ReAct Agent

Reasoning and acting loop with dynamic tool selection and observation feedback.

Langchain.Agent.ReAct Langchain.Core.Tool

Reasoning and acting loop with dynamic tool selection and observation feedback.

Key Concepts

Thought-Action-Observation: Iterative cycle where the LLM reasons about the problem, chooses a tool, executes it, and reflects on the observation.
Stop Sequences: Halt generation cleanly after tool actions to allow the runtime to execute Haskell functions.
Step Bounds: Prevent infinite loops with max iteration limits and error recovery.

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 FlexibleContexts #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE UndecidableInstances #-}

module Ollama.ReAct (runApp) where

import Control.Monad.Except (runExceptT)
import qualified Data.Text.IO as T
import Langchain.Prelude
import Langchain.Tool.Calculator (calculatorTool)
import Langchain.Tool.FileSystem (readFileTool)

runApp :: IO ()
runApp = do
  writeFile "/tmp/budget.txt" "120 + 85"
  o <- newOllama "qwen3.5:2b" defaultConfig
  let tools = [readFileTool, calculatorTool]
      agent = createReActAgent o tools
      prompt =
        [ userMessage
            "Read the expression inside /tmp/budget.txt using read_file, then evaluate it using calculator."
        ]

  res <- runExceptT $ runReActAgent agent prompt
  case res of
    Left err -> T.putStrLn $ errorMessage err
    Right msg -> T.putStrLn $ extractMessageText msg

{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE UndecidableInstances #-}

module OpenAI.ReAct (runApp) where

import Control.Monad.Except (runExceptT)
import qualified Data.Text.IO as T
import Langchain.Prelude
import Langchain.Tool.Calculator (calculatorTool)
import Langchain.Tool.FileSystem (readFileTool)
import OpenAI.Common (defaultModelName, getOpenRouterModel)

runApp :: IO ()
runApp = do
  writeFile "/tmp/budget.txt" "120 + 85"
  o <- getOpenRouterModel defaultModelName
  let tools = [readFileTool, calculatorTool]
      agent = createReActAgent o tools
      prompt =
        [ userMessage
            "Read the expression inside /tmp/budget.txt using read_file, then evaluate it using calculator."
        ]

  res <- runExceptT $ runReActAgent agent prompt
  case res of
    Left err -> T.putStrLn $ errorMessage err
    Right msg -> T.putStrLn $ extractMessageText msg

Core Types & Functions

ChatModel m => m -> [Tool] -> Text -> IO (Either LangchainError Text)

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 reactollama

OpenAI / OpenRouter

Ensure your OPENROUTER_API_KEY or OPENAI_API_KEY is exported:

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