(unnamed)" + path = str(entry.get("path") or "") + text_w = fm.horizontalAdvance(label) + chip_w = text_w + CITATION_CHIP_PAD_X * 2 + if x + chip_w > right_edge and hit_rects: + # No room for another chip on this row — stop (overflow). + break + chip_rect = QRect(x, chip_y, chip_w, chip_h) + # Subtle pill background so the chip reads as tappable. + bg = QColor(100, 210, 255, 34) + border = QColor(100, 210, 255, 110) + path_rect = QPainterPath() + path_rect.addRoundedRect(chip_rect, chip_h / 2, chip_h / 2) + p.fillPath(path_rect, bg) + p.setPen(QPen(border, 1)) + p.drawPath(path_rect) + # Label (underlined so it's recognisably a link even at a glance). + link_font = QFont(font) + link_font.setUnderline(True) + p.setFont(link_font) + p.setPen(BLUE if path else DIM) + p.drawText( + chip_rect, + int(Qt.AlignmentFlag.AlignCenter), + label, + ) + p.setFont(font) + if path: + hit_rects.append((chip_rect, path)) + x += chip_w + CITATION_CHIP_GAP + p.restore() + return hit_rects + + +def _update_vibrancy_mask(win: QWidget) -> None: + try: + from Quartz import CGRectMake, CGPathCreateWithRoundedRect # type: ignore[reportMissingImports] + from Quartz.QuartzCore import CAShapeLayer # type: ignore[reportMissingImports] + effect = getattr(win, "_ns_effect", None) + if effect is None: + return + w, h = win.width(), win.height() + # Effect view lives in frame_view coords — keep its frame synced with + # the Qt contentView's frame (they should be identical for frameless windows). + try: + ns_win = getattr(win, "_ns_window", None) + if ns_win is not None: + qt_frame = ns_win.contentView().frame() + effect.setFrame_(qt_frame) + except Exception: + pass + bounds = CGRectMake(0, 0, w, h) + mask = CAShapeLayer.layer() + path = CGPathCreateWithRoundedRect(bounds, R, R, None) + mask.setPath_(path) + effect.setWantsLayer_(True) + effect.layer().setMask_(mask) + except Exception: + pass + + +class TranscriptionOverlay(QWidget): + """Thread-safe: wake word calls schedule_wake_prompt() from a background thread.""" + + _wake_listen_signal = Signal() + + def __init__(self, app: QApplication) -> None: + super().__init__() + self._app = app + self._q: queue.Queue[tuple[str, str]] = queue.Queue() + self._history: list[tuple[str, QColor, str]] = [] + # Clickable citation chips + their on-screen hit rectangles. + # Populated when a `cited_paths` state is pushed; consulted by + # mousePressEvent to open the underlying file when clicked. + self._citations: list[dict] = [] + self._citation_hit_rects: list[tuple[QRect, str]] = [] + self._drag_offset: QPoint | None = None + self._pulse_on = True + self._recording = False + self._prompt_armed = False + self._pill_label = "Listening..." + self._wake_capture_fn: Callable[[], None] | None = None + # wake / call state + self._wake_mode = False + self._wake_greeted = False + self._wake_text = "" + self._cam_pixmap = QPixmap() + self._cam_bridge = _CamBridge() + self._cam_running = False + self._cam_bridge.frame_ready.connect(self._on_cam_frame) + self._cam_bridge.greeted.connect(self._on_wake_greeted) + + # meeting capture state + self._meeting_mode: bool = False + self._meeting_transcript: str = "" # rolling committed words (trimmed) + self._meeting_interim: str = "" # current partial phrase + self._meeting_actions: list[tuple[str, str]] = [] # (task, status) + + self._dock_mode: str = DOCK_TOP + + self._font_label = QFont(".AppleSystemUIFont", 15, QFont.Weight.Bold) + self._font_body = QFont(".AppleSystemUIFont", 14) + self._font_small = QFont(".AppleSystemUIFont", 12) + self._font_close = QFont(".AppleSystemUIFont", 16, QFont.Weight.Medium) + + # Deliberately NOT using Qt.Tool — on macOS Qt auto-hides Tool + # windows when the app deactivates, which cannot be overridden from + # AppKit. Frameless + StaysOnTop + DoesNotAcceptFocus gives us a + # regular borderless window that stays visible when focus shifts. + self.setWindowFlags( + Qt.WindowType.FramelessWindowHint + | Qt.WindowType.WindowStaysOnTopHint + | Qt.WindowType.WindowDoesNotAcceptFocus + ) + self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground, True) + self.setAttribute(Qt.WidgetAttribute.WA_ShowWithoutActivating, True) + self.setMouseTracking(True) + self.resize(W_PILL, H_PILL) + self._reposition(W_PILL, H_PILL) + # Show briefly so NSApp registers the NSWindow in its windows() list, + # then immediately hide. _apply_macos_overlay searches that list. + self.show() + QApplication.processEvents() + self.hide() + _apply_macos_overlay(self) + _update_vibrancy_mask(self) + + self._poll_timer = QTimer(self) + self._poll_timer.timeout.connect(self._poll) + self._poll_timer.start(POLL_MS) + + self._pulse_timer = QTimer(self) + self._pulse_timer.timeout.connect(self._pulse_tick) + + self._autohide_timer = QTimer(self) + self._autohide_timer.setSingleShot(True) + self._autohide_timer.timeout.connect(self.hide) + + self._wake_listen_signal.connect(self._on_wake_sequence) + + self._mac_hotkey_bridge = _MacGlobalHotkeyBridge(self) + self._mac_hotkey_bridge.backtick.connect(self._on_global_backtick) + self._mac_hotkey_bridge.right_option_down.connect(self._on_global_right_option_down) + self._mac_hotkey_bridge.right_option_up.connect(self._on_global_right_option_up) + self._macos_global_hotkey_monitor = None + if ( + sys.platform == "darwin" + and os.environ.get("ALI_ENABLE_HOTKEY") != "1" + and os.environ.get("ALI_DISABLE_GLOBAL_HOTKEYS") != "1" + ): + self._install_macos_global_hotkeys() + + # ── Public ─────────────────────────────────────────────────────────────── + + def push(self, state: str, text: str = "") -> None: + self._q.put((state, text)) + + def schedule_wake_prompt(self, start_capture: Callable[[], None]) -> None: + """ + Conversational wake: show armed pill + pulse, play a listen chime on macOS, + then invoke start_capture() (typically request_ptt_session_from_wake). + Safe to call from non-Qt threads. + """ + self._wake_capture_fn = start_capture + self._wake_listen_signal.emit() + + @Slot() + def _on_wake_sequence(self) -> None: + if self._prompt_armed: + return # already armed — ignore duplicate wake trigger + self._autohide_timer.stop() + self._wake_mode = False + self._prompt_armed = True + self._recording = False + self._pill_label = "Hi — I'm listening…" + self._history.clear() + self._dock_mode = DOCK_TOP + self._pulse_on = True + self._set_size(W_PILL, H_PILL) + self._present() + self._pulse_timer.start(PULSE_MS) + self.update() + QTimer.singleShot(0, self._play_wake_greeting) + # Start capture almost immediately so wake feels instant. + QTimer.singleShot(120, self._emit_wake_capture) + + def _play_wake_greeting(self) -> None: + if sys.platform != "darwin": + return + try: + from voice.speak import _voice + proc = subprocess.Popen( + ["/usr/bin/say", "-v", _voice(), "-r", "160", "Hi"], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + try: + from voice.speak import track_tts_process + track_tts_process(proc) + except Exception: + pass + # #region agent log + _dlog("overlay:_play_wake_greeting", "wake greeting launched", {"pid": proc.pid}, "H2") + # #endregion + except Exception: + # #region agent log + _dlog("overlay:_play_wake_greeting:error", "wake greeting failed", {}, "H2") + # #endregion + + def _emit_wake_capture(self) -> None: + fn = self._wake_capture_fn + self._wake_capture_fn = None + if fn is not None: + fn() + + def _install_macos_global_hotkeys(self) -> None: + """ + Deliver `` ` `` and Right Option without pynput: on macOS, CGEventTap + + Qt can SIGTRAP, so we use NSEvent.addGlobalMonitorForEventsMatchingMask. + Requires Accessibility for the host app (Terminal, Cursor, etc.). + """ + try: + import AppKit + from AppKit import NSEvent + except ImportError: + print("[overlay] AppKit unavailable — global hotkeys skipped", flush=True) + return + + emitter = self._mac_hotkey_bridge + # US/ANSI grave / backtick (kVK_ANSI_Grave); Right Option (kVK_RightOption) + grave_code = 50 + right_option_code = 61 + + def handler(event) -> None: # type: ignore[no-untyped-def] + try: + et = event.type() + kc = int(event.keyCode()) + if kc == grave_code and et == AppKit.NSEventTypeKeyDown: + if event.isARepeat(): + return + emitter.backtick.emit() + return + if kc == right_option_code: + if et == AppKit.NSEventTypeKeyDown: + emitter.right_option_down.emit() + elif et == AppKit.NSEventTypeKeyUp: + emitter.right_option_up.emit() + except Exception: + pass + + mask = (1 << AppKit.NSEventTypeKeyDown) | (1 << AppKit.NSEventTypeKeyUp) + monitor = NSEvent.addGlobalMonitorForEventsMatchingMask_handler_(mask, handler) + if monitor is None: + print( + "[overlay][warn] Global ` and Right Option inactive — grant " + "Accessibility to this app in System Settings → Privacy & Security " + "(or set ALI_ENABLE_HOTKEY=1 to use pynput; may crash with Qt).", + flush=True, + ) + else: + self._macos_global_hotkey_monitor = monitor + print( + "[overlay] Global hotkeys: ` and Right Option (needs Accessibility)", + flush=True, + ) + + @Slot() + def _on_global_backtick(self) -> None: + from voice.capture import invoke_backtick_callback + + invoke_backtick_callback() + + @Slot() + def _on_global_right_option_down(self) -> None: + from voice.capture import invoke_right_option_down + + invoke_right_option_down() + + @Slot() + def _on_global_right_option_up(self) -> None: + from voice.capture import invoke_right_option_up + + invoke_right_option_up() + + # ── Input ──────────────────────────────────────────────────────────────── + + def mousePressEvent(self, e) -> None: # type: ignore[override] + if e.button() == Qt.MouseButton.LeftButton: + x = e.position().x() + y = e.position().y() + if self._hit_close(x, y): + self._do_hide() + return + # Citation chip clicks open the underlying file / app. + for rect, path in self._citation_hit_rects: + if rect.contains(int(x), int(y)): + _open_citation_target(path) + return + self._drag_offset = e.globalPosition().toPoint() - self.frameGeometry().topLeft() + + def mouseMoveEvent_cursor_hint(self, x: float, y: float) -> None: + """Visual affordance: change cursor to pointing hand over citations.""" + for rect, _ in self._citation_hit_rects: + if rect.contains(int(x), int(y)): + self.setCursor(Qt.CursorShape.PointingHandCursor) + return + self.setCursor(Qt.CursorShape.ArrowCursor) + + def mouseMoveEvent(self, e) -> None: # type: ignore[override] + if self._drag_offset and (e.buttons() & Qt.MouseButton.LeftButton): + self.move(e.globalPosition().toPoint() - self._drag_offset) + else: + self.mouseMoveEvent_cursor_hint(e.position().x(), e.position().y()) + + def mouseReleaseEvent(self, e) -> None: # type: ignore[override] + if e.button() == Qt.MouseButton.LeftButton: + self._drag_offset = None + + def resizeEvent(self, e) -> None: # type: ignore[override] + super().resizeEvent(e) + _update_vibrancy_mask(self) + + def _hit_close(self, x: float, y: float) -> bool: + cx, cy = self.width() - 23, 19 + return (x - cx) ** 2 + (y - cy) ** 2 <= 16 ** 2 + + # ── Queue ──────────────────────────────────────────────────────────────── + + def _poll(self) -> None: + try: + while True: + state, text = self._q.get_nowait() + self._apply(state, text) + except queue.Empty: + pass + + # ── State ──────────────────────────────────────────────────────────────── + + def _on_cam_frame(self, img: QImage) -> None: + self._cam_pixmap = QPixmap.fromImage(img) + self.update() + + def _on_wake_greeted(self) -> None: + self._wake_greeted = True + self.update() + # Stay visible until user dismisses (× button or Space + Right Option) + + def _end_wake(self) -> None: + self._cam_running = False + self._wake_mode = False + self._wake_greeted = False + self._wake_text = "" + self.hide() + + def _start_camera(self) -> None: + import time + self._cam_running = True + + def _prepare_tts(text: str) -> "str | None": + import os, tempfile + api_key = os.environ.get("OPENAI_API_KEY", "") + if api_key: + try: + from openai import OpenAI # type: ignore[reportMissingImports] + client = OpenAI(api_key=api_key) + with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as f: + path = f.name + with client.audio.speech.with_streaming_response.create( + model="tts-1-hd", voice="nova", input=text, speed=1.0, + ) as resp: + resp.stream_to_file(path) + return path + except Exception as e: + print(f"[tts] OpenAI failed: {e} — falling back to say") + return None + + def _play_tts(path: "str | None", text: str) -> None: + import os, subprocess + if path: + subprocess.run(["afplay", path], check=True) + os.unlink(path) + else: + subprocess.run(["say", "-v", "Flo (English (US))", "-r", "160", text]) + + def _loop() -> None: + import cv2 # type: ignore[reportMissingImports] + cascade = cv2.CascadeClassifier( + cv2.data.haarcascades + "haarcascade_frontalface_default.xml" + ) + cap = cv2.VideoCapture(0) + face_first: float | None = None + greeted = False + tts_started = False + greeting = ( + f"{_time_greeting()}, {USER_NAME}. " + "While you were asleep I've been busy — " + "I found some great opportunities and took care of a few things. " + "Let me walk you through them." + ) + + while self._cam_running: + ok, frame = cap.read() + if not ok: + break + frame = cv2.flip(frame, 1) + grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) + faces = cascade.detectMultiScale(grey, 1.1, 5, minSize=(60, 60)) + + if len(faces) > 0 and not greeted and not tts_started: + if face_first is None: + face_first = time.time() + if time.time() - face_first >= 1.2: + greeted = True + tts_started = True + def _greet_sync(g=greeting) -> None: + # Pre-generate audio first, then show text + play simultaneously + audio_path = _prepare_tts(g) + self._cam_bridge.greeted.emit() + threading.Thread(target=_play_tts, args=(audio_path, g), daemon=True).start() + threading.Thread(target=_greet_sync, daemon=True).start() + elif not greeted and not tts_started: + face_first = None + + rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + fh, fw = rgb.shape[:2] + img = QImage(rgb.data, fw, fh, fw * 3, QImage.Format.Format_RGB888).copy() + self._cam_bridge.frame_ready.emit(img) + + cap.release() + + threading.Thread(target=_loop, daemon=True).start() + + def _apply(self, state: str, text: str) -> None: + self._autohide_timer.stop() + self._pulse_timer.stop() + + if state == "hidden": + self._dock_mode = DOCK_TOP + self._do_hide() + return + + if state == "wake": + if self._wake_mode: + return # already in wake mode — ignore duplicate trigger + self._cam_running = False # stop any lingering camera thread + self._dock_mode = DOCK_TOP + self._wake_mode = True + self._wake_greeted = False + self._wake_text = "" + self._reposition(W_WAKE, H_WAKE) + self.show() + self.raise_() + self._reassert_window_level() + self._start_camera() + return + + # ── Meeting mode states ────────────────────────────────────────────── + if state == "meeting_start": + self._meeting_mode = True + self._meeting_transcript = "" + self._meeting_interim = "" + self._meeting_actions = [] + self._dock_mode = DOCK_RIGHT + self._recording = False + self._prompt_armed = False + h = H_MEETING_BASE + self._reposition(W_MEETING, h) + self._present() + self._pulse_timer.start(PULSE_MS) + self.update() + return + + if state == "meeting_interim": + # Frequent — just update interim text and repaint; don't resize + self._meeting_interim = text + self.update() + return + + if state == "meeting_final": + # Committed utterance: append to rolling transcript, clear interim + self._meeting_interim = "" + combined = (self._meeting_transcript + " " + text).strip() + # Keep last MAX_TRANSCRIPT_CHARS visible + if len(combined) > MAX_TRANSCRIPT_CHARS: + combined = "…" + combined[-MAX_TRANSCRIPT_CHARS:] + self._meeting_transcript = combined + self.update() + return + + if state == "meeting_action": + self._meeting_actions.append((text, "Queued")) + self._meeting_actions = self._meeting_actions[-MAX_ACTIONS_SHOWN:] + n = len(self._meeting_actions) + h = H_MEETING_BASE + n * H_ACTION_ROW + 12 + self._reposition(W_MEETING, h) + self.update() + return + + if state == "meeting_action_update": + # text = "task_description|status" + if "|" in text: + task, status = text.split("|", 1) + for i, (t, _) in enumerate(self._meeting_actions): + if t == task: + self._meeting_actions[i] = (t, status) + break + self.update() + return + + if state == "meeting_stop": + self._meeting_mode = False + self._meeting_transcript = "" + self._meeting_interim = "" + self._meeting_actions = [] + self._pulse_timer.stop() + self._do_hide() + return + + if state == "recording": + self._dock_mode = DOCK_TOP + self._history.clear() + self._prompt_armed = False + self._recording = True + self._pill_label = "Listening..." + self._pulse_on = True + if not self._wake_mode: + self._set_size(W_PILL, H_PILL) + self.show() + self.raise_() + self._reassert_window_level() + self._pulse_timer.start(PULSE_MS) + self.update() + return + + self._recording = False + self._prompt_armed = False + + if state == "transcribing": + pass # no-op — don't show "Transcribing…" in history + elif state == "transcript": + # New command: reset history and dock back to top-center. + # Also clear any lingering citations from the previous turn. + self._history.clear() + self._citations = [] + self._citation_hit_rects = [] + self._dock_mode = DOCK_TOP + self._history.append((text, FG, "user")) + elif state == "intent": + pass # skip intent label — action line already conveys this + elif state == "action": + self._history.append((text, FG, "assistant")) + self._dock_mode = DOCK_RIGHT + elif state == "revealed": + label = f"Revealed: {text}" if text else "Revealed in Finder" + self._history.append((label, GREEN, "assistant")) + self._dock_mode = DOCK_RIGHT + elif state == "done": + self._history.append(("✓ Done", GREEN, "assistant")) + # No autohide — stay visible beside the app until next command + elif state == "error": + self._history.append((text or "Error", ERR, "assistant")) + elif state == "assistant": + self._history.append((text, FG, "assistant")) + # No autohide — stay visible until next command or × dismiss + elif state == "cited_paths": + # text is a JSON-encoded list of {label, path} dicts. Store them + # so paintEvent can render clickable chips. + import json as _json + try: + items = _json.loads(text or "[]") + except _json.JSONDecodeError: + items = [] + self._citations = [ + {"label": str(i.get("label", "")), "path": str(i.get("path", ""))} + for i in items + if isinstance(i, dict) and i.get("path") + ] + self._citation_hit_rects = [] + elif state == "cited": + # Legacy text-only citation — treat as a single chip without + # a path (not clickable, kept for backward compatibility). + self._citations = [{"label": text, "path": ""}] + self._citation_hit_rects = [] + else: + self._history.append((text, FG, "assistant")) + + self._history = self._history[-MAX_HIST:] + self._set_size(W_FULL, self._calc_height()) + self._present() + self.update() + + def _calc_height(self) -> int: + PAD_TOP = 18 + PAD_BOT = 18 + SEP = 10 # separator under user transcript + LINE_H = 26 # height per wrapped line of body text + SMALL_H = 22 # height for user transcript line + h = PAD_TOP + for text, _, kind in self._history: + if kind == "user": + h += SMALL_H + SEP + else: + lines = max(1, (len(text) + 46) // 47) + h += lines * LINE_H + 6 + if self._citations: + # Citation chips render in one horizontal row under the body. + h += CITATION_ROW_H + 6 + h += PAD_BOT + return min(MAX_H, max(H_PILL, h)) + + def _set_size(self, w: int, h: int) -> None: + self._reposition(w, h) + + def _reposition(self, w: int, h: int) -> None: + screen = QGuiApplication.screenAt(QCursor.pos()) or QGuiApplication.primaryScreen() + if screen: + geo = screen.availableGeometry() + if self._dock_mode == DOCK_RIGHT: + x = geo.right() - w - MARGIN_RIGHT + y = geo.top() + MARGIN # top-right, same row as pill + else: + x = geo.center().x() - w // 2 + y = geo.top() + MARGIN + self.setGeometry(x, y, w, h) + else: + self.resize(w, h) + + # ── Paint ───────────────────────────────────────────────────────────────── + + def paintEvent(self, _event) -> None: # type: ignore[override] + p = QPainter(self) + p.setRenderHints(QPainter.RenderHint.Antialiasing | QPainter.RenderHint.TextAntialiasing) + + w, h = self.width(), self.height() + vibrancy = getattr(self, "_vibrancy_active", False) + + shell = QPainterPath() + shell.addRoundedRect(QRect(0, 0, w, h), R, R) + + # ── Wake / call mode — camera feed + greeting ──────────────────────── + if self._wake_mode: + self._paint_wake(p, w, h, shell) + return + + # ── Meeting capture mode ────────────────────────────────────────────── + if self._meeting_mode: + self._paint_glass_body(p, shell, w, h, vibrancy) + self._paint_meeting(p, w, h) + return + + # ── 1. Soft drop shadow (two offset layers for bloom) ───────────────── + for offset, alpha in ((4, 14), (2, 8)): + s = QPainterPath() + s.addRoundedRect(QRect(offset // 2, offset, w - offset, h), R, R) + p.fillPath(s, QColor(0, 0, 0, alpha)) + + # ── 2. Glass body — translucent liquid tint ──────────────────────────── + if vibrancy: + p.fillPath(shell, QColor(18, 18, 22, 145)) # semi-opaque so text pops over blur + else: + p.fillPath(shell, QColor(34, 38, 48, 200)) # solid fallback + + # ── 3. Border — soft glass edge ─────────────────────────────────────── + border = QLinearGradient(0, 0, 0, h) + border.setColorAt(0.0, QColor(255, 255, 255, 68)) + border.setColorAt(0.5, QColor(210, 220, 240, 44)) + border.setColorAt(1.0, QColor(156, 168, 188, 30)) + p.setPen(QPen(QBrush(border), 1.2)) + p.drawPath(shell) + + # ── 4. Inner contour — slight edge depth with low opacity ───────────── + inner = QPainterPath() + inner.addRoundedRect(QRect(1, 1, w - 2, h - 2), R - 1, R - 1) + inner_hi = QLinearGradient(0, 1, 0, h) + inner_hi.setColorAt(0.0, QColor(255, 255, 255, 38)) + inner_hi.setColorAt(1.0, QColor(110, 122, 146, 24)) + p.setPen(QPen(QBrush(inner_hi), 0.8)) + p.drawPath(inner) + + # ── 5. Content ──────────────────────────────────────────────────────── + if self._recording or self._prompt_armed: + self._paint_pill(p) + else: + self._paint_expanded(p) + + def _paint_pill(self, p: QPainter) -> None: + w, h = self.width(), self.height() + cy = h // 2 + + # Blinking dot + p.setPen(Qt.PenStyle.NoPen) + dot = RED if self._pulse_on else QColor(200, 80, 76, 80) + p.setBrush(dot) + p.drawEllipse(QPoint(26, cy), 8, 8) + + # Mic icon + self._draw_mic(p, 52, cy) + + # Label + p.setPen(FG) + p.setFont(self._font_label) + p.drawText( + QRect(74, cy - 12, w - 90, 24), + Qt.AlignmentFlag.AlignVCenter, + self._pill_label, + ) + + def _paint_glass_body( + self, p: QPainter, shell: QPainterPath, w: int, h: int, vibrancy: bool + ) -> None: + """Shared glass background used by meeting mode (and the normal pill path).""" + for offset, alpha in ((4, 14), (2, 8)): + s = QPainterPath() + s.addRoundedRect(QRect(offset // 2, offset, w - offset, h), R, R) + p.fillPath(s, QColor(0, 0, 0, alpha)) + if vibrancy: + p.fillPath(shell, QColor(18, 18, 22, 145)) + else: + p.fillPath(shell, QColor(34, 38, 48, 200)) + border = QLinearGradient(0, 0, 0, h) + border.setColorAt(0.0, QColor(255, 255, 255, 68)) + border.setColorAt(0.5, QColor(210, 220, 240, 44)) + border.setColorAt(1.0, QColor(156, 168, 188, 30)) + p.setPen(QPen(QBrush(border), 1.2)) + p.drawPath(shell) + + def _paint_meeting(self, p: QPainter, w: int, h: int) -> None: + """Meeting capture overlay: live transcript + action items queue.""" + pad = 14 + + # ── Header ──────────────────────────────────────────────────────────── + dot_col = RED if self._pulse_on else QColor(200, 80, 76, 80) + p.setPen(Qt.PenStyle.NoPen) + p.setBrush(dot_col) + p.drawEllipse(QPoint(pad + 6, 22), 6, 6) + + p.setPen(FG) + p.setFont(self._font_label) + p.drawText(QRect(pad + 20, 10, w - 90, 24), Qt.AlignmentFlag.AlignVCenter, + "Meeting Capture") + + p.setPen(DIM) + p.setFont(self._font_small) + p.drawText(QRect(w - 60, 10, 50, 24), Qt.AlignmentFlag.AlignRight | Qt.AlignmentFlag.AlignVCenter, + "say stop") + + # Divider + p.setPen(QPen(QColor(255, 255, 255, 30), 1)) + p.drawLine(QPoint(pad, 38), QPoint(w - pad, 38)) + + # ── Transcript area ─────────────────────────────────────────────────── + tx_y = 46 + tx_h = 110 + tx_w = w - pad * 2 + + # Committed transcript (dim) + p.setPen(DIM) + p.setFont(self._font_small) + _flags = int(Qt.TextFlag.TextWordWrap) | int(Qt.AlignmentFlag.AlignLeft) | int(Qt.AlignmentFlag.AlignBottom) + p.drawText(QRect(pad, tx_y, tx_w, tx_h - 22), _flags, + self._meeting_transcript or "Listening to meeting…") + + # Interim text (live, brighter) — pulsing + if self._meeting_interim: + interim_alpha = 220 if self._pulse_on else 160 + p.setPen(QColor(246, 246, 250, interim_alpha)) + p.setFont(self._font_body) + p.drawText(QRect(pad, tx_y + tx_h - 26, tx_w, 22), + int(Qt.AlignmentFlag.AlignLeft) | int(Qt.AlignmentFlag.AlignVCenter), + self._meeting_interim) + else: + # Blinking cursor to signal active listening + if self._pulse_on: + p.setPen(QColor(100, 210, 255, 180)) + p.setFont(self._font_body) + p.drawText(QRect(pad, tx_y + tx_h - 26, 20, 22), + Qt.AlignmentFlag.AlignLeft, "▌") + + if not self._meeting_actions: + return + + # Divider before actions + sep_y = tx_y + tx_h + 4 + p.setPen(QPen(QColor(255, 255, 255, 30), 1)) + p.drawLine(QPoint(pad, sep_y), QPoint(w - pad, sep_y)) + + p.setPen(DIM) + p.setFont(self._font_small) + p.drawText(QRect(pad, sep_y + 4, 120, 18), Qt.AlignmentFlag.AlignLeft, "Action Items") + + # ── Action items ────────────────────────────────────────────────────── + STATUS_COLOR = { + "Queued": QColor(196, 194, 202), + "Running": BLUE, + "done": GREEN, + "error": ERR, + } + STATUS_LABEL = { + "Queued": "Queued", + "Running": "Running…", + "done": "✓ Done", + "error": "✗ Error", + } + + ay = sep_y + 26 + for task, status in self._meeting_actions: + sc = STATUS_COLOR.get(status, DIM) + label = STATUS_LABEL.get(status, status) + + # Subtle row background + p.setPen(Qt.PenStyle.NoPen) + p.setBrush(QColor(255, 255, 255, 12)) + p.drawRoundedRect(pad, ay, w - pad * 2, H_ACTION_ROW - 4, 8, 8) + + p.setPen(FG) + p.setFont(self._font_small) + p.drawText(QRect(pad + 10, ay + 2, w - 130, H_ACTION_ROW - 6), + int(Qt.AlignmentFlag.AlignLeft) | int(Qt.AlignmentFlag.AlignVCenter), + task) + + p.setPen(sc) + p.drawText(QRect(w - 110, ay + 2, 96, H_ACTION_ROW - 6), + int(Qt.AlignmentFlag.AlignRight) | int(Qt.AlignmentFlag.AlignVCenter), + label) + + ay += H_ACTION_ROW + + def _paint_wake(self, p: QPainter, w: int, h: int, shell: QPainterPath) -> None: + # Low alpha — let desktop vibrancy bleed through the whole panel + p.fillPath(shell, QColor(18, 18, 22, 60)) + border = QLinearGradient(0, 0, 0, h) + border.setColorAt(0, QColor(255, 255, 255, 70)) + border.setColorAt(1, QColor(255, 255, 255, 20)) + p.setPen(QPen(QBrush(border), 1.2)) + p.drawPath(shell) + + pad = 16 + cam_x, cam_y = pad, (h - CAM_H) // 2 + + # Camera feed (rounded) + if not self._cam_pixmap.isNull(): + cam_path = QPainterPath() + cam_path.addRoundedRect(QRect(cam_x, cam_y, CAM_W, CAM_H), 14, 14) + p.setClipPath(cam_path) + scaled = self._cam_pixmap.scaled( + CAM_W, CAM_H, + Qt.AspectRatioMode.KeepAspectRatioByExpanding, + Qt.TransformationMode.SmoothTransformation, + ) + ox = (scaled.width() - CAM_W) // 2 + oy = (scaled.height() - CAM_H) // 2 + p.drawPixmap(cam_x - ox, cam_y - oy, scaled) + p.setClipping(False) + p.setPen(QPen(QColor(255, 255, 255, 50), 1)) + p.drawPath(cam_path) + else: + p.fillRect(QRect(cam_x, cam_y, CAM_W, CAM_H), QColor(40, 40, 44)) + + # Recording indicator (top-right corner when listening) + if self._recording: + dot_color = RED if self._pulse_on else QColor(200, 80, 76, 80) + p.setPen(Qt.PenStyle.NoPen) + p.setBrush(dot_color) + p.drawEllipse(QPoint(w - 20, 16), 6, 6) + p.setPen(DIM) + p.setFont(self._font_small) + p.drawText(QRect(w - 110, 8, 82, 16), Qt.AlignmentFlag.AlignRight, "Listening…") + + # Text area (right of camera) + tx = cam_x + CAM_W + pad + tw = w - tx - pad + + if not self._wake_greeted: + p.setPen(DIM) + p.setFont(self._font_small) + p.drawText(QRect(tx, cam_y + 10, tw, 30), Qt.AlignmentFlag.AlignLeft, "Ali is watching...") + # progress dots + p.setPen(FG) + p.setFont(self._font_body) + p.drawText(QRect(tx, cam_y + 50, tw, 30), Qt.AlignmentFlag.AlignLeft, "Detecting face...") + else: + p.setPen(GREEN) + p.setFont(self._font_label) + p.drawText(QRect(tx, cam_y + 8, tw, 28), Qt.AlignmentFlag.AlignLeft, + f"{_time_greeting()}, {USER_NAME}!") + p.setPen(FG) + p.setFont(self._font_small) + p.drawText( + QRect(tx, cam_y + 44, tw, CAM_H - 50), + int(Qt.TextFlag.TextWordWrap), + "While you were asleep I've been busy — I found great opportunities and took care of things.", + ) + + def _draw_mic(self, p: QPainter, cx: int, cy: int) -> None: + pen = QPen(DIM, 1.8) + pen.setCapStyle(Qt.PenCapStyle.RoundCap) + p.setPen(pen) + p.setBrush(Qt.BrushStyle.NoBrush) + body = QPainterPath() + body.addRoundedRect(cx - 5, cy - 10, 10, 14, 5, 5) + p.drawPath(body) + p.drawArc(QRect(cx - 8, cy + 2, 16, 9), 180 * 16, -180 * 16) + p.drawLine(QPoint(cx, cy + 11), QPoint(cx, cy + 15)) + p.drawLine(QPoint(cx - 5, cy + 15), QPoint(cx + 5, cy + 15)) + + def _paint_expanded(self, p: QPainter) -> None: + w, h = self.width(), self.height() + pad = 22 + + # Subtle × button + p.setPen(QColor(180, 178, 195, 100)) + p.setFont(self._font_close) + p.drawText(QRect(w - 34, 8, 22, 22), Qt.AlignmentFlag.AlignCenter, "×") + + if not self._history: + return + + y = 18 + + for text, colour, kind in self._history: + if kind == "user": + # Command: small, muted — one line, italic + p.setPen(QColor(168, 165, 180)) + p.setFont(self._font_small) + # Trim quotes, truncate to fit one line + display = text.strip('"').strip("'") + if len(display) > 58: + display = display[:55] + "…" + p.drawText( + QRect(pad, y, w - pad * 2 - 30, 22), + int(Qt.AlignmentFlag.AlignLeft) | int(Qt.AlignmentFlag.AlignVCenter), + display, + ) + y += 22 + # Hairline separator + p.setPen(QPen(QColor(255, 255, 255, 22), 0.8)) + p.drawLine(QPoint(pad, y + 4), QPoint(w - pad, y + 4)) + y += 14 + else: + # Response / status — larger, colour-coded + lines = max(1, (len(text) + 46) // 47) + th = lines * 26 + p.setPen(colour) + p.setFont(self._font_body) + _flags = int(Qt.TextFlag.TextWordWrap) | int(Qt.AlignmentFlag.AlignLeft) + p.drawText(QRect(pad, y, w - pad * 2, th), _flags, text) + y += th + 6 + + # Clickable citation chips — painted as pill-shaped links after the + # main body; each chip's on-screen rect is stashed for hit-testing + # in mousePressEvent. + if self._citations: + self._citation_hit_rects = _paint_citation_chips( + p, + citations=self._citations, + font=self._font_small, + pad_left=pad, + y=y, + max_width=w - pad * 2, + ) + y += CITATION_ROW_H + 6 + else: + self._citation_hit_rects = [] + + # ── Timers ──────────────────────────────────────────────────────────────── + + def _pulse_tick(self) -> None: + if self.isVisible(): + self._pulse_on = not self._pulse_on + self.update() + + def _do_hide(self) -> None: + self._pulse_timer.stop() + self._autohide_timer.stop() + self._recording = False + self._prompt_armed = False + self._wake_capture_fn = None + self.hide() + + def _present(self) -> None: + """ + Show overlay above the current app/space without activating a new space. + """ + self.show() + self.raise_() + self._reassert_window_level() + + def _reassert_window_level(self) -> None: + """ + Re-apply NSWindow level / collection / hides-on-deactivate every + time we show. Qt can reset these after a resize or re-parent. + """ + try: + ns_win = getattr(self, "_ns_window", None) + if ns_win is None: + return + ns_win.setLevel_(101) # NSPopUpMenuWindowLevel + ns_win.setCollectionBehavior_(1 | 8 | 64 | 256) + try: + ns_win.setHidesOnDeactivate_(False) + except Exception: + pass + ns_win.orderFrontRegardless() + except Exception: + pass + + def closeEvent(self, _event) -> None: # type: ignore[override] + self._cam_running = False # signal camera thread to stop before Qt tears down diff --git a/Ali/ui/web_overlay.py b/Ali/ui/web_overlay.py new file mode 100644 index 00000000..9e40c3ac --- /dev/null +++ b/Ali/ui/web_overlay.py @@ -0,0 +1,145 @@ +""" +WebSocket bridge overlay for the Tauri/React UI. +""" + +from __future__ import annotations + +import asyncio +import json +import queue +import subprocess +import sys +import threading +import time +from typing import Any, Callable + +import websockets # pyright: ignore[reportMissingImports] + +POLL_MS = 40 + + +class TranscriptionOverlay: + """ + UI bridge that keeps the same push(state, text) contract expected by the agent. + """ + + def __init__(self, host: str = "127.0.0.1", port: int = 8765) -> None: + self._host = host + self._port = port + self._q: queue.Queue[tuple[str, str]] = queue.Queue() + self._clients: set[Any] = set() + self._recent: list[dict[str, str]] = [] + self._lock = threading.Lock() + + self._loop = asyncio.new_event_loop() + self._ready = threading.Event() + self._stopped = threading.Event() + self._thread = threading.Thread(target=self._run_loop, daemon=True) + self._thread.start() + self._ready.wait(timeout=5) + + def push(self, state: str, text: str = "") -> None: + self._q.put((state, text)) + + def schedule_wake_prompt(self, start_capture: Callable[[], None]) -> None: + """Match Qt overlay: armed state → spoken 'Hi' → then start capture (bg thread).""" + self.push("prompt_ready", "") + + def _seq() -> None: + if sys.platform == "darwin": + try: + subprocess.Popen( + ["/usr/bin/say", "-r", "210", "Hi"], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + except Exception: + pass + time.sleep(0.78) + start_capture() + + threading.Thread(target=_seq, daemon=True).start() + + def run_forever(self) -> None: + """ + Keep process alive while the UI runs out-of-process. + """ + print(f"[overlay] Web UI bridge on ws://{self._host}:{self._port}") + try: + while not self._stopped.is_set(): + time.sleep(0.2) + except KeyboardInterrupt: + pass + finally: + self.close() + + def close(self) -> None: + if self._stopped.is_set(): + return + self._stopped.set() + self._q.put(("hidden", "")) + if self._loop.is_running(): + self._loop.call_soon_threadsafe(self._loop.stop) + self._thread.join(timeout=2) + + def _run_loop(self) -> None: + asyncio.set_event_loop(self._loop) + self._server = self._loop.run_until_complete(self._start_server()) + try: + self._loop.run_forever() + finally: + self._server.close() + self._loop.run_until_complete(self._server.wait_closed()) + self._loop.close() + + async def _start_server(self): + server = await websockets.serve(self._handle_client, self._host, self._port) + self._loop.create_task(self._broadcast_loop()) + self._ready.set() + return server + + async def _handle_client(self, websocket) -> None: + with self._lock: + self._clients.add(websocket) + recent = list(self._recent) + + for evt in recent: + await websocket.send(json.dumps(evt)) + + await websocket.send(json.dumps({"state": "system", "text": "Connected to Ali backend"})) + + try: + await websocket.wait_closed() + finally: + with self._lock: + self._clients.discard(websocket) + + async def _broadcast_loop(self) -> None: + while not self._stopped.is_set(): + try: + state, text = self._q.get_nowait() + except queue.Empty: + await asyncio.sleep(POLL_MS / 1000) + continue + event = {"state": state, "text": text} + + with self._lock: + self._recent.append(event) + self._recent = self._recent[-20:] + clients = list(self._clients) + + if not clients: + continue + + dead: list[Any] = [] + payload = json.dumps(event) + for client in clients: + try: + await client.send(payload) + except Exception: + dead.append(client) + + if dead: + with self._lock: + for client in dead: + self._clients.discard(client) diff --git a/Ali/voice/__init__.py b/Ali/voice/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/Ali/voice/capture.py b/Ali/voice/capture.py new file mode 100644 index 00000000..fd0d0856 --- /dev/null +++ b/Ali/voice/capture.py @@ -0,0 +1,422 @@ +""" +Layer 1 — Voice Capture +Push-to-talk: hold Right Option to record, release to stop. +Yields raw audio bytes for each completed utterance. +""" + +import asyncio +import io +import os +import struct +import threading +import time +import wave +from typing import AsyncGenerator, Callable + +import pyaudio # pyright: ignore[reportMissingModuleSource] +from pynput import keyboard # pyright: ignore[reportMissingModuleSource] + +# #region agent log +def _dlog(loc: str, msg: str, data: dict, hid: str = "H6") -> None: + try: + import json as _j, os as _o, time as _t + _p = "/Users/alspenceramitojr/Desktop/Ali/.cursor/debug-4ea166.log" + _o.makedirs(_o.path.dirname(_p), exist_ok=True) + with open(_p, "a") as _f: + _f.write(_j.dumps({"sessionId":"4ea166","hypothesisId":hid,"location":loc, + "message":msg,"data":data,"timestamp":int(_t.time()*1000)})+"\n") + _f.flush() + except Exception: + pass +# #endregion + +SAMPLE_RATE = 16000 +CHANNELS = 1 +CHUNK = 1024 +FORMAT = pyaudio.paInt16 + +# The hotkey that triggers recording +TRIGGER_KEY = keyboard.Key.alt_r + +# Set while listen_for_command is active — wake word / demo hotkey call +# request_ptt_session_from_wake() to reuse the same path as Right Option. +_ptt_start_flag: threading.Event | None = None + +# macOS: backtick is delivered via AppKit global monitor (ui/overlay.py) → Qt +# signal → this callback. Set by listen_for_command while the async loop runs. +_backtick_callback: Callable[[], None] | None = None +_right_option_down: Callable[[], None] | None = None +_right_option_up: Callable[[], None] | None = None + + +def register_backtick_callback(cb: Callable[[], None] | None) -> None: + """Wire the same handler as pynput's on_backtick (macOS global ` key).""" + global _backtick_callback + _backtick_callback = cb + + +def invoke_backtick_callback() -> None: + """Called from Qt main thread when global backtick fires.""" + cb = _backtick_callback + if cb is None: + print( + "[voice] Backtick ignored — voice loop not ready yet (wait for " + "\"ready — say 'Ali'…\").", + flush=True, + ) + return + try: + cb() + except Exception as e: + print(f"[voice] backtick callback error: {e}", flush=True) + + +def register_right_option_callbacks( + down: Callable[[], None] | None, + up: Callable[[], None] | None, +) -> None: + """AppKit global monitor → same path as pynput Right Option.""" + global _right_option_down, _right_option_up + _right_option_down, _right_option_up = down, up + + +def invoke_right_option_down() -> None: + fn = _right_option_down + if fn is not None: + try: + fn() + except Exception as e: + print(f"[voice] Right Option down error: {e}", flush=True) + + +def invoke_right_option_up() -> None: + fn = _right_option_up + if fn is not None: + try: + fn() + except Exception as e: + print(f"[voice] Right Option up error: {e}", flush=True) + +# Next capture after start_flag is triggered via wake/backtick: end-of-utterance +# by silence (Option release still works to cut short). +_conversational_lock = threading.Lock() +_next_session_conversational = False + +CONV_RMS_THRESHOLD = 180.0 +CONV_SILENCE_SEC = 0.88 +CONV_MIN_VOICE_SEC = 0.38 +CONV_MAX_SEC = 10.0 + + +def _pcm16_rms(data: bytes) -> float: + n = len(data) // 2 + if n <= 0: + return 0.0 + fmt = f"{n}h" + samples = struct.unpack(fmt, data[: n * 2]) + return (sum(s * s for s in samples) / n) ** 0.5 + + +def _record_conversational( + stop_flag: threading.Event, + stream, + frames: list[bytes], + chunk: int, +) -> None: + t0 = time.monotonic() + last_loud = t0 + voice_since: float | None = None + peak_rms = 0.0 + end_reason = "stop_flag" + + while not stop_flag.is_set(): + data = stream.read(chunk, exception_on_overflow=False) + frames.append(data) + now = time.monotonic() + rms = _pcm16_rms(data) + if rms > peak_rms: + peak_rms = rms + if now - t0 > CONV_MAX_SEC: + end_reason = "max_sec" + break + + if rms >= CONV_RMS_THRESHOLD: + last_loud = now + if voice_since is None: + voice_since = now + + if voice_since is not None: + if (now - voice_since) >= CONV_MIN_VOICE_SEC and (now - last_loud) >= CONV_SILENCE_SEC: + end_reason = "silence_after_voice" + break + # #region agent log + _dlog( + "capture:_record_conversational", + "conversational capture ended", + { + "end_reason": end_reason, + "seconds": round(time.monotonic() - t0, 2), + "voice_started": voice_since is not None, + "peak_rms": round(peak_rms, 2), + "threshold": CONV_RMS_THRESHOLD, + }, + "H6", + ) + # #endregion + + +def request_ptt_session_from_wake(overlay=None) -> None: + """ + Start a capture session from wake word or `` ` ``: recording UI + mic. + Uses silence-based end-of-utterance (hands-free); releasing Right Option + still stops early. + """ + global _next_session_conversational + with _conversational_lock: + _next_session_conversational = True + try: + from voice.wake_word import recording_active + + recording_active.set() + except Exception: + pass + if overlay: + overlay.push("recording") + if _ptt_start_flag is not None: + _ptt_start_flag.set() + + +async def listen_for_command( + overlay=None, + *, + after_ptt_armed: Callable[[], None] | None = None, + on_backtick: Callable[[], None] | None = None, +) -> AsyncGenerator[bytes, None]: + """ + Async generator. Each iteration yields PCM audio bytes for one utterance. + Blocks until push-to-talk key is held, records until released. + + Uses threading.Event (not asyncio.Event) because the keyboard listener + runs in its own thread — threading.Event can be set/checked across threads + without needing the asyncio event loop. + + overlay: optional TranscriptionOverlay — if provided, push("recording") is + called from the keyboard thread the instant Right Option is pressed. + + after_ptt_armed: invoked once the PTT bridge is live (after _ptt_start_flag + is set). Used to start wake-word listening only after wake can + trigger the same capture path as Right Option. + + on_backtick: if set, `` ` `` (backtick) invokes this instead of starting a + second pynput listener (macOS often SIGTRAPs with two listeners). + """ + audio = pyaudio.PyAudio() + input_device = _get_active_input_device(audio) + if input_device: + print( + "[voice] Active mic: " + f'#{input_device["index"]} "{input_device["name"]}" ' + f'({int(input_device["defaultSampleRate"])} Hz)' + ) + else: + print("[voice] Active mic: unknown (could not read PyAudio default input device)") + + # threading.Events work across threads; asyncio.Events don't + global _ptt_start_flag + start_flag = threading.Event() + _ptt_start_flag = start_flag + stop_flag = threading.Event() + is_recording = threading.Event() + held_keys: set = set() + + def on_press(key): + held_keys.add(key) + try: + if on_backtick is not None and key.char == "`": + on_backtick() + return + except AttributeError: + pass + # Space + Right Option → dismiss overlay + if key in (TRIGGER_KEY, keyboard.Key.space) and \ + TRIGGER_KEY in held_keys and keyboard.Key.space in held_keys: + if overlay: + overlay.push("hidden") + if is_recording.is_set(): + stop_flag.set() + return + if key == TRIGGER_KEY and not is_recording.is_set(): + try: + from voice.wake_word import recording_active + recording_active.set() + except Exception: + pass + if overlay: + overlay.push("recording") + start_flag.set() + + def on_release(key): + held_keys.discard(key) + if key == TRIGGER_KEY and is_recording.is_set(): + stop_flag.set() + try: + from voice.wake_word import recording_active + recording_active.clear() + except Exception: + pass + + # macOS: pynput's Listener can SIGTRAP under Qt; disabled by default. Backtick + # is handled by AppKit global monitor in ui/overlay.py (see + # invoke_backtick_callback). Set ALI_ENABLE_HOTKEY=1 to use pynput instead. + _hotkey_enabled = os.environ.get("ALI_ENABLE_HOTKEY") == "1" + listener = None + if _hotkey_enabled: + listener = keyboard.Listener(on_press=on_press, on_release=on_release) + listener.start() + + print( + "[voice] Ready — say “Ali”, press ` (backtick), or hold Right Option to record", + flush=True, + ) + loop = asyncio.get_event_loop() + # macOS: starting speech_recognition / a second mic consumer in the same + # process immediately after PyAudio+pynput init can SIGTRAP ("trace trap"). + # Arm wake-word only after the asyncio loop is waiting on PTT (idle path). + if after_ptt_armed is not None: + delay = float(os.environ.get("ALI_WAKE_ARM_DELAY", "0.9")) + + async def _arm_wake_when_safe() -> None: + await asyncio.sleep(delay) + try: + after_ptt_armed() + except Exception as e: + print(f"[voice] Failed to start wake listener: {e}", flush=True) + + loop.create_task(_arm_wake_when_safe()) + + def _ro_down() -> None: + if is_recording.is_set(): + return + try: + from voice.wake_word import recording_active + + recording_active.set() + except Exception: + pass + if overlay: + overlay.push("recording") + start_flag.set() + + def _ro_up() -> None: + if is_recording.is_set(): + stop_flag.set() + try: + from voice.wake_word import recording_active + + recording_active.clear() + except Exception: + pass + + register_backtick_callback(on_backtick) + register_right_option_callbacks(_ro_down, _ro_up) + + global _next_session_conversational + + try: + while True: + # Wait for key press without blocking the event loop + await loop.run_in_executor(None, start_flag.wait) + start_flag.clear() + stop_flag.clear() + is_recording.set() + + with _conversational_lock: + conversational = _next_session_conversational + _next_session_conversational = False + + if conversational: + print( + "[voice] Recording... hands-free — pause when done, " + "or tap Right Option to stop early" + ) + else: + print("[voice] Recording... (release Right Option to stop)") + frames = [] + + stream = audio.open( + format=FORMAT, + channels=CHANNELS, + rate=SAMPLE_RATE, + input=True, + frames_per_buffer=CHUNK, + ) + + # Record in a thread so blocking stream.read() doesn't stall the loop + if conversational: + + def _record() -> None: + _record_conversational(stop_flag, stream, frames, CHUNK) + + else: + + def _record() -> None: + while not stop_flag.is_set(): + data = stream.read(CHUNK, exception_on_overflow=False) + frames.append(data) + + await loop.run_in_executor(None, _record) + + stream.stop_stream() + stream.close() + is_recording.clear() + try: + from voice.wake_word import recording_active + + recording_active.clear() + except Exception: + pass + + duration = len(frames) * CHUNK / SAMPLE_RATE + print(f"[voice] Captured {duration:.1f}s of audio ({len(frames)} chunks)") + + if len(frames) < 3: + print("[voice] Too short — ignored") + continue + + audio_bytes = _frames_to_wav(frames) + yield audio_bytes + + finally: + _ptt_start_flag = None + register_backtick_callback(None) + register_right_option_callbacks(None, None) + if listener is not None: + listener.stop() + audio.terminate() + + +def _frames_to_wav(frames: list[bytes]) -> bytes: + buf = io.BytesIO() + with wave.open(buf, "wb") as wf: + wf.setnchannels(CHANNELS) + wf.setsampwidth(2) # 16-bit + wf.setframerate(SAMPLE_RATE) + wf.writeframes(b"".join(frames)) + return buf.getvalue() + + +def _get_active_input_device(audio: pyaudio.PyAudio) -> dict | None: + """ + Return the current default input device reported by PortAudio. + This mirrors the mic the app will use when opening input=True stream + without an explicit device index. + """ + try: + info = audio.get_default_input_device_info() + return { + "index": int(info.get("index", -1)), + "name": str(info.get("name", "unknown")), + "defaultSampleRate": float(info.get("defaultSampleRate", 0.0)), + } + except Exception: + return None diff --git a/Ali/voice/deepgram_stream.py b/Ali/voice/deepgram_stream.py new file mode 100644 index 00000000..3ed3c5ed --- /dev/null +++ b/Ali/voice/deepgram_stream.py @@ -0,0 +1,108 @@ +""" +Real-time streaming transcription via Deepgram Nova-2 (SDK v6). + +Streams 16kHz PCM-16 audio from PyAudio to Deepgram's WebSocket API. +Calls on_interim(text) for partial words and on_final(text) for committed utterances. + +Requires: pip install deepgram-sdk +""" +from __future__ import annotations + +import threading +from typing import Callable + +import pyaudio + +from config.settings import DEEPGRAM_API_KEY + +SAMPLE_RATE = 16000 +CHANNELS = 1 +CHUNK = 1024 +FORMAT = pyaudio.paInt16 + +_meeting_active = threading.Event() + + +def start_meeting_audio() -> None: + _meeting_active.set() + + +def stop_meeting_audio() -> None: + _meeting_active.clear() + + +def is_meeting_active() -> bool: + return _meeting_active.is_set() + + +def stream_transcription_sync( + stop_event: threading.Event, + on_interim: Callable[[str], None], + on_final: Callable[[str], None], +) -> None: + """ + Blocking — run inside a thread. + Opens mic, streams to Deepgram until stop_event is set. + """ + try: + from deepgram import DeepgramClient # type: ignore[reportMissingImports] + from deepgram.listen.v1.socket_client import ( # type: ignore[reportMissingImports] + ListenV1Results, + ) + from deepgram.core.events import EventType # type: ignore[reportMissingImports] + except ImportError: + raise RuntimeError("pip install deepgram-sdk") + + dg = DeepgramClient(access_token=DEEPGRAM_API_KEY) + + audio = pyaudio.PyAudio() + stream = audio.open( + format=FORMAT, + channels=CHANNELS, + rate=SAMPLE_RATE, + input=True, + frames_per_buffer=CHUNK, + ) + + print("[deepgram] Streaming started") + try: + with dg.listen.v1.connect( + model="nova-2", + encoding="linear16", + sample_rate=SAMPLE_RATE, + interim_results=True, + vad_events=True, + utterance_end_ms=1200, + ) as connection: + + def _on_message(msg) -> None: + if not isinstance(msg, ListenV1Results): + return + try: + text = msg.channel.alternatives[0].transcript.strip() + if not text: + return + if msg.is_final: + on_final(text) + else: + on_interim(text) + except Exception: + pass + + connection.on(EventType.MESSAGE, _on_message) + + # Run the listener in a background thread so we can keep sending audio + listener = threading.Thread(target=connection.start_listening, daemon=True) + listener.start() + + while not stop_event.is_set(): + data = stream.read(CHUNK, exception_on_overflow=False) + connection.send_media(data) + + connection.send_close_stream() + listener.join(timeout=2.0) + finally: + stream.stop_stream() + stream.close() + audio.terminate() + print("[deepgram] Streaming stopped") diff --git a/Ali/voice/meeting_capture.py b/Ali/voice/meeting_capture.py new file mode 100644 index 00000000..7423d9db --- /dev/null +++ b/Ali/voice/meeting_capture.py @@ -0,0 +1,140 @@ +""" +Meeting capture mode. + +Streams mic audio via Deepgram for real-time word display, then +periodically sends the rolling transcript to Gemma 4 to extract +action items, and executes them via the orchestrator. +""" +from __future__ import annotations + +import asyncio +import threading +import time +from typing import Any, Callable + +# How often (seconds) to send new transcript to Gemma 4 for action extraction. +EXTRACT_INTERVAL = 12.0 + +# Stop-words in Deepgram final transcript that end the meeting. +STOP_PHRASES = {"stop", "stop meeting", "end meeting", "stop capture", "ali stop"} + + +class MeetingCapture: + """ + Lifecycle: create → await run() to stream; call stop() to end. + + Callbacks (all called from asyncio loop): + on_interim(text) — partial words, update overlay live + on_final(text) — committed utterance, append to transcript + on_action_found(item) — new action item dict from Gemma 4 + on_action_done(task, status) — execution result ("done" | "error") + """ + + def __init__( + self, + on_interim: Callable[[str], None], + on_final: Callable[[str], None], + on_action_found: Callable[[dict[str, Any]], None], + on_action_done: Callable[[str, str], None], + ) -> None: + self._on_interim = on_interim + self._on_final = on_final + self._on_action_found = on_action_found + self._on_action_done = on_action_done + + self._stop_event = threading.Event() + self._final_segments: list[str] = [] # all committed text + self._unsent_finals: list[str] = [] # not yet sent to Gemma 4 + self._captured_items: list[dict[str, Any]] = [] + self._lock = threading.Lock() + self._loop: asyncio.AbstractEventLoop | None = None + + # ── Public ──────────────────────────────────────────────────────────────── + + def stop(self) -> None: + self._stop_event.set() + + async def run(self) -> None: + from voice.deepgram_stream import stream_transcription_sync, start_meeting_audio, stop_meeting_audio + from intent.meeting_intelligence import extract_action_items, item_to_intent + from orchestrator.orchestrator import Orchestrator + + self._loop = asyncio.get_event_loop() + orchestrator = Orchestrator() + + start_meeting_audio() + + def _interim(text: str) -> None: + if self._loop: + self._loop.call_soon_threadsafe(self._on_interim, text) + + def _final(text: str) -> None: + # Check for stop command inside the stream + if text.lower().strip().rstrip(".!?") in STOP_PHRASES: + self._stop_event.set() + return + with self._lock: + self._final_segments.append(text) + self._unsent_finals.append(text) + if self._loop: + self._loop.call_soon_threadsafe(self._on_final, text) + + # Start Deepgram in a background thread + stream_thread = threading.Thread( + target=stream_transcription_sync, + args=(self._stop_event, _interim, _final), + daemon=True, + ) + stream_thread.start() + + last_extract = time.monotonic() + + try: + while not self._stop_event.is_set(): + await asyncio.sleep(1.0) + + if time.monotonic() - last_extract < EXTRACT_INTERVAL: + continue + + with self._lock: + segment = " ".join(self._unsent_finals).strip() + self._unsent_finals.clear() + + last_extract = time.monotonic() + + if not segment: + continue + + print(f"[meeting] Analyzing segment: {segment[:80]}…") + + try: + new_items = await extract_action_items(segment, self._captured_items) + except Exception as e: + print(f"[meeting] Extraction error: {e}") + continue + + for item in new_items: + self._captured_items.append(item) + self._on_action_found(item) + print(f"[meeting] Action found: {item.get('task')}") + + # Execute asynchronously — don't block the stream + asyncio.create_task( + self._execute_item(item, orchestrator) + ) + finally: + self._stop_event.set() + stop_meeting_audio() + stream_thread.join(timeout=3.0) + + async def _execute_item(self, item: dict[str, Any], orchestrator) -> None: + from intent.meeting_intelligence import item_to_intent + task = item.get("task", "") + try: + intent = item_to_intent(item) + if intent.goal.value != "unknown": + await orchestrator.run(intent) + self._on_action_done(task, "done") + except Exception as e: + print(f"[meeting] Execution failed for '{task}': {e}") + self._on_action_done(task, "error") diff --git a/Ali/voice/speak.py b/Ali/voice/speak.py new file mode 100644 index 00000000..9897b2a8 --- /dev/null +++ b/Ali/voice/speak.py @@ -0,0 +1,77 @@ +""" +Tiny TTS helper — non-blocking macOS `say` by default. + +Callable from any thread. Returns immediately; speech plays in the background. +""" + +from __future__ import annotations + +import subprocess +import sys +import threading + + +# "Ava (Enhanced)" is a neural voice on macOS 13+; fallback to Samantha if missing. +_PREFERRED_VOICES = ["Ava (Enhanced)", "Nicky (Enhanced)", "Zoe (Enhanced)", "Samantha"] +DEFAULT_VOICE = _PREFERRED_VOICES[0] +DEFAULT_RATE = "160" +tts_active = threading.Event() + + +def _best_available_voice() -> str: + """Return the first installed enhanced voice, or Samantha.""" + try: + result = subprocess.run( + ["/usr/bin/say", "-v", "?"], + capture_output=True, text=True, timeout=3, + ) + installed = result.stdout.lower() + for v in _PREFERRED_VOICES: + if v.lower().split(" (")[0] in installed: + return v + except Exception: + pass + return "Samantha" + + +_VOICE_CACHE: str | None = None + + +def _voice() -> str: + global _VOICE_CACHE + if _VOICE_CACHE is None: + _VOICE_CACHE = _best_available_voice() + return _VOICE_CACHE + + +def track_tts_process(proc: subprocess.Popen[bytes]) -> None: + """Mark TTS as active until this process exits.""" + tts_active.set() + + def _wait() -> None: + try: + proc.wait(timeout=12) + except Exception: + pass + finally: + tts_active.clear() + + threading.Thread(target=_wait, daemon=True).start() + + +def speak(text: str, voice: str | None = None, rate: str = DEFAULT_RATE) -> None: + """Speak `text` asynchronously. Safe no-op on non-macOS.""" + if not text or not text.strip(): + return + if sys.platform != "darwin": + return + chosen_voice = voice or _voice() + try: + proc = subprocess.Popen( + ["/usr/bin/say", "-v", chosen_voice, "-r", rate, text], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + track_tts_process(proc) + except Exception: + pass diff --git a/Ali/voice/transcribe.py b/Ali/voice/transcribe.py new file mode 100644 index 00000000..be9d8f2e --- /dev/null +++ b/Ali/voice/transcribe.py @@ -0,0 +1,96 @@ +""" +Layer 1 — Speech-to-Text + +Priority order: + 1. faster-whisper — loads in ~3s, transcribes in ~0.1s. Best for the demo. + 2. Cactus CLI — `cactus transcribe` uses Parakeet (0.6B). 0.03s inference + but ~2.5 min cold-load. Use if pre-warmed at startup. + +Demo note: faster-whisper is the default because its model loads quickly. +Cactus/Parakeet is faster per-call but the cold-start dominates in real use. +The audio never leaves the device in either case. +""" + +import asyncio +import os +import shutil +import tempfile + +try: + from faster_whisper import WhisperModel # type: ignore + WHISPER_AVAILABLE = True +except ImportError: + WHISPER_AVAILABLE = False + +CACTUS_CLI = shutil.which("cactus") +CACTUS_AVAILABLE = CACTUS_CLI is not None + +from config.settings import WHISPER_MODEL_SIZE + +_whisper_model = None + + +def warmup(): + """ + Pre-load the Whisper model at startup so the first real transcription + is instant. Call this once from main.py before entering the listen loop. + """ + print("[stt] Warming up Whisper model...") + _get_whisper() + print("[stt] Ready.") + + +def _get_whisper(): + global _whisper_model + if _whisper_model is None: + _whisper_model = WhisperModel(WHISPER_MODEL_SIZE, device="cpu", compute_type="int8") + return _whisper_model + + +async def transcribe(audio_bytes: bytes) -> str: + """ + Transcribe raw WAV audio bytes → text string. + Uses faster-whisper by default (fast cold-start). + Falls back to Cactus if Whisper is unavailable. + """ + if WHISPER_AVAILABLE: + return await asyncio.get_event_loop().run_in_executor( + None, _transcribe_whisper, audio_bytes + ) + + if CACTUS_AVAILABLE: + return await _transcribe_cactus_cli(audio_bytes) + + raise RuntimeError( + "No STT backend available. Run: pip install faster-whisper" + ) + + +def _transcribe_whisper(audio_bytes: bytes) -> str: + model = _get_whisper() + with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f: + f.write(audio_bytes) + tmp_path = f.name + try: + segments, _ = model.transcribe(tmp_path, beam_size=5) + return " ".join(seg.text for seg in segments).strip() + finally: + os.unlink(tmp_path) + + +async def _transcribe_cactus_cli(audio_bytes: bytes) -> str: + with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f: + f.write(audio_bytes) + tmp_path = f.name + try: + proc = await asyncio.create_subprocess_exec( + CACTUS_CLI, "transcribe", tmp_path, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + stdout, stderr = await proc.communicate() + if proc.returncode != 0: + raise RuntimeError(stderr.decode().strip()) + return stdout.decode().strip() + finally: + os.unlink(tmp_path) diff --git a/Ali/voice/wake_word.py b/Ali/voice/wake_word.py new file mode 100644 index 00000000..7c406016 --- /dev/null +++ b/Ali/voice/wake_word.py @@ -0,0 +1,195 @@ +""" +Wake-word listener: detects 'Ali' or 'Hey Ali' and fires a callback. +Uses SpeechRecognition + Google API in short bursts, pausing while the +main push-to-talk is recording (to avoid PyAudio mic conflicts). +Falls back gracefully if the library isn't installed. +""" +from __future__ import annotations + +import threading +import time +from typing import Callable + +# #region agent log +def _dlog(loc: str, msg: str, data: dict, hid: str = "H1") -> None: + try: + import json as _j, os as _o, time as _t + _p = "/Users/alspenceramitojr/Desktop/Ali/.cursor/debug-4ea166.log" + _o.makedirs(_o.path.dirname(_p), exist_ok=True) + with open(_p, "a") as _f: + _f.write(_j.dumps({"sessionId":"4ea166","hypothesisId":hid,"location":loc, + "message":msg,"data":data,"timestamp":int(_t.time()*1000)})+"\n") + _f.flush() + except Exception: + pass +# #endregion + +# Set to True by voice/capture.py while Right Option is held. +recording_active = threading.Event() + +# Avoid stacking multiple wake callbacks (parallel Google threads + repeated “ali”). +_WAKE_COOLDOWN_SEC = 4.0 +_wake_lock = threading.Lock() +_last_wake_mono: float | None = None +_INLINE_COMMAND_PREFIXES = ( + "open ", + "find ", + "show ", + "reveal ", + "locate ", + "send ", + "text ", + "message ", + "email ", + "what ", + "who ", + "where ", + "when ", + "how ", + "why ", +) +_WAKE_ALIASES = {"ali", "al", "ally", "allie"} + + +def _rms16(frame_data: bytes) -> float: + if not frame_data: + return 0.0 + # 16-bit little-endian mono PCM from SpeechRecognition AudioData + import array + samples = array.array("h") + samples.frombytes(frame_data[: (len(frame_data) // 2) * 2]) + if not samples: + return 0.0 + return (sum(int(s) * int(s) for s in samples) / len(samples)) ** 0.5 + + +def start_wake_word_listener(callback: Callable[[str], None]) -> None: + """Start a background thread that calls callback() when 'Ali' is heard.""" + + def _check(recognizer, audio, audio_end_mono: float) -> None: + global _last_wake_mono + try: + frame_data = getattr(audio, "frame_data", b"") or b"" + rms = _rms16(frame_data) + # #region agent log + _dlog( + "wake_word:_check:pre_recognize", + "captured chunk before recognize_google", + {"bytes": len(frame_data), "rms": round(rms, 2)}, + "H7", + ) + # #endregion + t0 = time.monotonic() + text = recognizer.recognize_google(audio).lower() + google_ms = int((time.monotonic() - t0) * 1000) + print(f"[wake_word] Heard: \"{text}\" ({google_ms}ms)") + words = {w.strip(".,!?").lower() for w in text.split()} + has_wake = any(w in _WAKE_ALIASES for w in words) + has_wake_like_prefix = any(w.startswith("al") for w in words if len(w) >= 2) + has_wake = has_wake or has_wake_like_prefix + inline_command = text.startswith(_INLINE_COMMAND_PREFIXES) and len(text.split()) >= 2 + if not has_wake and not inline_command: + # #region agent log + _dlog("wake_word:_check:no_ali", "google returned but no ali", + {"text": text, "google_ms": google_ms}, "H1") + # #endregion + return + with _wake_lock: + now = time.monotonic() + if _last_wake_mono is not None and (now - _last_wake_mono) < _WAKE_COOLDOWN_SEC: + return + _last_wake_mono = now + post_speech_ms = int((time.monotonic() - audio_end_mono) * 1000) + print(f"[wake_word] Heard: '{text}' → triggering") + # #region agent log + _dlog("wake_word:_check:trigger", "wake trigger firing callback", + {"text": text, "google_ms": google_ms, + "has_wake": has_wake, "inline_command": inline_command, + "wake_alias_hit": sorted(list(words & _WAKE_ALIASES)), + "ms_since_audio_end": post_speech_ms}, "H1") + # #endregion + callback(text) + except Exception as e: + err_type = type(e).__name__ + if "UnknownValueError" in err_type: + print("[wake_word] Google: couldn't understand audio") + elif "RequestError" in err_type: + print(f"[wake_word] Google API error (no internet?): {e}") + else: + print(f"[wake_word] Recognition error: {err_type}: {e}") + + def _run() -> None: + try: + import speech_recognition as sr # type: ignore[reportMissingImports] + except ImportError: + print("[wake_word] speech_recognition not installed — skipping voice wake word") + return + + r = sr.Recognizer() + r.energy_threshold = 300 + r.dynamic_energy_threshold = False # don't let it drift too high in quiet rooms + r.pause_threshold = 0.6 + r.non_speaking_duration = 0.35 + + try: + mic = sr.Microphone() + except Exception as e: + print(f"[wake_word] No microphone: {e}") + return + + with mic as source: + print("[wake_word] Calibrating ambient noise…") + r.adjust_for_ambient_noise(source, duration=1.0) + # Cap the calibrated threshold so quiet rooms don't kill detection + if r.energy_threshold > 600: + r.energy_threshold = 600 + print(f"[wake_word] Ready — threshold={r.energy_threshold:.0f} say 'Ali' to wake") + + last_tts_log_mono = 0.0 + last_timeout_log_mono = 0.0 + timeout_count = 0 + last_error_log_mono = 0.0 + while True: + # Don't open mic while push-to-talk is using it + tts_busy = False + try: + from voice.speak import tts_active + tts_busy = tts_active.is_set() + except Exception: + tts_busy = False + if recording_active.is_set(): + recording_active.wait(timeout=5) + continue + if tts_busy: + now_mono = time.monotonic() + if now_mono - last_tts_log_mono > 0.8: + # #region agent log + _dlog("wake_word:tts_suppressed", "skipping wake listen during TTS", {}, "H5") + # #endregion + last_tts_log_mono = now_mono + continue + try: + listen_started = time.monotonic() + with mic as source: + audio = r.listen(source, timeout=2, phrase_time_limit=2.4) + audio_end_mono = time.monotonic() + timeout_count = 0 + frame_bytes = len(getattr(audio, "frame_data", b"") or b"") + print(f"[wake_word] Audio captured ({frame_bytes} bytes) — sending to Google…") + if not recording_active.is_set(): + threading.Thread(target=_check, args=(r, audio, audio_end_mono), daemon=True).start() + except Exception as e: + err_type = type(e).__name__ + now_mono = time.monotonic() + if err_type == "WaitTimeoutError": + timeout_count += 1 + if now_mono - last_timeout_log_mono > 5.0: + print(f"[wake_word] Listening… (no speech in last 5s, threshold={r.energy_threshold:.0f})") + last_timeout_log_mono = now_mono + timeout_count = 0 + else: + if now_mono - last_error_log_mono > 2.0: + print(f"[wake_word] Listen error: {err_type}: {e}") + last_error_log_mono = now_mono + + threading.Thread(target=_run, daemon=True, name="wake-word").start() diff --git a/tests.txt b/tests.txt new file mode 100644 index 00000000..541ba1b8 --- /dev/null +++ b/tests.txt @@ -0,0 +1,3 @@ +python scripts/debug_local_flow.py --transcript "find my resume" --execute --auto-approve + +source ~/Documents/cactus/venv/bin/activate \ No newline at end of file