app4.py

import gradio as gr
import os
import time
import requests
import base64

import pymongo
import certifi


token = '5UAYO8UWHNQKT3UUS9H8V360L76MD72DRIUY9QC2'

# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.

uri = "mongodb+srv://clementrof:[email protected]/?retryWrites=true&w=majority"

# Create a new client and connect to the server
client = pymongo.MongoClient(uri, tlsCAFile=certifi.where())

# Send a ping to confirm a successful connection
try:
    client.admin.command('ping')
    print("Pinged your deployment. You successfully connected to MongoDB!")
except Exception as e:
    print(e)

# Access your database
db = client.get_database('camila')
records = db.info


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#########################################

def LLM_call(message_log):

    serverless_api_id = '4whzcbwuriohqh'
    # Define the URL you want to send the request to
    url = f"https://api.runpod.ai/v2/{serverless_api_id}/run"

    # Define your custom headers
    headers = {
        "Authorization": f"Bearer {token}",
        "Accept": "application/json",
        "Content-Type": "application/json"
    }

       

    # Define your data (this could also be a JSON payload)
    data = {

        "input": {
                "prompt": message_log,
                "max_new_tokens": 4500,
                "temperature": 0.7,
                "top_k": 50,
                "top_p": 0.9,
                "repetition_penalty": 1.2,
                "batch_size": 8,
                "stop": ["</s>"]
            }
    }
   
    


    # Send the POST request with headers and data
    call = requests.post(url, headers=headers, json=data)
    response_data = call.json()
    msg_id = response_data['id']
    print("Message ID:", msg_id)
    output = "Output not available"
    # Poll the API until the response is ready
    while True:
        # Get the status using the message ID
        response = requests.get(f"https://api.runpod.ai/v2/{serverless_api_id}/status/{msg_id}", headers=headers)

        if response.status_code == 200:
            response_data = response.json()
            status = response_data.get('status')

            if status == 'COMPLETED':
                # Access the 'output' directly from the response
                output = response_data.get('output', 'Output not available')
                print("Response content:", output)
                break  # Exit the loop once the response is ready
            elif status == 'FAILED':
                error_message = response_data.get('error', 'Unknown error')
                print("Request failed. Reason:", error_message)
                break  # Exit the loop if the request failed
        else:
            print("Failed to get status. HTTP status code:", response.status_code)

        # Wait for a short time before polling again (e.g., 2 seconds)
        time.sleep(2)
    
    return output

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def print_like_dislike(x: gr.LikeData):
    print(x.index, x.value, x.liked)


# def add_text(history, text):
#     history = history + [(text, None)]
#     return history, gr.Textbox(value="", interactive=False)
    
def add_text(history, text):
    history = history + [((text[0], None),)]  # Make sure to put the tuple inside a list
    return history, gr.Textbox(value="", interactive=False)



def add_file(history, file):
    history = history + [((file.name,), None)]
    return history

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def bot(history):
    ID=2
    existing_user_doc = records.find_one({'ID': ID})
    if existing_user_doc:
        message_log = [{"role": "system", "content": f"I want you to act as a woman named Julie. Use colloquial language. Julie is 25 years old, she is very hot physically, she loves watching football, she loves to talk about sex. Julie loves sex and being fucked. She never refuses anything. You'll answer to a man, call him baby. Write very short answers, 15 words."},
        ]
        messages = existing_user_doc['message']
        if len(messages)>5:
            messages = messages[-5:]

        message_log.extend(messages)
        print (history)
        new_message = {"role": "user", "content": history}
        message_log.append(new_message)
            

        response = LLM_call(message_log)

    else:
        new_user_doc = {
            'ID': ID,
            'message': []
        }
        records.insert_one(new_user_doc)
        response = "Hello"

    history[-1][1] = ""
    for character in response:
        history[-1][1] += character
        time.sleep(0.05)
        yield history


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with gr.Blocks() as demo:
    chatbot = gr.Chatbot(
        [],
        elem_id="chatbot",
        bubble_full_width=False,
        avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.jpg"))),
    )

    with gr.Row():
        txt = gr.Textbox(
            scale=4,
            show_label=False,
            placeholder="Enter text and press enter, or upload an image",
            container=False,
        )
        btn = gr.UploadButton("📁", file_types=["image", "video", "audio"])

    txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
        bot, chatbot, chatbot, api_name="bot_response"
    )
    txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
    file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then(
        bot, chatbot, chatbot
    )

    chatbot.like(print_like_dislike, None, None)


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