v0.6 Retrieval Components

[kreneskyp]

Retrieval Components

IX now supports loading retrieval components. Retrieval components allow the ingestion and querying of data for use in LLM contexts. This concept covers everything from reading source code to importing data from web services.

This release focuses on the core support for these types of components. Later releases will expand the set of support components as well as improved ingestion workflows.

Supported Components

• Parsers: LanguageParser
• Loaders: GenericLoader (files), WebBaseLoader (urls)
• Text Splitters: `RecursiveTextSplitter
• Vector store: Choma DB, Redis
• Embeddings: OpenAI and more.
• Chains: ConversationalRetrievalChain

Example chain: File Loader

Initial support is for a combined ingestion + querying in a single chain.

Loader (documents) -> Text Splitter (chunks) -> VectorStore (as retriever) -> Retrieval Chain 

Example chain: Web loader

Agent collaboration

This release introduces DelegateToAgentChain. A simple form of delegation between agents.

FastAPI

#155 #156 #157 #158 #159 #160 #162 #163 #164 #165 #167

FastAPI has replaced all GraphQL endpoints for REST based access. All UX components updated to use FastAPI along with updated React hooks for easy integration.

Streaming events (chat messages, message streams, artifact updates) still use a graphql subscription over websockets + django-channels. This remains the easiest solution for multi-user chat even if it means keeping graphql around.

Misc

• NodeTypeFields.get_fields improvements #169 Get fields simplify #174 - NodeTypeFields.get_fields can now import from Pydantic models, ABCs, and methods. This covers all the ways LangChain defines components and initializers

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This discussion was created from the release v0.6 Retrieval Components .