3c58fd555b
New tools added to ToBeMigrated/ directory: ai_marketing_tools/: - ai_backlinker: AI-powered backlink generation - ai_google_ads_generator: Google Ads generation with templates ai_writers/: - ai_blog_faqs_writer: FAQ generation for blogs - ai_copywriter: Multiple copywriter frameworks (AIDA, PAS, 4C, 4R, etc.) - ai_finance_report_generator: Financial report generation - ai_story_illustrator: Story illustration - ai_story_video_generator: Story video generation - ai_story_writer: AI story writing - github_blogs: GitHub blog integration - speech_to_blog: Audio to blog conversion - twitter_writers: Twitter/X content generation - youtube_writers: YouTube content generation These tools are in ToBeMigrated/ for future migration to the main backend.
312 lines
13 KiB
Python
312 lines
13 KiB
Python
"""
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Streamlit UI for FAQ Generator
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This module provides a user-friendly interface for generating FAQs from various content sources.
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"""
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import streamlit as st
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from pathlib import Path
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from typing import Optional
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import json
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import requests
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from bs4 import BeautifulSoup
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import logging
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import pyperclip
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from .faqs_generator_blog import FAQGenerator, FAQConfig, TargetAudience, FAQStyle, SearchDepth
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# Set up logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def copy_to_clipboard(text: str) -> None:
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"""Copy text to clipboard and show success message."""
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try:
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pyperclip.copy(text)
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st.success("Copied to clipboard!")
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except Exception as e:
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st.error(f"Failed to copy to clipboard: {str(e)}")
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def fetch_url_content(url):
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"""Fetch and extract content from a URL."""
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try:
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response = requests.get(url)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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# Remove script and style elements
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for script in soup(["script", "style"]):
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script.decompose()
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# Get text
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text = soup.get_text()
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# Break into lines and remove leading and trailing space
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lines = (line.strip() for line in text.splitlines())
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# Break multi-headlines into a line each
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chunks = (phrase.strip() for line in lines for phrase in line.split(" "))
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# Drop blank lines
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text = '\n'.join(chunk for chunk in chunks if chunk)
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return text
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except Exception as e:
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st.error(f"Error fetching URL content: {str(e)}")
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return None
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def main():
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st.title("FAQ Generator")
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st.markdown("Generate comprehensive FAQs from your content with research integration.")
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# Initialize session state variables if they don't exist
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if 'search_queries' not in st.session_state:
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st.session_state.search_queries = []
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if 'selected_queries' not in st.session_state:
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st.session_state.selected_queries = []
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if 'research_completed' not in st.session_state:
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st.session_state.research_completed = False
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if 'research_results' not in st.session_state:
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st.session_state.research_results = {}
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if 'faq_config' not in st.session_state:
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st.session_state.faq_config = None
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if 'generator' not in st.session_state:
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st.session_state.generator = FAQGenerator()
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if 'generated_faqs' not in st.session_state:
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st.session_state.generated_faqs = None
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if 'output_format' not in st.session_state:
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st.session_state.output_format = "Preview"
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# Sidebar for configuration
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with st.sidebar:
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st.header("Configuration")
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# Basic settings
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num_faqs = st.slider("Number of FAQs", 1, 20, 5)
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target_audience = st.selectbox(
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"Target Audience",
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[audience.value for audience in TargetAudience]
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)
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faq_style = st.selectbox(
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"FAQ Style",
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[style.value for style in FAQStyle]
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)
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# Advanced settings
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with st.expander("Advanced Settings"):
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include_emojis = st.checkbox("Include Emojis", value=True)
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include_code_examples = st.checkbox("Include Code Examples", value=True)
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include_references = st.checkbox("Include References", value=True)
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search_depth = st.selectbox(
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"Search Depth",
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[depth.value for depth in SearchDepth]
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)
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time_range = st.selectbox(
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"Time Range",
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["last_month", "last_6_months", "last_year", "all_time"]
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)
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language = st.text_input("Language", value="English")
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# Main content area
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content_type = st.radio(
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"Content Source",
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["Direct Input", "File Upload", "URL"]
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)
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content = ""
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if content_type == "Direct Input":
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content = st.text_area("Enter your content", height=300)
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elif content_type == "URL":
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url = st.text_input("Enter URL")
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if url:
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content = fetch_url_content(url)
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if content:
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st.text_area("Extracted Content", content, height=300)
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# Step 1: Generate search queries
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if content and not st.session_state.search_queries:
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if st.button("Generate Search Queries"):
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with st.spinner("Generating search queries..."):
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search_queries = st.session_state.generator.generate_search_queries(content)
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if search_queries:
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st.session_state.search_queries = search_queries
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st.session_state.selected_queries = [] # Reset selected queries
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st.session_state.research_completed = False # Reset research status
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st.session_state.research_results = {} # Reset research results
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st.session_state.faq_config = None # Reset config
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st.session_state.generated_faqs = None # Reset generated FAQs
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st.success("Search queries generated successfully!")
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# Step 2: Display and select search queries
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if st.session_state.search_queries:
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st.subheader("Select Search Queries")
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st.info("Select the queries you want to use for web research. You can select multiple queries.")
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# Create checkboxes for each search query
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selected_queries = []
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for query in st.session_state.search_queries:
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if st.checkbox(query, key=f"query_{query}", value=query in st.session_state.selected_queries):
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selected_queries.append(query)
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# Update selected queries in session state
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st.session_state.selected_queries = selected_queries
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# Step 3: Do web research
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if st.session_state.selected_queries and not st.session_state.research_completed:
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if st.button("Do Web Research"):
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try:
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# Create config with selected queries
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config = FAQConfig(
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num_faqs=num_faqs,
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target_audience=TargetAudience(target_audience),
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faq_style=FAQStyle(faq_style),
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include_emojis=include_emojis,
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include_code_examples=include_code_examples,
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include_references=include_references,
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search_depth=SearchDepth(search_depth),
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time_range=time_range,
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language=language,
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selected_search_queries=selected_queries
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)
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# Store config in session state
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st.session_state.faq_config = config
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# Update generator with config
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st.session_state.generator.config = config
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# Do research
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with st.spinner("Conducting web research..."):
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research_results = st.session_state.generator._conduct_research(content)
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st.session_state.research_completed = True
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st.session_state.research_results = research_results
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st.success("Web research completed successfully!")
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# Display research results
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st.subheader("Research Results")
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for query, results in research_results.items():
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with st.expander(f"Results for: {query}"):
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if isinstance(results, dict):
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st.json(results)
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else:
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st.text(results)
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except Exception as e:
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st.error(f"Error during web research: {str(e)}")
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st.error("Please try again with different search queries or adjust the search depth.")
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# Step 4: Generate FAQs
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if st.session_state.research_completed and st.session_state.research_results and st.session_state.faq_config:
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if st.button("Generate FAQs"):
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try:
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# Update generator with stored config
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st.session_state.generator.config = st.session_state.faq_config
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# Generate FAQs
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with st.spinner("Generating FAQs..."):
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logger.info("Starting FAQ generation...")
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faqs = st.session_state.generator.generate_faqs(content)
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logger.info(f"Generated {len(faqs) if faqs else 0} FAQs")
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if not faqs:
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st.error("No FAQs were generated. Please try again.")
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return
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st.session_state.generated_faqs = faqs
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st.success("FAQs generated successfully!")
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except Exception as e:
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logger.error(f"Error generating FAQs: {str(e)}")
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st.error(f"Error generating FAQs: {str(e)}")
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st.error("Please try again or adjust your settings.")
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# Display generated FAQs if they exist
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if st.session_state.generated_faqs:
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st.subheader("Generated FAQs")
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# Output format selection
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output_format = st.radio(
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"Output Format",
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["Preview", "Markdown", "HTML", "JSON"],
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key="output_format"
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)
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# Create columns for copy and download buttons
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col1, col2 = st.columns(2)
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if output_format == "Preview":
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# Create a formatted text for copying
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preview_text = ""
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for i, faq in enumerate(st.session_state.generated_faqs, 1):
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preview_text += f"{i}. {faq.question}\n"
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preview_text += f"{faq.answer}\n\n"
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if faq.code_example:
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preview_text += f"Code Example:\n{faq.code_example}\n\n"
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if faq.references:
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preview_text += "References:\n"
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for ref in faq.references:
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preview_text += f"- {ref['source']}\n"
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preview_text += "\n"
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with col1:
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if st.button("Copy to Clipboard", key="copy_preview"):
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copy_to_clipboard(preview_text)
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# Display the FAQs
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for i, faq in enumerate(st.session_state.generated_faqs, 1):
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with st.expander(f"{i}. {faq.question}"):
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st.markdown(faq.answer)
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if faq.code_example:
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st.code(faq.code_example)
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if faq.references:
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st.markdown("**References:**")
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for ref in faq.references:
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st.markdown(f"- {ref['source']}")
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elif output_format == "Markdown":
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markdown_output = st.session_state.generator.to_markdown()
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st.code(markdown_output, language="markdown")
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with col1:
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if st.button("Copy to Clipboard", key="copy_markdown"):
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copy_to_clipboard(markdown_output)
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with col2:
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st.download_button(
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"Download Markdown",
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markdown_output,
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file_name="faqs.md",
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mime="text/markdown"
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)
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elif output_format == "HTML":
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html_output = st.session_state.generator.to_html()
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st.code(html_output, language="html")
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with col1:
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if st.button("Copy to Clipboard", key="copy_html"):
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copy_to_clipboard(html_output)
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with col2:
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st.download_button(
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"Download HTML",
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html_output,
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file_name="faqs.html",
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mime="text/html"
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)
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elif output_format == "JSON":
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json_output = json.dumps([faq.__dict__ for faq in st.session_state.generated_faqs], indent=2)
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st.code(json_output, language="json")
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with col1:
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if st.button("Copy to Clipboard", key="copy_json"):
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copy_to_clipboard(json_output)
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with col2:
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st.download_button(
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"Download JSON",
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json_output,
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file_name="faqs.json",
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mime="application/json"
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)
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if __name__ == "__main__":
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main() |