| |
| """ |
| Simple bulk loader for raw text summaries and reports |
| Just drop your .txt files in a folder and run this script |
| """ |
|
|
| from app import Me |
| import os |
|
|
| def main(): |
| |
| me = Me() |
| |
| print("=== Simple RAG Text Loader ===\n") |
| print("ℹ️ Note: All files in me/ directory are automatically loaded on startup!") |
| print(" Just add .txt, .pdf, or .md files to me/ and restart the app.\n") |
| |
| |
| single_file = "data/summary.txt" |
| if os.path.exists(single_file): |
| print(f"Loading single file: {single_file}") |
| with open(single_file, 'r', encoding='utf-8') as f: |
| content = f.read() |
| me.bulk_load_text_content(content, "summary_report") |
| |
| |
| text_directory = "data/reports" |
| if os.path.exists(text_directory): |
| print(f"Loading all text files from: {text_directory}") |
| me.load_directory(text_directory) |
| |
| |
| specific_files = [ |
| "data/project_summary.txt", |
| "data/technical_report.txt", |
| "data/meeting_notes.txt" |
| ] |
| |
| existing_files = [f for f in specific_files if os.path.exists(f)] |
| if existing_files: |
| print(f"Loading {len(existing_files)} specific files...") |
| me.load_text_files(existing_files) |
| |
| |
| sample_text = """ |
| Alexandre completed a major project involving AI implementation |
| for a Fortune 500 company. The project improved efficiency by 40% |
| and was delivered 2 weeks ahead of schedule. Technologies used |
| included Python, TensorFlow, and cloud deployment on AWS. |
| """ |
| |
| print("Loading sample text content...") |
| me.bulk_load_text_content(sample_text, "sample_project_info") |
| |
| |
| print("\n💡 If you added new files to me/, you can reload them:") |
| print(" me.reload_me_directory()") |
| |
| |
| print("\n=== Knowledge Base Stats ===") |
| me.get_knowledge_stats() |
| |
| print("\n✅ Raw text loading completed!") |
| print("Your RAG system now has the text content available for chat.") |
|
|
| if __name__ == "__main__": |
| main() |