Version 1 (#160)

New front-end
Launch Chat API
Manage Sources
Enable re-embedding of all contents
Sources can be added without a notebook now
Improved settings
Enable model selector on all chats
Background processing for better experience
Dark mode
Improved Notes

Improved Docs: 
- Remove all Streamlit references from documentation
- Update deployment guides with React frontend setup
- Fix Docker environment variables format (SURREAL_URL, SURREAL_PASSWORD)
- Update docker image tag from :latest to :v1-latest
- Change navigation references (Settings → Models to just Models)
- Update development setup to include frontend npm commands
- Add MIGRATION.md guide for users upgrading from Streamlit
- Update quick-start guide with correct environment variables
- Add port 5055 documentation for API access
- Update project structure to reflect frontend/ directory
- Remove outdated source-chat documentation files

open_notebook/graphs/chat.py

@@ -20,19 +20,54 @@ class ThreadState(TypedDict):
     notebook: Optional[Notebook]
     context: Optional[str]
     context_config: Optional[dict]
+    model_override: Optional[str]
 
 
 def call_model_with_messages(state: ThreadState, config: RunnableConfig) -> dict:
-    system_prompt = Prompter(prompt_template="chat").render(data=state)
+    system_prompt = Prompter(prompt_template="chat").render(data=state)  # type: ignore[arg-type]
     payload = [SystemMessage(content=system_prompt)] + state.get("messages", [])
-    model = asyncio.run(
-        provision_langchain_model(
-            str(payload),
-            config.get("configurable", {}).get("model_id"),
-            "chat",
-            max_tokens=10000,
-        )
+    model_id = (
+        config.get("configurable", {}).get("model_id")
+        or state.get("model_override")
     )
+    
+    # Handle async model provisioning from sync context
+    def run_in_new_loop():
+        """Run the async function in a new event loop"""
+        new_loop = asyncio.new_event_loop()
+        try:
+            asyncio.set_event_loop(new_loop)
+            return new_loop.run_until_complete(
+                provision_langchain_model(
+                    str(payload),
+                    model_id,
+                    "chat",
+                    max_tokens=10000,
+                )
+            )
+        finally:
+            new_loop.close()
+            asyncio.set_event_loop(None)
+    
+    try:
+        # Try to get the current event loop
+        asyncio.get_running_loop()
+        # If we're in an event loop, run in a thread with a new loop
+        import concurrent.futures
+        with concurrent.futures.ThreadPoolExecutor() as executor:
+            future = executor.submit(run_in_new_loop)
+            model = future.result()
+    except RuntimeError:
+        # No event loop running, safe to use asyncio.run()
+        model = asyncio.run(
+            provision_langchain_model(
+                str(payload),
+                model_id,
+                "chat",
+                max_tokens=10000,
+            )
+        )
+    
     ai_message = model.invoke(payload)
     return {"messages": ai_message}