mirror of
https://github.com/hwchase17/langchain
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66c41c0dbf
This PR adds a self-querying template using Qdrant as a vector store. The template uses an artificial dataset and was implemented in a way that simplifies passing different components and choosing LLM and embedding providers. --------- Co-authored-by: Erick Friis <erick@langchain.dev>
33 lines
734 B
TOML
33 lines
734 B
TOML
[tool.poetry]
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name = "self-query-qdrant"
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version = "0.1.0"
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description = "Self-querying retriever using Qdrant"
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authors = ["Kacper Łukawski <lukawski.kacper@gmail.com>"]
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license = "Apache 2.0"
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readme = "README.md"
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packages = [{include = "self_query_qdrant"}]
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[tool.poetry.dependencies]
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python = ">=3.9,<3.13"
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langchain = ">=0.0.325"
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openai = "^0.28.1"
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qdrant-client = ">=1.6"
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lark = "^1.1.8"
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tiktoken = "^0.5.1"
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[tool.poetry.group.dev.dependencies]
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langchain-cli = ">=0.0.15"
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[tool.poetry.group.dev.dependencies.python-dotenv]
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extras = [
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"cli",
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]
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version = "^1.0.0"
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[tool.langserve]
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export_module = "self_query_qdrant"
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export_attr = "chain"
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[build-system]
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requires = ["poetry-core"]
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build-backend = "poetry.core.masonry.api"
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