langchain/templates/nvidia-rag-canonical/pyproject.toml

[tool.poetry]
name = "nvidia-rag-canonical"
version = "0.1.0"
description = "RAG with NVIDIA"
authors = ["Sagar Bogadi Manjunath <sbogadimanju@nvidia.com>"]
readme = "README.md"

[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
pymilvus = ">=2.3.0"
langchain-nvidia-aiplay = "^0.0.2"
pypdf = ">=4.0.1"
langchain-text-splitters = ">=0.0.1,<0.1"

[tool.poetry.group.dev.dependencies]
langchain-cli = ">=0.0.21"

[tool.langserve]
export_module = "nvidia_rag_canonical"
export_attr = "chain"

[tool.templates-hub]
use-case = "rag"
author = "LangChain"
integrations = ["Milvus", "NVIDIA"]
tags = ["vectordbs"]

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
templates: Add NVIDIA Canonical RAG example chain (#15758) - Description: Adds a RAG template that uses NVIDIA AI playground and embedding models, along with Milvus vector store - Dependencies: This template depends on the AI playground service in NVIDIA NGC. API keys with a significant trial compute are available (10k queries at the time of writing). This template also depends on the Milvus Vector store which is publicly available. Note: [A quick link to get a key](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/codellama-13b/api) when you have an NGC account. Generate Key button at the top right of the code window. --------- Co-authored-by: Sagar B Manjunath <sbogadimanju@nvidia.com> Co-authored-by: Erick Friis <erick@langchain.dev> 2024-01-11 02:39:16 +00:00			`[tool.poetry]`
			`name = "nvidia-rag-canonical"`
			`version = "0.1.0"`
			`description = "RAG with NVIDIA"`
			`authors = ["Sagar Bogadi Manjunath <sbogadimanju@nvidia.com>"]`
			`readme = "README.md"`

			`[tool.poetry.dependencies]`
			`python = ">=3.8.1,<4.0"`
			`langchain = "^0.1"`
			`pymilvus = ">=2.3.0"`
			`langchain-nvidia-aiplay = "^0.0.2"`
community: support advanced text extraction options for pdf documents (#20265) Description: - Updated constructors in PyPDFParser and PyPDFLoader to handle `extraction_mode` and additional kwargs, aligning with the capabilities of `PageObject.extract_text()` from pypdf. - Added `test_pypdf_loader_with_layout` along with a corresponding example text file to validate layout extraction from PDFs. Issue: fixes #19735 Dependencies: This change requires updating the pypdf dependency from version 3.4.0 to at least 4.0.0. Additional changes include the addition of a new test test_pypdf_loader_with_layout and an example text file to ensure the functionality of layout extraction from PDFs aligns with the new capabilities. --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev> 2024-07-17 20:47:09 +00:00			`pypdf = ">=4.0.1"`
templates: use langchain-text-splitters (#18360) - deps - import - import 2024-03-01 03:00:58 +00:00			`langchain-text-splitters = ">=0.0.1,<0.1"`
templates: Add NVIDIA Canonical RAG example chain (#15758) - Description: Adds a RAG template that uses NVIDIA AI playground and embedding models, along with Milvus vector store - Dependencies: This template depends on the AI playground service in NVIDIA NGC. API keys with a significant trial compute are available (10k queries at the time of writing). This template also depends on the Milvus Vector store which is publicly available. Note: [A quick link to get a key](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/codellama-13b/api) when you have an NGC account. Generate Key button at the top right of the code window. --------- Co-authored-by: Sagar B Manjunath <sbogadimanju@nvidia.com> Co-authored-by: Erick Friis <erick@langchain.dev> 2024-01-11 02:39:16 +00:00
			`[tool.poetry.group.dev.dependencies]`
templates: bump (#17074) 2024-02-06 01:12:12 +00:00			`langchain-cli = ">=0.0.21"`
templates: Add NVIDIA Canonical RAG example chain (#15758) - Description: Adds a RAG template that uses NVIDIA AI playground and embedding models, along with Milvus vector store - Dependencies: This template depends on the AI playground service in NVIDIA NGC. API keys with a significant trial compute are available (10k queries at the time of writing). This template also depends on the Milvus Vector store which is publicly available. Note: [A quick link to get a key](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/codellama-13b/api) when you have an NGC account. Generate Key button at the top right of the code window. --------- Co-authored-by: Sagar B Manjunath <sbogadimanju@nvidia.com> Co-authored-by: Erick Friis <erick@langchain.dev> 2024-01-11 02:39:16 +00:00
			`[tool.langserve]`
			`export_module = "nvidia_rag_canonical"`
			`export_attr = "chain"`

			`[tool.templates-hub]`
			`use-case = "rag"`
			`author = "LangChain"`
			`integrations = ["Milvus", "NVIDIA"]`
			`tags = ["vectordbs"]`

			`[build-system]`
			`requires = ["poetry-core"]`
			`build-backend = "poetry.core.masonry.api"`