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import gradio as gr
import requests
import os
# Hugging Face Inference API token
HF_TOKEN = os.getenv("HF_TOKEN")
def call_llama(prompt):
headers = {
"Authorization": f"Bearer {HF_TOKEN}",
"Content-Type": "application/json"
}
payload = {
"inputs": prompt,
"parameters": {"max_new_tokens": 500},
}
response = requests.post(
"https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.1",
headers=headers,
json=payload
)
output = response.json()
return output[0]["generated_text"] if isinstance(output, list) else output
def organize_tasks(task_list):
prompt = f"""
You are a helpful assistant that creates a time-blocked schedule from 9AM to 5PM.
Here are today's tasks with durations:
{task_list}
Return a schedule in table format (Time | Task).
"""
return call_llama(prompt)
gr.Interface(
fn=organize_tasks,
inputs=gr.Textbox(label="Enter tasks & durations (one per line)", lines=8, placeholder="e.g.\nWrite report - 90 min\nEmails - 30 min"),
outputs=gr.Textbox(label="Generated Schedule"),
title="🧠 Task Scheduler with LLaMA",
description="Powered by LLaMA via Hugging Face Inference API",
).launch()
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