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import streamlit as st
from few_shot import FewShotPosts
from post_generator import generate_post
import json
# Improved app with more functionality
def main():
st.set_page_config(page_title="LinkedIn Post Generator", layout="wide")
st.title("🚀 LinkedIn Post Generator")
st.markdown(
"""
**Create impactful LinkedIn posts effortlessly.**
Customize your post with advanced options, analyze generated content, and save your creations.
"""
)
# Sidebar for advanced options
st.sidebar.title("🔧 Customization Options")
st.sidebar.markdown("Use these settings to personalize your generated post.")
fs = FewShotPosts()
tags = fs.get_tags()
# User input sections
st.sidebar.subheader("Post Preferences")
selected_tag = st.sidebar.selectbox("Topic (Tag):", options=tags)
selected_length = st.sidebar.radio("Post Length:", ["Short", "Medium", "Long"])
selected_language = st.sidebar.radio("Language:", ["English", "Hinglish"])
selected_tone = st.sidebar.selectbox(
"Tone/Style:", ["Motivational", "Professional", "Informal", "Neutral"]
)
custom_context = st.sidebar.text_area(
"Additional Context (Optional):",
placeholder="Provide extra details or a specific direction for your post...",
)
# History tracking
if "generated_posts" not in st.session_state:
st.session_state.generated_posts = []
# Main content
st.subheader("Generate Your LinkedIn Post")
if st.button("Generate Post"):
with st.spinner("Generating your post..."):
try:
# Generate post
post = generate_post(selected_length, selected_language, selected_tag)
# Add tone and context to the prompt dynamically
if selected_tone:
post = f"**Tone**: {selected_tone}\n\n{post}"
if custom_context:
post += f"\n\n**Context Added**: {custom_context}"
# Save to session history
st.session_state.generated_posts.append(post)
st.success("Post generated successfully!")
st.markdown("### Your LinkedIn Post:")
st.write(post)
# Post analysis
st.markdown("### Post Analysis:")
post_analysis(post)
except Exception as e:
st.error(f"An error occurred: {e}")
# Display session history
if st.session_state.generated_posts:
st.markdown("### Generated Posts History:")
for i, history_post in enumerate(st.session_state.generated_posts):
st.markdown(f"**Post {i + 1}:**")
st.write(history_post)
# Save and Download
st.markdown("---")
st.subheader("Save or Share Your Post")
if st.session_state.generated_posts:
if st.button("Download All Posts"):
download_posts(st.session_state.generated_posts)
if st.button("Clear History"):
st.session_state.generated_posts = []
st.info("History cleared!")
# Footer
st.markdown(
"""
---
📝 *Powered by OpenAI's ChatGroq and LangChain.*
📧 For feedback, contact: [support@example.com](mailto:support@example.com)
"""
)
def post_analysis(post):
"""Perform basic analysis of the generated post."""
word_count = len(post.split())
char_count = len(post)
tone_keywords = {
"Motivational": ["inspire", "achieve", "goal", "success"],
"Professional": ["expertise", "career", "opportunity", "industry"],
"Informal": ["hey", "cool", "fun", "awesome"],
}
st.write(f"**Word Count:** {word_count}")
st.write(f"**Character Count:** {char_count}")
# Detect tone based on keywords (simple heuristic)
detected_tone = "Neutral"
for tone, keywords in tone_keywords.items():
if any(keyword in post.lower() for keyword in keywords):
detected_tone = tone
break
st.write(f"**Detected Tone:** {detected_tone}")
def download_posts(posts):
"""Allow users to download their posts."""
posts_json = json.dumps(posts, indent=4)
st.download_button(
label="📥 Download Posts",
data=posts_json,
file_name="generated_posts.json",
mime="application/json",
)
# Run the app
if __name__ == "__main__":
main()
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