Update app.py

app.py

@@ -351,69 +351,6 @@ class PersonalAIResearchAssistant:
             "response": content,
             "knowledge_base_state": context
         }
-
-    def generate_weekly_report(self) -> Dict:
-        """
-        Generate a weekly summary of research and insights
-        
-        Returns:
-            Weekly report of activity and key findings
-        """
-        # Get weekly statistics
-        one_week_ago = datetime.now().isoformat()  # Simplified, should subtract 7 days
-        
-        # Count activities in the last week
-        recent_research = [d for d in self.knowledge_base["research_digests"] 
-                          if d["timestamp"] > one_week_ago]
-        recent_code = [c for c in self.knowledge_base["code_analyses"] 
-                      if c["timestamp"] > one_week_ago]
-        recent_connections = [c for c in self.knowledge_base["concept_connections"] 
-                             if c["timestamp"] > one_week_ago]
-        
-        # Build context for the report
-        context = {
-            "period": "weekly",
-            "research_count": len(recent_research),
-            "code_analyses_count": len(recent_code),
-            "concept_connections_count": len(recent_connections),
-            "topics_explored": list(set([r["topic"] for r in recent_research])),
-            "recent_research": recent_research[:3],  # Include only top 3
-            "recent_connections": recent_connections[:3]
-        }
-        
-        # Build the prompt
-        prompt = f"""Generate a weekly research summary based on the following activity:
-        
-        {json.dumps(context, indent=2)}
-        
-        Please include:
-        1. Overview of research activity
-        2. Key findings and insights
-        3. Emerging patterns or trends
-        4. Suggestions for further exploration
-        
-        Format as a concise weekly report.
-        """
-        
-        # Make the API call
-        response = self.client.chat.completions.create(
-            messages=[
-                {"role": "system", "content": "You are a research assistant generating a weekly summary of research activities and findings."},
-                {"role": "user", "content": prompt}
-            ],
-            model=self.model
-        )
-        
-        content = response.choices[0].message.content
-        
-        report = {
-            "type": "weekly_report",
-            "timestamp": datetime.now().isoformat(),
-            "content": content,
-            "stats": context
-        }
-        
-        return report
     
     def get_kb_stats(self):
         """Get statistics about the knowledge base"""
@@ -600,24 +537,6 @@ def query_knowledge_base(query):
     except Exception as e:
         return f"Error: {str(e)}"
 
-def generate_report_handler():
-    """Generate weekly report"""
-    # Check if API key is set
-    check_result = check_api_key()
-    if check_result:
-        return check_result
-    
-    try:
-        # Generate report
-        result = para_instance.generate_weekly_report()
-        
-        # Format response
-        response = f"# Weekly Research Report\n\n{result['content']}"
-        
-        return response
-    except Exception as e:
-        return f"Error: {str(e)}"
-
 # Create the Gradio interface
 def create_gradio_app():
     # Define CSS for styling
@@ -803,15 +722,6 @@ def create_gradio_app():
                     outputs=[kb_output]
                 )
                 
-                report_btn = gr.Button("Generate Weekly Report")
-                report_output = gr.Markdown("Report will appear here...")
-                
-                report_btn.click(
-                    fn=generate_report_handler,
-                    inputs=[],
-                    outputs=[report_output]
-                )
-                
                 gr.Markdown("""
                 ### Example Queries:
                 - "What have we learned about quantum computing?"
@@ -835,7 +745,6 @@ def create_gradio_app():
         - Code execution and analysis
         - Concept connections discovery
         - Persistent knowledge base
-        - Weekly research reports
         """)
     
     return app