Update post_generator.py

post_generator.py

@@ -1,8 +1,10 @@
+import re  # For handling hashtags
 from llm_helper import llm
 from few_shot import FewShotPosts
 
 few_shot = FewShotPosts()
 
+
 def get_length_str(length):
     if length == "Short":
         return "1 to 5 lines"
@@ -23,17 +25,13 @@ def generate_closing_line(language, tag, tone):
     - Add hashtags only at the end, i.e., after the closing line and not before it.
     - The closing line must encourage engagement or provide a call to action, relevant to the topic.
     - Use the language: "{language}" (Hinglish means Hindi phrases written in English script).
-
     Examples:
     - Topic: "Job Search", Tone: "Motivational", Language: "English"
       Closing Line: "Your dream job is closer than you think. Stay determined! 🚀"
-
     - Topic: "Mental Health", Tone: "Professional", Language: "English"
       Closing Line: "Your mental well-being is essential. Let’s discuss ways to manage stress. 💡"
-
     - Topic: "Dating", Tone: "Informal", Language: "Hinglish"
       Closing Line: "Apka perfect date idea kya hai? Neeche share karein! 😄"
-
     Now, write a relevant closing line for the following inputs:
     Topic: "{tag}"
     Tone: "{tone}"
@@ -43,24 +41,53 @@ def generate_closing_line(language, tag, tone):
     return response.content.strip()
 
 
+def extract_hashtags(content):
+    """
+    Extract all hashtags from the given content.
+    """
+    return re.findall(r"#\w+", content)
+
+
+def remove_hashtags(content):
+    """
+    Remove all hashtags from the given content.
+    """
+    return re.sub(r"#\w+", "", content).strip()
+
+
 def generate_post(length, language, tag, selected_tone=None):
     """
-    Generate a LinkedIn post dynamically with LLM including a generated closing line.
+    Generate a LinkedIn post dynamically with LLM, ensuring hashtags are added only at the end.
     """
+    # Generate the main content
     prompt = get_prompt(length, language, tag)
     response = llm.invoke(prompt)
-    post_content = response.content
+    post_content = response.content.strip()  # Clean up whitespace
+
+    # Extract and remove hashtags from the main content
+    hashtags = extract_hashtags(post_content)
+    post_content = remove_hashtags(post_content)
 
-    # Generate a dynamic closing line using LLM
+    # Generate the closing line
+    closing_line = ""
     if selected_tone and tag:
         try:
             closing_line = generate_closing_line(language, tag, selected_tone)
-            post_content += f"\n\n\n{closing_line}"
+            # Extract and remove hashtags from the closing line
+            hashtags += extract_hashtags(closing_line)
+            closing_line = remove_hashtags(closing_line).strip()
         except Exception as e:
-            # Fallback in case of LLM failure
-            post_content += f"\n\nThank you for reading. Your feedback is valued! 🙌"
+            closing_line = "Thank you for reading. Your feedback is valued! 🙌"
+
+    # Combine the cleaned main content and closing line
+    full_post = f"{post_content}\n\n{closing_line}"
+
+    # Add unique hashtags at the end of the post
+    if hashtags:
+        unique_hashtags = " ".join(set(hashtags))  # Remove duplicates
+        full_post += f"\n\n{unique_hashtags}"
 
-    return post_content
+    return full_post
 
 
 def get_prompt(length, language, tag):
@@ -86,4 +113,4 @@ def get_prompt(length, language, tag):
 
 
 if __name__ == "__main__":
-    print(generate_post("Medium", "English", "Mental Health"))
+    print(generate_post("Medium", "English", "Mental Health"))