Update main.py

main.py

@@ -1,77 +1,80 @@
-from fastapi import FastAPI
-import gradio as gr
-import google.generativeai as genai
-from weather import get_current_weather
-import os
-import uvicorn
-import json
-
-app = FastAPI()
-genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
-model = genai.GenerativeModel('gemini-pro')
-
-# Tools configuration
-tools = [
-    {
-        "name": "get_current_weather",
-        "description": "Get current weather information",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "location": {
-                    "type": "string",
-                    "description": "City name, e.g. Paris, France"
-                }
-            },
-            "required": ["location"]
-        }
-    }
-]
-
-def execute_tool_call(tool_call):
-    func_name = tool_call["name"]
-    args = json.loads(tool_call["arguments"])
-    
-    if func_name == "get_current_weather":
-        return get_current_weather(args["location"])
-    else:
-        return f"Error: Unknown function {func_name}"
-
-def process_message(message):
-    # Generate tool use suggestions
-    response = model.generate_content(
-        f"Analyze if user needs weather info: {message}. Respond ONLY with JSON:"
-        '{{"needs_weather": true|false, "location": "city"}}'
-    )
-    
-    try:
-        analysis = json.loads(response.text)
-        if analysis.get("needs_weather", False):
-            location = analysis.get("location", "London")
-            return get_current_weather(location)
-    except:
-        pass
-    
-    # Regular response
-    chat = model.start_chat(history=[])
-    response = chat.send_message(message)
-    return response.text
-
-# Gradio Interface
-with gr.Blocks() as demo:
-    chatbot = gr.Chatbot(height=500)
-    msg = gr.Textbox(label="Message")
-    clear = gr.Button("Clear")
-
-    def respond(message, chat_history):
-        bot_message = process_message(message)
-        chat_history.append((message, bot_message))
-        return "", chat_history
-
-    msg.submit(respond, [msg, chatbot], [msg, chatbot])
-    clear.click(lambda: None, None, chatbot, queue=False)
-
-app = gr.mount_gradio_app(app, demo, path="/")
-
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+from fastapi import FastAPI
+import gradio as gr
+import google.generativeai as genai
+from weather import get_current_weather
+import os
+import uvicorn
+import json
+
+app = FastAPI()
+genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+model = genai.GenerativeModel('gemini-pro')
+
+# Tools configuration
+tools = [
+    {
+        "name": "get_current_weather",
+        "description": "Get current weather information",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "City name, e.g. Paris, France"
+                }
+            },
+            "required": ["location"]
+        }
+    }
+]
+
+def execute_tool_call(tool_call):
+    func_name = tool_call["name"]
+    args = json.loads(tool_call["arguments"])
+    
+    if func_name == "get_current_weather":
+        return get_current_weather(args["location"])
+    else:
+        return f"Error: Unknown function {func_name}"
+
+def process_message(message):
+    # Generate tool use suggestions
+    response = model.generate_content(
+        f"Analyze if user needs weather info: {message}. Respond ONLY with JSON:"
+        '{{"needs_weather": true|false, "location": "city"}}'
+    )
+    
+    try:
+        analysis = json.loads(response.text)
+        if analysis.get("needs_weather", False):
+            location = analysis.get("location", "London")
+            return get_current_weather(location)
+    except:
+        pass
+    
+    # Regular response
+    chat = model.start_chat(history=[])
+    response = chat.send_message(message)
+    return response.text
+
+# Gradio Interface with new message format
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(height=500, type="messages")
+    msg = gr.Textbox(label="Message")
+    clear = gr.Button("Clear")
+
+    def respond(message, chat_history):
+        bot_message = process_message(message)
+        # Append user and bot messages
+        chat_history.append({"role": "user", "content": message})
+        chat_history.append({"role": "assistant", "content": bot_message})
+        return "", chat_history
+
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+app = gr.mount_gradio_app(app, demo, path="/")
+
+if __name__ == "__main__":
+    port = int(os.getenv("PORT", 8000))
+    uvicorn.run(app, host="0.0.0.0", port=port)