more troubleshooting...

app/main.py

@@ -3,15 +3,13 @@ from langserve import add_routes
 from langchain_core.runnables import RunnableLambda
 from pydantic import BaseModel
 from typing import List, Literal, Optional, Dict, Any
-import gradio as gr
-from datetime import datetime
 import logging
 
 # Set up logging
 logger = logging.getLogger(__name__)
 
 # ─────────────────────────────────────────
-# Schemas
+# Keep existing schemas for backwards compatibility
 # ─────────────────────────────────────────
 
 class ChatMessage(BaseModel):
@@ -22,7 +20,7 @@ class ChatUIInput(BaseModel):
     messages: List[ChatMessage]
 
 class ChatFedInput(BaseModel):
-    query: str
+    query: str  # Keep original strict validation
     reports_filter: Optional[str] = ""
     sources_filter: Optional[str] = ""
     subtype_filter: Optional[str] = ""
@@ -30,12 +28,50 @@ class ChatFedInput(BaseModel):
     session_id: Optional[str] = None
     user_id: Optional[str] = None
 
+# ─────────────────────────────────────────
+# Add new flexible schema for ChatUI compatibility
+# ─────────────────────────────────────────
+
+class FlexibleChatInput(BaseModel):
+    """Flexible input that accepts multiple field names"""
+    query: Optional[str] = None
+    text: Optional[str] = None
+    input: Optional[str] = None
+    prompt: Optional[str] = None
+    content: Optional[str] = None
+    messages: Optional[List[Dict[str, Any]]] = None
+    
+    # Keep RAG filters
+    reports_filter: Optional[str] = ""
+    sources_filter: Optional[str] = ""
+    subtype_filter: Optional[str] = ""
+    year_filter: Optional[str] = ""
+    session_id: Optional[str] = None
+    user_id: Optional[str] = None
+    
+    def extract_query(self) -> str:
+        """Extract query from any available field"""
+        # Try direct fields
+        for field in [self.query, self.text, self.input, self.prompt, self.content]:
+            if field and field.strip():
+                return field.strip()
+        
+        # Try messages
+        if self.messages:
+            for msg in reversed(self.messages):
+                if isinstance(msg, dict) and msg.get('role') == 'user':
+                    content = msg.get('content') or msg.get('text')
+                    if content:
+                        return str(content).strip()
+        
+        return ""
+
 class ChatFedOutput(BaseModel):
     result: str
     metadata: Dict[str, Any]
 
 # ─────────────────────────────────────────
-# Logic
+# Updated handlers
 # ─────────────────────────────────────────
 
 def process_chatfed_query_core(query: str) -> ChatFedOutput:
@@ -47,139 +83,65 @@ def process_chatfed_query_core(query: str) -> ChatFedOutput:
         }
     )
 
-def chatui_handler(data) -> ChatFedOutput:
-    """Handler for chat UI input - accepts raw dict and returns ChatFedOutput"""
+def flexible_handler(data: FlexibleChatInput) -> ChatFedOutput:
+    """Handler for flexible input that accepts multiple formats"""
     try:
-        # Handle both dict and Pydantic model input
-        if isinstance(data, dict):
-            messages = data.get("messages", [])
-            
-            # NEW: Handle case where ChatUI sends 'text' instead of 'messages'
-            if not messages and "text" in data:
-                # Convert text to messages format
-                messages = [{"role": "user", "content": data["text"]}]
-            
-        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
+        query = data.extract_query()
         
-        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):
-            # Try multiple possible field names that ChatUI might send
-            query = (data.get("query") or 
-                    data.get("text") or 
-                    data.get("input") or 
-                    data.get("prompt") or
-                    data.get("content") or "")
-            
-            # Also check if it's in messages format
-            if not query and "messages" in data:
-                messages = data["messages"]
-                for msg in reversed(messages):
-                    if isinstance(msg, dict) and msg.get("role") == "user":
-                        query = msg.get("content", "")
-                        break
-        else:
-            # Handle Pydantic model
-            query = data.query if hasattr(data, 'query') else ""
-            
         if not query:
-            logger.warning(f"No query found in langserve input: {data}")
             return ChatFedOutput(
-                result="No query provided",
-                metadata={"error": True, "source": "langserve", "raw_input": str(data)}
+                result="No query found. Please provide text in one of these fields: query, text, prompt, content, or messages array.",
+                metadata={"error": True, "source": "flexible", "provided_fields": list(data.__dict__.keys())}
             )
             
         result = process_chatfed_query_core(query)
-        result.metadata["source"] = "langserve"
-        result.metadata["extracted_query"] = query
+        result.metadata.update({
+            "source": "flexible",
+            "extracted_query": query,
+            "input_method": "flexible_handler"
+        })
         return result
         
     except Exception as e:
-        logger.error(f"Error in langserve_handler: {str(e)}, input: {data}")
+        logger.error(f"Error in flexible_handler: {str(e)}")
         return ChatFedOutput(
-            result=f"Error processing request: {str(e)}",
-            metadata={"error": True, "source": "langserve", "raw_input": str(data)}
+            result=f"Error: {str(e)}",
+            metadata={"error": True, "source": "flexible"}
         )
 
-# ─────────────────────────────────────────
-# Gradio Interface
-# ─────────────────────────────────────────
-
-def create_gradio_interface():
-    with gr.Blocks(title="ChatFed UI") as demo:
-        gr.Markdown("## ChatFed Dev UI")
-        
-        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
+def legacy_langserve_handler(data: ChatFedInput) -> ChatFedOutput:
+    """Original handler for backwards compatibility"""
+    try:
+        result = process_chatfed_query_core(data.query)
+        result.metadata["source"] = "legacy_langserve"
+        return result
+    except Exception as e:
+        return ChatFedOutput(
+            result=f"Error: {str(e)}",
+            metadata={"error": True, "source": "legacy_langserve"}
+        )
 
 # ─────────────────────────────────────────
-# App Startup
+# App setup with multiple endpoints
 # ─────────────────────────────────────────
 
-app = FastAPI(
-    title="ChatFed API",
-    description="API for ChatFed query processing",
-    version="1.0.0"
-)
+app = FastAPI(title="ChatFed API", version="1.0.0")
 
-# Register LangServe-compatible endpoints
+# Legacy endpoint (strict validation)
 add_routes(
     app,
-    RunnableLambda(chatui_handler),
-    path="/chatfed-chatui",
-    input_type=ChatUIInput,
+    RunnableLambda(legacy_langserve_handler),
+    path="/chatfed-strict",
+    input_type=ChatFedInput,
     output_type=ChatFedOutput
 )
 
+# New flexible endpoint for ChatUI (THIS IS WHAT YOU SHOULD USE)
 add_routes(
     app,
-    RunnableLambda(langserve_handler),
+    RunnableLambda(flexible_handler),
     path="/chatfed",
-    input_type=ChatFedInput,
+    input_type=FlexibleChatInput,
     output_type=ChatFedOutput
 )