Support OpenAI's new O1 Model Series (#912)

- Major
   - The new O1 series doesn't seem to support streaming, response_format enforcement, 
      stop words or temperature currently. 
   - Remove any markdown json codeblock in chat actors expecting json responses

- Minor
   - Override block display styling of links by Katex in chat messages

src/interface/web/app/components/chatMessage/chatMessage.module.css

@@ -18,6 +18,11 @@ div.chatMessageWrapper p:not(:last-child) {
     margin-bottom: 16px;
 }
 
+/* Override some link styling by Katex to improve rendering */
+div.chatMessageWrapper a span {
+    display: revert !important;
+}
+
 div.khojfullHistory {
     border-width: 1px;
     padding-left: 4px;

src/khoj/processor/conversation/openai/gpt.py

@@ -14,6 +14,7 @@
 from khoj.processor.conversation.utils import (
     construct_structured_message,
     generate_chatml_messages_with_context,
+    remove_json_codeblock,
 )
 from khoj.utils.helpers import ConversationCommand, is_none_or_empty
 from khoj.utils.rawconfig import LocationData
@@ -85,6 +86,7 @@ def extract_questions(
     # Extract, Clean Message from GPT's Response
     try:
         response = response.strip()
+        response = remove_json_codeblock(response)
         response = json.loads(response)
         response = [q.strip() for q in response["queries"] if q.strip()]
         if not isinstance(response, list) or not response:

src/khoj/processor/conversation/openai/utils.py

@@ -45,15 +45,28 @@ def completion_with_backoff(
         openai_clients[client_key] = client
 
     formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
+    stream = True
+
+    # Update request parameters for compatability with o1 model series
+    # Refer: https://platform.openai.com/docs/guides/reasoning/beta-limitations
+    if model.startswith("o1"):
+        stream = False
+        temperature = 1
+        model_kwargs.pop("stop", None)
+        model_kwargs.pop("response_format", None)
 
     chat = client.chat.completions.create(
-        stream=True,
+        stream=stream,
         messages=formatted_messages,  # type: ignore
         model=model,  # type: ignore
         temperature=temperature,
         timeout=20,
         **(model_kwargs or dict()),
     )
+
+    if not stream:
+        return chat.choices[0].message.content
+
     aggregated_response = ""
     for chunk in chat:
         if len(chunk.choices) == 0:
@@ -112,24 +125,36 @@ def llm_thread(g, messages, model_name, temperature, openai_api_key=None, api_ba
             client: openai.OpenAI = openai_clients[client_key]
 
         formatted_messages = [{"role": message.role, "content": message.content} for message in messages]
+        stream = True
+
+        # Update request parameters for compatability with o1 model series
+        # Refer: https://platform.openai.com/docs/guides/reasoning/beta-limitations
+        if model_name.startswith("o1"):
+            stream = False
+            temperature = 1
+            model_kwargs.pop("stop", None)
+            model_kwargs.pop("response_format", None)
 
         chat = client.chat.completions.create(
-            stream=True,
+            stream=stream,
             messages=formatted_messages,
             model=model_name,  # type: ignore
             temperature=temperature,
             timeout=20,
             **(model_kwargs or dict()),
         )
 
-        for chunk in chat:
-            if len(chunk.choices) == 0:
-                continue
-            delta_chunk = chunk.choices[0].delta
-            if isinstance(delta_chunk, str):
-                g.send(delta_chunk)
-            elif delta_chunk.content:
-                g.send(delta_chunk.content)
+        if not stream:
+            g.send(chat.choices[0].message.content)
+        else:
+            for chunk in chat:
+                if len(chunk.choices) == 0:
+                    continue
+                delta_chunk = chunk.choices[0].delta
+                if isinstance(delta_chunk, str):
+                    g.send(delta_chunk)
+                elif delta_chunk.content:
+                    g.send(delta_chunk.content)
     except Exception as e:
         logger.error(f"Error in llm_thread: {e}", exc_info=True)
     finally:

src/khoj/processor/conversation/utils.py

@@ -1,4 +1,3 @@
-import json
 import logging
 import math
 import queue
@@ -24,6 +23,8 @@
     "gpt-4-0125-preview": 20000,
     "gpt-4-turbo-preview": 20000,
     "gpt-4o-mini": 20000,
+    "o1-preview": 20000,
+    "o1-mini": 20000,
     "TheBloke/Mistral-7B-Instruct-v0.2-GGUF": 3500,
     "NousResearch/Hermes-2-Pro-Mistral-7B-GGUF": 3500,
     "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF": 20000,
@@ -220,8 +221,9 @@ def truncate_messages(
     try:
         if loaded_model:
             encoder = loaded_model.tokenizer()
-        elif model_name.startswith("gpt-"):
-            encoder = tiktoken.encoding_for_model(model_name)
+        elif model_name.startswith("gpt-") or model_name.startswith("o1"):
+            # as tiktoken doesn't recognize o1 model series yet
+            encoder = tiktoken.encoding_for_model("gpt-4o" if model_name.startswith("o1") else model_name)
         elif tokenizer_name:
             if tokenizer_name in state.pretrained_tokenizers:
                 encoder = state.pretrained_tokenizers[tokenizer_name]
@@ -278,10 +280,19 @@ def truncate_messages(
         )
 
     if system_message:
-        system_message.role = "user" if "gemma-2" in model_name else "system"
+        # Default system message role is system.
+        # Fallback to system message role of user for models that do not support this role like gemma-2 and openai's o1 model series.
+        system_message.role = "user" if "gemma-2" in model_name or model_name.startswith("o1") else "system"
     return messages + [system_message] if system_message else messages
 
 
 def reciprocal_conversation_to_chatml(message_pair):
     """Convert a single back and forth between user and assistant to chatml format"""
     return [ChatMessage(content=message, role=role) for message, role in zip(message_pair, ["user", "assistant"])]
+
+
+def remove_json_codeblock(response):
+    """Remove any markdown json codeblock formatting if present. Useful for non schema enforceable models"""
+    if response.startswith("```json") and response.endswith("```"):
+        response = response[7:-3]
+    return response

src/khoj/routers/helpers.py

@@ -88,6 +88,7 @@
 from khoj.processor.conversation.utils import (
     ThreadedGenerator,
     generate_chatml_messages_with_context,
+    remove_json_codeblock,
     save_to_conversation_log,
 )
 from khoj.processor.speech.text_to_speech import is_eleven_labs_enabled
@@ -298,9 +299,7 @@ async def aget_relevant_information_sources(
 
     try:
         response = response.strip()
-        # Remove any markdown json codeblock formatting if present (useful for gemma-2)
-        if response.startswith("```json"):
-            response = response[7:-3]
+        response = remove_json_codeblock(response)
         response = json.loads(response)
         response = [q.strip() for q in response["source"] if q.strip()]
         if not isinstance(response, list) or not response or len(response) == 0:
@@ -353,7 +352,9 @@ async def aget_relevant_output_modes(
         response = await send_message_to_model_wrapper(relevant_mode_prompt, response_type="json_object")
 
     try:
-        response = json.loads(response.strip())
+        response = response.strip()
+        response = remove_json_codeblock(response)
+        response = json.loads(response)
 
         if is_none_or_empty(response):
             return ConversationCommand.Text
@@ -433,9 +434,7 @@ async def generate_online_subqueries(
     # Validate that the response is a non-empty, JSON-serializable list
     try:
         response = response.strip()
-        # Remove any markdown json codeblock formatting if present (useful for gemma-2)
-        if response.startswith("```json") and response.endswith("```"):
-            response = response[7:-3]
+        response = remove_json_codeblock(response)
         response = json.loads(response)
         response = [q.strip() for q in response["queries"] if q.strip()]
         if not isinstance(response, list) or not response or len(response) == 0: