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import os | |
import chromadb | |
from sentence_transformers import SentenceTransformer | |
from loguru import logger | |
class SentenceTransformerEmbeddings: | |
def __init__(self, model_name: str = 'all-MiniLM-L6-v2'): | |
self.model = SentenceTransformer(model_name) | |
def __call__(self, input: list[str]) -> list[list[float]]: | |
embeddings = self.model.encode(input) | |
return embeddings.tolist() | |
def initialize_chromadb(): | |
"""Initialize ChromaDB and load documents if needed""" | |
try: | |
# Set up paths | |
base_path = os.path.dirname(os.path.abspath(__file__)) | |
doc_path = os.path.join(base_path, 'a2023-45.txt') | |
index_path = os.path.join(base_path, 'index.txt') | |
chroma_path = os.path.join(base_path, 'chroma_db') | |
# Check if required files exist | |
if not os.path.exists(doc_path): | |
logger.error(f"Document file not found at {doc_path}") | |
return False | |
if not os.path.exists(index_path): | |
logger.error(f"Index file not found at {index_path}") | |
return False | |
# Ensure ChromaDB directory exists | |
os.makedirs(chroma_path, exist_ok=True) | |
# Initialize ChromaDB | |
chroma_client = chromadb.PersistentClient(path=chroma_path) | |
embedding_function = SentenceTransformerEmbeddings() | |
# Check if collection exists and has content | |
collections = chroma_client.list_collections() | |
collection_exists = any(col.name == "legal_documents" for col in collections) | |
if collection_exists: | |
collection = chroma_client.get_collection( | |
name="legal_documents", | |
embedding_function=embedding_function | |
) | |
if collection.count() > 0: | |
logger.info("ChromaDB collection already exists and has content") | |
return True | |
# If we get here, we need to create or repopulate the collection | |
logger.info("Loading documents into ChromaDB...") | |
# Delete existing collection if it exists | |
if collection_exists: | |
chroma_client.delete_collection("legal_documents") | |
# Create new collection | |
collection = chroma_client.create_collection( | |
name="legal_documents", | |
embedding_function=embedding_function | |
) | |
# Read and process documents | |
with open(doc_path, 'r', encoding='utf-8') as f: | |
document = f.read().strip() | |
with open(index_path, 'r', encoding='utf-8') as f: | |
index_content = [line.strip() for line in f.readlines() if line.strip()] | |
# Process document into sections | |
sections = [] | |
current_section = "" | |
current_title = "" | |
for line in document.split('\n'): | |
line = line.strip() | |
if any(index_line in line for index_line in index_content): | |
if current_section and current_title: | |
sections.append({ | |
"title": current_title, | |
"content": current_section.strip() | |
}) | |
current_title = line | |
current_section = "" | |
else: | |
if line: | |
current_section += line + "\n" | |
if current_section and current_title: | |
sections.append({ | |
"title": current_title, | |
"content": current_section.strip() | |
}) | |
# Prepare and add data to ChromaDB | |
if sections: | |
documents = [] | |
metadatas = [] | |
ids = [] | |
for i, section in enumerate(sections): | |
if section["content"].strip(): | |
documents.append(section["content"]) | |
metadatas.append({ | |
"title": section["title"], | |
"source": "a2023-45.txt", | |
"section_number": i + 1 | |
}) | |
ids.append(f"section_{i+1}") | |
collection.add( | |
documents=documents, | |
metadatas=metadatas, | |
ids=ids | |
) | |
logger.info(f"Successfully loaded {len(documents)} sections into ChromaDB") | |
return True | |
else: | |
logger.error("No valid sections found in document") | |
return False | |
except Exception as e: | |
logger.error(f"Error initializing ChromaDB: {str(e)}") | |
return False | |
def test_chromadb_content(): | |
"""Test if ChromaDB has the required content""" | |
try: | |
# First ensure ChromaDB is initialized | |
if not initialize_chromadb(): | |
return False | |
# Set up ChromaDB path | |
base_path = os.path.dirname(os.path.abspath(__file__)) | |
chroma_path = os.path.join(base_path, 'chroma_db') | |
# Initialize ChromaDB | |
chroma_client = chromadb.PersistentClient(path=chroma_path) | |
# Get collection | |
collection = chroma_client.get_collection( | |
name="legal_documents", | |
embedding_function=SentenceTransformerEmbeddings() | |
) | |
# Check collection size | |
count = collection.count() | |
if count == 0: | |
logger.error("Collection is empty") | |
return False | |
logger.info(f"Found {count} documents in ChromaDB") | |
# Test query to verify content | |
test_results = collection.query( | |
query_texts=["What are the general provisions?"], | |
n_results=1 | |
) | |
if not test_results['documents']: | |
logger.error("Test query returned no results") | |
return False | |
logger.info("ChromaDB content verification successful") | |
return True | |
except Exception as e: | |
logger.error(f"Error testing ChromaDB: {str(e)}") | |
return False | |
if __name__ == "__main__": | |
success = test_chromadb_content() | |
if success: | |
print("ChromaDB content verification successful") | |
else: | |
print("ChromaDB content verification failed") |