app.py

import gradio as gr
from openai import OpenAI
import os
from io import BytesIO
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
from docx import Document

# Custom CSS
css = '''
.gradio-container{max-width: 1000px !important}
h1{text-align:center}
footer {
    visibility: hidden
}
'''

# Set up OpenAI client
ACCESS_TOKEN = os.getenv("HF_TOKEN")

client = OpenAI(
    base_url="https://api-inference.huggingface.co/v1/",
    api_key=ACCESS_TOKEN,
)

# Function to handle chat responses
def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""
    
    for message in client.chat.completions.create(
        model="meta-llama/Meta-Llama-3.1-8B-Instruct",
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
        messages=messages,
    ):
        token = message.choices[0].delta.content
        response += token
        yield response

# Function to save chat history to a text file
def save_as_txt(history):
    file_path = "chat_history.txt"
    with open(file_path, "w") as f:
        for user_message, assistant_message in history:
            f.write(f"User: {user_message}\n")
            f.write(f"Assistant: {assistant_message}\n")
    return file_path

# Function to save chat history to a DOCX file
def save_as_docx(history):
    file_path = "chat_history.docx"
    doc = Document()
    doc.add_heading('Chat History', 0)
    
    for user_message, assistant_message in history:
        doc.add_paragraph(f"User: {user_message}")
        doc.add_paragraph(f"Assistant: {assistant_message}")
    
    doc.save(file_path)
    return file_path

# Function to save chat history to a PDF file
def save_as_pdf(history):
    file_path = "chat_history.pdf"
    buffer = BytesIO()
    c = canvas.Canvas(buffer, pagesize=letter)
    width, height = letter
    y = height - 40
    
    c.drawString(30, y, "Chat History")
    y -= 30
    
    for user_message, assistant_message in history:
        c.drawString(30, y, f"User: {user_message}")
        y -= 20
        c.drawString(30, y, f"Assistant: {assistant_message}")
        y -= 30
        
        if y < 40:
            c.showPage()
            y = height - 40
            
    c.save()
    buffer.seek(0)
    
    with open(file_path, "wb") as f:
        f.write(buffer.read())
    
    return file_path

# Function to handle file saving based on format
def handle_file_save(history, file_format):
    if file_format == "txt":
        return save_as_txt(history)
    elif file_format == "docx":
        return save_as_docx(history)
    elif file_format == "pdf":
        return save_as_pdf(history)
    return None

# Handler function for Gradio app
def save_handler(message, history, system_message, max_tokens, temperature, top_p, file_format):
    response = respond(message, history, system_message, max_tokens, temperature, top_p)
    saved_file = handle_file_save(history, file_format)
    return saved_file

# Gradio interface
demo = gr.Interface(
    fn=save_handler,
    inputs=[
        gr.Textbox(value="", label="Message"),
        gr.State(),
        gr.Textbox(value="", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-P",
        ),
        gr.Dropdown(
            choices=["txt", "docx", "pdf"],
            label="Save as",
        ),
    ],
    outputs=gr.File(label="Download Chat History"),
    css=css,
    theme="allenai/gradio-theme",
)

if __name__ == "__main__":
    demo.launch()