Copyright	(c) 2025 Tushar Adhatrao
License	MIT
Maintainer	Tushar Adhatrao <tusharadhatrao@gmail.com>
Safe Haskell	Safe-Inferred
Language	Haskell2010

Langchain.Agents.Core

Description

Agents use LLMs as reasoning engines to determine actions dynamically This module implements the core agent execution loop and interfaces, supporting tool interaction and memory management.

Example agent execution flow:

executor <- AgentExecutor
  { executor = myAgent
  , executorMemory = emptyMemory
  , maxIterations = 5
  , returnIntermediateSteps = True
  }
result <- runAgentExecutor executor "Explain quantum computing"

Synopsis

data AgentAction = AgentAction {
- actionToolName :: Text
- actionInput :: Text
- actionLog :: Text
}
data AgentFinish = AgentFinish {
- returnValues :: Map Text Text
- finishLog :: Text
}
data AgentStep
- = Continue AgentAction
- | Finish AgentFinish
class Agent a where
- planNextAction :: BaseMemory m => a -> AgentState m -> IO (Either String AgentStep)
- agentPrompt :: a -> IO PromptTemplate
- agentTools :: a -> IO [AnyTool]
data AnyTool = forall a.Tool a => AnyTool {
- anyTool :: a
- textToInput :: Text -> Input a
- outputToText :: Output a -> Text
}
data BaseMemory m => AgentState m = AgentState {
- agentMemory :: m
- agentToolResults :: [(Text, Text)]
- agentSteps :: [AgentAction]
}
data AgentExecutor a m = AgentExecutor {
- executor :: a
- executorMemory :: m
- maxIterations :: Int
- returnIntermediateSteps :: Bool
}
runAgent :: (Agent a, BaseMemory m) => a -> AgentState m -> Text -> IO (Either String AgentFinish)
runAgentLoop :: (Agent a, BaseMemory m) => a -> AgentState m -> Int -> Int -> IO (Either String AgentFinish)
runAgentExecutor :: (Agent a, BaseMemory m) => AgentExecutor a m -> Text -> IO (Either String (Maybe AgentFinish))
executeTool :: [AnyTool] -> Text -> Text -> IO (Either String Text)
runSingleStep :: (Agent a, BaseMemory m) => a -> AgentState m -> IO (Either String AgentStep)
customAnyTool :: Tool a => a -> (Text -> Input a) -> (Output a -> Text) -> AnyTool

Documentation

data AgentAction Source #

Represents an action to be taken by the agent

Constructors

AgentAction
Fields actionToolName :: Text Tool name actionInput :: Text Input actionLog :: Text Execution log

Instances

Instances details

Show AgentAction Source #
Instance details Defined in Langchain.Agents.Core Methods showsPrec :: Int -> AgentAction -> ShowS # show :: AgentAction -> String # showList :: [AgentAction] -> ShowS #
Eq AgentAction Source #
Instance details Defined in Langchain.Agents.Core Methods (==) :: AgentAction -> AgentAction -> Bool # (/=) :: AgentAction -> AgentAction -> Bool #

data AgentFinish Source #

Represents that agent has finished work with final value

Constructors

AgentFinish
Fields returnValues :: Map Text Text finishLog :: Text

Instances

Instances details

Show AgentFinish Source #
Instance details Defined in Langchain.Agents.Core Methods showsPrec :: Int -> AgentFinish -> ShowS # show :: AgentFinish -> String # showList :: [AgentFinish] -> ShowS #
Eq AgentFinish Source #
Instance details Defined in Langchain.Agents.Core Methods (==) :: AgentFinish -> AgentFinish -> Bool # (/=) :: AgentFinish -> AgentFinish -> Bool #

data AgentStep Source #

Type that will be return from LLM Could be either Continue, making another call to LLM or Finish with final value

Constructors

Continue AgentAction
Finish AgentFinish

Instances

Instances details

Show AgentStep Source #
Instance details Defined in Langchain.Agents.Core Methods showsPrec :: Int -> AgentStep -> ShowS # show :: AgentStep -> String # showList :: [AgentStep] -> ShowS #
Eq AgentStep Source #
Instance details Defined in Langchain.Agents.Core Methods (==) :: AgentStep -> AgentStep -> Bool # (/=) :: AgentStep -> AgentStep -> Bool #

class Agent a where Source #

Core agent class defining required operations

Plan next action based on state
Provide prompt template
Expose available tools

Methods

planNextAction :: BaseMemory m => a -> AgentState m -> IO (Either String AgentStep) Source #

agentPrompt :: a -> IO PromptTemplate Source #

agentTools :: a -> IO [AnyTool] Source #

Instances

Instances details

LLM llm => Agent (ReactAgent llm) Source #
Instance details Defined in Langchain.Agents.React Methods planNextAction :: BaseMemory m => ReactAgent llm -> AgentState m -> IO (Either String AgentStep) Source # agentPrompt :: ReactAgent llm -> IO PromptTemplate Source # agentTools :: ReactAgent llm -> IO [AnyTool] Source #

data AnyTool Source #

Dynamic tool wrapper allowing heterogeneous tool collections Converts between Text and tool-specific input/output types.

Example usage:

calculatorTool :: AnyTool
calculatorTool = customAnyTool
  Calculator
  (\t -> read (T.unpack t) :: (Int, Int))
  (T.pack . show)

Constructors

forall a.Tool a => AnyTool
Fields anyTool :: a textToInput :: Text -> Input a outputToText :: Output a -> Text

data BaseMemory m => AgentState m Source #

Type for maintaining state of the agent

Constructors

AgentState
Fields agentMemory :: m Memory for storing chat history agentToolResults :: [(Text, Text)] Tool results agentSteps :: [AgentAction] Agent steps happened so far

Instances

Instances details

(BaseMemory m, Show m) => Show (AgentState m) Source #
Instance details Defined in Langchain.Agents.Core Methods showsPrec :: Int -> AgentState m -> ShowS # show :: AgentState m -> String # showList :: [AgentState m] -> ShowS #
(BaseMemory m, Eq m) => Eq (AgentState m) Source #
Instance details Defined in Langchain.Agents.Core Methods (==) :: AgentState m -> AgentState m -> Bool # (/=) :: AgentState m -> AgentState m -> Bool #

data AgentExecutor a m Source #

Agent execution engine

Constructors

AgentExecutor
Fields executor :: a executorMemory :: m Memory state maxIterations :: Int Iteration limits returnIntermediateSteps :: Bool Step tracking

Instances

Instances details

(Show a, Show m) => Show (AgentExecutor a m) Source #
Instance details Defined in Langchain.Agents.Core Methods showsPrec :: Int -> AgentExecutor a m -> ShowS # show :: AgentExecutor a m -> String # showList :: [AgentExecutor a m] -> ShowS #
(Eq a, Eq m) => Eq (AgentExecutor a m) Source #
Instance details Defined in Langchain.Agents.Core Methods (==) :: AgentExecutor a m -> AgentExecutor a m -> Bool # (/=) :: AgentExecutor a m -> AgentExecutor a m -> Bool #
(Agent a, BaseMemory m) => Runnable (AgentExecutor a m) Source #	Runnable instance for agent execution Allows integration with LangChain workflows. Example: response <- invoke myAgentExecutor "Solve 5+3" case response of Right result -> print result Left err -> print err
Instance details Defined in Langchain.Agents.Core Associated Types type RunnableInput (AgentExecutor a m) Source # type RunnableOutput (AgentExecutor a m) Source # Methods invoke :: AgentExecutor a m -> RunnableInput (AgentExecutor a m) -> IO (Either String (RunnableOutput (AgentExecutor a m))) Source # batch :: AgentExecutor a m -> [RunnableInput (AgentExecutor a m)] -> IO (Either String [RunnableOutput (AgentExecutor a m)]) Source # stream :: AgentExecutor a m -> RunnableInput (AgentExecutor a m) -> (RunnableOutput (AgentExecutor a m) -> IO ()) -> IO (Either String ()) Source #
type RunnableInput (AgentExecutor a m) Source #
Instance details Defined in Langchain.Agents.Core type RunnableInput (AgentExecutor a m) = Text
type RunnableOutput (AgentExecutor a m) Source #
Instance details Defined in Langchain.Agents.Core type RunnableOutput (AgentExecutor a m) = AgentFinish

runAgent :: (Agent a, BaseMemory m) => a -> AgentState m -> Text -> IO (Either String AgentFinish) Source #

Run the full agent execution loop Handles:

Memory updates
Action planning
Tool execution
Iteration control

Example flow:

User input -> memory
Plan action -> execute tool
Store result -> memory
Repeat until finish

Throws errors for:

Tool not found [[5]]
Execution errors
Iteration limits

runAgentLoop :: (Agent a, BaseMemory m) => a -> AgentState m -> Int -> Int -> IO (Either String AgentFinish) Source #

Helper function for runAgent

runAgentExecutor :: (Agent a, BaseMemory m) => AgentExecutor a m -> Text -> IO (Either String (Maybe AgentFinish)) Source #

Similar to runAgent, but for AgentExecutor

executeTool :: [AnyTool] -> Text -> Text -> IO (Either String Text) Source #

Execute a single tool call Handles tool lookup and input/output conversion.

Example:

tools = [calculatorTool, wikipediaTool]
executeTool tools "calculator" "(5, 3)"
-- Returns Right "8"

runSingleStep :: (Agent a, BaseMemory m) => a -> AgentState m -> IO (Either String AgentStep) Source #

Alias for planNextAction

customAnyTool :: Tool a => a -> (Text -> Input a) -> (Output a -> Text) -> AnyTool Source #

Helper for creating custom tool wrappers Requires conversion functions between Text and tool-specific types.

Example:

weatherTool = customAnyTool
  WeatherAPI
  parseLocation
  formatWeatherResponse