app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import random
from datetime import datetime
from PyPDF2 import PdfReader
import json
from transformers import AutoModelForCausalLM, AutoTokenizer

# Replace 'username/your_model_name' with your Hugging Face model name
model_name = "username/your_model_name"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

def generate_tweet(prompt):
    # Tokenize the input
    inputs = tokenizer(prompt, return_tensors="pt")
    
    # Generate text using the model
    outputs = model.generate(
        inputs["input_ids"], 
        max_length=280,  # Limit tweets to 280 characters
        num_return_sequences=1,  # Number of tweets to generate
        top_k=50,  # Sampling from top k tokens
        top_p=0.95,  # Sampling from top p cumulative probability
        temperature=0.7,  # Adjust creativity
        do_sample=True,  # Enable sampling
    )
    
    # Decode the generated text
    tweet = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return tweet

interface = gr.Interface(
    fn=generate_tweet,  # The function to call
    inputs="text",      # User input is a single text box
    outputs="text",     # Output is text
    title="AI Tweet Generator",
    description="Enter a topic or a few words, and the AI will generate a creative tweet!"
)

# Launch the app
interface.launch()