Update app.py

app.py

@@ -31,7 +31,7 @@ topics = ['AI', 'Tech', 'Business Startups', 'Entrepreneurship']
 def generate_post(topic=None):
     if topic is None:
         topic = random.choice(topics)
-    prompt = f"Generate a high-quality, educational, and informative X (Twitter) post under 270 characters showcasing your expertise in {topic}. Make it engaging, insightful, and professional."
+    prompt = f"Generate a high-quality, educational, and informative X (Twitter) post under 280 characters showcasing expertise in {topic}. Make it engaging, insightful, and professional. Include relevant hashtags if natural."
     response = query({
         "messages": [
             {
@@ -41,24 +41,28 @@ def generate_post(topic=None):
         ],
         "model": "deepseek-ai/DeepSeek-V3.2:novita",
         "max_tokens": 200,
-        "temperature": 0.7
+        "temperature": 0.8
     })
     post_content = response["choices"][0]["message"]["content"].strip()
-    # Ensure under 270 chars
+    # Ensure under 280 chars
     if len(post_content) > 280:
         post_content = post_content[:277] + "..."
     return post_content
 
-# Tweepy setup for X API
-auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
-auth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)
-api = tweepy.API(auth)
+# Tweepy v2 Client setup (for posting tweets)
+client = tweepy.Client(
+    consumer_key=CONSUMER_KEY,
+    consumer_secret=CONSUMER_SECRET,
+    access_token=ACCESS_TOKEN,
+    access_token_secret=ACCESS_SECRET
+)
 
-# Function to post to X
+# Function to post to X (using v2 API)
 def post_to_x(content):
     try:
-        api.update_status(status=content)
-        return f"Posted successfully: {content}"
+        response = client.create_tweet(text=content)
+        tweet_id = response.data['id']
+        return f"Posted successfully! View: https://x.com/user/status/{tweet_id}\n\n{content}"
     except Exception as e:
         return f"Error posting: {str(e)}"
 
@@ -73,13 +77,15 @@ def run_scheduler():
     schedule.every(2).hours.do(auto_post)
     while True:
         schedule.run_pending()
-        time.sleep(60)  # Check every minute
+        time.sleep(60)
 
 # Start scheduler in background
 threading.Thread(target=run_scheduler, daemon=True).start()
 
-# Gradio interface for manual generation and posting
+# Gradio interface
 def manual_generate(topic):
+    if topic == "Random":
+        topic = None
     content = generate_post(topic)
     return content
 
@@ -88,16 +94,16 @@ def manual_post(content):
 
 with gr.Blocks() as demo:
     gr.Markdown("# AI/Tech/Startups/Entrepreneurship X Post Generator")
-    gr.Markdown("Use this interface to manually generate and post high-quality content. Auto-posting runs every 2 hours in the background.")
+    gr.Markdown("Generate and post high-quality content. Auto-posting every 2 hours in background.")
     
     with gr.Row():
-        topic_input = gr.Dropdown(choices=topics + ["Random"], label="Select Topic", value="Random")
+        topic_input = gr.Dropdown(choices=topics + ["Random"], label="Topic", value="Random")
         generate_btn = gr.Button("Generate Post")
     
-    output_text = gr.Textbox(label="Generated Post (under 270 chars)", lines=5)
+    output_text = gr.Textbox(label="Generated Post", lines=6)
     
-    post_btn = gr.Button("Post to X")
-    post_result = gr.Textbox(label="Post Result")
+    post_btn = gr.Button("Post to X Now")
+    post_result = gr.Textbox(label="Result", lines=4)
     
     generate_btn.click(manual_generate, inputs=topic_input, outputs=output_text)
     post_btn.click(manual_post, inputs=output_text, outputs=post_result)