Langchain Monad

The LangchainT monad transformer providing unified environment configuration and error management.

Langchain.Core.Monad Control.Monad.Reader

The LangchainT monad transformer providing unified environment configuration and error management.

Key Concepts

LangchainT Transformer: Newtype wrapper around ReaderT env (ExceptT LangchainError m) a for compositional execution.
Decoupled Environment: Parametric over env, allowing providers and end-developers to supply their own specialized configs.
Typeclass Compatibility: Implements MonadReader, MonadError, MonadIO, and MonadTrans for smooth integration with your existing application monad stack.

Working Code Example

Compare local execution via Ollama and cloud API execution via OpenAI / OpenRouter. Use the toggle tabs or the global provider switcher in the header to switch:

{-# LANGUAGE OverloadedStrings #-}

module Ollama.Monad (runApp) where

import qualified Data.Text.IO as T
import Langchain.Prelude
import Langchain.Provider.Ollama

runApp :: IO ()
runApp = do
  o <- newOllama "gemma3" defaultConfig
  let msg = [userMessage "Write a poem about functional programming"]
  res <- runLangchainT () $ do
    let chatReq =
          withOptions
            (defaultOptions {optTemperature = Just 0.7, optTopP = Just 0.9, optNumCtx = Just 100096})
            (chatRequestFor o msg)
    invoke o msg (Just chatReq)
  case res of
    Left err -> T.putStrLn $ errorMessage err
    Right m -> T.putStrLn $ extractMessageText m

{-# LANGUAGE OverloadedStrings #-}

module OpenAI.Monad (runApp) where

import Data.Aeson (object, (.=))
import qualified Data.Text.IO as T
import Langchain.Prelude
import OpenAI.Common (defaultModelName, getOpenRouterModel)

runApp :: IO ()
runApp = do
  o <- getOpenRouterModel defaultModelName
  let msg = [userMessage "Write a poem about functional programming"]
  res <- runLangchainT () $ do
    let chatReq =
          object
            [ "temperature" .= (0.7 :: Double)
            , "top_p" .= (0.9 :: Double)
            , "max_tokens" .= (2048 :: Int)
            ]
    invoke o msg (Just chatReq)
  case res of
    Left err -> T.putStrLn $ errorMessage err
    Right m -> T.putStrLn $ extractMessageText m

Core Types & Functions

LangchainT { runLangchainT :: ReaderT env (ExceptT LangchainError m) a }

env -> LangchainT env m a -> m (Either LangchainError a)

Running This Example

Local Ollama

Ensure your Ollama daemon is running locally with the target model:

ollama run gemma3 # or your desired model
stack run monadollama

OpenAI / OpenRouter

Ensure your OPENROUTER_API_KEY or OPENAI_API_KEY is exported:

export OPENROUTER_API_KEY="your-api-key"
stack run monadopenai