Create main.py

main.py

@@ -0,0 +1,127 @@
+import os
+import logging
+import requests
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+from fastapi.middleware.cors import CORSMiddleware
+from oauth import router as oauth_router
+from audit import explain_risks
+
+# ------------------------------------------------
+# 🔧 Logging setup
+# ------------------------------------------------
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+)
+logger = logging.getLogger(__name__)
+logger.info("🚀 Starting Privacy Audit Backend (Hugging Face API)...")
+
+# ------------------------------------------------
+# ⚙️ FastAPI app init
+# ------------------------------------------------
+app = FastAPI(title="Privacy Audit API", version="1.1.0")
+
+# Allow frontend access (CORS)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# ------------------------------------------------
+# 🔐 OAuth router
+# ------------------------------------------------
+try:
+    app.include_router(oauth_router)
+    logger.info("✅ OAuth router loaded successfully.")
+except Exception as e:
+    logger.exception(f"⚠️ Failed to include OAuth router: {e}")
+
+# ------------------------------------------------
+# 🤖 Hugging Face API setup
+# ------------------------------------------------
+HF_API_URL = "https://api-inference.huggingface.co/models/google/flan-t5-small"
+HF_TOKEN = os.getenv("HF_TOKEN")  # Set in Hugging Face Space secrets
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+def generate_plain_text(input_text: str):
+    """Call Hugging Face API instead of local model."""
+    logger.info(f"🧩 Generating explanation for input: {input_text[:60]}...")
+    try:
+        payload = {"inputs": f"Explain privacy risks in plain language:\n{input_text}"}
+        response = requests.post(HF_API_URL, headers=headers, json=payload, timeout=60)
+        if response.status_code == 200:
+            result = response.json()
+            if isinstance(result, list) and "generated_text" in result[0]:
+                explanation = result[0]["generated_text"]
+            else:
+                explanation = result[0].get("generated_text", str(result))
+            logger.info("✅ Text generation complete.")
+            return explanation
+        else:
+            logger.error(f"❌ HF API Error: {response.status_code} {response.text}")
+            return f"Error: {response.text}"
+    except Exception as e:
+        logger.exception(f"❌ Error generating text: {e}")
+        return "Error: Could not generate explanation."
+
+# ------------------------------------------------
+# 📤 Models
+# ------------------------------------------------
+class AuditInput(BaseModel):
+    findings: str
+
+# ------------------------------------------------
+# 🔍 Endpoints
+# ------------------------------------------------
+@app.get("/ping")
+def ping():
+    return {"status": "ok", "message": "Backend is alive!"}
+
+@app.post("/analyze")
+def analyze(data: dict):
+    try:
+        os_apps = data.get("os_apps", [])
+        browser_exts = data.get("browser_extensions", [])
+        account_apps = data.get("account_apps", [])
+        explanation = explain_risks(os_apps, browser_exts, account_apps)
+        return {"plain_language": explanation}
+    except Exception as e:
+        logger.exception(f"❌ Error in /analyze: {e}")
+        return {"error": str(e)}
+
+@app.get("/audit")
+def audit_mvp():
+    findings = "App X has camera access, App Y has location access, Chrome has 5 extensions"
+    explanation = generate_plain_text(findings)
+    return {
+        "findings": findings,
+        "plain_language": explanation,
+        "risk_level": "Medium"
+    }
+
+@app.post("/audit")
+async def audit_mvp(data: dict):
+    try:
+        os_apps = data.get("os_apps", [])
+        browser_exts = data.get("browser_extensions", [])
+        account_apps = data.get("account_apps", [])
+
+        findings_text = (
+            f"Detected {len(os_apps)} installed apps, "
+            f"{len(browser_exts)} browser extensions, and "
+            f"{len(account_apps)} connected account apps."
+        )
+        explanation = generate_plain_text(findings_text)
+
+        return {
+            "findings": findings_text,
+            "plain_language": explanation,
+            "risk_level": "Medium"
+        }
+    except Exception as e:
+        logger.exception(f"❌ Error in /audit: {e}")
+        return {"error": str(e)}