Update app.py

app.py

@@ -4,6 +4,7 @@ import gradio as gr
 from datetime import datetime
 from dotenv import load_dotenv
 from openai import OpenAI
+from prompt import SYSTEM_PROMPT, format_exploration_prompt
 
 # Load environment variables
 load_dotenv()
@@ -22,46 +23,111 @@ class ExplorationPathGenerator:
             if exploration_parameters is None:
                 exploration_parameters = {}
 
-            system_prompt = """You are an expert art historian AI that helps users explore art history topics by generating interconnected exploration paths. Generate a JSON response with nodes representing concepts, artworks, or historical events, and connections showing their relationships."""
-
-            user_prompt = f"""Query: {query}
-Selected Path: {json.dumps(selected_path)}
-Parameters: {json.dumps(exploration_parameters)}
-Generate an exploration path that includes:
-- Multiple interconnected nodes
-- Clear relationships between nodes
-- Depth-based organization
-- Relevant historical context
-Response must be valid JSON with this structure:
-{{
-    "nodes": [
-        {{
-            "id": "unique_string",
-            "title": "node_title",
-            "description": "detailed_description",
-            "depth": number,
-            "connections": [
-                {{
-                    "target_id": "connected_node_id",
-                    "relationship": "description of relationship"
-                }}
-            ]
-        }}
-    ]
-}}"""
+            # Use the prompt from prompt.py
+            formatted_prompt = format_exploration_prompt(
+                user_query=query,
+                selected_path=selected_path,
+                exploration_parameters=exploration_parameters
+            )
 
             response = self.client.chat.completions.create(
                 model="mixtral-8x7b-32768",
                 messages=[
-                    {"role": "system", "content": system_prompt},
-                    {"role": "user", "content": user_prompt}
+                    {"role": "system", "content": SYSTEM_PROMPT},
+                    {"role": "user", "content": formatted_prompt}
                 ],
                 temperature=0.7,
                 max_tokens=4000
             )
 
             result = json.loads(response.choices[0].message.content)
-            return result
+            
+            # Convert exploration response to graph format
+            nodes = []
+            node_id_counter = 0
+
+            # Add meta insights as central node
+            node_id_counter += 1
+            meta_node = {
+                "id": f"meta_{node_id_counter}",
+                "title": "Exploration Summary",
+                "description": result["exploration_summary"]["current_context"],
+                "depth": 0,
+                "connections": []
+            }
+            nodes.append(meta_node)
+
+            # Create nodes from standard axes
+            for axis in result["knowledge_axes"]["standard_axes"]:
+                node_id_counter += 1
+                axis_node = {
+                    "id": f"std_{node_id_counter}",
+                    "title": axis["name"],
+                    "description": f"Current values: {', '.join(axis['current_values'])}",
+                    "depth": 1,
+                    "connections": []
+                }
+                
+                # Connect to meta node
+                meta_node["connections"].append({
+                    "target_id": axis_node["id"],
+                    "relevance_score": 0.8
+                })
+
+                # Add potential values as nodes
+                for value in axis["potential_values"]:
+                    node_id_counter += 1
+                    value_node = {
+                        "id": f"val_{node_id_counter}",
+                        "title": value["value"],
+                        "description": value["contextual_rationale"],
+                        "depth": 2,
+                        "connections": []
+                    }
+                    nodes.append(value_node)
+                    axis_node["connections"].append({
+                        "target_id": value_node["id"],
+                        "relevance_score": value["relevance_score"] / 100
+                    })
+                
+                nodes.append(axis_node)
+
+            # Create nodes from emergent axes
+            for axis in result["knowledge_axes"]["emergent_axes"]:
+                node_id_counter += 1
+                emergent_node = {
+                    "id": f"emg_{node_id_counter}",
+                    "title": f"{axis['name']} (Emergent)",
+                    "description": f"Parent axis: {axis['parent_axis']}",
+                    "depth": 2,
+                    "connections": []
+                }
+                
+                # Connect to meta node
+                meta_node["connections"].append({
+                    "target_id": emergent_node["id"],
+                    "relevance_score": 0.6
+                })
+
+                # Add innovative values
+                for value in axis["innovative_values"]:
+                    node_id_counter += 1
+                    value_node = {
+                        "id": f"inv_{node_id_counter}",
+                        "title": value["value"],
+                        "description": value["discovery_potential"],
+                        "depth": 3,
+                        "connections": []
+                    }
+                    nodes.append(value_node)
+                    emergent_node["connections"].append({
+                        "target_id": value_node["id"],
+                        "relevance_score": value["innovation_score"] / 100
+                    })
+                
+                nodes.append(emergent_node)
+
+            return {"nodes": nodes}
 
         except Exception as e:
             print(f"Error generating exploration path: {e}")
@@ -123,8 +189,8 @@ Response must be valid JSON with this structure:
                 html_content += "<strong>Connections:</strong><ul>"
                 for conn in node['connections']:
                     html_content += f"<li>Connected to: {conn['target_id']}"
-                    if 'relationship' in conn:
-                        html_content += f" - {conn['relationship']}"
+                    if 'relevance_score' in conn:
+                        html_content += f" (Relevance: {conn['relevance_score']:.2f})"
                     html_content += "</li>"
                 html_content += "</ul>"
             
@@ -163,10 +229,10 @@ def explore(query: str, path_history: str = "[]", parameters: str = "{}", depth:
             exploration_parameters=exploration_parameters
         )
 
-        # Create visualization using the simplified HTML method
+        # Create visualization
         graph_html = generator.create_visualization_html(result.get('nodes', []))
         
-        summary = f"Generated {len(result.get('nodes', []))} nodes for your query"
+        summary = f"Exploration path generated with {len(result.get('nodes', []))} nodes"
         
         return json.dumps(result), graph_html, summary
 
@@ -186,15 +252,15 @@ def create_interface() -> gr.Blocks:
         theme=gr.themes.Soft()
     ) as interface:
         gr.Markdown("""
-        # Art History Exploration Path Generator
-        Generate interactive exploration paths through art history topics.
+        # Knowledge Exploration Path Generator
+        Generate interactive exploration paths through complex topics.
         """)
 
         with gr.Row():
             with gr.Column(scale=1):
                 query_input = gr.Textbox(
                     label="Exploration Query",
-                    placeholder="Enter your art history exploration query...",
+                    placeholder="Enter your exploration query...",
                     lines=2
                 )
                 
@@ -208,7 +274,7 @@ def create_interface() -> gr.Blocks:
                 
                 domain = gr.Textbox(
                     label="Domain Context",
-                    placeholder="Optional: Specify art history period or movement",
+                    placeholder="Optional: Specify domain context",
                     lines=1
                 )
                 
@@ -221,18 +287,14 @@ def create_interface() -> gr.Blocks:
 
         generate_btn.click(
             fn=explore,
-            inputs=[query_input, gr.Textbox(value="[]", visible=False), 
-                   gr.Textbox(value="{}", visible=False), depth, domain],
-            outputs=[text_output, graph_output, summary_output]
-        )
-
-        gr.Examples(
-            examples=[
-                ["Explore the evolution of Renaissance painting techniques", 5, "Renaissance"],
-                ["Investigate the influence of Japanese art on Impressionism", 7, "Impressionism"],
-                ["Analyze the development of Cubism through Picasso's work", 6, "Cubism"]
+            inputs=[
+                query_input,
+                gr.Textbox(value="[]", visible=False),
+                gr.Textbox(value="{}", visible=False),
+                depth,
+                domain
             ],
-            inputs=[query_input, depth, domain]
+            outputs=[text_output, graph_output, summary_output]
         )
 
         return interface