Update app.py

app.py

@@ -371,7 +371,6 @@ class VisualConsensusEngine:
         mistral_key = session_keys.get("mistral") or MISTRAL_API_KEY
         sambanova_key = session_keys.get("sambanova") or SAMBANOVA_API_KEY
         
-        # Research Agent stays visible but is no longer an active participant
         self.models = {
             'mistral': {
                 'name': 'Mistral Large',
@@ -472,27 +471,6 @@ class VisualConsensusEngine:
         """Update the visual roundtable state for this session"""
         if self.update_callback:
             self.update_callback(state_update)
-
-    def log_research_activity(self, speaker: str, function: str, query: str, result: str, log_function=None):
-        """Log research activity to the discussion log"""
-        if log_function:
-            # Log the research request
-            log_function('research_request', 
-                        speaker="Research Agent", 
-                        content=f"Research requested by {speaker}: {function.replace('_', ' ').title()} - '{query}'",
-                        function=function,
-                        query=query,
-                        requesting_expert=speaker)
-            
-            # Log the research result (truncated for readability)
-            result_preview = result[:300] + "..." if len(result) > 300 else result
-            log_function('research_result', 
-                        speaker="Research Agent", 
-                        content=f"Research completed: {function.replace('_', ' ').title()}\n\n{result_preview}",
-                        function=function,
-                        query=query,
-                        full_result=result,
-                        requesting_expert=speaker)
     
     def handle_function_calls(self, completion, original_prompt: str, calling_model: str) -> str:
         """UNIFIED function call handler with enhanced research capabilities"""
@@ -581,11 +559,6 @@ class VisualConsensusEngine:
                         'timestamp': datetime.now().strftime('%H:%M:%S'),
                         **kwargs
                     })
-
-                # Get query parameter for logging
-                query_param = arguments.get("query") or arguments.get("topic") or arguments.get("technology") or arguments.get("company")
-                if query_param and result:
-                    self.log_research_activity(calling_model_name, function_name, query_param, result, session_log_function)
                     
                 # Add function result to conversation
                 messages.append({
@@ -925,36 +898,44 @@ class VisualConsensusEngine:
         return time_estimates.get(function_name, "1-3 minutes")
 
     def show_research_error(self, function: str, query: str, error: str, requesting_model_name: str = None):
-        """Show research error"""
-        session = get_or_create_session_state(self.session_id)
-        current_state = session["roundtable_state"]
-        all_messages = list(current_state.get("messages", []))
-        participants = current_state.get("participants", [])
-        
-        existing_bubbles = list(current_state.get("showBubbles", []))
-        # Ensure both Research Agent AND the calling model stay visible
-        if "Research Agent" not in existing_bubbles:
-            existing_bubbles.append("Research Agent")
-        # Keep the current speaker (the one who requested research) visible
-        current_speaker = current_state.get("currentSpeaker")
-        if current_speaker and current_speaker not in existing_bubbles and current_speaker != "Research Agent":
-            existing_bubbles.append(current_speaker)
-        
-        message = {
-            "speaker": "Research Agent",
-            "text": f"❌ **Research Error**: {function.replace('_', ' ').title()}\n📝 Query: \"{query}\"\n⚠️ Error: {error}\n🔄 Continuing with available data",
-            "type": "research_error"
+        """Show research error from the specific agent and dismiss it"""
+        function_to_agent = {
+            "search_web": "web_search",
+            "search_wikipedia": "wikipedia", 
+            "search_academic": "arxiv",
+            "search_technology_trends": "github",
+            "search_financial_data": "sec_edgar"
         }
-        all_messages.append(message)
         
-        self.update_visual_state({
-            "participants": participants,
-            "messages": all_messages,
-            "currentSpeaker": requesting_model_name,
-            "thinking": [],
-            "showBubbles": existing_bubbles + ["Research Agent"]
-        })
-        time.sleep(1)
+        if function in function_to_agent:
+            agent_name = function_to_agent[function]
+            research_agent = self.research_agents[agent_name]
+            agent_display_name = research_agent.manifest.identification.conversationalName
+            
+            session = get_or_create_session_state(self.session_id)
+            current_state = session["roundtable_state"]
+            all_messages = list(current_state.get("messages", []))
+            
+            # Show error message from the specific agent
+            error_message = {
+                "speaker": agent_display_name,
+                "text": f"❌ **Research Error**\n🔬 {function.replace('_', ' ').title()}\n📝 Query: \"{query}\"\n⚠️ Error: {error}\n🔄 Research failed, returning to discussion",
+                "type": "research_error"
+            }
+            all_messages.append(error_message)
+            
+            existing_bubbles = list(current_state.get("showBubbles", []))
+            self.update_visual_state({
+                "participants": current_state.get("participants", []),
+                "messages": all_messages,
+                "currentSpeaker": requesting_model_name,
+                "thinking": [],
+                "showBubbles": existing_bubbles
+            })
+            time.sleep(1)
+            
+            # Dismiss the research agent since research failed
+            self.dismiss_research_agent(agent_name, "current_conversation")
 
     def update_research_progress(self, progress_text: str, function_name: str = None):
         """Update research progress from the specific active research agent"""
@@ -1264,7 +1245,7 @@ class VisualConsensusEngine:
             # Show latest position from each expert
             latest_positions = {}
             for msg in all_messages:
-                if msg["speaker"] != current_model_name and msg["speaker"] != "Research Agent":
+                if msg["speaker"] != current_model_name and not msg["speaker"].endswith("Research Agent")):
                     latest_positions[msg["speaker"]] = {
                         'text': msg['text'][:150] + "..." if len(msg['text']) > 150 else msg['text'],
                         'confidence': msg.get('confidence', 5)
@@ -1307,15 +1288,13 @@ class VisualConsensusEngine:
                                    log_function=None):
         """Run expert consensus with protocol-appropriate intensity and Research Agent integration"""
         
-        # Get only active models (Research Agent is visual-only now)
         available_models = [model for model, info in self.models.items() if info['available']]
         if not available_models:
             return "❌ No AI models available"
         
         model_roles = self.assign_roles(available_models, role_assignment)
         
-        # Visual participants include Research Agent but active participants don't
-        visual_participant_names = [self.models[model]['name'] for model in available_models] + ["Research Agent"]
+        visual_participant_names = [self.models[model]['name'] for model in available_models]
         
         # Get protocol-appropriate style
         protocol_style = self.protocol_styles.get(decision_protocol, self.protocol_styles['consensus'])
@@ -1329,7 +1308,6 @@ class VisualConsensusEngine:
         log_event('phase', content=f"🎯 Starting Expert Analysis: {question}")
         log_event('phase', content=f"📊 Configuration: {len(available_models)} experts, {decision_protocol} protocol, {role_assignment} roles, {topology} topology")
         
-        # Initialize visual state with Research Agent visible
         self.update_visual_state({
             "participants": visual_participant_names,
             "messages": [],
@@ -1341,7 +1319,6 @@ class VisualConsensusEngine:
         
         all_messages = []
         
-        # Phase 1: Initial expert analysis (Research Agent activates only through function calls)
         log_event('phase', content="📝 Phase 1: Expert Initial Analysis")
         
         for model in available_models:
@@ -1451,7 +1428,7 @@ Provide your expert analysis:"""
                 all_messages.append(message)
             
             # Update with new message
-            responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and msg["speaker"] != "Research Agent"))
+            responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and not msg["speaker"].endswith("Research Agent")))
             
             self.update_visual_state({
                 "participants": visual_participant_names,
@@ -1571,7 +1548,7 @@ Your expert response:"""
                         all_messages.append(message)
                     
                     # Update visual state
-                    responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and msg["speaker"] != "Research Agent"))
+                    responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and not msg["speaker"].endswith("Research Agent")))
                     
                     self.update_visual_state({
                         "participants": visual_participant_names,
@@ -1621,9 +1598,13 @@ Your expert response:"""
         final_positions = {}
         confidence_scores = []
         
+        # Get list of all research agent names
+        research_agent_names = [agent.manifest.identification.conversationalName for agent in self.research_agents.values()]
+        
         for msg in all_messages:
             speaker = msg["speaker"]
-            if speaker not in [moderator_title, 'Consilium', 'Research Agent']:
+            if (speaker not in [moderator_title, 'Consilium'] and 
+                speaker not in research_agent_names):
                 if speaker not in final_positions:
                     final_positions[speaker] = []
                 final_positions[speaker].append(msg)
@@ -1731,7 +1712,7 @@ Provide your synthesis:"""
                  content=consensus_result,
                  confidence=avg_confidence)
         
-        responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and msg["speaker"] != "Research Agent"))
+        responded_speakers = list(set(msg["speaker"] for msg in all_messages if msg.get("speaker") and not msg["speaker"].endswith("Research Agent")))
         
         self.update_visual_state({
             "participants": visual_participant_names,
@@ -1885,18 +1866,14 @@ def check_model_status_session(session_id_state: str = None, request: gr.Request
         'Mistral Large': mistral_key,
         'DeepSeek-R1': sambanova_key,
         'Meta-Llama-3.3-70B-Instruct': sambanova_key,
-        'QwQ-32B': sambanova_key,
-        'Research Agent': True
+        'QwQ-32B': sambanova_key
     }
     
     for model_name, available in models.items():
-        if model_name == 'Research Agent':
-            status = "✅ Available (Built-in + Native Function Calling)"
+        if available:
+            status = f"✅ Available (Key: {available[:3]}...)"
         else:
-            if available:
-                status = f"✅ Available (Key: {available[:3]}...)"
-            else:
-                status = "❌ Not configured"
+            status = "❌ Not configured"
         status_info += f"**{model_name}:** {status}\n\n"
     
     return status_info
@@ -1907,15 +1884,11 @@ with gr.Blocks(title="🎭 Consilium: Multi-AI Expert Consensus Platform - OFP (
     # 🎭 Consilium: Multi-AI Expert Consensus Platform - OFP (Open Floor Protocol) Version
     **Watch expert AI models collaborate with live research to solve your most complex decisions**
 
-    🏆 **Gradio Agents and MCP Hackathon 2025** submission with [custom Gradio component](https://huggingface.co/spaces/Agents-MCP-Hackathon/gradio_consilium_roundtable). 📼 **Demo Videos:** [UI Demo](https://youtu.be/ciYLqI-Nawc) | [MCP Demo](https://youtu.be/r92vFUXNg74)
-
-
     ### 🚀 Features:
     
     * Visual roundtable of the AI models, including speech bubbles to see the discussion in real time.
-    * MCP mode enabled to also use it directly in, for example, Claude Desktop (without the visual table).
     * Includes Mistral (**mistral-large-latest**) via their API and the Models **DeepSeek-R1**, **Meta-Llama-3.3-70B-Instruct** and **QwQ-32B** via the SambaNova API.
-    * Research Agent with 5 sources (**Web Search**, **Wikipedia**, **arXiv**, **GitHub**, **SEC EDGAR**) for comprehensive live research.
+    * Research Agents with 5 sources (**Web Search**, **Wikipedia**, **arXiv**, **GitHub**, **SEC EDGAR**) for comprehensive live research.
     * Assign different roles to the models, the protocol they should follow, and decide the communication strategy.
     * Pick one model as the lead analyst (had the best results when picking Mistral).
     * Configure the amount of discussion rounds.
@@ -2126,19 +2099,6 @@ with gr.Blocks(title="🎭 Consilium: Multi-AI Expert Consensus Platform - OFP (
         ```bash
         python app.py
         ```
-        
-        ### 🔗 MCP Integration
-        Add to your Claude Desktop config:
-        ```json
-        {
-          "mcpServers": {
-            "consilium": {
-              "command": "npx",
-              "args": ["mcp-remote", "http://localhost:7860/gradio_api/mcp/sse"]
-            }
-          }
-        }
-        ```
         """)
     
     with gr.Tab("📚 Documentation"):
@@ -2224,5 +2184,5 @@ if __name__ == "__main__":
         server_port=7860,
         share=False,
         debug=False,
-        mcp_server=True
+        mcp_server=False
     )