Update app.py

app.py

@@ -12,19 +12,30 @@ auth = tweepy.OAuth1UserHandler(api_key, api_secret, access_token, access_token_
 api = tweepy.API(auth)
 from gradio_client import Client
 
-client = Client("https://tonic-surerag.hf.space/--replicas/m666j/")
-result = client.predict(
-		"write  a twitter post about marketing",	# str  in 'User Input' Textbox component
-							api_name="/predict"
-)
-print(result)
-cut_text = result[:160]
-print(cut_text)
+# 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/")
 
-clientw.create_tweet(text =result)
-# user_name = "@khaym2002"
-# tweet_id = "troll"
+def generate_and_tweet(query):
+    # Generate text based on the user's query
+    result = model_client.predict(query, api_name="/predict")
+    
+    # Cut the text to fit Twitter's character limit if necessary
+    tweet_text = result[:280]  # Twitter's character limit is 280
+    
+    # Post the generated text to Twitter
+    response = clientw.create_tweet(text=tweet_text)
+    
+    # Return the tweet URL or confirmation
+    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}"
 
-# # Search for replies to the tweet
-# replies = tweepy.Cursor(api.search, q=f"to:{user_name}", since_id=tweet_id, tweet_mode="extended").items()
-# print(replies)
+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()