Getting the twitter dashboard working.
This commit is contained in:
ajaysi
@@ -1,342 +1,211 @@
|
||||
import streamlit as st
|
||||
import re
|
||||
import streamlit.components.v1 as components
|
||||
from typing import Dict, List
|
||||
import json
|
||||
import time
|
||||
from typing import Dict, List, Tuple, Optional
|
||||
import random
|
||||
import emoji
|
||||
from datetime import datetime
|
||||
|
||||
from ....gpt_providers.text_generation.main_text_generation import llm_text_gen
|
||||
from .tweet_generator import smart_tweet_generator
|
||||
|
||||
# Constants
|
||||
MAX_TWEET_LENGTH = 280
|
||||
EMOJI_CATEGORIES = {
|
||||
"Humorous": ["😄", "😂", "🤣", "😊", "😉", "😎", "🤪", "😜", "🤓", "😇"],
|
||||
"Informative": ["📚", "📊", "📈", "🔍", "💡", "📝", "📋", "🔎", "📖", "📑"],
|
||||
"Inspirational": ["✨", "🌟", "💫", "⭐", "🔥", "💪", "🙌", "👏", "💯", "🎯"],
|
||||
"Serious": ["🤔", "💭", "🧐", "📢", "🔔", "⚖️", "🎓", "📊", "🔬", "📰"],
|
||||
"Casual": ["👋", "👍", "🙋", "💁", "🤗", "👌", "✌️", "🤝", "👊", "🙏"]
|
||||
}
|
||||
|
||||
def count_characters(text: str) -> int:
|
||||
"""Count characters in tweet, accounting for emojis."""
|
||||
return len(text)
|
||||
|
||||
def extract_hashtags(text: str) -> List[str]:
|
||||
"""Extract hashtags from tweet text."""
|
||||
return re.findall(r'#\w+', text)
|
||||
|
||||
def suggest_hashtags(topic: str, tone: str) -> List[str]:
|
||||
"""Suggest relevant hashtags based on topic and tone."""
|
||||
# Enhanced hashtag suggestions based on topic and tone
|
||||
base_hashtags = {
|
||||
"professional": ["#Business", "#Leadership", "#Innovation"],
|
||||
"casual": ["#Life", "#Fun", "#Trending"],
|
||||
"informative": ["#Learn", "#Tips", "#HowTo"],
|
||||
"humorous": ["#Funny", "#LOL", "#Humor"],
|
||||
"inspirational": ["#Motivation", "#Success", "#Growth"]
|
||||
}
|
||||
|
||||
topic_hashtags = {
|
||||
"tech": ["#Technology", "#TechNews", "#Innovation"],
|
||||
"business": ["#Business", "#Entrepreneurship", "#Startup"],
|
||||
"marketing": ["#Marketing", "#DigitalMarketing", "#SocialMedia"],
|
||||
"education": ["#Education", "#Learning", "#Knowledge"],
|
||||
"health": ["#Health", "#Wellness", "#Fitness"]
|
||||
}
|
||||
|
||||
# Combine base and topic hashtags
|
||||
suggested = base_hashtags.get(tone.lower(), []) + topic_hashtags.get(topic.lower(), [])
|
||||
return list(set(suggested))[:5] # Return unique hashtags, max 5
|
||||
|
||||
def suggest_emojis(tone: str, count: int = 3) -> List[str]:
|
||||
"""Suggest emojis based on tone."""
|
||||
emoji_map = {
|
||||
"professional": ["💼", "📊", "🎯", "💡", "📈"],
|
||||
"casual": ["😊", "👍", "🙌", "✨", "🌟"],
|
||||
"informative": ["📚", "🔍", "💡", "📝", "🎓"],
|
||||
"humorous": ["😄", "😂", "🤣", "😉", "😎"],
|
||||
"inspirational": ["✨", "🌟", "💫", "🔥", "💪"]
|
||||
}
|
||||
return emoji_map.get(tone.lower(), ["✨"])[:count]
|
||||
|
||||
def predict_tweet_performance(tweet: str, target_audience: str, tone: str) -> Dict:
|
||||
"""Predict tweet performance with enhanced metrics."""
|
||||
char_count = count_characters(tweet)
|
||||
hashtags = extract_hashtags(tweet)
|
||||
|
||||
# Enhanced performance metrics
|
||||
metrics = {
|
||||
"character_count": {
|
||||
"score": min(100, (char_count / 280) * 100),
|
||||
"status": "optimal" if 100 <= char_count <= 200 else "suboptimal",
|
||||
"suggestion": "Consider adjusting length for optimal engagement" if char_count < 100 or char_count > 200 else "Length is optimal"
|
||||
},
|
||||
"hashtag_usage": {
|
||||
"score": min(100, (len(hashtags) / 3) * 100),
|
||||
"status": "optimal" if 1 <= len(hashtags) <= 3 else "suboptimal",
|
||||
"suggestion": "Add more hashtags" if len(hashtags) < 1 else "Reduce hashtag count" if len(hashtags) > 3 else "Hashtag count is optimal"
|
||||
},
|
||||
"engagement_potential": {
|
||||
"score": 0,
|
||||
"status": "needs_improvement",
|
||||
"suggestion": ""
|
||||
},
|
||||
"audience_alignment": {
|
||||
"score": 0,
|
||||
"status": "needs_improvement",
|
||||
"suggestion": ""
|
||||
}
|
||||
}
|
||||
|
||||
# Calculate engagement potential
|
||||
engagement_triggers = ["?", "!", "RT", "like", "follow", "check", "learn", "discover"]
|
||||
trigger_count = sum(1 for trigger in engagement_triggers if trigger.lower() in tweet.lower())
|
||||
metrics["engagement_potential"]["score"] = min(100, (trigger_count / 3) * 100)
|
||||
metrics["engagement_potential"]["status"] = "optimal" if trigger_count >= 1 else "needs_improvement"
|
||||
metrics["engagement_potential"]["suggestion"] = "Add engagement triggers" if trigger_count < 1 else "Good engagement potential"
|
||||
|
||||
# Calculate audience alignment
|
||||
audience_keywords = {
|
||||
"professionals": ["business", "industry", "professional", "career"],
|
||||
"students": ["learn", "study", "education", "student"],
|
||||
"general": ["everyone", "people", "community", "world"]
|
||||
}
|
||||
keyword_count = sum(1 for keyword in audience_keywords.get(target_audience.lower(), [])
|
||||
if keyword.lower() in tweet.lower())
|
||||
metrics["audience_alignment"]["score"] = min(100, (keyword_count / 2) * 100)
|
||||
metrics["audience_alignment"]["status"] = "optimal" if keyword_count >= 1 else "needs_improvement"
|
||||
metrics["audience_alignment"]["suggestion"] = "Add audience-specific keywords" if keyword_count < 1 else "Good audience alignment"
|
||||
|
||||
# Calculate overall score
|
||||
overall_score = sum(metric["score"] for metric in metrics.values()) / len(metrics)
|
||||
|
||||
def load_feature_data() -> Dict:
|
||||
"""Load feature data from a structured format."""
|
||||
return {
|
||||
"metrics": metrics,
|
||||
"overall_score": overall_score,
|
||||
"status": "excellent" if overall_score >= 80 else "good" if overall_score >= 60 else "fair" if overall_score >= 40 else "needs_improvement"
|
||||
"tweet_generation": {
|
||||
"title": "Tweet Generation & Optimization",
|
||||
"icon": "🐦",
|
||||
"description": "Create and optimize engaging tweets with AI assistance",
|
||||
"features": [
|
||||
{
|
||||
"name": "Smart Tweet Generator",
|
||||
"description": "Generate multiple tweet variations with optimal character count, hashtags, and emojis",
|
||||
"status": "active",
|
||||
"icon": "✨",
|
||||
"function": smart_tweet_generator
|
||||
},
|
||||
{
|
||||
"name": "Tweet Performance Predictor",
|
||||
"description": "Predict engagement rates and best posting times for maximum impact",
|
||||
"status": "coming_soon",
|
||||
"icon": "📊"
|
||||
}
|
||||
]
|
||||
},
|
||||
"content_strategy": {
|
||||
"title": "Content Strategy Tools",
|
||||
"icon": "📅",
|
||||
"description": "Plan and manage your Twitter content strategy effectively",
|
||||
"features": [
|
||||
{
|
||||
"name": "Content Calendar Generator",
|
||||
"description": "Create weekly/monthly content plans with theme-based scheduling",
|
||||
"status": "coming_soon",
|
||||
"icon": "🗓️"
|
||||
},
|
||||
{
|
||||
"name": "Hashtag Strategy Manager",
|
||||
"description": "Research and manage trending hashtags for better reach",
|
||||
"status": "coming_soon",
|
||||
"icon": "#️⃣"
|
||||
}
|
||||
]
|
||||
},
|
||||
"visual_content": {
|
||||
"title": "Visual Content Creation",
|
||||
"icon": "🎨",
|
||||
"description": "Create engaging visual content for your tweets",
|
||||
"features": [
|
||||
{
|
||||
"name": "Image Generator",
|
||||
"description": "Create tweet cards, infographics, and quote designs",
|
||||
"status": "coming_soon",
|
||||
"icon": "🖼️"
|
||||
},
|
||||
{
|
||||
"name": "Video Content Assistant",
|
||||
"description": "Generate video scripts and optimize captions",
|
||||
"status": "coming_soon",
|
||||
"icon": "🎥"
|
||||
}
|
||||
]
|
||||
},
|
||||
"engagement": {
|
||||
"title": "Engagement & Community",
|
||||
"icon": "🤝",
|
||||
"description": "Manage and enhance community engagement",
|
||||
"features": [
|
||||
{
|
||||
"name": "Reply Generator",
|
||||
"description": "Generate context-aware responses with appropriate tone",
|
||||
"status": "coming_soon",
|
||||
"icon": "💬"
|
||||
},
|
||||
{
|
||||
"name": "Community Tools",
|
||||
"description": "Create polls and plan Q&A sessions",
|
||||
"status": "coming_soon",
|
||||
"icon": "👥"
|
||||
}
|
||||
]
|
||||
},
|
||||
"analytics": {
|
||||
"title": "Analytics & Optimization",
|
||||
"icon": "📈",
|
||||
"description": "Track performance and optimize your Twitter strategy",
|
||||
"features": [
|
||||
{
|
||||
"name": "Performance Analytics",
|
||||
"description": "Track tweet performance and engagement metrics",
|
||||
"status": "coming_soon",
|
||||
"icon": "📊"
|
||||
},
|
||||
{
|
||||
"name": "A/B Testing Assistant",
|
||||
"description": "Test and optimize tweet variations for better results",
|
||||
"status": "coming_soon",
|
||||
"icon": "🔍"
|
||||
}
|
||||
]
|
||||
},
|
||||
"research": {
|
||||
"title": "Research & Intelligence",
|
||||
"icon": "🔎",
|
||||
"description": "Gain insights and stay ahead of trends",
|
||||
"features": [
|
||||
{
|
||||
"name": "Market Research",
|
||||
"description": "Analyze competitors and track industry trends",
|
||||
"status": "coming_soon",
|
||||
"icon": "📊"
|
||||
},
|
||||
{
|
||||
"name": "Content Inspiration",
|
||||
"description": "Get trending topic suggestions and content ideas",
|
||||
"status": "coming_soon",
|
||||
"icon": "💡"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
def generate_tweet_variations(
|
||||
hook: str,
|
||||
target_audience: str,
|
||||
tone: str,
|
||||
call_to_action: str = "",
|
||||
keywords: str = "",
|
||||
length: str = "medium",
|
||||
num_variations: int = 3
|
||||
) -> List[Dict]:
|
||||
"""Generate multiple tweet variations with enhanced AI suggestions."""
|
||||
# Enhanced prompt template for better AI suggestions
|
||||
prompt_template = f"""
|
||||
Create {num_variations} engaging tweet variations with the following parameters:
|
||||
- Hook/Topic: {hook}
|
||||
- Target Audience: {target_audience}
|
||||
- Tone: {tone}
|
||||
- Call to Action: {call_to_action}
|
||||
- Keywords: {keywords}
|
||||
- Length: {length}
|
||||
|
||||
Each tweet should:
|
||||
1. Start with an attention-grabbing hook
|
||||
2. Include relevant hashtags
|
||||
3. Use appropriate emojis
|
||||
4. End with a clear call-to-action
|
||||
5. Stay within Twitter's character limit
|
||||
6. Match the specified tone and audience
|
||||
|
||||
Format each tweet as a JSON object with:
|
||||
- text: The tweet content
|
||||
- hashtags: List of suggested hashtags
|
||||
- emojis: List of suggested emojis
|
||||
- engagement_score: Predicted engagement score (0-100)
|
||||
"""
|
||||
|
||||
# Simulate AI-generated tweets (replace with actual AI call)
|
||||
sample_tweets = [
|
||||
{
|
||||
"text": f"🚀 {hook} #Innovation #Tech",
|
||||
"hashtags": ["#Innovation", "#Tech"],
|
||||
"emojis": ["🚀"],
|
||||
"engagement_score": 85
|
||||
},
|
||||
{
|
||||
"text": f"💡 {hook} #Business #Growth",
|
||||
"hashtags": ["#Business", "#Growth"],
|
||||
"emojis": ["💡"],
|
||||
"engagement_score": 75
|
||||
},
|
||||
{
|
||||
"text": f"✨ {hook} #Success #Leadership",
|
||||
"hashtags": ["#Success", "#Leadership"],
|
||||
"emojis": ["✨"],
|
||||
"engagement_score": 80
|
||||
}
|
||||
]
|
||||
|
||||
return sample_tweets[:num_variations]
|
||||
|
||||
def suggest_improvements(tweet: str, performance: Dict) -> List[str]:
|
||||
"""Generate actionable improvement suggestions."""
|
||||
suggestions = []
|
||||
metrics = performance["metrics"]
|
||||
|
||||
# Character count suggestions
|
||||
if metrics["character_count"]["status"] == "suboptimal":
|
||||
suggestions.append(f"📝 {metrics['character_count']['suggestion']}")
|
||||
|
||||
# Hashtag suggestions
|
||||
if metrics["hashtag_usage"]["status"] == "suboptimal":
|
||||
suggestions.append(f"#️⃣ {metrics['hashtag_usage']['suggestion']}")
|
||||
|
||||
# Engagement suggestions
|
||||
if metrics["engagement_potential"]["status"] == "needs_improvement":
|
||||
suggestions.append(f"🎯 {metrics['engagement_potential']['suggestion']}")
|
||||
|
||||
# Audience alignment suggestions
|
||||
if metrics["audience_alignment"]["status"] == "needs_improvement":
|
||||
suggestions.append(f"👥 {metrics['audience_alignment']['suggestion']}")
|
||||
|
||||
return suggestions
|
||||
|
||||
def render_tweet_card(tweet: Dict, index: int) -> None:
|
||||
"""Render an enhanced tweet card with interactive elements."""
|
||||
def render_feature_card(feature: Dict) -> None:
|
||||
"""Render a single feature card with its details."""
|
||||
with st.container():
|
||||
st.markdown(f"""
|
||||
<div style='padding: 20px; border-radius: 10px; background-color: #f0f2f6; margin-bottom: 20px;'>
|
||||
<h3 style='margin: 0;'>Tweet Variation {index + 1}</h3>
|
||||
<p style='margin: 10px 0;'>{tweet['text']}</p>
|
||||
<div style='display: flex; gap: 10px;'>
|
||||
<span style='background-color: #e1e4e8; padding: 5px 10px; border-radius: 15px; font-size: 0.8em;'>
|
||||
Score: {tweet['engagement_score']}%
|
||||
</span>
|
||||
</div>
|
||||
<h3 style='margin: 0;'>{feature['icon']} {feature['name']}</h3>
|
||||
<p style='margin: 10px 0;'>{feature['description']}</p>
|
||||
<span style='background-color: {'#4CAF50' if feature['status'] == 'active' else '#ffd700'};
|
||||
padding: 5px 10px; border-radius: 15px; font-size: 0.8em;'>
|
||||
{feature['status'].title()}
|
||||
</span>
|
||||
</div>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
# Interactive elements
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
if st.button(f"Copy Tweet {index + 1}", key=f"copy_{index}"):
|
||||
st.write("Tweet copied to clipboard!")
|
||||
with col2:
|
||||
if st.button(f"Save Tweet {index + 1}", key=f"save_{index}"):
|
||||
st.write("Tweet saved!")
|
||||
|
||||
def smart_tweet_generator():
|
||||
"""Enhanced Smart Tweet Generator with improved UI and AI integration."""
|
||||
st.title("✨ Smart Tweet Generator")
|
||||
st.markdown("Create engaging tweets with AI-powered optimization")
|
||||
def render_category_section(category: Dict) -> None:
|
||||
"""Render a category section with all its features."""
|
||||
st.markdown(f"### {category['icon']} {category['title']}")
|
||||
st.markdown(f"*{category['description']}*")
|
||||
|
||||
# Input section with improved UI
|
||||
with st.expander("Tweet Parameters", expanded=True):
|
||||
col1, col2 = st.columns(2)
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
render_feature_card(category['features'][0])
|
||||
with col2:
|
||||
render_feature_card(category['features'][1])
|
||||
|
||||
def run_dashboard():
|
||||
"""Main function to run the Twitter dashboard."""
|
||||
# Header
|
||||
st.title("🐦 Twitter AI Writer Dashboard")
|
||||
st.markdown("""
|
||||
Welcome to your all-in-one Twitter content creation and management platform.
|
||||
Explore our AI-powered tools to enhance your Twitter marketing strategy.
|
||||
""")
|
||||
|
||||
# Load feature data
|
||||
features = load_feature_data()
|
||||
|
||||
# Create tabs for different sections
|
||||
tab1, tab2, tab3 = st.tabs(["🎯 Quick Actions", "📊 Analytics", "⚙️ Settings"])
|
||||
|
||||
with tab1:
|
||||
st.markdown("### 🚀 Quick Actions")
|
||||
col1, col2, col3 = st.columns(3)
|
||||
|
||||
with col1:
|
||||
hook = st.text_area("Tweet Hook/Topic",
|
||||
placeholder="Enter your main message or topic...",
|
||||
help="The main message or topic of your tweet")
|
||||
|
||||
target_audience = st.selectbox(
|
||||
"Target Audience",
|
||||
["Professionals", "Students", "General"],
|
||||
help="Select your target audience"
|
||||
)
|
||||
|
||||
tone = st.radio(
|
||||
"Tweet Tone",
|
||||
["Professional", "Casual", "Informative", "Humorous", "Inspirational"],
|
||||
horizontal=True,
|
||||
help="Choose the tone for your tweet"
|
||||
)
|
||||
|
||||
if st.button("📝 Create New Tweet", use_container_width=True):
|
||||
# Call the Smart Tweet Generator
|
||||
smart_tweet_generator()
|
||||
with col2:
|
||||
call_to_action = st.text_input(
|
||||
"Call to Action",
|
||||
placeholder="e.g., Learn more, Follow us...",
|
||||
help="What action do you want your audience to take?"
|
||||
)
|
||||
|
||||
keywords = st.text_input(
|
||||
"Keywords/Hashtags",
|
||||
placeholder="Enter keywords separated by commas",
|
||||
help="Keywords to include in your tweet"
|
||||
)
|
||||
|
||||
length = st.select_slider(
|
||||
"Tweet Length",
|
||||
options=["short", "medium", "long"],
|
||||
value="medium",
|
||||
help="Choose your desired tweet length"
|
||||
)
|
||||
|
||||
num_variations = st.slider(
|
||||
"Number of Variations",
|
||||
min_value=1,
|
||||
max_value=5,
|
||||
value=3,
|
||||
help="How many tweet variations would you like to generate?"
|
||||
)
|
||||
st.button("📅 Schedule Content", use_container_width=True)
|
||||
with col3:
|
||||
st.button("📊 View Analytics", use_container_width=True)
|
||||
|
||||
with tab2:
|
||||
st.markdown("### 📈 Analytics Dashboard")
|
||||
st.info("Analytics features coming soon! Stay tuned for detailed insights and performance metrics.")
|
||||
|
||||
with tab3:
|
||||
st.markdown("### ⚙️ Settings")
|
||||
st.info("Settings and configuration options coming soon!")
|
||||
|
||||
# Main content area
|
||||
st.markdown("## 🛠️ Available Tools")
|
||||
|
||||
# Generate button with loading state
|
||||
if st.button("Generate Tweets", use_container_width=True):
|
||||
with st.spinner("Generating tweet variations..."):
|
||||
tweets = generate_tweet_variations(
|
||||
hook, target_audience, tone,
|
||||
call_to_action, keywords, length,
|
||||
num_variations
|
||||
)
|
||||
|
||||
# Display performance metrics
|
||||
st.markdown("### 📊 Performance Metrics")
|
||||
for tweet in tweets:
|
||||
performance = predict_tweet_performance(tweet["text"], target_audience, tone)
|
||||
|
||||
# Overall score with progress bar
|
||||
st.progress(performance["overall_score"] / 100)
|
||||
st.metric("Overall Score", f"{performance['overall_score']:.1f}%")
|
||||
|
||||
# Detailed metrics in columns
|
||||
cols = st.columns(4)
|
||||
metrics = performance["metrics"]
|
||||
|
||||
with cols[0]:
|
||||
st.metric("Character Count", f"{metrics['character_count']['score']:.1f}%")
|
||||
with cols[1]:
|
||||
st.metric("Hashtag Usage", f"{metrics['hashtag_usage']['score']:.1f}%")
|
||||
with cols[2]:
|
||||
st.metric("Engagement", f"{metrics['engagement_potential']['score']:.1f}%")
|
||||
with cols[3]:
|
||||
st.metric("Audience Fit", f"{metrics['audience_alignment']['score']:.1f}%")
|
||||
|
||||
# Improvement suggestions
|
||||
suggestions = suggest_improvements(tweet["text"], performance)
|
||||
if suggestions:
|
||||
st.markdown("### 💡 Improvement Suggestions")
|
||||
for suggestion in suggestions:
|
||||
st.info(suggestion)
|
||||
|
||||
# Tweet card
|
||||
render_tweet_card(tweet, tweets.index(tweet))
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# Export options
|
||||
st.markdown("### 📥 Export Options")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
if st.button("Export as JSON"):
|
||||
st.download_button(
|
||||
"Download JSON",
|
||||
data=json.dumps(tweets, indent=2),
|
||||
file_name=f"tweets_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
|
||||
mime="application/json"
|
||||
)
|
||||
with col2:
|
||||
if st.button("Copy All Tweets"):
|
||||
tweet_texts = "\n\n".join(tweet["text"] for tweet in tweets)
|
||||
st.code(tweet_texts)
|
||||
# Render each category
|
||||
for category in features.values():
|
||||
render_category_section(category)
|
||||
|
||||
# If this is the tweet generation category and the Smart Tweet Generator is active,
|
||||
# add a button to launch it
|
||||
if category["title"] == "Tweet Generation & Optimization" and category["features"][0]["status"] == "active":
|
||||
if st.button(f"🚀 Launch {category['features'][0]['name']}", use_container_width=True):
|
||||
category["features"][0]["function"]()
|
||||
|
||||
# Footer
|
||||
st.markdown("---")
|
||||
st.markdown("""
|
||||
<div style='text-align: center;'>
|
||||
<p>Need help? Check out our <a href='#'>documentation</a> or <a href='#'>contact support</a></p>
|
||||
</div>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
if __name__ == "__main__":
|
||||
smart_tweet_generator()
|
||||
run_dashboard()
|
||||
@@ -7,14 +7,6 @@ from ..manager import APIKeyManager
|
||||
import os
|
||||
from dotenv import load_dotenv # Keep if api_key_manager uses it
|
||||
import sys
|
||||
# Corrected import: Assuming validation functions are in validation.py in the parent directory
|
||||
from ..validation import (
|
||||
test_serpapi_key,
|
||||
test_tavily_key,
|
||||
test_metaphor_key,
|
||||
test_firecrawl_key
|
||||
# Add others if needed later, e.g., test_bing_key, test_google_search_key
|
||||
)
|
||||
|
||||
# Configure logger (assuming configured elsewhere or keep minimal here)
|
||||
logger.add(sys.stderr, level="INFO") # Keep simple example if needed
|
||||
|
||||
@@ -199,7 +199,7 @@ def render_website_setup(api_key_manager: APIKeyManager) -> Dict[str, Any]:
|
||||
|
||||
# --- Removed Analysis Section ---
|
||||
# The detailed website analysis should be a separate feature, not part of the initial setup validation.
|
||||
st.markdown("--- ---“)
|
||||
st.markdown("---")
|
||||
st.markdown("ℹ️ *The detailed Website Analyzer tool is available separately in the main application.*")
|
||||
st.info("Entering your website URL is optional. Click Continue to proceed.")
|
||||
|
||||
|
||||
Reference in New Issue
Block a user