Update app.py

app.py

@@ -1,14 +1,11 @@
 import gradio as gr
 import wikipedia
-#from langchain_community.chat_models import ChatOpenAI
+from langchain_openai import ChatOpenAI   # ✅ correct modern import
 from langchain.memory import ConversationBufferMemory
 from langchain.agents import initialize_agent, AgentType
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.tools import Tool
 
-from langchain_openai import ChatOpenAI
-
-
 # Optional: Tavily client
 try:
     from tavily import TavilyClient
@@ -35,10 +32,11 @@ def search_wikipedia(query: str) -> str:
     except wikipedia.exceptions.PageError:
         return "No relevant Wikipedia page found."
 
+
 tools = [
     Tool(name="Temperature", func=get_current_temperature, description="Get current temperature"),
     Tool(name="Search Wikipedia", func=search_wikipedia, description="Search Wikipedia"),
-    Tool(name="Create Your Own", func=create_your_own, description="Custom tool for processing input")
+    Tool(name="Create Your Own", func=create_your_own, description="Custom tool for processing input"),
 ]
 
 
@@ -58,9 +56,11 @@ class cbfs:
         if tavily_available and tavily_key:
             self.tavily = TavilyClient(api_key=tavily_key)
 
-        # Memory
+        # Conversation memory
         self.memory = ConversationBufferMemory(
-            return_messages=True, memory_key="chat_history", ai_prefix="Assistant"
+            return_messages=True,
+            memory_key="chat_history",
+            ai_prefix="Assistant"
         )
 
         # Prompt
@@ -68,17 +68,17 @@ class cbfs:
             ("system", "You are a helpful but sassy assistant. Remember what the user tells you in the conversation."),
             MessagesPlaceholder(variable_name="chat_history"),
             ("user", "{input}"),
-            MessagesPlaceholder(variable_name="agent_scratchpad")
+            MessagesPlaceholder(variable_name="agent_scratchpad"),
         ])
 
-        # Agent
+        # Initialize agent
         self.chain = initialize_agent(
             tools=tools,
             llm=self.model,
             agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
             verbose=True,
             memory=self.memory,
-            handle_parsing_errors=True
+            handle_parsing_errors=True,
         )
 
     def convchain(self, query: str) -> str:
@@ -87,30 +87,27 @@ class cbfs:
 
         try:
             result = self.chain.invoke({"input": query})
-            print("🔍 Raw agent result:", result)  # log to HuggingFace
+            print("🔍 Raw agent result:", result)
 
-            # Extract possible outputs
             if isinstance(result, dict):
                 response = (
-                    result.get("output") or
-                    result.get("output_text") or
-                    str(result)
+                    result.get("output")
+                    or result.get("output_text")
+                    or str(result)
                 )
             else:
                 response = str(result)
 
-            # Fallback: if still empty, just ask the model directly
+            # fallback direct LLM call
             if not response.strip():
                 print("⚠️ No structured output, falling back to direct LLM call")
                 resp = self.model.invoke(query)
                 response = getattr(resp, "content", str(resp))
 
-            # Save to memory
             self.memory.save_context({"input": query}, {"output": response})
             return response
 
         except Exception as e:
-            print("❌ Execution Error:", str(e))
             return f"❌ Error: {str(e)}"
 
 
@@ -119,8 +116,16 @@ class cbfs:
 # ----------------------
 with gr.Blocks() as demo:
     with gr.Row():
-        openai_key = gr.Textbox(label="🔑 OpenAI API Key", type="password", placeholder="Paste your key")
-        tavily_key = gr.Textbox(label="🔑 Tavily API Key (optional)", type="password", placeholder="Paste your Tavily key")
+        openai_key = gr.Textbox(
+            label="🔑 OpenAI API Key",
+            type="password",
+            placeholder="Paste your key"
+        )
+        tavily_key = gr.Textbox(
+            label="🔑 Tavily API Key (optional)",
+            type="password",
+            placeholder="Paste your Tavily key"
+        )
 
     chatbot_state = gr.State(None)
 
@@ -138,7 +143,11 @@ with gr.Blocks() as demo:
             return None, f"❌ Error: {str(e)}"
 
     init_btn = gr.Button("Initialize Chatbot")
-    init_btn.click(fn=init_chatbot, inputs=[openai_key, tavily_key], outputs=[chatbot_state, status])
+    init_btn.click(
+        fn=init_chatbot,
+        inputs=[openai_key, tavily_key],
+        outputs=[chatbot_state, status]
+    )
 
     def process_query(query, chatbot):
         if chatbot is None:
@@ -148,7 +157,7 @@ with gr.Blocks() as demo:
     inp.submit(process_query, inputs=[inp, chatbot_state], outputs=output)
 
 
-#demo.launch(share=True)
+# 🚀 Launch (no share=True on Spaces)
 demo.launch()