Create summarizer.py

utils/summarizer.py

@@ -0,0 +1,46 @@
+import openai
+import os
+from youtube_transcript_api import YouTubeTranscriptApi
+from dotenv import load_dotenv
+import fitz  # PyMuPDF
+
+load_dotenv()
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+
+# ---------- 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
+
+
+# ---------- 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)}"