Multi-Agent Collaboration Notebook

authors.yaml

@@ -2,6 +2,16 @@
 
 # You can optionally customize how your information shows up cookbook.openai.com over here.
 # If your information is not present here, it will be pulled from your GitHub profile.
+rajpathak-openai:
+  name: "Raj Pathak"
+  website: "https://www.linkedin.com/in/rajpathakopenai/"
+  avatar: "https://avatars.githubusercontent.com/u/208723614?s=400&u=c852eed3be082f7fbd402b5a45e9b89a0bfed1b8&v=4"
+
+chelseahu-openai:
+  name: "Chelsea Hu"
+  website: "https://www.linkedin.com/in/chelsea-tsaiszuhu/"
+  avatar: "https://avatars.githubusercontent.com/u/196863678?v=4"
+
 prashantmital-openai:
   name: "Prashant Mital"
   website: "https://www.linkedin.com/in/pmital/"
@@ -336,3 +346,4 @@ tompakeman-oai:
   name: "Tom Pakeman"
   website: "https://www.linkedin.com/in/tom-pakeman/"
   avatar: "https://avatars.githubusercontent.com/u/204937754"
+

examples/agents_sdk/multi-agent-portfolio-collaboration/.gitignore

@@ -0,0 +1,74 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Installer logs
+distutils.log
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Jupyter Notebook checkpoints
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# mypy
+.mypy_cache/
+.dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# VS Code
+.vscode/
+
+# Mac OS
+.DS_Store
+
+# Output and log directories
+outputs/
+logs/
+
+# Project-specific logs and outputs
+*.log
+*.jsonl
+
+# Secret keys and environment variables
+.env
+.env.* 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/__init__.py

@@ -0,0 +1 @@
+# This file marks the agents directory as a Python package. 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/config.py

@@ -0,0 +1,30 @@
+from dataclasses import dataclass
+from investment_agents.fundamental import build_fundamental_agent
+from investment_agents.macro import build_macro_agent
+from investment_agents.quant import build_quant_agent
+from investment_agents.editor import build_editor_agent, build_memo_edit_tool
+from investment_agents.pm import build_head_pm_agent, SpecialistRequestInput
+import asyncio
+
+@dataclass
+class InvestmentAgentsBundle:
+    head_pm: object
+    fundamental: object
+    macro: object
+    quant: object
+
+
+def build_investment_agents() -> InvestmentAgentsBundle:
+    fundamental = build_fundamental_agent()
+    macro = build_macro_agent()
+    quant = build_quant_agent()
+    editor = build_editor_agent()
+    memo_edit_tool = build_memo_edit_tool(editor)
+    head_pm = build_head_pm_agent(fundamental, macro, quant, memo_edit_tool)
+    return InvestmentAgentsBundle(
+        head_pm=head_pm,
+        fundamental=fundamental,
+        macro=macro,
+        quant=quant,
+    )
+

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/editor.py

@@ -0,0 +1,40 @@
+from agents import Agent, ModelSettings, function_tool, Runner, RunContextWrapper
+from tools import write_markdown, read_file, list_output_files
+from utils import load_prompt, DISCLAIMER
+from pydantic import BaseModel
+import json
+
+default_model = "gpt-4.1"
+
+class MemoEditorInput(BaseModel):
+    fundamental: str
+    macro: str
+    quant: str
+    pm: str
+    files: list[str]
+
+def build_editor_agent():
+    tool_retry_instructions = load_prompt("tool_retry_prompt.md")
+    editor_prompt = load_prompt("editor_base.md")
+    return Agent(
+        name="Memo Editor Agent",
+        instructions=(editor_prompt + DISCLAIMER + tool_retry_instructions),
+        tools=[write_markdown, read_file, list_output_files],
+        model=default_model,
+        model_settings=ModelSettings(temperature=0),
+    )
+
+def build_memo_edit_tool(editor):
+    @function_tool(
+        name_override="memo_editor",
+        description_override="Stitch analysis sections into a Markdown memo and save it. This is the ONLY way to generate and save the final investment report. All memos must be finalized through this tool.",
+    )
+    async def memo_edit_tool(ctx: RunContextWrapper, input: MemoEditorInput) -> str:
+        result = await Runner.run(
+            starting_agent=editor,
+            input=json.dumps(input.model_dump()),
+            context=ctx.context,
+            max_turns=40,
+        )
+        return result.final_output
+    return memo_edit_tool 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/fundamental.py

@@ -0,0 +1,28 @@
+from agents import Agent, WebSearchTool, ModelSettings
+from utils import load_prompt, DISCLAIMER, repo_path
+from pathlib import Path
+
+default_model = "gpt-4.1"
+default_search_context = "medium"
+RECENT_DAYS = 15
+
+def build_fundamental_agent():
+    tool_retry_instructions = load_prompt("tool_retry_prompt.md")
+    fundamental_prompt = load_prompt("fundamental_base.md", RECENT_DAYS=RECENT_DAYS)
+    # Set up the Yahoo Finance MCP server
+    from agents.mcp import MCPServerStdio
+    server_path = str(repo_path("mcp/yahoo_finance_server.py"))
+    yahoo_mcp_server = MCPServerStdio(
+        params={"command": "python", "args": [server_path]},
+        client_session_timeout_seconds=300,
+        cache_tools_list=True,
+    )
+
+    return Agent(
+        name="Fundamental Analysis Agent",
+        instructions=(fundamental_prompt + DISCLAIMER + tool_retry_instructions),
+        mcp_servers=[yahoo_mcp_server],
+        tools=[WebSearchTool(search_context_size=default_search_context)],
+        model=default_model,
+        model_settings=ModelSettings(parallel_tool_calls=True, temperature=0),
+    ) 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/macro.py

@@ -0,0 +1,18 @@
+from agents import Agent, WebSearchTool, ModelSettings
+from tools import get_fred_series
+from utils import load_prompt, DISCLAIMER
+
+default_model = "gpt-4.1"
+default_search_context = "medium"
+RECENT_DAYS = 45
+
+def build_macro_agent():
+    tool_retry_instructions = load_prompt("tool_retry_prompt.md")
+    macro_prompt = load_prompt("macro_base.md", RECENT_DAYS=RECENT_DAYS)
+    return Agent(
+        name="Macro Analysis Agent",
+        instructions=(macro_prompt + DISCLAIMER + tool_retry_instructions),
+        tools=[WebSearchTool(search_context_size=default_search_context), get_fred_series],
+        model=default_model,
+        model_settings=ModelSettings(parallel_tool_calls=True, temperature=0),
+    ) 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/pm.py

@@ -0,0 +1,69 @@
+from agents import Agent, ModelSettings, function_tool, Runner
+from utils import load_prompt, DISCLAIMER
+from dataclasses import dataclass
+from pydantic import BaseModel
+import json
+import asyncio
+
+
+class SpecialistRequestInput(BaseModel):
+    section: str  # e.g., 'fundamental', 'macro', 'quant', or 'pm'
+    user_question: str
+    guidance: str
+
+# Core async functions for each specialist
+async def specialist_analysis_func(agent, input: SpecialistRequestInput):
+    result = await Runner.run(
+        starting_agent=agent,
+        input=json.dumps(input.model_dump()),
+        max_turns=75,
+    )
+    return result.final_output
+
+async def run_all_specialists_parallel(
+    fundamental, macro, quant,
+    fundamental_input: SpecialistRequestInput,
+    macro_input: SpecialistRequestInput,
+    quant_input: SpecialistRequestInput
+):
+    results = await asyncio.gather(
+        specialist_analysis_func(fundamental, fundamental_input),
+        specialist_analysis_func(macro, macro_input),
+        specialist_analysis_func(quant, quant_input)
+    )
+    return {
+        "fundamental": results[0],
+        "macro": results[1],
+        "quant": results[2]
+    }
+
+def build_head_pm_agent(fundamental, macro, quant, memo_edit_tool):
+    def make_agent_tool(agent, name, description):
+        @function_tool(name_override=name, description_override=description)
+        async def agent_tool(input: SpecialistRequestInput):
+            return await specialist_analysis_func(agent, input)
+        return agent_tool
+    fundamental_tool = make_agent_tool(fundamental, "fundamental_analysis", "Generate the Fundamental Analysis section.")
+    macro_tool = make_agent_tool(macro, "macro_analysis", "Generate the Macro Environment section.")
+    quant_tool = make_agent_tool(quant, "quantitative_analysis", "Generate the Quantitative Analysis section.")
+
+    @function_tool(name_override="run_all_specialists_parallel", description_override="Run all three specialist analyses (fundamental, macro, quant) in parallel and return their results as a dict.")
+    async def run_all_specialists_tool(fundamental_input: SpecialistRequestInput, macro_input: SpecialistRequestInput, quant_input: SpecialistRequestInput):
+        return await run_all_specialists_parallel(
+            fundamental, macro, quant,
+            fundamental_input, macro_input, quant_input
+        )
+
+    return Agent(
+        name="Head Portfolio Manager Agent",
+        instructions=(
+            load_prompt("pm_base.md") + DISCLAIMER
+        ),
+        model="gpt-4.1",
+        #Reasoning model
+        #model="o4-mini",
+        tools=[fundamental_tool, macro_tool, quant_tool, memo_edit_tool, run_all_specialists_tool],
+        # Settings for a reasoning model
+        #model_settings=ModelSettings(parallel_tool_calls=True, reasoning={"summary": "auto", "effort": "high"}, tool_choice="auto")
+        model_settings=ModelSettings(parallel_tool_calls=True, tool_choice="auto", temperature=0)
+    ) 

examples/agents_sdk/multi-agent-portfolio-collaboration/investment_agents/quant.py

@@ -0,0 +1,27 @@
+from agents import Agent, ModelSettings
+from tools import run_code_interpreter, get_fred_series, read_file, list_output_files
+from utils import load_prompt, DISCLAIMER, repo_path
+from pathlib import Path
+
+default_model = "gpt-4.1"
+
+def build_quant_agent():
+    tool_retry_instructions = load_prompt("tool_retry_prompt.md")
+    quant_prompt = load_prompt("quant_base.md")
+    # Set up the Yahoo Finance MCP server
+    from agents.mcp import MCPServerStdio
+    server_path = str(repo_path("mcp/yahoo_finance_server.py"))
+    yahoo_mcp_server = MCPServerStdio(
+        params={"command": "python", "args": [server_path]},
+        client_session_timeout_seconds=300,
+        cache_tools_list=True,
+    )
+
+    return Agent(
+        name="Quantitative Analysis Agent",
+        instructions=(quant_prompt + DISCLAIMER + tool_retry_instructions),
+        mcp_servers=[yahoo_mcp_server],
+        tools=[run_code_interpreter, get_fred_series, read_file, list_output_files],
+        model=default_model,
+        model_settings=ModelSettings(parallel_tool_calls=True, temperature=0),
+    )