import time import gradio as gr import os import json import requests #Streaming endpoint API_URL = os.getenv("API_URL") + "/generate_stream" def predict(inputs, top_p, temperature, top_k, repetition_penalty, history=[]): if not inputs.startswith("User: "): inputs = "User: " + inputs + "\n" payload = { "inputs": inputs, #"My name is Jane and I", "parameters": { "details": True, "do_sample": True, "max_new_tokens": 100, "repetition_penalty": repetition_penalty, #1.03, "seed": 0, "temperature": temperature, #0.5, "top_k": top_k, #10, "top_p": top_p #0.95 } } headers = { 'accept': 'text/event-stream', 'Content-Type': 'application/json' } history.append(inputs) # make a POST request to the API endpoint using the requests.post method, passing in stream=True response = requests.post(API_URL, headers=headers, json=payload, stream=True) token_counter = 0 partial_words = "" # loop over the response data using the iter_lines method of the response object for chunk in response.iter_lines(): # check whether each line is non-empty if chunk: # decode each line as response data is in bytes partial_words = partial_words + json.loads(chunk.decode()[5:])['token']['text'] if token_counter == 0: history.append(" " + partial_words) else: history[-1] = partial_words chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list token_counter+=1 yield chat, history #{chatbot: chat, state: history} #[(partial_words, history)] title = """

Streaming your Chatbot output with Gradio

""" description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form: ``` User: Assistant: User: Assistant: ... ``` In this app, you can explore the outputs of a 20B large language model. """ with gr.Blocks(css = """#col_container {width: 700px; margin-left: auto; margin-right: auto;} "#chatbot {height: 400px; overflow: auto;}""") as demo: gr.HTML(title) with gr.Column(elem_id = "col_container"): chatbot = gr.Chatbot(elem_id='chatbot') #c inputs = gr.Textbox(placeholder= "Hi my name is Joe.", label= "Type an input and press Enter") #t state = gr.State([]) #s b1 = gr.Button() #inputs, top_p, temperature, top_k, repetition_penalty with gr.Accordion("Parameters", open=False): top_p = gr.Slider( minimum=-0, maximum=1.0, value=0.95, step=0.05, interactive=True, label="Top-p (nucleus sampling)",) temperature = gr.Slider( minimum=-0, maximum=5.0, value=0.5, step=0.1, interactive=True, label="Temperature",) top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",) repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", ) #b1.click(predict, [t,s], [c,s]) #inputs.submit(predict, [t,s], [c,s]) inputs.submit( predict, [inputs, top_p, temperature, top_k, repetition_penalty, state], [chatbot, state],) b1.click( predict, [inputs, top_p, temperature, top_k, repetition_penalty, state], [chatbot, state],) gr.Markdown(description) demo.queue().launch(debug=True)