Delete app.py

app.py

@@ -1,129 +0,0 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-from PyPDF2 import PdfReader
-
-# Initialize the Inference Client
-client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    uploaded_pdf=None
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    # Add previous conversation history to the messages
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    # If a new message is entered, add it to the conversation history
-    messages.append({"role": "user", "content": message})
-
-    # If a PDF is uploaded, process its content
-    if uploaded_pdf is not None:
-        file_content = extract_pdf_text(uploaded_pdf)
-        if file_content:
-            messages.append({"role": "user", "content": f"Document Content: {file_content}"})
-
-    # Get response from the model
-    response = ""
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-
-
-def extract_pdf_text(file):
-    """Extract text from a PDF file."""
-    try:
-        reader = PdfReader(file)
-        text = ""
-        for page in reader.pages:
-            text += page.extract_text()
-        return text
-    except Exception as e:
-        return f"Error extracting text from PDF: {str(e)}"
-
-
-# CSS for styling the interface
-css = """
-body {
-    background-color: #1e2a38; /* Dark blue background */
-    color: #ffffff; /* White text for readability */
-    font-family: 'Arial', sans-serif; /* Clean and modern font */
-}
-.gr-button {
-    background-color: #42B3CE !important; /* Light blue button */
-    color: #2e3b4e !important; /* Dark text for contrast */
-    border: none !important;
-    padding: 10px 20px !important;
-    border-radius: 8px !important;
-    font-size: 16px;
-    font-weight: bold;
-    transition: background-color 0.3s ease, transform 0.2s ease;
-}
-.gr-button:hover {
-    background-color: #3189A2 !important; /* Darker blue on hover */
-    transform: scale(1.05);
-}
-.gr-button:active {
-    background-color: #267b88 !important; /* Even darker when clicked */
-}
-.gr-slider-container {
-    color: white !important; /* White slider labels */
-    font-size: 14px;
-}
-.gr-slider {
-    background-color: #0b2545 !important; /* Slider track color */
-    border-radius: 8px;
-}
-.gr-slider .gr-slider-active {
-    background-color: #42B3CE !important; /* Active slider color */
-}
-.gr-textbox input {
-    background-color: #2f3b4d;
-    color: white;
-    border: 2px solid #42B3CE;
-    padding: 12px;
-    border-radius: 8px;
-    font-size: 16px;
-    transition: border 0.3s ease;
-}
-.gr-textbox input:focus {
-    border-color: #3189A2;
-}
-"""
-
-# Gradio interface
-demo = gr.Interface(
-    fn=respond,
-    inputs=[
-        gr.Textbox(label="Your Message", placeholder="Type your question here...", lines=4),
-        gr.File(label="Upload a PDF", file_count="single", type="file"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens", visible=False),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature", visible=False),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)", visible=False),
-    ],
-    outputs="text",
-    css=css,  # Custom CSS
-    live=True,
-    title="Health Assistant Chat",
-    description="This is a health assistant that can chat with you about health-related topics. You can also upload a document for analysis.",
-)
-
-if __name__ == "__main__":
-    demo.launch(share=True)