Update api.py

api.py

@@ -74,79 +74,99 @@
 #     logger.info("Starting Uvicorn server...")
 #     uvicorn.run(app, host="0.0.0.0", port=3000)
 
-from flask import Flask, request, jsonify,Response
-from flask_cors import CORS
+from flask import Flask, request, jsonify
 from model_loader import ModelLoader
 from services.text_filter import TextFilterService
-from services.image_ocr import ImageOCRService
+from services.llm_text_filter import ArticleClassifier
+from services.image_ocr import ImageClassifier
+from typing import Optional
+from PIL import Image
 import logging
-import os
-import json
-# Set Hugging Face cache directory
-os.environ["HF_HOME"] = "/app/cache"
+import io
 
-# Logging setup
 logging.basicConfig(
     level=logging.INFO,
-    format="%(asctime)s [%(levelname)s] %(message)s"
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    handlers=[
+        logging.StreamHandler()
+    ]
 )
+
 logger = logging.getLogger(__name__)
 
 app = Flask(__name__)
 logger.info("Starting Flask app...")
-CORS(app)
-# Load model and services
+
 model_loader = ModelLoader()
 logger.info("ModelLoader initialized.")
 
 text_filter_service = TextFilterService(model_loader)
 logger.info("TextFilterService initialized.")
 
-image_ocr_service = ImageOCRService()
-logger.info("ImageOCRService initialized.")
+image_classifier = ImageClassifier()
+logger.info("ImageClassifier initialized.")
 
 @app.route("/filtercomment", methods=["POST"])
 def filter_comment():
-    data = request.get_json()
-    logger.info("Received request: %s", data)
-
-    text = data.get("text")
-    image_url = data.get("image_url")
+    text = request.form.get("text")
+    image_url = request.form.get("image_url")
+    article = request.form.get("article", "false").lower() == "true"
+    image_file = request.files.get("image_file")
+    logger.info("Received request: text=%s, image_url=%s, article=%s, image_file=%s", text, image_url, article, image_file.filename if image_file else None)
     final_text = ""
 
+    # Case 1: Image file upload
+    if image_file:
+        try:
+            logger.info("Processing uploaded image file: %s", image_file.filename)
+            image_bytes = image_file.read()
+            image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+            result = image_classifier.classify(image)
+            logger.info("Image classification result: %s", result)
+            return jsonify({"image_classification": result})
+        except Exception as e:
+            logger.error("Image file processing failed: %s", str(e))
+            return jsonify({"error": f"Image file processing failed: {str(e)}"}), 400
+
+    # Case 2: Extract text from image URL
     if image_url:
         logger.info("Image URL provided: %s", image_url)
         try:
-            final_text = image_ocr_service.extract_text(image_url)
+            logger.info("Fetching image from URL...")
+            # You need to implement image_ocr_service.extract_text or use image_classifier if that's your OCR
+            final_text = image_classifier.extract_text(image_url)
             logger.info("Generated text: %s", final_text)
         except Exception as e:
             logger.error("Image processing failed: %s", str(e))
             return jsonify({"error": f"Image processing failed: {str(e)}"}), 400
 
+    # Case 3: Use provided text
     elif text:
+        logger.info("Text input provided.")
         final_text = text
     else:
         logger.warning("No input provided.")
-        return jsonify({"error": "Either 'text' or 'image_url' must be provided."}), 400
+        return jsonify({"error": "Either 'text', 'image_url', or 'image_file' must be provided."}), 400
 
     try:
-        results = text_filter_service.process_text(final_text)
-        results["extracted_text"] = final_text
-        logger.info("Text filtering complete. Results: %s", results)
-        # Ensure results dict is JSON serializable
-        safe_results = {
-            k: float(v) if isinstance(v, (float, int)) or hasattr(v, "item") else v
-            for k, v in results.items()
-        }
-        safe_results["extracted_text"] = final_text
-        
-        logger.info("Returning response now...")
-        return Response(json.dumps(safe_results), mimetype="application/json")
+        logger.info("Processing text through TextFilterService...")
+        if article:
+            logger.info("Classifying article...")
+            classifier = ArticleClassifier(final_text)
+            result = classifier.classify()
+            logger.info("Article classification complete: %s", final_text)
+            return jsonify(result)
+        else:
+            results = text_filter_service.process_text(final_text)
+            results["extracted_text"] = final_text
+            logger.info("Text filtering complete. Results: %s", results)
+            return jsonify(results)
 
     except Exception as e:
         logger.exception("Text filtering failed.")
         return jsonify({"error": f"Text filtering failed: {str(e)}"}), 500
 
 if __name__ == "__main__":
+    logger.info("Starting Flask server...")
     app.run(host="0.0.0.0", port=7860)