anotehr change

app.py

@@ -1021,6 +1021,9 @@
 
     
 
+
+    
+
 import os
 import gradio as gr
 from pinecone import Pinecone
@@ -1609,20 +1612,20 @@ def create_graph_visualization(graph_data: List[Dict]) -> go.Figure:
     
     return fig
 
-def create_interface(search_system: EnhancedLegalSearchSystem):
+def create_interface(graph_search_system: EnhancedLegalSearchSystem):
     """Create Gradio interface with interactive graph"""
-    
+    search_system = LegalSearchSystem()
+
     with gr.Blocks(css="footer {display: none !important;}") as demo:
         gr.Markdown("""
-        # Enhanced Legal Search System
-        Enter your legal query below to search through documents and get an AI-powered analysis.
-        This system combines graph-based and semantic search capabilities for comprehensive legal research.
+        # Corporate Law Legal Search Engine
+        Enter your legal query below to search through documents and get an AI-powered analysis. Queries only related to corporate law will give relevant information.
         """)
         
         with gr.Row():
             query_input = gr.Textbox(
                 label="Legal Query",
-                placeholder="e.g., What are the reporting obligations for banks under the Money Laundering Act?",
+                placeholder="e.g., What are the key principles of contract law?",
                 lines=3
             )
             
@@ -1635,24 +1638,28 @@ def create_interface(search_system: EnhancedLegalSearchSystem):
         )
         
         with gr.Tabs():
+            with gr.TabItem("Search Results"):
+                docs_output = gr.Markdown(
+                    label="Retrieved Documents",
+                    value="Search results will appear here..."
+                )
+            
             with gr.TabItem("AI Legal Analysis"):
-                analysis_output = gr.Markdown(
+                summary_output = gr.Markdown(
                     label="AI-Generated Legal Analysis",
                     value="Analysis will appear here..."
                 )
-            
-            with gr.TabItem("Retrieved Documents"):
-                docs_output = gr.Markdown(
+
+            with gr.TabItem("Retrieved Documents through Graph Rag"):
+                docs_output_graph = gr.Markdown(
                     label="Source Documents",
                     value="Search results will appear here..."
                 )
-                
-            with gr.TabItem("Related Concepts"):
-                concepts_output = gr.Json(
-                    label="Related Legal Concepts",
+                graph_analysis_output = gr.JSON(
+                    label="Related Concepts",
                     value={}
                 )
-            
+
             with gr.TabItem("Knowledge Graph"):
                 # Graph visualization
                 graph_output = gr.Plot(
@@ -1664,39 +1671,48 @@ def create_interface(search_system: EnhancedLegalSearchSystem):
                     interactive=False,
                     lines=10
                 )
-        
+
         async def process_query(query):
             if not query.strip():
                 return (
                     "Please enter a query",
-                    "No analysis available",
-                    "No documents available",
+                    "No documents available from Pinecone",
+                    "No analysis available from Pinecone",
+                    "No documents available from Neo4j",
                     {},
                     None,
                     ""
                 )
             
-            results = await search_system.process_legal_query(query)
-            graph_data = search_system.generate_document_graph(query)
+            # Run the regular RAG search
+            rag_results = search_system.search(query)
+
+            # Run the graph-based RAG search
+            graph_results = await graph_search_system.process_legal_query(query)
+
+            graph_data = graph_search_system.generate_document_graph(query)
             graph_fig = create_graph_visualization(graph_data)
-            
+
             return (
-                results['status'],
-                results['answer'],
-                results['documents'],
-                {"related_concepts": results['related_concepts']},
+                rag_results['status'],
+                rag_results['documents'],
+                rag_results['analysis'],
+                graph_results['documents'],
+                {"related_concepts": graph_results['related_concepts']},
                 graph_fig,
                 "Click on a node to view document content"
             )
-        
+    
+    
         search_button.click(
             fn=process_query,
             inputs=[query_input],
             outputs=[
                 status_output,
-                analysis_output,
                 docs_output,
-                concepts_output,
+                summary_output,
+                docs_output_graph,
+                graph_analysis_output,
                 graph_output,
                 selected_doc_content
             ]
@@ -1706,7 +1722,6 @@ def create_interface(search_system: EnhancedLegalSearchSystem):
 
 
 
-
 class LegalSearchSystem:
     def __init__(
         self,
@@ -1892,8 +1907,17 @@ class LegalSearchSystem:
                     }
                 ))
         
-        return
-    
+        return sorted(documents, key=lambda x: x.metadata['page_number'])
+
+    def _format_documents(self, results: List[Dict]) -> str:
+        """
+        Format search results as markdown.
+        """
+        markdown = "### Retrieved Documents\n\n"
+        for i, result in enumerate(results, 1):
+            markdown += f"**Document {i}** (Page {result['metadata']['page_number']})\n"
+            markdown += f"```\n{result['metadata']['text']}\n```\n\n"
+        return markdown
 
 if __name__ == "__main__":
     graph_search_system = EnhancedLegalSearchSystem(