forked from phoenix-oss/llama-stack-mirror
8e7ab146f8
# What does this PR do? his PR allows users to customize the template used for chunks when inserted into the context. Additionally, this enables metadata injection into the context of an LLM for RAG. This makes a naive and crude assumption that each chunk should include the metadata, this is obviously redundant when multiple chunks are returned from the same document. In order to remove any sort of duplication of chunks, we'd have to make much more significant changes so this is a reasonable first step that unblocks users requesting this enhancement in https://github.com/meta-llama/llama-stack/issues/1767. In the future, this can be extended to support citations. List of Changes: - `llama_stack/apis/tools/rag_tool.py` - Added `chunk_template` field in `RAGQueryConfig`. - Added `field_validator` to validate the `chunk_template` field in `RAGQueryConfig`. - Ensured the `chunk_template` field includes placeholders `{index}` and `{chunk.content}`. - Updated the `query` method to use the `chunk_template` for formatting chunk text content. - `llama_stack/providers/inline/tool_runtime/rag/memory.py` - Modified the `insert` method to pass `doc.metadata` for chunk creation. - Enhanced the `query` method to format results using `chunk_template` and exclude unnecessary metadata fields like `token_count`. - `llama_stack/providers/utils/memory/vector_store.py` - Updated `make_overlapped_chunks` to include metadata serialization and token count for both content and metadata. - Added error handling for metadata serialization issues. - `pyproject.toml` - Added `pydantic.field_validator` as a recognized `classmethod` decorator in the linting configuration. - `tests/integration/tool_runtime/test_rag_tool.py` - Refactored test assertions to separate `assert_valid_chunk_response` and `assert_valid_text_response`. - Added integration tests to validate `chunk_template` functionality with and without metadata inclusion. - Included a test case to ensure `chunk_template` validation errors are raised appropriately. - `tests/unit/rag/test_vector_store.py` - Added unit tests for `make_overlapped_chunks`, verifying chunk creation with overlapping tokens and metadata integrity. - Added tests to handle metadata serialization errors, ensuring proper exception handling. - `docs/_static/llama-stack-spec.html` - Added a new `chunk_template` field of type `string` with a default template for formatting retrieved chunks in RAGQueryConfig. - Updated the `required` fields to include `chunk_template`. - `docs/_static/llama-stack-spec.yaml` - Introduced `chunk_template` field with a default value for RAGQueryConfig. - Updated the required configuration list to include `chunk_template`. - `docs/source/building_applications/rag.md` - Documented the `chunk_template` configuration, explaining how to customize metadata formatting in RAG queries. - Added examples demonstrating the usage of the `chunk_template` field in RAG tool queries. - Highlighted default values for `RAG` agent configurations. # Resolves https://github.com/meta-llama/llama-stack/issues/1767 ## Test Plan Updated both `test_vector_store.py` and `test_rag_tool.py` and tested end-to-end with a script. I also tested the quickstart to enable this and specified this metadata: ```python document = RAGDocument( document_id="document_1", content=source, mime_type="text/html", metadata={"author": "Paul Graham", "title": "How to do great work"}, ) ``` Which produced the output below:  This highlights the usefulness of the additional metadata. Notice how the metadata is redundant for different chunks of the same document. I think we can update that in a subsequent PR. # Documentation I've added a brief comment about this in the documentation to outline this to users and updated the API documentation. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
325 lines
12 KiB
TOML
325 lines
12 KiB
TOML
[build-system]
|
|
requires = ["setuptools>=61.0"]
|
|
build-backend = "setuptools.build_meta"
|
|
|
|
[project]
|
|
name = "llama_stack"
|
|
version = "0.2.6"
|
|
authors = [{ name = "Meta Llama", email = "llama-oss@meta.com" }]
|
|
description = "Llama Stack"
|
|
readme = "README.md"
|
|
requires-python = ">=3.10"
|
|
license = { "text" = "MIT" }
|
|
classifiers = [
|
|
"License :: OSI Approved :: MIT License",
|
|
"Programming Language :: Python :: 3",
|
|
"Operating System :: OS Independent",
|
|
"Intended Audience :: Developers",
|
|
"Intended Audience :: Information Technology",
|
|
"Intended Audience :: Science/Research",
|
|
"Topic :: Scientific/Engineering :: Artificial Intelligence",
|
|
"Topic :: Scientific/Engineering :: Information Analysis",
|
|
]
|
|
dependencies = [
|
|
"blobfile",
|
|
"fire",
|
|
"httpx",
|
|
"huggingface-hub",
|
|
"jinja2>=3.1.6",
|
|
"jsonschema",
|
|
"llama-stack-client>=0.2.6",
|
|
"openai>=1.66",
|
|
"prompt-toolkit",
|
|
"python-dotenv",
|
|
"pydantic>=2",
|
|
"requests",
|
|
"rich",
|
|
"setuptools",
|
|
"termcolor",
|
|
"tiktoken",
|
|
"pillow",
|
|
"h11>=0.16.0",
|
|
"kubernetes",
|
|
]
|
|
|
|
[project.optional-dependencies]
|
|
dev = [
|
|
"pytest",
|
|
"pytest-asyncio",
|
|
"pytest-cov",
|
|
"pytest-html",
|
|
"pytest-json-report",
|
|
"nbval", # For notebook testing
|
|
"black",
|
|
"ruff",
|
|
"types-requests",
|
|
"types-setuptools",
|
|
"pre-commit",
|
|
"uvicorn",
|
|
"fastapi",
|
|
"ruamel.yaml", # needed for openapi generator
|
|
]
|
|
# These are the dependencies required for running unit tests.
|
|
unit = [
|
|
"sqlite-vec",
|
|
"openai",
|
|
"aiosqlite",
|
|
"aiohttp",
|
|
"pypdf",
|
|
"chardet",
|
|
"qdrant-client",
|
|
"opentelemetry-exporter-otlp-proto-http",
|
|
]
|
|
# These are the core dependencies required for running integration tests. They are shared across all
|
|
# providers. If a provider requires additional dependencies, please add them to your environment
|
|
# separately. If you are using "uv" to execute your tests, you can use the "--with" flag to specify extra
|
|
# dependencies.
|
|
test = [
|
|
"openai",
|
|
"aiosqlite",
|
|
"aiohttp",
|
|
"torch>=2.6.0",
|
|
"torchvision>=0.21.0",
|
|
"opentelemetry-sdk",
|
|
"opentelemetry-exporter-otlp-proto-http",
|
|
"chardet",
|
|
"pypdf",
|
|
"mcp",
|
|
"datasets",
|
|
"autoevals",
|
|
"transformers",
|
|
]
|
|
docs = [
|
|
"sphinx-autobuild",
|
|
"myst-parser",
|
|
"sphinx-rtd-theme",
|
|
"sphinx_rtd_dark_mode",
|
|
"sphinx-copybutton",
|
|
"sphinx-tabs",
|
|
"sphinx-design",
|
|
"sphinxcontrib.redoc",
|
|
"sphinxcontrib.video",
|
|
"sphinxcontrib.mermaid",
|
|
"tomli",
|
|
]
|
|
codegen = ["rich", "pydantic", "jinja2>=3.1.6"]
|
|
ui = [
|
|
"streamlit",
|
|
"pandas",
|
|
"llama-stack-client>=0.2.6",
|
|
"streamlit-option-menu",
|
|
]
|
|
|
|
[project.urls]
|
|
Homepage = "https://github.com/meta-llama/llama-stack"
|
|
|
|
[project.scripts]
|
|
llama = "llama_stack.cli.llama:main"
|
|
install-wheel-from-presigned = "llama_stack.cli.scripts.run:install_wheel_from_presigned"
|
|
|
|
[tool.setuptools]
|
|
packages = { find = {} }
|
|
license-files = []
|
|
|
|
[[tool.uv.index]]
|
|
name = "pytorch-cpu"
|
|
url = "https://download.pytorch.org/whl/cpu"
|
|
explicit = true
|
|
|
|
[tool.uv.sources]
|
|
torch = [{ index = "pytorch-cpu" }]
|
|
torchvision = [{ index = "pytorch-cpu" }]
|
|
|
|
[tool.ruff]
|
|
line-length = 120
|
|
exclude = [
|
|
"./.git",
|
|
"./docs/*",
|
|
"./build",
|
|
"./venv",
|
|
"*.pyi",
|
|
".pre-commit-config.yaml",
|
|
"*.md",
|
|
".flake8",
|
|
]
|
|
|
|
[tool.ruff.lint]
|
|
select = [
|
|
"UP", # pyupgrade
|
|
"B", # flake8-bugbear
|
|
"B9", # flake8-bugbear subset
|
|
"C", # comprehensions
|
|
"E", # pycodestyle
|
|
"F", # Pyflakes
|
|
"N", # Naming
|
|
"W", # Warnings
|
|
"DTZ", # datetime rules
|
|
"I", # isort (imports order)
|
|
"RUF001", # Checks for ambiguous Unicode characters in strings
|
|
"RUF002", # Checks for ambiguous Unicode characters in docstrings
|
|
"RUF003", # Checks for ambiguous Unicode characters in comments
|
|
"PLC2401", # Checks for the use of non-ASCII characters in variable names
|
|
"PLC2403", # Checks for the use of non-ASCII characters in import statements
|
|
"PLE2510", # Checks for strings that contain the control character BS.
|
|
"PLE2512", # Checks for strings that contain the raw control character SUB.
|
|
"PLE2513", # Checks for strings that contain the raw control character ESC.
|
|
"PLE2514", # Checks for strings that contain the raw control character NUL (0 byte).
|
|
"PLE2515", # Checks for strings that contain the zero width space character.
|
|
]
|
|
ignore = [
|
|
# The following ignores are desired by the project maintainers.
|
|
"E402", # Module level import not at top of file
|
|
"E501", # Line too long
|
|
"F405", # Maybe undefined or defined from star import
|
|
"C408", # Ignored because we like the dict keyword argument syntax
|
|
"N812", # Ignored because import torch.nn.functional as F is PyTorch convention
|
|
|
|
# These are the additional ones we started ignoring after moving to ruff. We should look into each one of them later.
|
|
"C901", # Complexity of the function is too high
|
|
]
|
|
unfixable = [
|
|
"PLE2515",
|
|
] # Do not fix this automatically since ruff will replace the zero-width space with \u200b - let's do it manually
|
|
|
|
# Ignore the following errors for the following files
|
|
[tool.ruff.lint.per-file-ignores]
|
|
"tests/**/*.py" = ["DTZ"] # Ignore datetime rules for tests
|
|
"llama_stack/providers/inline/scoring/basic/utils/ifeval_utils.py" = ["RUF001"]
|
|
"llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py" = [
|
|
"RUF001",
|
|
"PLE2515",
|
|
]
|
|
|
|
[tool.mypy]
|
|
mypy_path = ["llama_stack"]
|
|
packages = ["llama_stack"]
|
|
plugins = ['pydantic.mypy']
|
|
disable_error_code = []
|
|
warn_return_any = true
|
|
# # honor excludes by not following there through imports
|
|
follow_imports = "silent"
|
|
# Note: some entries are directories, not files. This is because mypy doesn't
|
|
# respect __init__.py excludes, so the only way to suppress these right now is
|
|
# to exclude the entire directory.
|
|
exclude = [
|
|
# As we fix more and more of these, we should remove them from the list
|
|
"^llama_stack/apis/common/training_types\\.py$",
|
|
"^llama_stack/cli/download\\.py$",
|
|
"^llama_stack/cli/stack/_build\\.py$",
|
|
"^llama_stack/distribution/build\\.py$",
|
|
"^llama_stack/distribution/client\\.py$",
|
|
"^llama_stack/distribution/request_headers\\.py$",
|
|
"^llama_stack/distribution/routers/",
|
|
"^llama_stack/distribution/server/endpoints\\.py$",
|
|
"^llama_stack/distribution/server/server\\.py$",
|
|
"^llama_stack/distribution/stack\\.py$",
|
|
"^llama_stack/distribution/store/registry\\.py$",
|
|
"^llama_stack/distribution/utils/exec\\.py$",
|
|
"^llama_stack/distribution/utils/prompt_for_config\\.py$",
|
|
"^llama_stack/models/llama/llama3/chat_format\\.py$",
|
|
"^llama_stack/models/llama/llama3/interface\\.py$",
|
|
"^llama_stack/models/llama/llama3/tokenizer\\.py$",
|
|
"^llama_stack/models/llama/llama3/tool_utils\\.py$",
|
|
"^llama_stack/models/llama/llama3_3/prompts\\.py$",
|
|
"^llama_stack/providers/inline/agents/meta_reference/",
|
|
"^llama_stack/providers/inline/agents/meta_reference/agent_instance\\.py$",
|
|
"^llama_stack/providers/inline/agents/meta_reference/agents\\.py$",
|
|
"^llama_stack/providers/inline/agents/meta_reference/safety\\.py$",
|
|
"^llama_stack/providers/inline/datasetio/localfs/",
|
|
"^llama_stack/providers/inline/eval/meta_reference/eval\\.py$",
|
|
"^llama_stack/providers/inline/inference/meta_reference/config\\.py$",
|
|
"^llama_stack/providers/inline/inference/meta_reference/inference\\.py$",
|
|
"^llama_stack/models/llama/llama3/generation\\.py$",
|
|
"^llama_stack/models/llama/llama3/multimodal/model\\.py$",
|
|
"^llama_stack/models/llama/llama4/",
|
|
"^llama_stack/providers/inline/inference/meta_reference/parallel_utils\\.py$",
|
|
"^llama_stack/providers/inline/inference/meta_reference/quantization/fp8_impls\\.py$",
|
|
"^llama_stack/providers/inline/inference/meta_reference/quantization/loader\\.py$",
|
|
"^llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers\\.py$",
|
|
"^llama_stack/providers/inline/inference/vllm/",
|
|
"^llama_stack/providers/inline/post_training/common/validator\\.py$",
|
|
"^llama_stack/providers/inline/post_training/torchtune/post_training\\.py$",
|
|
"^llama_stack/providers/inline/safety/code_scanner/",
|
|
"^llama_stack/providers/inline/safety/llama_guard/",
|
|
"^llama_stack/providers/inline/safety/prompt_guard/",
|
|
"^llama_stack/providers/inline/scoring/basic/",
|
|
"^llama_stack/providers/inline/scoring/braintrust/",
|
|
"^llama_stack/providers/inline/scoring/llm_as_judge/",
|
|
"^llama_stack/providers/remote/agents/sample/",
|
|
"^llama_stack/providers/remote/datasetio/huggingface/",
|
|
"^llama_stack/providers/remote/datasetio/nvidia/",
|
|
"^llama_stack/providers/remote/inference/anthropic/",
|
|
"^llama_stack/providers/remote/inference/bedrock/",
|
|
"^llama_stack/providers/remote/inference/cerebras/",
|
|
"^llama_stack/providers/remote/inference/databricks/",
|
|
"^llama_stack/providers/remote/inference/fireworks/",
|
|
"^llama_stack/providers/remote/inference/gemini/",
|
|
"^llama_stack/providers/remote/inference/groq/",
|
|
"^llama_stack/providers/remote/inference/nvidia/",
|
|
"^llama_stack/providers/remote/inference/openai/",
|
|
"^llama_stack/providers/remote/inference/passthrough/",
|
|
"^llama_stack/providers/remote/inference/runpod/",
|
|
"^llama_stack/providers/remote/inference/sambanova/",
|
|
"^llama_stack/providers/remote/inference/sample/",
|
|
"^llama_stack/providers/remote/inference/tgi/",
|
|
"^llama_stack/providers/remote/inference/together/",
|
|
"^llama_stack/providers/remote/inference/watsonx/",
|
|
"^llama_stack/providers/remote/safety/bedrock/",
|
|
"^llama_stack/providers/remote/safety/nvidia/",
|
|
"^llama_stack/providers/remote/safety/sample/",
|
|
"^llama_stack/providers/remote/tool_runtime/bing_search/",
|
|
"^llama_stack/providers/remote/tool_runtime/brave_search/",
|
|
"^llama_stack/providers/remote/tool_runtime/model_context_protocol/",
|
|
"^llama_stack/providers/remote/tool_runtime/tavily_search/",
|
|
"^llama_stack/providers/remote/tool_runtime/wolfram_alpha/",
|
|
"^llama_stack/providers/remote/post_training/nvidia/",
|
|
"^llama_stack/providers/remote/vector_io/chroma/",
|
|
"^llama_stack/providers/remote/vector_io/milvus/",
|
|
"^llama_stack/providers/remote/vector_io/pgvector/",
|
|
"^llama_stack/providers/remote/vector_io/qdrant/",
|
|
"^llama_stack/providers/remote/vector_io/sample/",
|
|
"^llama_stack/providers/remote/vector_io/weaviate/",
|
|
"^llama_stack/providers/tests/conftest\\.py$",
|
|
"^llama_stack/providers/utils/bedrock/client\\.py$",
|
|
"^llama_stack/providers/utils/bedrock/refreshable_boto_session\\.py$",
|
|
"^llama_stack/providers/utils/inference/embedding_mixin\\.py$",
|
|
"^llama_stack/providers/utils/inference/litellm_openai_mixin\\.py$",
|
|
"^llama_stack/providers/utils/inference/model_registry\\.py$",
|
|
"^llama_stack/providers/utils/inference/openai_compat\\.py$",
|
|
"^llama_stack/providers/utils/inference/prompt_adapter\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/config\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/kvstore\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/mongodb/mongodb\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/postgres/postgres\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/redis/redis\\.py$",
|
|
"^llama_stack/providers/utils/kvstore/sqlite/sqlite\\.py$",
|
|
"^llama_stack/providers/utils/memory/vector_store\\.py$",
|
|
"^llama_stack/providers/utils/scoring/aggregation_utils\\.py$",
|
|
"^llama_stack/providers/utils/scoring/base_scoring_fn\\.py$",
|
|
"^llama_stack/providers/utils/telemetry/dataset_mixin\\.py$",
|
|
"^llama_stack/providers/utils/telemetry/trace_protocol\\.py$",
|
|
"^llama_stack/providers/utils/telemetry/tracing\\.py$",
|
|
"^llama_stack/strong_typing/auxiliary\\.py$",
|
|
"^llama_stack/strong_typing/deserializer\\.py$",
|
|
"^llama_stack/strong_typing/inspection\\.py$",
|
|
"^llama_stack/strong_typing/schema\\.py$",
|
|
"^llama_stack/strong_typing/serializer\\.py$",
|
|
"^llama_stack/templates/dev/dev\\.py$",
|
|
"^llama_stack/templates/groq/groq\\.py$",
|
|
"^llama_stack/templates/llama_api/llama_api\\.py$",
|
|
"^llama_stack/templates/sambanova/sambanova\\.py$",
|
|
"^llama_stack/templates/template\\.py$",
|
|
]
|
|
|
|
[[tool.mypy.overrides]]
|
|
# packages that lack typing annotations, do not have stubs, or are unavailable.
|
|
module = ["yaml", "fire"]
|
|
ignore_missing_imports = true
|
|
|
|
[tool.pydantic-mypy]
|
|
init_forbid_extra = true
|
|
init_typed = true
|
|
warn_required_dynamic_aliases = true
|
|
|
|
[tool.ruff.lint.pep8-naming]
|
|
classmethod-decorators = ["classmethod", "pydantic.field_validator"]
|