Update app.py

app.py

@@ -5,374 +5,106 @@ import json
 import asyncio
 import aiohttp
 from typing import Dict, Any, List, Tuple
-from datetime import datetime
-import os
 
 class MCPClient:
-    """MCP Client for communicating with the MCP server"""
-    
     def __init__(self, server_url: str):
         self.server_url = server_url.rstrip('/')
         self.session = None
-    
+
     async def initialize_session(self):
-        """Initialize aiohttp session"""
         if not self.session:
             self.session = aiohttp.ClientSession()
-    
+
     async def close_session(self):
-        """Close aiohttp session"""
         if self.session:
             await self.session.close()
             self.session = None
-    
+
     async def call_tool(self, tool_name: str, arguments: Dict[str, Any] = None) -> Dict[str, Any]:
-        """Call a tool on the MCP server"""
         if arguments is None:
             arguments = {}
-        
+
         await self.initialize_session()
-        
+
         mcp_request = {
             "jsonrpc": "2.0",
             "id": 1,
             "method": "tools/call",
-            "params": {
-                "name": tool_name,
-                "arguments": arguments
-            }
+            "params": {"name": tool_name, "arguments": arguments}
         }
-        
+
         try:
-            async with self.session.post(
-                f"{self.server_url}/mcp",
-                json=mcp_request,
-                headers={"Content-Type": "application/json"}
-            ) as response:
-                if response.status == 200:
-                    result = await response.json()
-                    if "result" in result and "content" in result["result"]:
-                        content = result["result"]["content"][0]["text"]
-                        return json.loads(content)
-                    return result
-                else:
-                    return {
-                        "success": False,
-                        "error": f"HTTP {response.status}: {await response.text()}"
-                    }
+            async with self.session.post(f"{self.server_url}/mcp", json=mcp_request) as response:
+                return await response.json()
         except Exception as e:
-            return {
-                "success": False,
-                "error": f"Connection error: {str(e)}"
-            }
-    
+            return {"success": False, "error": str(e)}
+
     async def list_tools(self) -> List[Dict[str, Any]]:
-        """List available tools on the MCP server"""
         await self.initialize_session()
-        
-        mcp_request = {
-            "jsonrpc": "2.0",
-            "id": 1,
-            "method": "tools/list"
-        }
-        
+        mcp_request = {"jsonrpc": "2.0", "id": 1, "method": "tools/list"}
         try:
-            async with self.session.post(
-                f"{self.server_url}/mcp",
-                json=mcp_request,
-                headers={"Content-Type": "application/json"}
-            ) as response:
-                if response.status == 200:
-                    result = await response.json()
-                    return result.get("result", {}).get("tools", [])
-                return []
-        except Exception as e:
+            async with self.session.post(f"{self.server_url}/mcp", json=mcp_request) as response:
+                result = await response.json()
+                return result.get("result", {}).get("tools", [])
+        except:
             return []
 
 class AIAssistant:
-    """AI Assistant with MCP integration"""
-    
     def __init__(self, openai_api_key: str, mcp_client: MCPClient):
-        try:
-            self.openai_client = openai.OpenAI(
-                api_key=openai_api_key,
-                timeout=30.0
-            )
-        except Exception as e:
-            # Fallback for older OpenAI versions
-            openai.api_key = openai_api_key
-            self.openai_client = openai
+        openai.api_key = openai_api_key
+        self.openai_client = openai
         self.mcp_client = mcp_client
         self.available_tools = []
-    
+
     async def initialize(self):
-        """Initialize the assistant by fetching available tools"""
         self.available_tools = await self.mcp_client.list_tools()
-    
-    def get_system_prompt(self) -> str:
-        """Generate system prompt with available tools"""
-        tools_description = "\n".join([
-            f"- {tool['name']}: {tool['description']}"
-            for tool in self.available_tools
-        ])
-        
-        return f"""You are an AI assistant with access to SAP business systems and news data through specialized tools. 
-
-Available tools:
-{tools_description}
-
-When a user asks for information that can be retrieved using these tools, you should:
-1. Identify which tool(s) would be helpful
-2. Call the appropriate tool(s) with the right parameters
-3. Interpret and present the results in a user-friendly way
 
-For SAP-related queries (purchase orders, requisitions), use the SAP tools.
-For news-related queries, use the news tools.
-
-You can call tools by responding with: CALL_TOOL: tool_name(parameter1=value1, parameter2=value2)
-"""
-    
-    def extract_tool_calls(self, response: str) -> List[Dict[str, Any]]:
-        """Extract tool calls from AI response"""
-        tool_calls = []
-        lines = response.split('\n')
-        
-        for line in lines:
-            if line.strip().startswith('CALL_TOOL:'):
-                try:
-                    tool_part = line.strip()[10:].strip()
-                    
-                    if '(' in tool_part and ')' in tool_part:
-                        tool_name = tool_part.split('(')[0].strip()
-                        params_str = tool_part.split('(')[1].split(')')[0]
-                        
-                        params = {}
-                        if params_str.strip():
-                            for param in params_str.split(','):
-                                if '=' in param:
-                                    key, value = param.split('=', 1)
-                                    key = key.strip()
-                                    value = value.strip().strip('"\'')
-                                    try:
-                                        if value.isdigit():
-                                            value = int(value)
-                                        elif value.lower() in ['true', 'false']:
-                                            value = value.lower() == 'true'
-                                    except:
-                                        pass
-                                    params[key] = value
-                        
-                        tool_calls.append({
-                            'name': tool_name,
-                            'arguments': params
-                        })
-                except Exception as e:
-                    continue
-        
-        return tool_calls
-    
     async def process_message(self, user_message: str) -> Tuple[str, str]:
-        """Process user message and handle tool calls"""
-        tool_info = ""
-        
         try:
-            messages = [
-                {"role": "system", "content": self.get_system_prompt()},
-                {"role": "user", "content": user_message}
-            ]
-            
-            response = self.openai_client.chat.completions.create(
+            response = self.openai_client.ChatCompletion.create(
                 model="gpt-3.5-turbo",
-                messages=messages,
+                messages=[{"role": "user", "content": user_message}],
                 temperature=0.7,
                 max_tokens=1000
             )
-            
-            ai_response = response.choices[0].message.content
-            tool_calls = self.extract_tool_calls(ai_response)
-            
-            if tool_calls:
-                tool_results = []
-                
-                for tool_call in tool_calls:
-                    tool_info += f"🔧 Calling: {tool_call['name']}\n"
-                    
-                    result = await self.mcp_client.call_tool(
-                        tool_call['name'], 
-                        tool_call['arguments']
-                    )
-                    
-                    tool_results.append({
-                        'tool': tool_call['name'],
-                        'result': result
-                    })
-                    
-                    if result.get('success'):
-                        tool_info += f"✅ {tool_call['name']} completed\n"
-                    else:
-                        tool_info += f"❌ {tool_call['name']} failed: {result.get('error', 'Unknown error')}\n"
-                
-                tool_results_text = "\n\n".join([
-                    f"Tool: {tr['tool']}\nResult: {json.dumps(tr['result'], indent=2)}"
-                    for tr in tool_results
-                ])
-                
-                final_messages = messages + [
-                    {"role": "assistant", "content": ai_response},
-                    {"role": "user", "content": f"Here are the tool results:\n\n{tool_results_text}\n\nPlease interpret these results and provide a helpful response to the user."}
-                ]
-                
-                final_response = self.openai_client.chat.completions.create(
-                    model="gpt-3.5-turbo",
-                    messages=final_messages,
-                    temperature=0.7,
-                    max_tokens=1000
-                )
-                
-                return final_response.choices[0].message.content, tool_info
-            else:
-                return ai_response, ""
-                
+            return response.choices[0].message.content, ""
         except Exception as e:
-            return f"❌ Error processing your request: {str(e)}", ""
+            return f"❌ Error: {str(e)}", ""
 
-# Global variables
+# Globals
 assistant = None
-mcp_client = None
-
-def test_connection(mcp_url):
-    """Test MCP server connection"""
-    if not mcp_url or mcp_url == "https://your-ngrok-url.ngrok.io":
-        return "❌ Please enter a valid MCP server URL"
-    
-    try:
-        response = requests.get(f"{mcp_url.rstrip('/')}/health", timeout=10)
-        if response.status_code == 200:
-            data = response.json()
-            return f"✅ Connected successfully!\nStatus: {data.get('status', 'Unknown')}\nTools: {len(data.get('available_tools', []))}"
-        else:
-            return f"❌ Connection failed: HTTP {response.status_code}"
-    except Exception as e:
-        return f"❌ Connection error: {str(e)}"
 
 async def initialize_assistant(openai_key, mcp_url):
-    """Initialize the AI assistant"""
-    global assistant, mcp_client
-    
-    if not openai_key:
-        return "❌ Please enter your OpenAI API key"
-    
-    if not mcp_url or mcp_url == "https://your-ngrok-url.ngrok.io":
-        return "❌ Please enter a valid MCP server URL"
-    
-    try:
-        mcp_client = MCPClient(mcp_url)
-        assistant = AIAssistant(openai_key, mcp_client)
-        await assistant.initialize()
-        return f"✅ AI Assistant initialized with {len(assistant.available_tools)} tools available"
-    except Exception as e:
-        return f"❌ Failed to initialize: {str(e)}"
+    global assistant
+    if not openai_key or not mcp_url:
+        return "❌ Provide valid OpenAI API key and MCP URL"
+
+    mcp_client = MCPClient(mcp_url)
+    assistant = AIAssistant(openai_key, mcp_client)
+    await assistant.initialize()
+    return f"✅ Initialized with {len(assistant.available_tools)} tools"
 
 def chat_interface(message, history, openai_key, mcp_url):
-    """Main chat interface"""
     global assistant
-    
     if not assistant:
         init_result = asyncio.run(initialize_assistant(openai_key, mcp_url))
         if "❌" in init_result:
             history.append([message, init_result])
             return history, ""
-    
-    try:
-        response, tool_info = asyncio.run(assistant.process_message(message))
-        
-        # Format response with tool info if available
-        if tool_info:
-            full_response = f"**Tool Execution:**\n{tool_info}\n\n**Response:**\n{response}"
-        else:
-            full_response = response
-            
-        history.append([message, full_response])
-        return history, ""
-    except Exception as e:
-        error_response = f"❌ Error: {str(e)}"
-        history.append([message, error_response])
-        return history, ""
 
-# Create Gradio interface
-with gr.Blocks(title="AI Assistant with SAP & News Integration", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤖 AI Assistant with SAP & News Integration")
-    gr.Markdown("Chat with an AI that can access SAP business data and news through natural language queries.")
-    
-    with gr.Row():
-        with gr.Column(scale=2):
-            chatbot = gr.Chatbot(
-                height=500,
-                show_label=False,
-                container=True,
-                bubble_full_width=False
-            )
-            
-            msg = gr.Textbox(
-                placeholder="Ask me about SAP data, news, or anything else...",
-                show_label=False,
-                container=False
-            )
-            
-            with gr.Row():
-                submit_btn = gr.Button("Send", variant="primary")
-                clear_btn = gr.Button("Clear", variant="secondary")
-        
-        with gr.Column(scale=1):
-            gr.Markdown("### ⚙️ Configuration")
-            
-            openai_key = gr.Textbox(
-                label="OpenAI API Key",
-                type="password",
-                placeholder="sk-..."
-            )
-            
-            mcp_url = gr.Textbox(
-                label="MCP Server URL",
-                value="https://your-ngrok-url.ngrok.io",
-                placeholder="https://abc123.ngrok.io"
-            )
-            
-            test_btn = gr.Button("Test Connection", variant="secondary")
-            connection_status = gr.Textbox(label="Connection Status", interactive=False)
-            
-            gr.Markdown("### 📋 Example Queries")
-            gr.Markdown("""
-            - "Show me recent purchase orders"
-            - "Get purchase requisitions"
-            - "What's the latest tech news?"
-            - "Get news from BBC"
-            - "Show me business news from the US"
-            """)
-    
-    # Event handlers
-    def respond(message, history, openai_key, mcp_url):
-        return chat_interface(message, history, openai_key, mcp_url)
-    
-    submit_btn.click(
-        respond,
-        [msg, chatbot, openai_key, mcp_url],
-        [chatbot, msg]
-    )
-    
-    msg.submit(
-        respond,
-        [msg, chatbot, openai_key, mcp_url],
-        [chatbot, msg]
-    )
-    
-    clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg])
-    
-    test_btn.click(
-        test_connection,
-        [mcp_url],
-        [connection_status]
-    )
+    response, _ = asyncio.run(assistant.process_message(message))
+    history.append([message, response])
+    return history, ""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🤖 MCP Assistant")
+    chatbot = gr.Chatbot(height=400)
+    msg = gr.Textbox(placeholder="Ask me anything...")
+    openai_key = gr.Textbox(type="password", label="OpenAI API Key")
+    mcp_url = gr.Textbox(label="MCP Server URL")
+
+    submit_btn = gr.Button("Send")
+    submit_btn.click(chat_interface, [msg, chatbot, openai_key, mcp_url], [chatbot, msg])
+    msg.submit(chat_interface, [msg, chatbot, openai_key, mcp_url], [chatbot, msg])
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()