Update app.py

app.py

@@ -1,11 +1,7 @@
-import gradio as gr
+ import gradio as gr
 from huggingface_hub import InferenceClient
 from typing import List, Tuple
 import logging
-import PyPDF2
-import pytesseract
-from PIL import Image
-import io
 
 # Configure logging for better debugging and monitoring
 logging.basicConfig(
@@ -22,47 +18,8 @@ except Exception as e:
     logger.error(f"Failed to initialize InferenceClient: {str(e)}")
     raise
 
-def extract_text_from_pdf(pdf_file) -> str:
-    """
-    Extracts text from an uploaded PDF file.
-    Args:
-        pdf_file: Path to the uploaded PDF file or file-like object.
-    Returns:
-        str: Extracted text from the PDF.
-    """
-    try:
-        text = ""
-        with open(pdf_file, "rb") as file:
-            reader = PyPDF2.PdfReader(file)
-            for page in reader.pages:
-                text += page.extract_text() or ""
-        logger.info("Successfully extracted text from PDF")
-        return text.strip()
-    except Exception as e:
-        logger.error(f"Error extracting text from PDF: {str(e)}")
-        return ""
-
-def extract_text_from_image(image_file) -> str:
-    """
-    Extracts text from an uploaded image file using OCR.
-    Args:
-        image_file: Path to the uploaded image file or file-like object.
-    Returns:
-        str: Extracted text from the image.
-    """
-    try:
-        image = Image.open(image_file)
-        text = pytesseract.image_to_string(image)
-        logger.info("Successfully extracted text from image")
-        return text.strip()
-    except Exception as e:
-        logger.error(f"Error extracting text from image: {str(e)}")
-        return ""
-
 def respond(
     message: str,
-    pdf_file: str,
-    image_file: str,
     history: List[Tuple[str, str]],
     system_message: str,
     max_tokens: int,
@@ -70,11 +27,9 @@ def respond(
     top_p: float,
 ) -> str:
     """
-    Generates an educational response to a student's query, including text from uploaded PDFs or images.
+    Generates an educational response to a student's query using the HuggingFace Inference API.
     Args:
         message (str): The student's input question or query.
-        pdf_file (str): Path to the uploaded PDF file.
-        image_file (str): Path to the uploaded image file.
         history (List[Tuple[str, str]]): Chat history with student and AI teacher messages.
         system_message (str): The system prompt defining the AI teacher's behavior.
         max_tokens (int): Maximum number of tokens to generate.
@@ -87,8 +42,8 @@ def respond(
         RuntimeError: If the API call fails.
     """
     # Validate input parameters
-    if not message.strip() and not pdf_file and not image_file:
-        raise ValueError("At least one of message, PDF, or image must be provided")
+    if not message.strip():
+        raise ValueError("Input message cannot be empty")
     if max_tokens < 1 or max_tokens > 2048:
         raise ValueError("max_tokens must be between 1 and 2048")
     if temperature < 0.1 or temperature > 2.0:
@@ -96,20 +51,6 @@ def respond(
     if top_p < 0.1 or top_p > 1.0:
         raise ValueError("top_p must be between 0.1 and 1.0")
 
-    # Combine text from message, PDF, and image
-    combined_message = message.strip()
-    if pdf_file:
-        pdf_text = extract_text_from_pdf(pdf_file)
-        if pdf_text:
-            combined_message += "\n\n[From PDF]:\n" + pdf_text
-    if image_file:
-        image_text = extract_text_from_image(image_file)
-        if image_text:
-            combined_message += "\n\n[From Image]:\n" + image_text
-
-    if not combined_message.strip():
-        raise ValueError("No valid text extracted from inputs")
-
     # Construct the message history
     messages = [{"role": "system", "content": system_message}]
     for user_msg, assistant_msg in history:
@@ -117,7 +58,7 @@ def respond(
             messages.append({"role": "user", "content": user_msg})
         if assistant_msg:
             messages.append({"role": "assistant", "content": assistant_msg})
-    messages.append({"role": "user", "content": combined_message})
+    messages.append({"role": "user", "content": message})
 
     response = ""
     try:
@@ -137,23 +78,20 @@ def respond(
 
 def main():
     """
-    Sets up and launches the Gradio ChatInterface for the AI Teacher chatbot with PDF and image upload support.
+    Sets up and launches the Gradio ChatInterface for the AI Teacher chatbot.
     """
     # Define default system message for an AI teacher
     default_system_message = (
         "You are an AI Teacher, a knowledgeable and patient educator dedicated to helping students and learners. "
         "Your goal is to explain concepts clearly, provide step-by-step guidance, and encourage critical thinking. "
         "Adapt your explanations to the learner's level, ask follow-up questions to deepen understanding, and provide examples where helpful. "
-        "Be supportive, professional, and engaging in all interactions. "
-        "If provided with text from uploaded PDFs or images, treat it as part of the student's question and respond accordingly."
+        "Be supportive, professional, and engaging in all interactions."
     )
 
-    # Create Gradio ChatInterface with file upload components
+    # Create Gradio ChatInterface with settings compatible with older Gradio versions
     demo = gr.ChatInterface(
         fn=respond,
         additional_inputs=[
-            gr.File(label="Upload PDF", file_types=[".pdf"]),
-            gr.File(label="Upload Image", file_types=[".png", ".jpg", ".jpeg"]),
             gr.Textbox(
                 value=default_system_message,
                 label="AI Teacher Prompt",
@@ -188,8 +126,7 @@ def main():
         title="AI Teacher: Your Study Companion",
         description=(
             "Welcome to AI Teacher, your personal guide for learning and studying! "
-            "Ask questions by typing, or upload a PDF or image containing your question. "
-            "I'll provide clear explanations, examples, and tips to help you succeed. "
+            "Ask questions about any subject, and I'll provide clear explanations, examples, and tips to help you succeed. "
             "Adjust the settings to customize how I respond to your questions."
         ),
         theme="soft",