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c475dd2 b2af2fe 450b759 c475dd2 450b759 c475dd2 450b759 c475dd2 b64f5fb c475dd2 b64f5fb 5697929 b64f5fb 1984678 5697929 1623793 5697929 1623793 5697929 1623793 5697929 1623793 5697929 c475dd2 5697929 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | import tweepy
import os
import gradio as gr
# Directly load the secrets from environment variables
api_key = os.getenv("API_key")
api_secret = os.getenv("API_key_secret")
bearer_token = os.getenv("Bearer_Token")
access_token = os.getenv("Access_Token")
access_token_secret = os.getenv("Access_Token_Secret")
clientw = tweepy.Client(bearer_token, api_key, api_secret, access_token, access_token_secret)
auth = tweepy.OAuth1UserHandler(api_key, api_secret, access_token, access_token_secret)
api = tweepy.API(auth)
from gradio_client import Client
# Assuming you have a Gradio client setup for your model
from gradio_client import Client
model_client = Client("https://tonic-surerag.hf.space/--replicas/m666j/")
def generate_and_tweet(query):
# Generate text based on the user's query
response = model_client.predict(query, api_name="/predict")
# Assuming the response is a dictionary and the generated text is under a key, e.g., 'generated_text'
# Adjust the key as per your model's response structure
if isinstance(response, dict) and 'generated_text' in response:
tweet_text = response['generated_text']
elif isinstance(response, str): # Direct string response
tweet_text = response
else:
return "Error: The model's response was not in the expected format."
# Ensure the tweet text is a string and trim it to Twitter's character limit
tweet_text = str(tweet_text)[:280] # Twitter's character limit is 280
tweet_text = result[:180] # Twitter's character limit is 280
response = clientw.create_tweet(text=tweet_text)
tweet_id = response.data['id']
tweet_url = f"https://twitter.com/user/status/{tweet_id}"
return f"Tweeted successfully! Here's the URL: {tweet_url}"
iface = gr.Interface(
fn=generate_and_tweet,
inputs="text",
outputs="text",
title="Generate and Tweet",
description="Enter your query to generate a Twitter post about it and automatically tweet it."
)
iface.launch()
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