GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
LangChain-HS offers a unique implementation in Haskell, bringing functional programming paradigms to AI development.
Good fit when
- You require a robust AI functionality with a preference or need for functional programming approaches
- Your project is already built on Haskell and you wish to integrate AI without switching languages
Avoid when
- When your team lacks experience with functional programming as Haskell requires a different mindset compared to imperative languages.
- If performance optimization is the top priority, given that Haskell might not match the speed of languages like Python in all scenarios.
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (1d since push)
- As of Sep 8, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 8, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/tusharad/langchain-hsSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
An open-source library implementing LangChain in Haskell, enabling developers to integrate AI functionalities using functional programming.
Capability facts
- Languages
- haskell
Source: github.language · Sep 8, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 8, 2026)
import Langchain.PreludeSource link
Tags
README
1. Plan and Execute Agent
For agents
This page has a .md twin and JSON over the API.