Update app.py

app.py

@@ -1,17 +1,17 @@
-import google.generativeai as genai
+import groq  # This assumes Groq provides a Python package named "groq"
 import pdfplumber
 import gradio as gr
 import os
 from dotenv import load_dotenv
-load_dotenv()
 
+load_dotenv()  # Loads environment variables from a .env file
 
-# Replace with your API key
-GOOGLE_API_KEY = os.getenv("GEMINI_API_KEY")
-genai.configure(api_key=GOOGLE_API_KEY)
+# Replace with your Groq API key in your .env file as GROQ_API_KEY
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+groq.configure(api_key=GROQ_API_KEY)
 
-# Load Gemini Pro model
-model = genai.GenerativeModel('gemini-2.5-pro-preview-03-25')
+# Load Groq's generative model (the model name 'groq-pro' is illustrative)
+model = groq.GenerativeModel('groq-pro')
 
 def extract_text_from_pdf(pdf_file):
     text = ""
@@ -27,13 +27,13 @@ def summarize_pdf(pdf_file):
     if not text.strip():
         return "No extractable text found in the PDF."
 
-    # Limit text size if needed (Gemini handles long input, but it's safer)
+    # Optional: Limit the text if needed for token limits
     text = text[:15000]
 
     prompt = f"Summarize the following PDF content:\n\n{text}"
 
     try:
-        response = model.generate_content(prompt)
+        response = model.generate_content(prompt)  # Adjust parameters per Groq's API
         return response.text.strip()
     except Exception as e:
         return f"Error during summarization: {e}"
@@ -43,8 +43,8 @@ iface = gr.Interface(
     fn=summarize_pdf,
     inputs=gr.File(label="Upload PDF", file_types=[".pdf"]),
     outputs="text",
-    title="PDF Summarizer with Gemini",
-    description="Upload a PDF and get a summary using Google's Gemini Pro model."
+    title="PDF Summarizer with Groq",
+    description="Upload a PDF and get a summary using Groq's generative AI API."
 )
 
 if __name__ == "__main__":