Update app.py

app.py

@@ -1,5 +1,60 @@
 import streamlit as st
-import streamlit as st
 from transformers import pipeline
 import PyPDF2
 import requests
+
+# Constants for Groq API
+GROQ_API_URL = "https://api.groq.com/your_endpoint"  # Replace with your Groq endpoint
+GROQ_SECRET_KEY = "your_secret_key"  # Replace with your secret key
+HUGGINGFACE_MODEL = "deepset/bert-base-cased-squad2"  # Choose your model
+
+# Load Hugging Face model for question-answering
+qa_pipeline = pipeline("question-answering", model=HUGGINGFACE_MODEL)
+
+# Function to extract text from PDF
+def extract_text_from_pdf(pdf_file):
+    reader = PyPDF2.PdfReader(pdf_file)
+    text = ''
+    for page in reader.pages:
+        text += page.extract_text() + '\n'
+    return text
+
+# Function to run inference using Groq
+def groq_inference(question, context):
+    headers = {
+        "Authorization": f"Bearer {GROQ_SECRET_KEY}",
+        "Content-Type": "application/json"
+    }
+    payload = {
+        "question": question,
+        "context": context
+    }
+    response = requests.post(GROQ_API_URL, headers=headers, json=payload)
+    if response.status_code == 200:
+        return response.json()['answer']
+    else:
+        return "Error: Unable to get response from Groq."
+
+# Streamlit UI
+st.title("Document Chatbot")
+st.write("Upload a PDF document to interact with it!")
+
+# File uploader
+uploaded_file = st.file_uploader("Choose a PDF file", type="pdf")
+
+if uploaded_file:
+    # Extract text from the uploaded PDF
+    document_text = extract_text_from_pdf(uploaded_file)
+    st.write("Document successfully uploaded and processed.")
+
+    # Chat interface
+    user_question = st.text_input("Ask a question about the document:")
+
+    if user_question:
+        # First try to get the answer from Hugging Face model
+        hf_answer = qa_pipeline(question=user_question, context=document_text)['answer']
+        st.write("Answer from Hugging Face Model:", hf_answer)
+
+        # Then try to get the answer from Groq
+        groq_answer = groq_inference(user_question, document_text)
+        st.write("Answer from Groq:", groq_answer)