Update prompts.py

prompts.py

@@ -20,87 +20,94 @@ Input is a JSON object containing:
 {
 "user_query": "Primary exploration intent or research question",
 "selected_path": [
-  {"axis": "string", "value": "string"}  // Current exploration context
+{"axis": "string", "value": "string"}  // Current exploration context
 ],
 "exploration_parameters": {
-  "depth": 0-10,  // Exploration granularity
-  "domain": "optional domain-specific context",
-  "previous_explorations": []  // Historical exploration context
+"depth": 0-10,  // Exploration granularity
+"domain": "optional domain-specific context",
+"previous_explorations": []  // Historical exploration context
 }
 }
 
+## CURRENT INPUT:
+{
+"user_query": "{{user_query}}",
+"selected_path": {{selected_path}},
+"exploration_parameters": {{exploration_parameters}}
+}
+
 ### Input Components Explained:
 1. `user_query`: The fundamental question or exploration intent
- - Can be broad or specific
- - Represents the initial knowledge seeking goal
- - Provides context for axis and value generation
+- Can be broad or specific
+- Represents the initial knowledge seeking goal
+- Provides context for axis and value generation
 
 2. `selected_path`: Current exploration context
- - Represents user's existing exploration trajectory
- - Each tuple defines an axis-value pair
- - Guides contextual relevance of future suggestions
+- Represents user's existing exploration trajectory
+- Each tuple defines an axis-value pair
+- Guides contextual relevance of future suggestions
 
 3. `exploration_parameters`:
- - `depth`: Controls exploration granularity
- - `domain`: Provides additional contextual constraints
- - `previous_explorations`: Tracks exploration history
+- `depth`: Controls exploration granularity
+- `domain`: Provides additional contextual constraints
+- `previous_explorations`: Tracks exploration history
 
 ## OUTPUT BLUEPRINT
 {
 "exploration_summary": {
-  "current_context": "Narrative summary of exploration state",
-  "complexity_level": 0-10
+"current_context": "Narrative summary of exploration state",
+"complexity_level": 0-10
 },
 "knowledge_axes": {
-  "standard_axes": [
-    {
-      "name": "string",
-      "current_values": [""],
-      "potential_values": [
-        {
-          "value": "string",
-          "relevance_score": 0-100,
-          "contextual_rationale": "Why this value matters"
-        }
-      ],
-      "axis_constraints": ["Logical limitations"]
-    }
-  ],
-  "emergent_axes": [
-    {
-      "name": "string",
-      "parent_axis": "string",
-      "innovative_values": [
-        {
-          "value": "string",
-          "innovation_score": 0-100,
-          "discovery_potential": "Unique exploration opportunity"
-        }
-      ]
-    }
-  ]
+"standard_axes": [
+  {
+    "name": "string",
+    "current_values": [""],
+    "potential_values": [
+      {
+        "value": "string",
+        "relevance_score": 0-100,
+        "contextual_rationale": "Why this value matters"
+      }
+    ],
+    "axis_constraints": ["Logical limitations"]
+  }
+],
+"emergent_axes": [
+  {
+    "name": "string",
+    "parent_axis": "string",
+    "innovative_values": [
+      {
+        "value": "string",
+        "innovation_score": 0-100,
+        "discovery_potential": "Unique exploration opportunity"
+      }
+    ]
+  }
+]
 },
 "navigation_strategies": {
-  "zoom_trajectories": [
-    {
-      "target_axis": "string",
-      "zoom_value": "string",
-      "unlocked_dimensions": [""],
-      "depth_increment": 1-3
-    }
-  ],
-  "dezoom_pathways": [
-    {
-      "removal_tuple": {"axis": "string", "value": "string"},
-      "contextual_expansion": "Broader exploration narrative",
-      "new_possibility_vectors": [""]
-    }
-  ]
+"zoom_trajectories": [
+  {
+    "target_axis": "string",
+    "zoom_value": "string",
+    "unlocked_dimensions": [""],
+    "depth_increment": 1-3
+  }
+],
+"dezoom_pathways": [
+  {
+    "removal_tuple": {"axis": "string", "value": "string"},
+    "contextual_expansion": "Broader exploration narrative",
+    "new_possibility_vectors": [""]
+  }
+]
 },
 "meta_insights": {
-  "exploration_efficiency": 0-100,
-  "knowledge_gap_indicators": [""],
-  "recommended_next_steps": [""]
+"exploration_efficiency": 0-100,
+"knowledge_gap_indicators": [""],
+"recommended_next_steps": [""]
 }
 }
 
@@ -163,4 +170,12 @@ DEFAULT_RESPONSE = {
       "knowledge_gap_indicators": ["initial state"],
       "recommended_next_steps": ["begin exploration"]
   }
-}
+}
+
+def format_exploration_prompt(user_query: str, selected_path: list, exploration_parameters: dict) -> str:
+  """Helper function to format the prompt with proper JSON structure"""
+  return CONTEXTUAL_ZOOM_PROMPT.format(
+      user_query=json.dumps(user_query),
+      selected_path=json.dumps(selected_path),
+      exploration_parameters=json.dumps(exploration_parameters)
+  )