Documentation Index Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
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Agent
Defined in the agent
Rust AI Agent SDK
The core Agent struct Agents are the primary execution unit in PraisonAI. They combine: - LLM provider for generating responses - Tools for performing actions - Memory for conversation history - Instructions for behavior
Fields Name Type Description idStringUnique agent ID nameStringAgent name instructionsStringSystem instructions llmArc<dyn LlmProvider>LLM provider toolsArc<RwLock<ToolRegistry>>Tool registry memoryArc<RwLock<Memory>>Memory configAgentConfigConfiguration
Methods newCreate a new agent builder
simplefn simple ( instructions : impl Into < String >) -> Result < Self >
Create an agent with minimal config
Parameters: Name Type instructionsimpl Into<String>
Get the agent ID
nameGet the agent name
instructionsfn instructions ( & self ) -> & str
Get the instructions
modelGet the LLM model name
chatasync fn chat ( & self , prompt : & str ) -> Result < String >
Chat with the agent (main entry point) This is the primary method for interacting with an agent. It handles the full conversation loop including tool calls.
Parameters: startasync fn start ( & self , prompt : & str ) -> Result < String >
Start a conversation (alias for chat)
Parameters: runasync fn run ( & self , task : & str ) -> Result < String >
Run a task (alias for chat)
Parameters: async fn add_tool ( & self , tool : impl Tool + ' static ) -> ()
Add a tool to the agent
Parameters: Name Type toolimpl Tool + 'static
async fn tool_count ( & self ) -> usize
Get the number of tools
clear_memoryasync fn clear_memory ( & self ) -> Result <()>
Clear conversation memory
historyasync fn history ( & self ) -> Result < Vec < Message >>
Get conversation history
Source
View on GitHub praisonai/src/agent/mod.rs at line 39
