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import streamlit as st
import pyperclip
from src.fabrics_processor.database import initialize_qdrant_database
from src.search_qdrant.database_query import query_qdrant_database
from src.fabrics_processor.logger import setup_logger
import logging
import atexit
from src.fabrics_processor.config import config
import time
# Configure logging
logger = setup_logger()
def init_session_state():
"""Initialize session state variables."""
if 'client' not in st.session_state:
client = initialize_qdrant_database(api_key=st.secrets["api_key"])
st.session_state.client = client
# Register cleanup function
atexit.register(lambda: client.close() if hasattr(client, '_transport') else None)
if 'selected_prompts' not in st.session_state:
st.session_state.selected_prompts = []
if 'comparing' not in st.session_state:
st.session_state.comparing = False
if 'comparison_selected' not in st.session_state:
st.session_state.comparison_selected = None
if 'status_key' not in st.session_state:
st.session_state.status_key = 0
def show_comparison_view(prompts):
"""Show a full-width comparison view of the selected prompts."""
st.write("## Compare Selected Prompts")
# Add the back button at the top
if st.button("Back to search"):
st.session_state.comparing = False
st.rerun()
# Create columns for each prompt
cols = st.columns(len(prompts))
# Track which prompt is selected for copying
selected_idx = None
for idx, (col, prompt) in enumerate(zip(cols, prompts)):
with col:
st.markdown(f"### {prompt.metadata['filename']}")
# Display content as markdown
st.markdown("### Content")
st.code(prompt.metadata["content"], language="markdown", wrap_lines=True)
# Add copy button for each prompt
if st.button(f"Use this prompt", key=f"compare_use_{idx}"):
st.code(prompt.metadata["content"], language="markdown", wrap_lines=True)
selected_idx = idx
# Handle selection
if selected_idx is not None:
st.session_state.comparing = False
st.rerun()
def search_interface():
"""Show the search interface."""
if st.session_state.comparing:
show_comparison_view(st.session_state.selected_prompts)
return
query = st.text_area("What are you trying to accomplish? I will then search for good prompts to give you a good start.")
if query:
try:
results = query_qdrant_database(
query=query,
client=st.session_state.client,
num_results=5,
collection_name=config.embedding.collection_name
)
if results:
st.write("Which prompts would you like to investigate? Max 3.")
# Create checkboxes for selection
selected = []
for r in results:
if st.checkbox(f"{r.metadata['filename']}", key=f"select_{r.id}"):
selected.append(r)
st.session_state.selected_prompts = selected
if selected:
col1, col2 = st.columns(2)
with col1:
if len(selected) == 1:
st.code(selected[0].metadata["content"], language="markdown", wrap_lines=True)
with col2:
if len(selected) > 1 and st.button("Compare"):
st.session_state.comparing = True
st.rerun()
except Exception as e:
logger.error(f"Error in search_interface: {e}", exc_info=True)
st.error(f"Error searching database: {e}")
def main():
"""Main function to run the Streamlit app."""
st.set_page_config(
page_title="Find fabric prompts",
page_icon="🔍",
layout="wide"
)
st.title("Find fabric prompts")
try:
init_session_state()
search_interface()
# Add credits at the bottom left
st.markdown("""
<style>
.credits {
position: fixed;
left: 1rem;
bottom: 1rem;
font-size: 0.8rem;
color: #666;
max-width: 600px;
}
</style>
<div class="credits">
This tool searches the great list of prompts available at <a href="https://github.com/danielmiessler/fabric">https://github.com/danielmiessler/fabric</a>.
A great commandline utilty build by Daniel Miessler to make the use of LLM more frictionless.<br>
All credits to him and his fellow fabric builders.
</div>
""", unsafe_allow_html=True)
except Exception as e:
logger.error(f"Error in main: {str(e)}")
st.error(f"An error occurred: {str(e)}")
if __name__ == "__main__":
main()
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