app.py

import gradio as gr
import openai
import tiktoken
from multiprocessing.pool import ThreadPool

enc = tiktoken.get_encoding("cl100k_base")

MODES = {
    "Short summary": "Succinctly summarize the following meeting transcript in a single paragraph.",
    "Detailed summary": "Summarize the following meeting transcript. The summary should include all the important points discussed in the meeting.",
    "Action points": "Summarize the following meeting transcript in form of action points.",
    "Further actions": "Who and what should be done next? Summarize the following meeting transcript in form of action points.",
    "Custom": "",
}

def summarize_part(text, api_key, model, topic):
    SUMMARY_PROMPT = f"Summarize the following meeting on {topic} in very great detail. The summary should include all the important points discussed in the meeting."
    response = openai.ChatCompletion.create(
        model=model,
        messages=[
        { "role": "system", "content": f"You are a meeting organizer. You want to summarize a meeting. You are given the following transcript of the meeting. {SUMMARY_PROMPT}" },
        { "role": "user", "content": text },
        ],
        api_key=api_key,
    )
    return response["choices"][0]["message"]["content"]

def shorten_text(text, api_key, model, topic):
    chunks = []
    words = text.split()
    for i in range(0, len(words), 1500):
        chunk = ""
        while len(enc.encode(chunk)) < 4000 and i < len(words):
            chunk += words[i] + " "
            i += 1
        chunks.append(chunk)

    with ThreadPool(4) as pool:
        shortened = pool.starmap(summarize_part, zip(chunks, [api_key]*len(chunks), [model]*len(chunks), [topic]*len(chunks)))
    
    return "".join(shortened)

def modify_text(file, api_key, command, model, topic, custom_command=None):
    text = file.read().decode("utf-8")
    if command == "Custom":
        prompt = custom_command
    else:
        prompt = MODES[command]

    if len(enc.encode(text)) < 4096:
        response = openai.ChatCompletion.create(
            model=model,
            messages=[
            { "role": "system", "content": f"You are a meeting organizer. You want to summarize a meeting on {topic}. You are given the following transcript of the meeting. {prompt}" },
            { "role": "user", "content": text },
            ],
            api_key=api_key,
        )
        return response["choices"][0]["message"]["content"]
    else:
        prompt = prompt.replace("meeting transcript", "meeting parts")
        shortened = text
        while len(enc.encode(shortened)) > 4096:
            shortened = shorten_text(shortened, api_key, model, topic)
        response = openai.ChatCompletion.create(
            model=model,
            messages=[
            { "role": "system", "content": f"You are a meeting organizer. You want to summarize a meeting on {topic}. You are given the following summary of the meeting parts. {prompt}" },
            { "role": "user", "content": shortened },
            ],
            api_key=api_key,
        )
        return response["choices"][0]["message"]["content"]

def show_command(command):
    if command == "Custom":
        return {custom_command: gr.update(visible=True)}
    else:
        return {custom_command: gr.update(visible=False)}

with gr.Blocks() as demo:
    gr.Markdown("# Meeting Summarizer")
    gr.Markdown("#### Short Summary | Detailed Summary | Action points | Further Actions | Custom Command")    
    with gr.Row():
        with gr.Column():
            api_key = gr.Textbox(lines=1,type='password', label="OpenAI API Key")
            file = gr.inputs.File(label="Upload Meeting Transcript")            
            # model = gr.Dropdown(options=['gpt-3.5-turbo', 'gpt-4'], label="OpenAI Model", default='gpt-3.5-turbo')
            model = gr.Dropdown(["gpt-3.5-turbo", "gpt-4"], label="Model", info="OpenAI LLM")
            topic = gr.Textbox(lines=1, label="Meeting Topic")
        with gr.Column():
            command = gr.Dropdown(list(MODES.keys()), label="Command", value="Short summary")
            custom_command = gr.Textbox(lines=2, label="Custom command", visible=False, value="Summarize the following meeting transcript in a single paragraph. The summary should include all the important points discussed in the meeting.")
            output_text = gr.Textbox(lines=10, label="Summary")

    command.change(show_command, command, custom_command)

    button = gr.Button(label="Process")
    button.click(modify_text, [file, api_key, command, model, topic, custom_command], output_text)

demo.title = "Meeting Summarizer-Demo"
demo.launch()