Update app.py

app.py

@@ -1,6 +1,7 @@
 from fastapi import FastAPI, Request
 import requests
 import os
+import json
 
 app = FastAPI()
 
@@ -27,8 +28,8 @@ async def generate_insight(request: Request):
         Analyze the following compliance document status data and return a JSON with:
         {{
           "summary": "...",
-          "risks": [...],
-          "recommendations": [...]
+          "risks": ["..."],
+          "recommendations": ["..."]
         }}
 
         Data:
@@ -41,9 +42,9 @@ async def generate_insight(request: Request):
         Analyze the resource usage data below. Return a JSON:
         {{
           "summary": "...",
-          "overutilized": [...],
-          "underutilized": [...],
-          "suggestions": [...]
+          "overutilized": ["..."],
+          "underutilized": ["..."],
+          "suggestions": ["..."]
         }}
 
         Data:
@@ -56,9 +57,39 @@ async def generate_insight(request: Request):
         Analyze participant growth metrics and return JSON like:
         {{
           "summary": "...",
-          "trends": [...],
-          "risks": [...],
-          "recommendations": [...]
+          "trends": ["..."],
+          "risks": ["..."],
+          "recommendations": ["..."]
+        }}
+
+        Data:
+        {json.dumps(data, indent=2)}
+        """
+    elif prompt_type == "intervention":
+        base_prompt = f"""
+        You are an incubation operations strategist.
+
+        Analyze intervention frequency, completion and category data. Return a JSON:
+        {{
+          "summary": "...",
+          "effective_areas": ["..."],
+          "gaps": ["..."],
+          "recommendations": ["..."]
+        }}
+
+        Data:
+        {json.dumps(data, indent=2)}
+        """
+    elif prompt_type == "consultant":
+        base_prompt = f"""
+        You are evaluating consultant performance for an incubator program.
+
+        Using metrics like hours, rating, and impact scores, return JSON like:
+        {{
+          "summary": "...",
+          "top_performers": ["..."],
+          "underperformers": ["..."],
+          "recommendations": ["..."]
         }}
 
         Data:
@@ -66,11 +97,11 @@ async def generate_insight(request: Request):
         """
     else:
         base_prompt = f"""
-        Analyze the following data and return an insightful summary with recommendations in JSON:
+        Analyze the following data and return a useful JSON summary:
         {{
           "summary": "...",
-          "details": [...],
-          "recommendations": [...]
+          "details": ["..."],
+          "recommendations": ["..."]
         }}
 
         Data:
@@ -85,8 +116,12 @@ async def generate_insight(request: Request):
 
     try:
         result = response.json()
+        insight_text = result["candidates"][0]["content"]["parts"][0]["text"]
+        return {
+            "insight": insight_text
+        }
+    except Exception:
         return {
-            "insight": result["candidates"][0]["content"]["parts"][0]["text"]
+            "error": "Gemini response format invalid",
+            "details": str(response.json())
         }
-    except Exception as e:
-        return {"error": "Gemini response format invalid", "details": str(response.json())}