| import gradio as gr |
| import requests |
| import os |
| import json |
|
|
| API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" |
|
|
| def translate(user, seed = 42): |
| prompt = f"Instruction: Details: {os.environ['secret_thing']}. Given the following English input sentence translate it into a Spanish sentence. \ninput: {user}" |
| data = { |
| "inputs": prompt, |
| "parameters": { |
| "top_p": 0.9, |
| "temperature": 0.1, |
| "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": False, |
| "wait_for_model": True, |
| }, |
| } |
| response = requests.request("POST", API_URL, json=data) |
| output = json.loads(response.content.decode("utf-8")) |
| output_tmp = output[0]['generated_text'] |
| answer = output_tmp.splitlines() |
| try: |
| return list(filter(lambda x: "output" in x, answer))[0] |
| except IndexError: |
| return ["no entiendo"] |
|
|
| demo = gr.Blocks() |
|
|
| with demo: |
| input_prompt = gr.Textbox(label="Enter the sentence : ", |
| value=f"", |
| lines=6) |
| |
| generated_txt = gr.Textbox(lines=3) |
|
|
| b1 = gr.Button("translate") |
| b1.click(translate,inputs=[input_prompt], outputs=generated_txt) |
| |
| demo.launch(enable_queue=True, debug=False) |
|
|
