Update kig_core/prompts.py

kig_core/prompts.py

@@ -84,14 +84,10 @@ SUMMARIZER_PROMPT = ChatPromptTemplate.from_template(SUMMARIZER_TEMPLATE)
 # This prompt guides the LLM to output structured Key Issues based on gathered context.
 # It references the Pydantic model 'KeyIssue' for the desired format.
 KEY_ISSUE_STRUCTURING_TEMPLATE = f"""Based on the provided context (summaries of relevant documents, research findings, etc.), identify and formulate distinct Key Issues related to the original user query.
-
 User Query: {{user_query}}
-
 Context:
 {{context}}
-
 For each Key Issue identified, provide the following information in the exact JSON format described below. Output a JSON list containing multiple KeyIssue objects.
-
 JSON Schema for each Key Issue object:
 {{
   "id": "Sequential integer ID starting from 1",
@@ -100,30 +96,27 @@ JSON Schema for each Key Issue object:
   "challenges": ["List of specific challenges related to this issue (strings)", "Each challenge as a separate string"],
   "potential_impact": "Brief description of the potential impact if not addressed (optional, max 30 words)"
 }}
-
 Example Format:
 [
-  {{
+  {{{{
     "id": 1,
     "title": "Scalability of AI Models in Low-Resource Settings",
     "description": "Deploying complex AI models for healthcare diagnostics in areas with limited computational power and data connectivity presents significant scalability challenges. Existing models often require substantial resources.",
     "challenges": ["High computational requirements of current models", "Intermittent or low-bandwidth network connectivity", "Lack of large, localized datasets for training/fine-tuning"],
     "potential_impact": "Limits equitable access to advanced AI-driven healthcare diagnostics."
-  }},
-  {{
+  }}}},
+  {{{{
     "id": 2,
     "title": "...",
     "description": "...",
     "challenges": ["...", "..."],
     "potential_impact": "..."
-  }}
+  }}}}
 ]
-
 Generate the JSON list of Key Issues based *only* on the provided context and user query. Ensure the output is a valid JSON list.
 """
 KEY_ISSUE_STRUCTURING_PROMPT = ChatPromptTemplate.from_template(KEY_ISSUE_STRUCTURING_TEMPLATE)
 
-
 # --- Initial Prompt Selection ---
 def get_initial_planner_prompt(plan_method: str, user_query: str) -> ChatPromptTemplate:
     if plan_method == "generation":