ai-ShopMind
It works by converting product descriptions into vector embeddings stored in Endee, a high-performance vector database. When a customer asks a question, the system finds the most semantically similar products using vector search, then generates a helpful answer grounded in the actual product catalog.
File Explorer
- config.yml
- ci.yml
- cd6e8227b13c_add_new_feature.py
- fada02c1d3ab_initial_schema_rootcause_and_.py
- env.py
- README
- script.py.mako
- __init__.py
- chunker.py
- document_processor.py
- fetch_charm.py
- fetch_manualslib.py
- fetchers.py
- index_manager.py
- indexer.py
- ingestion_manager.py
- pdf_parser.py
- run_ingestion.py
- __init__.py
- calibration.py
- config.py
- contradiction_detector.py
- cost_weighting.py
- data_prep.py
- mock_predictor.py
- predictor.py
- README.md
- registry.py
- retrain.py
- schemas.py
- trainer.py
- __init__.py
- base.py
- circuit_breaker.py
- gcp_local.py
- siliconeflow.py
- __init__.py
- admin.py
- diagnose.py
- feedback.py
- health.py
- metrics.py
- __init__.py
- bonuses.py
- history.py
- hybrid_score.py
- similarity.py
- weight_manager.py
- __init__.py
- diagnostic_service.py
- app.js
- index.html
- style.css
- __init__.py
- vin_decoder.py
- web_search.py
- __init__.py
- app_factory.py
- config.py
- database.py
- db_handlers.py
- embeddings.py
- embeddings_utils.py
- exceptions.py
- logger.py
- main.py
- metrics.py
- models.py
- protocols.py
- query_utils.py
- ranker.py
- retriever.py
- schemas.py
- types.py
- vector_store.py
- feature-01.webp
- feature-02.webp
- hero.webp
- architecture.md
- impact.md
- setup.md
- pipeline_checklist.py
- validate_training_pipeline.py
- __init__.py
- README.md
- test_real_torch_integration.py
- test_torch_model_loading.py
- test_workflow.py
- __init__.py
- build_test_faiss_index.py
- generate_test_data.py
- training_data.py
- __init__.py
- test_api.py
- test_llm_fallback.py
- test_torch_persistence.py
- test_training_pipeline_e2e.py
- __init__.py
- llm_contract_mock.py
- __init__.py
- test_chunker.py
- test_circuit_breaker.py
- test_embeddings.py
- test_indexer.py
- test_metrics_instrumentation.py
- test_model_registry_versioning.py
- test_pdf_parser.py
- test_providers.py
- test_ranker.py
- test_retriever.py
- test_schemas.py
- test_similarity.py
- test_sql_injection_prevention.py
- test_torch_v2_integration.py
- test_vector_store.py
- test_week2_integration.py
- __init__.py
- conftest.py
- run_e2e_torch.sh
- .dockerignore
- .env.example
- .gitignore
- .pre-commit-config.yaml
- alembic.ini
- ALEMBIC_QUICK_REFERENCE.sh
- ALEMBIC_SETUP_COMPLETE.md
- API.md
- check_db_schema.py
- CI_CD_CHECKLIST.md
- CI_CD_SETUP.md
- CI_CD_TROUBLESHOOTING.md
- CODE_ANALYSIS_COMPREHENSIVE.md
- CONTRIBUTING.md
- DEPLOYMENT.md
- docker-compose.yml
- Dockerfile
- GCP_LLM_QUICK_START.md
- GCP_LLM_SETUP.md
- GCP_LLM_SETUP_COMPLETE.md
- IMPLEMENTATION_STATUS.md
- PHASE3_METRICS_COMPLETE.md
- PHASE_5_CI_CD_COMPLETE.md
- PRODUCTION_READINESS.md
- pyproject.toml
- pytest.ini
- README.md
- requirements.txt
- setup_gcp_llm.py
- setup_gcp_llm.sh
- SQL_INJECTION_FIX_COMPLETE.md
- TORCH_QUICK_REFERENCE.md
- TRAINING_PIPELINE_IMPLEMENTATION_SUMMARY.md
- TRAINING_PIPELINE_QUICK_REFERENCE.md
- TRAINING_PIPELINE_VALIDATION.md
- V2_TORCH_IMPLEMENTATION.md
- validate_week1.py
- verify_alembic.py
- verify_embedding_consolidation.py
- verify_endpoints.py
- verify_integration.py
- verify_metrics.py
- WEEK2_IMPLEMENTATION_COMPLETE.md
- WEEK2_TORCH_INTEGRATION.md
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