troubleshoot chatui

app/main.py

@@ -3,7 +3,6 @@ from langserve import add_routes
 from langchain_core.runnables import RunnableLambda
 from pydantic import BaseModel
 from typing import List, Literal, Optional, Dict, Any
-from contextlib import asynccontextmanager
 import gradio as gr
 from datetime import datetime
 
@@ -35,32 +34,64 @@ class ChatFedOutput(BaseModel):
 # Logic
 # ─────────────────────────────────────────
 
-def process_chatfed_query_core(query: str) -> Dict[str, Any]:
-    return {
-        "result": f"Processed: {query}",
-        "metadata": {
+def process_chatfed_query_core(query: str) -> ChatFedOutput:
+    """Process query and return ChatFedOutput model"""
+    return ChatFedOutput(
+        result=f"Processed: {query}",
+        metadata={
             "session_id": f"session_{datetime.now().strftime('%Y%m%d%H%M%S')}"
         }
-    }
-
-from typing import cast
-
-def chatui_handler(data: ChatUIInput) -> ChatFedOutput:
-    # Handle case where data might be a dict instead of ChatUIInput object
-    if isinstance(data, dict):
-        data = ChatUIInput(**data)
-    
-    last_user_msg = next((m.content for m in reversed(data.messages) if m.role == "user"), "")
-    result = process_chatfed_query_core(query=last_user_msg)
-    
-    # 🚨 FIX: Wrap the string result
-    return ChatFedOutput(
-        result=result["result"],
-        metadata=result["metadata"]
     )
 
-def langserve_handler(data: ChatFedInput):
-    return process_chatfed_query_core(data.query)
+def chatui_handler(data) -> ChatFedOutput:
+    """Handler for chat UI input - accepts raw dict and returns ChatFedOutput"""
+    try:
+        # Handle both dict and Pydantic model input
+        if isinstance(data, dict):
+            messages = data.get("messages", [])
+        else:
+            messages = data.messages if hasattr(data, 'messages') else []
+        
+        # Find the last user message
+        last_user_msg = ""
+        for msg in reversed(messages):
+            if isinstance(msg, dict):
+                if msg.get("role") == "user":
+                    last_user_msg = msg.get("content", "")
+                    break
+            else:
+                if hasattr(msg, 'role') and msg.role == "user":
+                    last_user_msg = msg.content
+                    break
+        
+        result = process_chatfed_query_core(query=last_user_msg)
+        result.metadata["source"] = "chatui"
+        return result
+        
+    except Exception as e:
+        return ChatFedOutput(
+            result=f"Error processing chat UI request: {str(e)}",
+            metadata={"error": True, "source": "chatui"}
+        )
+
+def langserve_handler(data) -> ChatFedOutput:
+    """Handler for LangServe input - accepts raw dict and returns ChatFedOutput"""
+    try:
+        # Handle both dict and Pydantic model input
+        if isinstance(data, dict):
+            query = data.get("query", "")
+        else:
+            query = data.query if hasattr(data, 'query') else ""
+            
+        result = process_chatfed_query_core(query)
+        result.metadata["source"] = "langserve"
+        return result
+        
+    except Exception as e:
+        return ChatFedOutput(
+            result=f"Error processing request: {str(e)}",
+            metadata={"error": True, "source": "langserve"}
+        )
 
 # ─────────────────────────────────────────
 # Gradio Interface
@@ -69,29 +100,46 @@ def langserve_handler(data: ChatFedInput):
 def create_gradio_interface():
     with gr.Blocks(title="ChatFed UI") as demo:
         gr.Markdown("## ChatFed Dev UI")
-        query = gr.Textbox(label="Query")
-        btn = gr.Button("Send")
-        out = gr.Textbox(label="Response")
-
-        btn.click(fn=lambda q: process_chatfed_query_core(q)["result"], inputs=query, outputs=out)
+        
+        with gr.Row():
+            with gr.Column(scale=4):
+                query = gr.Textbox(label="Query", placeholder="Enter your query here...")
+            with gr.Column(scale=1):
+                btn = gr.Button("Send", variant="primary")
+        
+        out = gr.Textbox(label="Response", lines=10)
+
+        def process_query(q: str) -> str:
+            if not q.strip():
+                return "Please enter a query."
+            try:
+                result = process_chatfed_query_core(q)
+                return result.result
+            except Exception as e:
+                return f"Error processing query: {str(e)}"
+
+        btn.click(fn=process_query, inputs=query, outputs=out)
+        query.submit(fn=process_query, inputs=query, outputs=out)  # Allow Enter key
+    
     return demo
 
 # ─────────────────────────────────────────
 # App Startup
 # ─────────────────────────────────────────
 
-# Create Gradio app first
-demo = create_gradio_interface()
-
-# Get the FastAPI app from Gradio
-app = demo.app
+app = FastAPI(
+    title="ChatFed API",
+    description="API for ChatFed query processing",
+    version="1.0.0"
+)
 
 # Register LangServe-compatible endpoints
 add_routes(
     app,
     RunnableLambda(chatui_handler),
     path="/chatfed-chatui",
-    input_type=ChatUIInput
+    input_type=ChatUIInput,
+    output_type=ChatFedOutput
 )
 
 add_routes(
@@ -102,10 +150,38 @@ add_routes(
     output_type=ChatFedOutput
 )
 
+# Add health check endpoint
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy", "timestamp": datetime.now().isoformat()}
+
+# Add a simple root endpoint
+@app.get("/")
+async def root():
+    return {
+        "message": "ChatFed API is running",
+        "endpoints": {
+            "chatfed": "/chatfed",
+            "chatfed_chatui": "/chatfed-chatui", 
+            "gradio_ui": "/ui",
+            "docs": "/docs",
+            "health": "/health"
+        }
+    }
+
+# Mount Gradio at a specific path instead of root to avoid conflicts
+demo = create_gradio_interface()
+app.mount("/ui", demo)
+
 # ─────────────────────────────────────────
 # Run with uvicorn (dev/test only)
 # ─────────────────────────────────────────
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(
+        app, 
+        host="0.0.0.0", 
+        port=7860,
+        log_level="info"
+    )

requirements.txt

@@ -1,12 +1,24 @@
-gradio[mcp]
+# gradio[mcp]
+# gradio_client>=1.0.0
+# langgraph>=0.2.0
+# Pillow>=9.0.0
+# fastapi
+# langserve[all]
+# uvicorn[standard]
+# typing_extensions
+# python-multipart
+
+gradio>=4.0.0
 gradio_client>=1.0.0
 langgraph>=0.2.0
+langchain-core>=0.2.0
 Pillow>=9.0.0
-fastapi
-langserve[all]
-uvicorn[standard]
-typing_extensions
-python-multipart
+fastapi>=0.100.0
+langserve[all]>=0.0.30
+uvicorn[standard]>=0.23.0
+typing_extensions>=4.5.0
+python-multipart>=0.0.6
+pydantic>=2.0.0