Merge branch 'main' of https://github.com/PlatypusPus/MushroomEmpire

api/routers/analyze.py

@@ -123,10 +123,14 @@ async def analyze_dataset(file: UploadFile = File(...)):
             },
             "risk_assessment": {
                 "overall_risk_score": risk_assessment.get("overall_risk_score", 0),
-                "privacy_risks": risk_assessment.get("privacy_risks", []),
-                "ethical_risks": risk_assessment.get("ethical_risks", []),
-                "compliance_risks": risk_assessment.get("risk_categories", {}).get("compliance_risks", []),
-                "data_quality_risks": risk_assessment.get("risk_categories", {}).get("data_quality_risks", [])
+                "risk_level": risk_assessment.get("risk_level", "LOW"),
+                "presidio_enabled": risk_assessment.get("presidio_enabled", False),
+                "privacy_risks": risk_assessment.get("privacy_risks", {}),
+                "ethical_risks": risk_assessment.get("ethical_risks", {}),
+                "compliance_risks": risk_assessment.get("compliance_risks", {}),
+                "risk_categories": risk_assessment.get("risk_categories", {}),
+                "violations": risk_assessment.get("violations", []),
+                "insights": risk_assessment.get("insights", [])
             },
             "recommendations": report.get("recommendations", []),
             "report_file": f"/{report_path}",

api/routers/chatbot.py

@@ -1,7 +1,9 @@
 import ollama
 import chromadb
 from pypdf import PdfReader 
-from fastapi import FastAPI 
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
 import uvicorn
 
 from fastapi.middleware.cors import CORSMiddleware
@@ -34,11 +36,24 @@ for i, chunk in enumerate(chunks):
 print("Embeddings done!")
 
 
+# Allow browser calls from the frontend
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class ChatRequest(BaseModel):
+    prompt: str
+
 @app.post("/chat")
-async def chat_bot(prompt: str):
-    if not prompt:
-        return
-    query = prompt
+async def chat_bot(prompt: str | None = None, body: ChatRequest | None = None):
+    # Accept prompt from either query (?prompt=) or JSON body {"prompt": "..."}
+    query = prompt or (body.prompt if body else None)
+    if not query:
+        raise HTTPException(status_code=400, detail="Missing prompt")
     response = ollama.embed(model="nomic-embed-text", input=query)
     query_embedding = response["embeddings"][0]