lotus
Optimized Agentic and LLM Bulk Processing Over Your Data
파일 탐색기
최종 버전 다운로드 (.zip)- bug_report.md
- config.yml
- documentation_improvement.md
- feature_request.md
- performance_issue.md
- ast_tests.py
- cache_tests.py
- lm_tests.py
- multimodality_tests.py
- rm_tests.py
- utility_operators_tests.py
- publish.yml
- tests.yml
- PULL_REQUEST_TEMPLATE.md
- logo.png
- logo_with_text.png
- how_it_works.svg
- logo_cropped.png
- results_summary.png
- semantic_operators.svg
- biodex-reactions.csv
- biodex_tester.py
- metrics.py
- pipeline_tester.py
- README.md
- test_paper_results.py
- __init__.py
- evaluate.py
- load_data.py
- optimized_pipeline.pkl
- pipeline.py
- __init__.py
- evaluate.py
- load_data.py
- optimized_pipeline.pkl
- pipeline.py
- __init__.py
- evaluate.py
- load_data.py
- pipeline.py
- bench.py
- bench_hs.py
- README.md
- test_paper_results.py
- __init__.py
- main.py
- agentic_examples.rst
- agentic_filter.rst
- agentic_map_reduce.rst
- agentic_operators.rst
- approximation_cascades.rst
- conf.py
- configurations.rst
- core_concepts.rst
- corpus.rst
- data_connectors.rst
- DirectoryReader.rst
- evaluation.rst
- evaluation_advanced.rst
- index.rst
- installation.rst
- lazyframe.rst
- lazyframe_api.rst
- lazyframe_optimizations.rst
- llm.rst
- llm_as_judge.rst
- logo_with_text.png
- make.bat
- Makefile
- multimodal_models.rst
- pairwise_judge.rst
- prompt_strategies.rst
- reasoning_models.rst
- requirements-docs.txt
- reranker_models.rst
- retriever_models.rst
- sem_agg.rst
- sem_cluster.rst
- sem_dedup.rst
- sem_extract.rst
- sem_filter.rst
- sem_index.rst
- sem_join.rst
- sem_map.rst
- sem_partition.rst
- sem_search.rst
- sem_sim_join.rst
- sem_topk.rst
- semantic_operators.svg
- usage.rst
- vector_store.rst
- web_extract.rst
- web_search.rst
- buggy_filter.py
- codebase_sweep.py
- expense_reports.py
- README.md
- cache.py
- s3.py
- sql_db.py
- llm_as_judge.py
- llm_as_judge_response_format.py
- pairwise_eval.py
- parse_pdf.py
- Poems on Love and Life.pdf
- 01_predicate_pushdown.py
- 02_gepa_filter.py
- 03_cascade_thresholds.py
- lazyframe.py
- deepseek.py
- ollama.py
- openai.py
- 0.png
- 1.png
- 4.png
- 5.png
- 9.png
- filter.py
- join.py
- map.py
- topk.py
- agg.py
- agg_with_grouping.py
- cluster.py
- dedup.py
- extract.py
- extract_cot.py
- extract_deepseek_cot.py
- filter.py
- filter_cascade.py
- filter_cot.py
- filter_deepseek_cot.py
- join.py
- join_cascade.py
- map.py
- map_deepseek_cot.py
- map_fewshot.py
- partition.py
- search.py
- sim_join.py
- top_k.py
- top_k_deepseek_cot.py
- top_k_with_grouping.py
- concurrent_asyncio.py
- concurrent_threads.py
- eval_cache_isolation.py
- scoped_model_switching.py
- search_faiss.py
- search_qdrant.py
- search_weaviate.py
- arxiv_extract.py
- arxiv_topk.py
- google_topk.py
- pubmed_extract.py
- pubmed_topk.py
- tavily_extract.py
- tavily_topk.py
- you_extract.py
- you_topk.py
- __init__.py
- loop.py
- ops.py
- pipeline.py
- planner.py
- __init__.py
- base.py
- cascade.py
- gepa_optimizer.py
- predicate_pushdown.py
- __init__.py
- cache.py
- lazyframe.py
- nodes.py
- README.md
- run.py
- __init__.py
- __init__.py
- connectors.py
- __init__.py
- image.py
- __init__.py
- llm_as_judge.py
- pairwise_judge.py
- __init__.py
- directory_reader.py
- pptx.py
- __init__.py
- colbertv2_rm.py
- cross_encoder_reranker.py
- litellm_rm.py
- lm.py
- reranker.py
- rm.py
- sentence_transformers_rm.py
- __init__.py
- cascade_utils.py
- load_sem_index.py
- postprocessors.py
- sem_agg.py
- sem_cluster_by.py
- sem_dedup.py
- sem_extract.py
- sem_filter.py
- sem_index.py
- sem_join.py
- sem_map.py
- sem_partition_by.py
- sem_search.py
- sem_sim_join.py
- sem_topk.py
- __init__.py
- task_instructions.py
- __init__.py
- base.py
- repl.py
- __init__.py
- faiss_vs.py
- qdrant_vs.py
- vs.py
- weaviate_vs.py
- __init__.py
- cache.py
- long_context_strategy.py
- nl_expression.py
- pricing.py
- settings.py
- types.py
- utils.py
- web_search.py
- __init__.py
- base_test.py
- connector_tests.py
- deepseek_cot_tests.py
- extract_with_prefilter.py
- test_agentic_map_reduce.py
- test_ast.py
- test_cluster.py
- test_extract_cot.py
- test_filter.py
- test_gepa_optimizer.py
- test_lm.py
- test_lm_defaults.py
- test_long_context_strategy.py
- test_pricing.py
- test_qdrant.py
- test_serialization.py
- test_settings.py
- test_web_search_engines.py
- .gitignore
- .pre-commit-config.yaml
- .readthedocs.yaml
- CONTRIBUTING.md
- LICENSE
- mypy.ini
- pyproject.toml
- pytest.ini
- README.md
- uv.lock
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/lotus-data/lotus
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd lotus
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. 공식 설치 스크립트
쉬움 추천사전 준비물
- Python 3 pip 명령어를 쓰려면 Python이 필요합니다.
pip install lotus-ai
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
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