Upload app.py

app.py

@@ -0,0 +1,69 @@
+import logging
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel, HttpUrl
+from typing import List, Dict
+from concurrent.futures import ThreadPoolExecutor
+from process_interview import process_interview
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+app = FastAPI(
+    title="EvalBot API",
+    description="API to analyze audio interviews.",
+    version="1.0.0"
+)
+
+
+class AudioItem(BaseModel):
+    url: HttpUrl
+    user_id: str
+
+
+class AnalysisRequest(BaseModel):
+    audio_items: List[AudioItem]
+
+
+def process_item_wrapper(item: AudioItem) -> Dict:
+    try:
+        logger.info(f"Starting analysis for user '{item.user_id}' with URL: {item.url}")
+        result = process_interview(str(item.url))
+        return {
+            "user_id": item.user_id,
+            "url": str(item.url),
+            "status": "success",
+            "result": result
+        }
+    except Exception as e:
+        logger.error(f"Failed processing for user '{item.user_id}': {e}", exc_info=True)
+        return {
+            "user_id": item.user_id,
+            "url": str(item.url),
+            "status": "error",
+            "detail": str(e)
+        }
+
+
+@app.get("/health", summary="Check API Health")
+def health_check():
+    return {"status": "ok"}
+
+
+@app.post("/analyze", summary="Analyze a list of audio URLs")
+def analyze_audios(request: AnalysisRequest):
+    if not request.audio_items:
+        raise HTTPException(status_code=400, detail="No audio items provided.")
+
+    logger.info(f"Received request to analyze {len(request.audio_items)} audio items.")
+    results = []
+
+    with ThreadPoolExecutor(max_workers=5) as executor:
+        futures = [executor.submit(process_item_wrapper, item) for item in request.audio_items]
+
+        for future in futures:
+            results.append(future.result())
+
+    logger.info("Finished processing all items.")
+    return {"analysis_results": results}