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app.py

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+import asyncio
+import json
+import os
+import csv
+import concurrent.futures
+from typing import List
+from fastapi import FastAPI, BackgroundTasks
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+
+app = FastAPI(title="Lead Hunter AI API")
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class ScrapeRequest(BaseModel):
+    niche: str
+    location: str
+    limit: int = 10
+
+# Global progress state
+progress_data = {"status": "idle", "message": "Awaiting transmission...", "progress": 0}
+
+# Thread pool for running sync Playwright code outside the event loop
+_executor = concurrent.futures.ThreadPoolExecutor(max_workers=2)
+
+
+def _run_scrape(query: str, limit: int) -> list:
+    """Runs the sync Playwright scraper in a thread (safe for asyncio)."""
+    try:
+        from tools.google_maps_scraper import scrape_google_maps
+        return scrape_google_maps(query, limit)
+    except Exception as e:
+        print(f"[!] Scraper Error: {e}")
+        return []
+
+
+def _run_enrich(lead: dict) -> dict:
+    """Runs the sync httpx enricher in a thread."""
+    try:
+        from tools.contact_enricher import enrich_lead
+        return enrich_lead(lead)
+    except Exception as e:
+        print(f"[!] Enricher Error: {e}")
+        return lead
+
+
+async def run_workflow(niche: str, location: str, limit: int):
+    global progress_data
+    loop = asyncio.get_event_loop()
+
+    try:
+        # ── Stage 1: Scrape ──────────────────────────────────────────────
+        query = f"{niche} in {location}"
+        progress_data = {"status": "scraping", "message": f"Searching for {niche} in {location}...", "progress": 10}
+
+        raw_leads = await loop.run_in_executor(_executor, _run_scrape, query, limit)
+
+        if not raw_leads:
+            progress_data = {"status": "error", "message": "No businesses found. Try a different niche or location.", "progress": 100}
+            return
+
+        # ── Stage 2: Enrich ──────────────────────────────────────────────
+        progress_data = {"status": "enriching", "message": f"Found {len(raw_leads)} leads. Enriching contacts...", "progress": 40}
+
+        enriched_leads = []
+        for i, lead in enumerate(raw_leads):
+            progress_data["message"] = f"Enriching {i+1}/{len(raw_leads)}: {lead.get('name', '...')}"
+            progress_data["progress"] = 40 + int((i / len(raw_leads)) * 50)
+
+            enriched = await loop.run_in_executor(_executor, _run_enrich, lead)
+            enriched_leads.append(enriched)
+
+        # ── Stage 3: Save ────────────────────────────────────────────────
+        progress_data = {"status": "saving", "message": "Saving results...", "progress": 95}
+
+        os.makedirs(".tmp", exist_ok=True)
+        with open(".tmp/last_results.json", "w", encoding="utf-8") as f:
+            json.dump(enriched_leads, f, indent=2)
+
+        # Also save a named CSV
+        filename = f"{niche.lower().replace(' ','_')}_{location.lower().replace(' ','_')}.csv"
+        if enriched_leads:
+            keys = list(enriched_leads[0].keys())
+            with open(filename, "w", newline="", encoding="utf-8") as f:
+                w = csv.DictWriter(f, fieldnames=keys)
+                w.writeheader()
+                w.writerows(enriched_leads)
+
+        progress_data = {
+            "status": "complete",
+            "message": f"Done! {len(enriched_leads)} leads saved to {filename}",
+            "progress": 100,
+            "filename": filename,
+        }
+
+    except Exception as e:
+        print(f"[!] Workflow error: {e}")
+        progress_data = {"status": "error", "message": f"Error: {str(e)}", "progress": 100}
+
+
+@app.post("/api/scrape")
+async def start_scrape(request: ScrapeRequest, background_tasks: BackgroundTasks):
+    global progress_data
+    if progress_data.get("status") in ("scraping", "enriching", "saving"):
+        return {"error": "A scrape is already running"}
+    background_tasks.add_task(run_workflow, request.niche, request.location, request.limit)
+    return {"message": "Workflow started"}
+
+
+@app.get("/api/status")
+async def get_status():
+    return progress_data
+
+
+@app.get("/api/results")
+async def get_results():
+    try:
+        if os.path.exists(".tmp/last_results.json"):
+            with open(".tmp/last_results.json", "r", encoding="utf-8") as f:
+                return json.load(f)
+        return []
+    except Exception as e:
+        print(f"[!] Error reading results: {e}")
+        return []
+
+# Serve Static Files
+frontend_path = "frontend/dist"
+if os.path.exists(frontend_path):
+    # Mount assets folder
+    if os.path.exists(os.path.join(frontend_path, "assets")):
+        app.mount("/assets", StaticFiles(directory=os.path.join(frontend_path, "assets")), name="assets")
+
+    # Serve index.html for all other routes (SPA fallback)
+    @app.get("/{full_path:path}")
+    async def serve_frontend(full_path: str):
+        # Exclude /api calls
+        if full_path.startswith("api"):
+            return None
+        return FileResponse(os.path.join(frontend_path, "index.html"))
+
+if __name__ == "__main__":
+    import uvicorn
+    # Use 7860 as priority for HF Spaces
+    port = int(os.environ.get("PORT", 7860))
+    # Bind to 0.0.0.0 for containerization
+    uvicorn.run(app, host="0.0.0.0", port=port)