Update app.py

app.py

@@ -1,15 +1,10 @@
-"""qResearch: Dual-Agent Research System
-
-A research system that combines web search, analysis, and proper MLA formatting
-using a dual-agent approach with specialized roles.
-"""
+"""qResearch: Dual-Agent Research System"""
 
 import os
 import gradio as gr
 from smolagents import CodeAgent, HfApiModel, tool
 from typing import Dict, List, Optional, Tuple, Union
 
-# Advanced Research Tools
 @tool
 def web_search(query: str, max_results: int = 5) -> str:
     """Performs comprehensive web searches using DuckDuckGo
@@ -48,79 +43,61 @@ def analyze_content(text: str, analysis_type: str = "general") -> str:
     Returns:
         str: Structured analysis results including key points and findings
     """
-    points = []
-    
     if "academic" in analysis_type.lower():
-        points.extend([
-            "Key Arguments:",
-            "- Main thesis and supporting evidence",
-            "- Methodological approach",
-            "- Scholarly context and significance",
-            "\nAcademic Sources:",
-            "- Peer-reviewed citations",
-            "- Research foundations",
-        ])
+        return (
+            "Academic Analysis:\n"
+            "1. Main Arguments:\n"
+            f"   - Key points from text: {text[:200]}...\n"
+            "2. Evidence Quality:\n"
+            "   - Source credibility assessment\n"
+            "   - Data verification\n"
+            "3. Research Context:\n"
+            "   - Field relevance\n"
+            "   - Current research status"
+        )
     elif "citations" in analysis_type.lower():
-        points.extend([
-            "Citation Analysis:",
-            "- Author credentials",
-            "- Publication details",
-            "- Citation format and standards",
-            "\nBibliographic Information:",
-            "- Primary sources",
-            "- Secondary references",
-        ])
+        return (
+            "Citation Analysis:\n"
+            "1. Source Information:\n"
+            "   - Publication details\n"
+            "   - Author credentials\n"
+            "2. Reference Quality:\n"
+            "   - Academic standards\n"
+            "   - Citation format"
+        )
     else:
-        points.extend([
-            "Content Overview:",
-            "- Main topics and themes",
-            "- Key findings and insights",
-            "- Supporting evidence",
-            "\nRelevance and Context:",
-            "- Topic significance",
-            "- Current applications",
-        ])
-    
-    return "\n".join(points)
+        return (
+            "General Analysis:\n"
+            "1. Key Findings:\n"
+            f"   - Main points from content: {text[:200]}...\n"
+            "2. Supporting Evidence:\n"
+            "   - Data and examples\n"
+            "3. Practical Applications:\n"
+            "   - Real-world relevance\n"
+            "   - Implementation possibilities"
+        )
 
 class ResearchSystem:
     def __init__(self):
-        # System configuration
-        self.config = {
-            "max_research_depth": 3,
-            "min_sources": 2,
-            "format_style": "MLA",
-            "cache_results": True
-        }
-        
-        # Initialize model with role specialization
         self.model = HfApiModel(
             model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
             custom_role_conversions={
                 "tool-call": "assistant",
-                "tool-response": "user",
-                "researcher": "assistant",
-                "formatter": "assistant"
+                "tool-response": "user"
             }
         )
 
-        # Research agent with enhanced capabilities
         self.researcher = CodeAgent(
             tools=[web_search, analyze_content],
             model=self.model
         )
         
-        # Formatting agent specializing in academic standards
         self.formatter = CodeAgent(
             tools=[],
             model=self.model
         )
-        
-        # Result cache for performance
-        self.cache: Dict[str, Tuple[str, str]] = {}
 
     def create_interface(self):
-        """Creates an enhanced Gradio interface with advanced features"""
         with gr.Blocks(title="qResearch", theme=gr.themes.Soft()) as interface:
             gr.Markdown(
                 "# qResearch Pro\n"
@@ -134,7 +111,7 @@ class ResearchSystem:
                         label="Research Process",
                         height=600,
                         show_label=True,
-                        type="messages"  # Use new message format
+                        type="messages"
                     )
                     
                 with gr.Column(scale=1):
@@ -178,7 +155,6 @@ class ResearchSystem:
                 outputs=[chat]
             )
             
-            # Clear chat using the proper method
             def clear_chat():
                 return None
             
@@ -187,7 +163,6 @@ class ResearchSystem:
                 outputs=[chat]
             )
             
-            # Help information
             with gr.Accordion("Usage Guide", open=False):
                 gr.Markdown("""
                 ### How to Use qResearch Pro
@@ -206,56 +181,41 @@ class ResearchSystem:
                      query: str, 
                      depth: int = 3, 
                      num_sources: int = 5) -> List[Dict[str, str]]:
-        """
-        Processes a research query with enhanced capabilities
-        
-        Args:
-            query: The research query
-            depth: Desired research depth (1-5)
-            num_sources: Number of sources to include (1-10)
-            
-        Returns:
-            List of message dictionaries for the chatbot interface
-        """
+        """Processes a research query with enhanced capabilities"""
         try:
-            # Check cache first
-            if query in self.cache and self.config["cache_results"]:
-                raw_research, formatted = self.cache[query]
-                return [
-                    {"role": "user", "content": query},
-                    {"role": "assistant", "content": f"📚 Research Findings:\n{raw_research}"},
-                    {"role": "assistant", "content": f"📝 MLA Formatted:\n{formatted}"}
-                ]
+            # Initial broad search
+            initial_results = web_search(query, max_results=num_sources)
+            initial_analysis = analyze_content(initial_results, "general")
             
-            # Configure research parameters
-            research_prompt = (
-                f"Research Query: {query}\n"
-                f"Required Depth: {depth}\n"
-                f"Minimum Sources: {num_sources}\n"
-                "Please provide comprehensive research with:\n"
-                "1. Multiple reliable sources\n"
-                "2. Key findings and analysis\n"
-                "3. Supporting evidence and context"
-            )
+            # Focused research on key aspects
+            aspects = [
+                "overview",
+                "detailed analysis",
+                "current developments",
+                "expert opinions",
+                "practical applications"
+            ][:depth]
             
-            # Conduct research
-            raw_research = self.researcher.run(research_prompt)
+            detailed_research = []
+            for aspect in aspects:
+                aspect_query = f"{query} {aspect}"
+                search_results = web_search(aspect_query, max_results=2)
+                aspect_analysis = analyze_content(search_results, "academic")
+                detailed_research.append(f"=== {aspect.upper()} ===\n{aspect_analysis}\n")
             
-            # Format results
+            # Compile research findings
+            raw_research = (
+                f"INITIAL OVERVIEW:\n{initial_analysis}\n\n"
+                f"DETAILED RESEARCH:\n{''.join(detailed_research)}"
+            )
+            
+            # Format in MLA style
             format_prompt = (
-                "Format the following research in MLA style with:\n"
-                "1. Proper citations\n"
-                "2. Academic formatting\n"
-                "3. Bibliography\n\n"
-                f"Content to format:\n{raw_research}"
+                "Format this research in MLA style:\n"
+                f"{raw_research}"
             )
             formatted = self.formatter.run(format_prompt)
             
-            # Cache results
-            if self.config["cache_results"]:
-                self.cache[query] = (raw_research, formatted)
-            
-            # Return results in new message format
             return [
                 {"role": "user", "content": query},
                 {"role": "assistant", "content": f"📚 Research Findings:\n{raw_research}"},
@@ -273,6 +233,6 @@ if __name__ == "__main__":
     system = ResearchSystem()
     system.create_interface().launch(
         server_port=7860,
-        share=True,  # Enable public link
-        show_api=False  # Hide API docs
+        share=True,
+        show_api=False
     )