app.py

"""Translate via Bloom."""
# pylint: disable=invalid-name
from textwrap import dedent
from logzero import logger

import gradio as gr
import httpx

# Bloom
api_url = "https://api-inference.huggingface.co/models/bigscience/bloom"
timeout_ = httpx.Timeout(None, connect=10)


def bloom_tr(prompt_, from_lang, to_lang, input_prompt="translate this", seed=2, timeout=timeout_):
    """Translate via Bloom."""
    prompt = dedent(
        f"""
        Instruction : Given an {from_lang} input sentence translate it into {to_lang} sentence. \n input : \"{prompt_}\" \n {to_lang} :
    """
    ).strip()
    if len(prompt) == 0:
        prompt = input_prompt

    json_ = {
        "inputs": prompt,
        "parameters": {
            "top_p": 0.9,
            "temperature": 1.1,
            "max_new_tokens": 250,
            "return_full_text": False,
            "do_sample": False,
            "seed": seed,
            "early_stopping": False,
            "length_penalty": 0.0,
            "eos_token_id": None,
        },
        "options": {
            "use_cache": True,
            "wait_for_model": True,
        },
    }

    # headers=headers
    # response = requests.request("POST", api_url, json=json_)
    try:
        response = httpx.post(api_url, json=json_, timeout=timeout)
    except Exception as exc:
        logger.error(exc)
        return str(exc)

    # output = json.loads(response.content.decode("utf-8"))
    try:
        output = response.json()
    except Exception as exc:
        logger.error(exc)
        return str(exc)

    try:
        output_tmp = output[0]["generated_text"]
    except Exception as exc:
        logger.error(exc)
        return str(exc)

    solution = output_tmp.split(f"\n{to_lang}:")[0]

    if "\n\n" in solution:
        final_solution = solution.split("\n\n")[0]
    else:
        final_solution = solution

    try:
        _ = final_solution.splitlines()[-1]
    except Exception as exc:
        logger.error(exc)
        return str(exc)

    return _


langs = [
    "German",
    "French",
    "Italian",
    "Japanese",
    "Russian"
    "Spanish",
    "Hindi",
]

demo = gr.Blocks()

with demo:
    gr.Markdown("<h1><center>Translate with Bloom</center></h1>")
    gr.Markdown(
        dedent(
            """
            ## Model Details
            Reer to the space created by [Kishore](https://www.linkedin.com/in/kishore-kunisetty-925a3919a/) inorder to participate in [EuroPython22](https://huggingface.co/EuroPython2022)
            please like his project to support his contribution to EuroPython22. 😊
            """
        ).strip()
    )
    with gr.Row():
        from_lang = gr.Dropdown(
            ["English", "Chinese", ] + langs,
            value="English",
            label="select From language : ",
        )
        to_lang = gr.Dropdown(
            ["Chinese", "English", ] + langs,
            value="Hindi",
            label="select to Language : ",
        )

        input_prompt = gr.Textbox(
            label="Enter the sentence : ",
            value=f'Instruction: ... \ninput: "from sentence" \n{to_lang} :',
            lines=6,
        )

    generated_txt = gr.Textbox(lines=7)

    b1 = gr.Button("translate")
    b1.click(
        # translate,
        bloom_tr,
        inputs=[input_prompt, from_lang, to_lang],
        outputs=generated_txt,
    )

demo.launch(enable_queue=True, debug=True)