Create app.py

app.py

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+# Import necessary libraries
+import streamlit as st
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import PyPDF2
+import pytesseract
+from PIL import Image
+
+# Load StarCoder model and tokenizer
+model_name = "starcoder-plus" # Replace with the correct model name
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Streamlit app
+st.title("Conversational AI Chatbot")
+
+# User input for code-related question
+user_input = st.text_input("Enter your code-related question:")
+if user_input:
+    # Tokenize and generate code
+    inputs = tokenizer(user_input, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    code = tokenizer.decode(outputs[0])
+    st.code(code) # Display the generated code
+
+# User input for PDF reading
+pdf_file = st.file_uploader("Upload a PDF file:", type=["pdf"])
+if pdf_file:
+    pdf_reader = PyPDF2.PdfFileReader(pdf_file)
+    pdf_text = ""
+    for page_num in range(pdf_reader.numPages):
+        page = pdf_reader.getPage(page_num)
+        pdf_text += page.extractText()
+    st.text(pdf_text) # Display the extracted text
+
+# User input for OCR (image to text)
+image_file = st.file_uploader("Upload an image for OCR:", type=["png", "jpg", "jpeg"])
+if image_file:
+    image = Image.open(image_file)
+    ocr_text = pytesseract.image_to_string(image)
+    st.text(ocr_text) # Display the extracted text