rig-core 0.35.0

An opinionated library for building LLM powered applications.
Documentation 
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use crate::{
    agent::Agent,
    completion::{CompletionModel, Prompt, PromptError, ToolDefinition},
    tool::Tool,
};
use schemars::{JsonSchema, schema_for};
use serde::{Deserialize, Serialize};

#[derive(Debug, Clone, Serialize, Deserialize, JsonSchema)]
pub struct AgentToolArgs {
    /// The prompt for the agent to call.
    prompt: String,
}

impl<M: CompletionModel + 'static> Tool for Agent<M> {
    const NAME: &'static str = "agent_tool";

    type Error = PromptError;
    type Args = AgentToolArgs;
    type Output = String;

    async fn definition(&self, _prompt: String) -> ToolDefinition {
        let description = format!(
            "
            Prompt a sub-agent to do a task for you.

            Agent name: {name}
            Agent description: {description}
            Agent system prompt: {sysprompt}
            ",
            name = self.name(),
            description = self.description.clone().unwrap_or_default(),
            sysprompt = self.preamble.clone().unwrap_or_default()
        );
        ToolDefinition {
            name: <Self as Tool>::name(self),
            description,
            parameters: serde_json::to_value(schema_for!(AgentToolArgs))
                .expect("converting JSON schema to JSON value should never fail"),
        }
    }

    async fn call(&self, args: Self::Args) -> Result<Self::Output, Self::Error> {
        self.prompt(args.prompt).await
    }

    fn name(&self) -> String {
        self.name.clone().unwrap_or_else(|| Self::NAME.to_string())
    }
}