Spaces:
Sleeping
Sleeping
File size: 3,352 Bytes
500516e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
# src/create_database.py
import os
import json
from src.memory import MemoryManager # Corrected import path
import logging
from typing import List, Dict
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
def parse_data_update(file_path: str, keyword_dir: str) -> List[Dict[str, str]]:
if not os.path.exists(file_path):
logging.error(f"File not found: {file_path}")
return []
with open(file_path, 'r') as file_obj:
content = file_obj.read()
content = content.lower() # Normalize to lowercase
sections = []
lines = content.split('\n')
current_section = None
current_content = []
for line in lines:
if line.strip().startswith("chronique #") or line.strip().startswith("flash info fl-") or line.strip().startswith("chronique-faq #"):
if current_section:
sections.append({
"concept": current_section,
"description": "\n".join(current_content)
})
logging.info(f"Parsed section: {current_section}")
current_section = line.strip()
current_content = []
else:
current_content.append(line)
if current_section:
sections.append({
"concept": current_section,
"description": "\n".join(current_content)
})
logging.info(f"Parsed section: {current_section}")
return sections
def get_keywords(number: str, keyword_dir: str) -> List[str]:
keyword_file = os.path.join(keyword_dir, f"FL-{number}-KEYWORD.txt")
if not os.path.exists(keyword_file):
keyword_file = os.path.join(keyword_dir, f"INFO-{number}-KEYWORD.txt")
if not os.path.exists(keyword_file):
keyword_file = os.path.join(keyword_dir, f"CHRONIQUE{number}-KEYWORD.txt")
if not os.path.exists(keyword_file):
logging.warning(f"Keyword file not found: {keyword_file}")
return []
with open(keyword_file, 'r') as file_obj:
content = file_obj.read()
if 'KEYWORD = ' in content:
content = content.split('KEYWORD = ')[1]
tags = content.split(', ')
tags = [tag.strip() for tag in tags if tag.strip()] # Remove empty tags
logging.info(f"Keywords for {number}: {tags}")
return tags
def load_and_process_dataset(data_update_path: str, keyword_dir: str, db_path: str):
memory_manager = MemoryManager(db_path)
sections = parse_data_update(data_update_path, keyword_dir)
for section in sections:
concept = section['concept']
description = section['description']
number = concept.split('#')[1].split()[0] # Extract the number from the concept
tags = get_keywords(number, keyword_dir)
# Check if the section already exists in the database
if not memory_manager.section_exists(concept):
memory_manager.add_semantic_memory(concept, description, tags=tags)
logging.info(f"Added section: {concept}")
else:
logging.info(f"Section already exists: {concept}")
if __name__ == "__main__":
data_update_path = "data-update.txt"
keyword_dir = "keyword" # Updated keyword directory
db_path = "agent.db"
load_and_process_dataset(data_update_path, keyword_dir, db_path)
|