Update utils/summarizer.py

utils/summarizer.py

@@ -1,46 +1,15 @@
-import openai
 import os
-from youtube_transcript_api import YouTubeTranscriptApi
-from dotenv import load_dotenv
-import fitz  # PyMuPDF
+import requests
 
-load_dotenv()
-openai.api_key = os.getenv("OPENAI_API_KEY")
+HF_TOKEN = os.getenv("HF_TOKEN")
+API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 
+def summarize_text(text):
+    payload = {"inputs": text}
+    response = requests.post(API_URL, headers=headers, json=payload)
 
-# ---------- PDF Summarization ----------
-def extract_text_from_pdf(pdf_path):
-    text = ""
-    with fitz.open(pdf_path) as doc:
-        for page in doc:
-            text += page.get_text()
-    return text
+    if response.status_code != 200:
+        return f"❌ Error: {response.status_code} - {response.json()}"
 
-
-# ---------- YouTube Summarization ----------
-def get_youtube_transcript(video_url):
-    try:
-        video_id = video_url.split("v=")[-1].split("&")[0]
-        transcript = YouTubeTranscriptApi.get_transcript(video_id)
-        full_text = " ".join([entry["text"] for entry in transcript])
-        return full_text
-    except Exception as e:
-        return f"Error fetching transcript: {str(e)}"
-
-
-# ---------- Summarization using GPT ----------
-def summarize_text(text, engine="gpt-3.5-turbo"):
-    try:
-        response = openai.ChatCompletion.create(
-            model=engine,
-            messages=[
-                {"role": "system", "content": "You are a helpful summarization assistant."},
-                {"role": "user", "content": f"Summarize this:\n{text}"}
-            ],
-            temperature=0.5,
-            max_tokens=500
-        )
-        summary = response['choices'][0]['message']['content']
-        return summary
-    except Exception as e:
-        return f"Error during summarization: {str(e)}"
+    return response.json()[0]["summary_text"]