azureml-rag 0.1.23

Contains Retrieval Augmented Generation related utilities for Azure Machine Learning and OSS interoperability.

AzureML Retrieval Augmented Generation Utilities

This package is in alpha stage at the moment, use at risk of breaking changes and unstable behavior.

It contains utilities for:

• Processing text documents into chunks appropriate for use in LLM prompts, with metadata such is source url.
• Embedding chunks with OpenAI or HuggingFace embeddings models, including the ability to update a set of embeddings over time.
• Create MLIndex artifacts from embeddings, a yaml file capturing metadata needed to deserialize different kinds of Vector Indexes for use in langchain. Supported Index types:
  • FAISS index (via langchain)
  • Azure Cognitive Search index

Getting started

You can install AzureMLs RAG package using pip.

pip install azureml-rag

There are various extra installs you probably want to include based on intended use:

• faiss: When using FAISS based Vector Indexes
• cognitive_search: When using Azure Cognitive Search Indexes
• hugging_face: When using Sentence Transformer embedding models from HuggingFace (local inference)
• document_parsing: When cracking and chunking documents locally to put in an Index

MLIndex

MLIndex files describe an index of data + embeddings and the embeddings model used in yaml.

embeddings:
  dimension: 768
  kind: hugging_face
  model: sentence-transformers/all-mpnet-base-v2
  schema_version: '2'
index:
  api_version: 2021-04-30-Preview
  connection:
    id: /subscriptions/<subscription_id>/resourceGroups/<resource_group>/providers/Microsoft.MachineLearningServices/workspaces/<workspace>/connections/<acs_connection_name>
  connection_type: workspace_connection
  endpoint: https://<acs_name>.search.windows.net
  engine: azure-sdk
  field_mapping:
    content: content
    filename: sourcefile
    metadata: meta_json_string
    title: title
    url: sourcepage
    embedding: content_vector_hugging_face
  index: azureml-rag-test-206e03b6-3880-407b-9bc4-c0a1162d6c70
  kind: acs

Create MLIndex

Examples using MLIndex remotely with AzureML and locally with langchain live here: https://github.com/Azure/azureml-examples/tree/main/sdk/python/generative-ai/rag

Consume MLIndex

from azureml.rag.mlindex import MLIndex

retriever = MLIndex(uri_to_folder_with_mlindex).as_langchain_retriever()
retriever.get_relevant_documents('What is an AzureML Compute Instance?')

Changelog

0.1.23

• Ensure tiktoken encodings are packaged in wheel

0.1.22

• Set environment variables to pull encodings files from directory with cache key to avoid tiktoken external network call
• Fix mlflow log error when there's no files input

0.1.21

• Fix top level imports in update_acs task failing without helpful reason when old azure-search-documents is installed.

0.1.20

• Fix Crack'n'Chunk race-condition where same named files would overwrite each other.

0.1.19

• Various bug fixes:
  • Handle some malformed git urls in git_clone task
  • Try fall back when parsing csv with pandas fails
  • Allow chunking special tokens
  • Ensure logging with mlflow can't fail a task
• Update to support latest azure-search-documents==11.4.0b8

0.1.18

• Add FaissAndDocStore and FileBasedDocStore which closely mirror langchains' FAISS and InMemoryDocStore without the langchain or pickle dependency. These are default not used until PromptFlow support has been added.
• Pin azure-documents-search==11.4.0b6 as there's breaking changes in 11.4.0b7 and 11.4.0b8

0.1.17

• Update interactions with Azure Cognitive Search to use latest azure-documents-search SDK

0.1.16

• Convert api_type from Workspace Connections to lower case to appease langchains case sensitive checking.

0.1.15

• Add support for custom loaders
• Added logging for MLIndex.init to understand usage of MLindex

0.1.14

• Add Support for CustomKeys connections
• Add OpenAI support for QA Gen and Embeddings

0.1.13 (2023-07-12)

• Implement single node non-PRS embed task to enable clearer logs for users.

0.1.12 (2023-06-29)

• Fix casing check of ApiVersion, ApiType in infer_deployment util

0.1.11 (2023-06-28)

• Update casing check for workspace connection ApiVersion, ApiType
• int casting for temperature, max_tokens

0.1.10 (2023-06-26)

• Update data asset registering to have adjustable output_type
• Remove asset registering from generate_qa.py

0.1.9 (2023-06-22)

• Add azureml.rag.data_generation module.
• Fixed bug that would cause crack_and_chunk to fail for documents that contain non-utf-8 characters. Currently these characters will be ignored.
• Improved heading extraction from Markdown files. When use_rcts=False Markdown files will be split on headings and each chunk with have the heading context up to the root as a prefix (e.g. # Heading 1\n## Heading 2\n# Heading 3\n{content})

0.1.8 (2023-06-21)

• Add deployment inferring util for use in azureml-insider notebooks.

0.1.7 (2023-06-08)

• Improved telemetry for tasks (used in RAG Pipeline Components)

0.1.6 (2023-05-31)

• Fail crack_and_chunk task when no files were processed (usually because of a malformed input_glob)
• Change update_acs.py to default push_embeddings=True instead of False.

0.1.5 (2023-05-19)

• Add api_base back to MLIndex embeddings config for back-compat (until all clients start getting it from Workspace Connection).
• Add telemetry for tasks used in pipeline components, not enabled by default for SDK usage.

0.1.4 (2023-05-17)

• Fix bug where enabling rcts option on split_documents used nltk splitter instead.

0.1.3 (2023-05-12)

• Support Workspace Connection based auth for Git, Azure OpenAI and Azure Cognitive Search usage.

0.1.2 (2023-05-05)

• Refactored document chunking to allow insertion of custom processing logic

0.0.1 (2023-04-25)

Features Added

• Introduced package
• langchain Retriever for Azure Cognitive Search