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import streamlit as st | |
from models.vectorizer import Vectorizer | |
from models.prompt_search_engine import PromptSearchEngine | |
from models.data_reader import load_prompts_from_jsonl | |
from models.Query import Query, SimilarPrompt, SearchResponse, PromptVector, VectorResponse | |
from sentence_transformers import SentenceTransformer | |
import os | |
# Cache the prompts data to avoid reloading every time | |
def load_prompts(): | |
prompt_path = "models/prompts_data.jsonl" | |
return load_prompts_from_jsonl(prompt_path) | |
# Cache the search engine initialization | |
def get_search_engine(): | |
search_engine = PromptSearchEngine() | |
prompts = load_prompts() | |
search_engine.add_prompts_to_vector_database(prompts) | |
return search_engine | |
# Initialize search engine only once | |
search_engine = get_search_engine() | |
# Streamlit App Interface | |
st.title("Prompt Search Engine") | |
st.write("Search for similar prompts using the local search engine.") | |
# Input for the user's prompt | |
query_input = st.text_input("Enter your prompt:") | |
# Number of similar prompts to retrieve (k) | |
k = st.number_input("Number of similar prompts to retrieve:", min_value=1, max_value=10, value=3) | |
# Button to trigger search | |
if st.button("Search Prompts"): | |
if query_input: | |
similar_prompts, distances = search_engine.most_similar(query_input, top_k=k) | |
# Format and display search results | |
st.write(f"Search Results: ") | |
for i, (prompt, distance) in enumerate(zip(similar_prompts, distances)): | |
st.write(f"{i+1}. Prompt: {prompt}, Distance: {distance}") | |
else: | |
st.error("Please enter a prompt.") | |
# Additional functionality for vector similarity | |
st.write("---") | |
st.write("### Vector Similarities") | |
if st.button("Retrieve All Vector Similarities"): | |
if query_input: | |
query_embedding = search_engine.model.encode([query_input]) # Encode the prompt to a vector | |
all_similarities = search_engine.cosine_similarity(query_embedding, search_engine.index) | |
st.write(f"Vector Similarities: {all_similarities}") | |
else: | |
st.error("Please enter a prompt.") |