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langchain-hs-core: Core typeclasses and pure AST primitives for langchain-hs

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Zero HTTP dependency core package containing ChatModel, RunnableTree, ContentBlock, Tool, and StreamEvent primitives.

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Versions [RSS] 0.0.5.0, 0.0.6.0
Change log CHANGELOG.md
Dependencies aeson (>=2.0 && <3), async (>=2.2 && <2.3), base (>=4.17 && <5), base64-bytestring (>=1.2 && <1.3), bytestring (>=0.10 && <0.13), conduit (>=1.3 && <1.4), containers (>=0.6 && <0.9), directory (>=1.3 && <1.4), filepath (>=1.4 && <2), format-heavy (>=0.1 && <0.2), mtl (>=2.2 && <2.4), process (>=1.6 && <1.7), random (>=1.2 && <1.4), resourcet (>=1.2 && <1.4), scientific (>=0.3 && <0.4), sqlite-simple (>=0.4.18 && <0.5), stm (>=2.5 && <2.6), text (>=1.2 && <3), time (>=1.9 && <1.15) [details]
Tested with ghc ==9.12.4, ghc ==9.10.3, ghc ==9.8.4
License MIT
Copyright 2025-2026 Tushar Adhatrao
Author Tushar Adhatrao
Maintainer tusharadhatrao@gmail.com
Uploaded by tusharad at 2026-10-14T21:33:30Z
Category Web, AI, Control
Home page https://github.com/tusharad/langchain-hs#readme
Bug tracker https://github.com/tusharad/langchain-hs/issues
Source repo head: git clone https://github.com/tusharad/langchain-hs
Distributions Stackage:0.0.6.0
Reverse Dependencies 6 direct, 0 indirect [details]
Downloads 17 total (12 in the last 30 days)
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Readme for langchain-hs-core-0.0.6.0

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langchain-hs-core

The foundational, effect-polymorphic core framework of the langchain-hs AI ecosystem.

langchain-hs-core provides pure GADT abstract syntax trees, effect-polymorphic chat models, streaming protocols, tools, agents, vector stores, retrievers, document loaders, memory, cache, output parsers, guardrails, resilience, observability, and the canonical Langchain.Prelude without concrete provider-specific dependencies.

Key Primitives & Modules

  • Runnables & Pure ASTs (Langchain.Runnable): Pure GADT abstract syntax tree (RunnableTree m i o) for pipeline composition via |>> (sequential), &>& (parallel fan-out), runLambda, runPrim, and deferred evaluation via interpret.
  • Chat Models & Types (Langchain.Model, Langchain.Model.Types): Effect-polymorphic ChatModel typeclass, Message, Role, ContentBlock (multi-modal text, images, tool calls, tool results).
  • Streaming Protocols (Langchain.Stream): Conduit-based incremental token streaming via StreamEvent and LLMChunk.
  • Tools & Dynamic Calling (Langchain.Tool, Langchain.Tool.Binding): Effect-polymorphic Tool m, createTool, Generic Schemas, and built-in tools (Calculator, FileSystem, Shell). Provider-agnostic tool binding via ToolBinder.
  • Agents (Langchain.Agent.ReAct, Langchain.Agent.PlanAndExecute):
    • ReAct Agent: Full reasoning + acting agent loop with tool inspection, memory integration, callbacks, and step traces.
    • Plan-and-Execute Agent: Two-phase agent decomposing complex user goals into discrete execution plans.
  • Prompt Templates (Langchain.PromptTemplate): String prompt templates with {var} f-string interpolation and pre-bound partial variables.
  • Vector Stores (Langchain.VectorStore): Abstract VectorStore typeclass and thread-safe InMemoryVectorStore.
  • Retrievers (Langchain.Retriever): BM25 keyword search (BM25Retriever), vector similarity retriever, and Reciprocal Rank Fusion (HybridRetriever).
  • Document Loaders & Text Splitters (Langchain.DocumentLoader, Langchain.TextSplitter): Document metadata abstraction and splitters for character chunks, Markdown, programming code, and tokens.
  • Memory & Cache (Langchain.Memory, Langchain.Cache): BaseMemory, ConversationBufferMemory, WindowBufferMemory, and STM-backed in-memory LLMCache.
  • Output Parsers (Langchain.OutputParser): Strongly typed JSON Schema generation (JsonOutputParser) and structured parsing.
  • Guardrails & Safety (Langchain.Guardrails): Input and output content moderation, PII redaction, and semantic safety validations.
  • Resilience & Fault Tolerance (Langchain.Resilience): State-machine CircuitBreaker, exponential backoff RetryConfig, and fallback handlers.
  • Observability & Tracing (Langchain.Observability, Langchain.Callback): OpenTelemetry distributed tracing spans, structured JSON event logging, and lifecycle event callbacks.
  • Chains (Langchain.Chain.RetrievalQA): End-to-end question answering pipeline over indexed knowledge bases.
  • Langchain Monad (Langchain.Monad): Decoupled LangchainT env m a reader and error transformer.
  • Canonical Prelude (Langchain.Prelude): Batteries-included single-import entry point providing the full core framework API.

Installation

Add to your cabal or package.yaml dependencies:

build-depends:
    langchain-hs-core >= 0.0.6.0 && < 0.0.7.0

To connect concrete LLMs, combine with satellite provider packages:

  • langchain-hs-ollama: Local & offline models (Llama 3, DeepSeek, Gemma).
  • langchain-hs-openai: OpenAI, OpenRouter, and OpenAI-compatible cloud endpoints.
  • langchain-hs-gemini: Google Gemini with multi-modal support.
  • langchain-hs-mcp: Model Context Protocol tool client.

For cyclic state machines, checkpointers, and multi-agent coordination, add langchain-hs-graph (or use the umbrella langchain-hs package).

License

Distributed under the MIT License. See LICENSE for details.