Upload app_multiagent.py

app_multiagent.py

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+"""
+Streamlit App for Multi-Agent Research Assistant
+================================================
+Beautiful UI with real-time progress tracking and interactive results
+"""
+
+import streamlit as st
+import sys
+import os
+from datetime import datetime
+import json
+
+# Add the project directory to path
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+# Import the multi-agent system
+from multi_agent_system import MultiAgentSystem
+
+# Page configuration
+st.set_page_config(
+    page_title="Multi-Agent Research Assistant",
+    page_icon="🤖",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Custom CSS
+st.markdown("""
+<style>
+    .main-header {
+        font-size: 3rem;
+        font-weight: bold;
+        background: linear-gradient(90deg, #667eea 0%, #764ba2 100%);
+        -webkit-background-clip: text;
+        -webkit-text-fill-color: transparent;
+        text-align: center;
+        margin-bottom: 1rem;
+    }
+    .sub-header {
+        text-align: center;
+        color: #666;
+        margin-bottom: 2rem;
+    }
+    .agent-box {
+        padding: 1rem;
+        border-radius: 10px;
+        margin: 1rem 0;
+        border-left: 4px solid;
+    }
+    .researcher-box {
+        background-color: #e3f2fd;
+        border-color: #2196f3;
+    }
+    .analyst-box {
+        background-color: #f3e5f5;
+        border-color: #9c27b0;
+    }
+    .writer-box {
+        background-color: #e8f5e9;
+        border-color: #4caf50;
+    }
+    .critic-box {
+        background-color: #fff3e0;
+        border-color: #ff9800;
+    }
+    .metric-card {
+        background: white;
+        padding: 1.5rem;
+        border-radius: 10px;
+        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        text-align: center;
+    }
+    .stButton>button {
+        width: 100%;
+        background: linear-gradient(90deg, #667eea 0%, #764ba2 100%);
+        color: white;
+        border: none;
+        padding: 0.75rem;
+        font-size: 1.1rem;
+        font-weight: bold;
+        border-radius: 8px;
+        transition: transform 0.2s;
+    }
+    .stButton>button:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 4px 8px rgba(0,0,0,0.2);
+    }
+</style>
+""", unsafe_allow_html=True)
+
+
+# Initialize session state
+if 'system' not in st.session_state:
+    st.session_state.system = None
+if 'research_history' not in st.session_state:
+    st.session_state.research_history = []
+if 'current_result' not in st.session_state:
+    st.session_state.current_result = None
+
+
+def initialize_system(token):
+    """Initialize the multi-agent system"""
+    try:
+        with st.spinner("🤖 Initializing AI agents..."):
+            system = MultiAgentSystem(token=token, max_iterations=2)
+        st.success("✅ System initialized successfully!")
+        return system
+    except Exception as e:
+        st.error(f"❌ Initialization failed: {str(e)}")
+        return None
+
+
+def display_progress(step):
+    """Display progress bar based on current step"""
+    steps = {
+        "researcher": (25, "🔍 Researching..."),
+        "analyst": (50, "📊 Analyzing..."),
+        "writer": (75, "✍️ Writing report..."),
+        "critic": (90, "🎯 Quality check..."),
+        "complete": (100, "✅ Complete!")
+    }
+    
+    if step in steps:
+        progress, text = steps[step]
+        st.progress(progress)
+        st.info(text)
+
+
+def display_agent_output(agent_name, content, box_class):
+    """Display agent output in a styled box"""
+    st.markdown(f'<div class="agent-box {box_class}">', unsafe_allow_html=True)
+    st.markdown(f"### {agent_name}")
+    st.markdown(content)
+    st.markdown('</div>', unsafe_allow_html=True)
+
+
+def main():
+    # Header
+    st.markdown('<h1 class="main-header">🤖 Multi-Agent Research Assistant</h1>', unsafe_allow_html=True)
+    st.markdown('<p class="sub-header">Powered by LangGraph & Advanced AI Agents</p>', unsafe_allow_html=True)
+    
+    # Sidebar
+    with st.sidebar:
+        st.header("⚙️ Configuration")
+        
+        # Token input
+        token = st.text_input(
+            "HuggingFace API Token",
+            type="password",
+            help="Enter your HuggingFace API token"
+        )
+        
+        # Initialize button
+        if st.button("🚀 Initialize System"):
+            if token:
+                st.session_state.system = initialize_system(token)
+            else:
+                st.error("Please enter your HuggingFace token")
+        
+        st.divider()
+        
+        # System status
+        st.header("📊 System Status")
+        if st.session_state.system:
+            st.success("🟢 System Active")
+            st.metric("Research Queries", len(st.session_state.research_history))
+        else:
+            st.warning("🔴 System Inactive")
+        
+        st.divider()
+        
+        # Example questions
+        st.header("💡 Example Questions")
+        examples = [
+            "what is 2+2",
+            "calculate (15*3)+7",
+            "what is artificial intelligence",
+            "what is machine learning",
+            "what is python programming"
+        ]
+        
+        for example in examples:
+            if st.button(f"📝 {example}", key=f"ex_{example}"):
+                st.session_state.example_question = example
+        
+        st.divider()
+        
+        # History
+        st.header("📚 Research History")
+        if st.session_state.research_history:
+            for i, item in enumerate(reversed(st.session_state.research_history[-5:])):
+                with st.expander(f"🔍 {item['question'][:30]}..."):
+                    st.write(f"**Time:** {item['timestamp']}")
+                    st.write(f"**Score:** {item['score']}/10")
+        else:
+            st.info("No research history yet")
+        
+        st.divider()
+        
+        # Clear history
+        if st.button("🗑️ Clear History"):
+            st.session_state.research_history = []
+            st.session_state.current_result = None
+            st.rerun()
+    
+    # Main content
+    if not st.session_state.system:
+        # Welcome screen
+        col1, col2, col3 = st.columns([1, 2, 1])
+        with col2:
+            st.info("👈 Please initialize the system using the sidebar")
+            
+            st.markdown("### 🌟 Features")
+            features = [
+                "🔍 **Smart Research**: Automatic tool selection and execution",
+                "📊 **Deep Analysis**: AI-powered insight extraction",
+                "✍️ **Professional Reports**: Well-structured documentation",
+                "🎯 **Quality Assurance**: Automated review and refinement",
+                "🔄 **Iterative Improvement**: Multiple revision cycles"
+            ]
+            for feature in features:
+                st.markdown(feature)
+            
+            st.markdown("### 🛠️ Technology Stack")
+            tech = [
+                "LangGraph for agent orchestration",
+                "Meta Llama 3.1 8B Instruct",
+                "Pydantic for structured outputs",
+                "NumExpr for safe calculations"
+            ]
+            for item in tech:
+                st.markdown(f"- {item}")
+    
+    else:
+        # Research interface
+        st.markdown("## 🔍 Ask Your Question")
+        
+        # Check if example was clicked
+        default_question = st.session_state.get('example_question', '')
+        if default_question:
+            st.session_state.example_question = ''
+        
+        question = st.text_input(
+            "Enter your research question:",
+            value=default_question,
+            placeholder="e.g., what is 2+2, what is artificial intelligence...",
+            key="question_input"
+        )
+        
+        col1, col2 = st.columns([3, 1])
+        with col1:
+            research_button = st.button("🚀 Start Research", type="primary")
+        with col2:
+            clear_button = st.button("🔄 Clear Results")
+        
+        if clear_button:
+            st.session_state.current_result = None
+            st.rerun()
+        
+        if research_button and question:
+            # Create progress container
+            progress_container = st.container()
+            result_container = st.container()
+            
+            with progress_container:
+                st.markdown("### 🔄 Research in Progress")
+                progress_bar = st.progress(0)
+                status_text = st.empty()
+                
+                # Capture output
+                import io
+                from contextlib import redirect_stdout
+                
+                output_capture = io.StringIO()
+                
+                try:
+                    with redirect_stdout(output_capture):
+                        # Run research
+                        final_state = st.session_state.system.research(question)
+                    
+                    # Update progress
+                    progress_bar.progress(100)
+                    status_text.success("✅ Research Complete!")
+                    
+                    if final_state:
+                        # Store result
+                        st.session_state.current_result = final_state
+                        
+                        # Add to history
+                        st.session_state.research_history.append({
+                            'question': question,
+                            'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+                            'score': final_state['critique_output'].score
+                        })
+                        
+                        st.rerun()
+                    
+                except Exception as e:
+                    progress_bar.progress(100)
+                    status_text.error(f"❌ Error: {str(e)}")
+        
+        # Display results
+        if st.session_state.current_result:
+            st.markdown("---")
+            result = st.session_state.current_result
+            
+            # Metrics row
+            st.markdown("## 📊 Research Metrics")
+            col1, col2, col3, col4 = st.columns(4)
+            
+            with col1:
+                st.markdown('<div class="metric-card">', unsafe_allow_html=True)
+                st.metric("Quality Score", f"{result['critique_output'].score}/10")
+                st.markdown('</div>', unsafe_allow_html=True)
+            
+            with col2:
+                st.markdown('<div class="metric-card">', unsafe_allow_html=True)
+                st.metric("Iterations", result['report_iterations'])
+                st.markdown('</div>', unsafe_allow_html=True)
+            
+            with col3:
+                st.markdown('<div class="metric-card">', unsafe_allow_html=True)
+                st.metric("Confidence", f"{result['research_output'].confidence*100:.0f}%")
+                st.markdown('</div>', unsafe_allow_html=True)
+            
+            with col4:
+                st.markdown('<div class="metric-card">', unsafe_allow_html=True)
+                sources = ", ".join(result['research_output'].sources_used)
+                st.metric("Sources", len(result['research_output'].sources_used))
+                st.caption(sources)
+                st.markdown('</div>', unsafe_allow_html=True)
+            
+            st.markdown("---")
+            
+            # Tabbed interface for results
+            tab1, tab2, tab3, tab4 = st.tabs(["📄 Final Report", "🔍 Research", "📊 Analysis", "🎯 Quality Review"])
+            
+            with tab1:
+                report = result['report_output']
+                st.markdown(f"# {report.title}")
+                st.markdown(report.content)
+                
+                # Download button
+                st.download_button(
+                    label="📥 Download Report",
+                    data=report.content,
+                    file_name=f"research_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.txt",
+                    mime="text/plain"
+                )
+            
+            with tab2:
+                research = result['research_output']
+                display_agent_output(
+                    "🔍 Research Agent",
+                    f"""
+**Answer:** {research.answer}
+
+**Sources Used:** {', '.join(research.sources_used)}
+
+**Confidence:** {research.confidence*100:.1f}%
+                    """,
+                    "researcher-box"
+                )
+            
+            with tab3:
+                analysis = result['analysis_output']
+                display_agent_output(
+                    "📊 Analysis Agent",
+                    f"""
+**Key Points:**
+{chr(10).join(f'• {point}' for point in analysis.key_points)}
+
+**Implications:**
+{analysis.implications}
+                    """,
+                    "analyst-box"
+                )
+            
+            with tab4:
+                critique = result['critique_output']
+                
+                # Score gauge
+                score = critique.score
+                color = "🟢" if score >= 8 else "🟡" if score >= 6 else "🔴"
+                
+                st.markdown(f"### {color} Quality Score: {score}/10")
+                st.progress(score / 10)
+                
+                st.markdown(f"""
+**Status:** {"✅ Approved" if not critique.needs_revision else "🔄 Needs Revision"}
+                """)
+            
+            # Export all data
+            st.markdown("---")
+            if st.button("📦 Export Full Research Data (JSON)"):
+                export_data = {
+                    'question': result['question'],
+                    'timestamp': datetime.now().isoformat(),
+                    'research': {
+                        'answer': result['research_output'].answer,
+                        'sources': result['research_output'].sources_used,
+                        'confidence': result['research_output'].confidence
+                    },
+                    'analysis': {
+                        'key_points': result['analysis_output'].key_points,
+                        'implications': result['analysis_output'].implications
+                    },
+                    'report': {
+                        'title': result['report_output'].title,
+                        'content': result['report_output'].content
+                    },
+                    'quality': {
+                        'score': result['critique_output'].score,
+                        'needs_revision': result['critique_output'].needs_revision
+                    }
+                }
+                
+                st.download_button(
+                    label="📥 Download JSON",
+                    data=json.dumps(export_data, indent=2),
+                    file_name=f"research_data_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
+                    mime="application/json"
+                )
+
+
+if __name__ == "__main__":
+    main()