290 lines
4.7 KiB
Nix
290 lines
4.7 KiB
Nix
{ lib
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, buildPythonPackage
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, fetchFromGitHub
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, pythonRelaxDepsHook
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, hatchling
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, boilerpy3
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, events
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, httpx
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, jsonschema
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, lazy-imports
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, more-itertools
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, networkx
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, pandas
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, pillow
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, platformdirs
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, posthog
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, prompthub-py
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, pydantic
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, quantulum3
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, rank-bm25
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, requests
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, requests-cache
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, scikit-learn
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, sseclient-py
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, tenacity
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, tiktoken
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, tqdm
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, transformers
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, openai-whisper
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, boto3
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, botocore
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# , beir
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, selenium
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, coverage
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, dulwich
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# , jupytercontrib
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, mkdocs
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, mypy
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, pre-commit
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, psutil
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# , pydoc-markdown
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, pylint
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, pytest
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, pytest-asyncio
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, pytest-cov
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# , pytest-custom-exit-code
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, python-multipart
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, reno
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, responses
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, toml
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, tox
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, watchdog
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, elastic-transport
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, elasticsearch
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# , azure-ai-formrecognizer
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, beautifulsoup4
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, markdown
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, python-docx
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, python-frontmatter
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, python-magic
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, tika
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, black
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, huggingface-hub
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, sentence-transformers
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, mlflow
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, rapidfuzz
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, scipy
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, seqeval
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, pdf2image
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, pytesseract
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, faiss
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# , faiss-gpu
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, pinecone-client
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, onnxruntime
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, onnxruntime-tools
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# , onnxruntime-gpu
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, opensearch-py
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, pymupdf
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, langdetect
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, nltk
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, canals
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, jinja2
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, openai
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, aiorwlock
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, ray
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, psycopg2
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, sqlalchemy
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, sqlalchemy-utils
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, weaviate-client
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}:
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buildPythonPackage rec {
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pname = "farm-haystack";
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version = "1.23.0";
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pyproject = true;
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src = fetchFromGitHub {
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owner = "deepset-ai";
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repo = "haystack";
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rev = "refs/tags/v${version}";
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hash = "sha256-rZG7768kEV1fa9zyAu7DsXlX+2eV8FcDnEssGD2qvII=";
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};
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nativeBuildInputs = [
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hatchling
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pythonRelaxDepsHook
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];
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pythonRemoveDeps = [
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# We call it faiss, not faiss-cpu.
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"faiss-cpu"
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];
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propagatedBuildInputs = [
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boilerpy3
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events
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httpx
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jsonschema
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lazy-imports
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more-itertools
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networkx
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pandas
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pillow
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platformdirs
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posthog
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prompthub-py
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pydantic
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quantulum3
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rank-bm25
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requests
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requests-cache
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scikit-learn
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sseclient-py
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tenacity
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tiktoken
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tqdm
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transformers
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];
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env.HOME = "$(mktemp -d)";
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passthru.optional-dependencies = {
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# all = [
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# farm-haystack
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# ];
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# all-gpu = [
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# farm-haystack
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# ];
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audio = [
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openai-whisper
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];
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aws = [
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boto3
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botocore
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];
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# beir = [
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# beir
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# ];
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colab = [
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pillow
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];
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crawler = [
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selenium
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];
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dev = [
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coverage
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dulwich
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# jupytercontrib
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mkdocs
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mypy
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pre-commit
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psutil
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# pydoc-markdown
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pylint
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pytest
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pytest-asyncio
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pytest-cov
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# pytest-custom-exit-code
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python-multipart
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reno
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responses
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toml
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tox
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watchdog
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];
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elasticsearch7 = [
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elastic-transport
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elasticsearch
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];
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elasticsearch8 = [
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elastic-transport
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elasticsearch
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];
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file-conversion = [
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# azure-ai-formrecognizer
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beautifulsoup4
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markdown
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python-docx
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python-frontmatter
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python-magic
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# python-magic-bin
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tika
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];
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formatting = [
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black
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];
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inference = [
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huggingface-hub
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sentence-transformers
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transformers
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];
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metrics = [
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mlflow
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rapidfuzz
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scipy
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seqeval
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];
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ocr = [
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pdf2image
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pytesseract
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];
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only-faiss = [
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faiss
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];
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# only-faiss-gpu = [
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# faiss-gpu
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# ];
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only-pinecone = [
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pinecone-client
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];
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onnx = [
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onnxruntime
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onnxruntime-tools
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];
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# onnx-gpu = [
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# onnxruntime-gpu
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# onnxruntime-tools
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# ];
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opensearch = [
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opensearch-py
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];
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pdf = [
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pymupdf
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];
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preprocessing = [
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langdetect
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nltk
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];
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preview = [
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canals
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jinja2
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lazy-imports
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openai
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pandas
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rank-bm25
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requests
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tenacity
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tqdm
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];
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ray = [
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aiorwlock
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ray
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];
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sql = [
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psycopg2
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sqlalchemy
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sqlalchemy-utils
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];
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weaviate = [
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weaviate-client
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];
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};
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# the setup for test is intensive, hopefully can be done at some point
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doCheck = false;
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pythonImportsCheck = [ "haystack" ];
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meta = with lib; {
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description = "LLM orchestration framework to build customizable, production-ready LLM applications";
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longDescription = ''
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LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots
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'';
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changelog = "https://github.com/deepset-ai/haystack/releases/tag/${src.rev}";
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homepage = "https://github.com/deepset-ai/haystack";
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license = licenses.asl20;
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maintainers = with maintainers; [ happysalada ];
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};
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}
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