app.py

import torch
import os 
import requests
import spaces 
import gradio as gr 

api_token = os.environ.get("TOKEN")

API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
headers = {"Authorization": f"Bearer {api_token}"}
@spaces.GPU

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

def analyze_sentiment(text):
    prompt = f"<|begin_of_text|><|start_header_id|>system<|end_header_id|>You're a sentiment analyzer. Your role is to evaluate the general feeling of the prompt. Answer only with 'positive' or 'negative'. Don't add any explanations. Here's the text to analyze (don't add any text) : {text}<|eot_id|><|start_header_id|>user<|end_header_id|>"

    output = query({
        "inputs": prompt,
    })

    # Assurez-vous de gérer correctement la sortie de l'API
    if isinstance(output, list) and len(output) > 0:
        return output[0].get('generated_text', 'Erreur: Réponse inattendue')
    else:
        return "Erreur: Réponse inattendue de l'API"

demo = gr.Interface(
    fn = analyze_sentiment,
    inputs=["text"],
    outputs=["text"],
)

demo.launch()