Struct OpenApiToolset 

pub struct OpenApiToolset { /* private fields */ }

A set of tools generated from an OpenAPI specification.

Each operation in the spec becomes a tool that can be registered with a rig agent. The toolset is designed to be parsed once and reused across requests.

Implementations

impl OpenApiToolset

pub fn from_file(path: impl AsRef<Path>) -> Result<Self>

Parse an OpenAPI spec from a YAML or JSON file.

Examples found in repository

examples/jsonplaceholder.rs (line 9)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    let toolset = OpenApiToolset::from_file("examples/openapi.yaml")?;
    println!("Loaded {} tools from OpenAPI spec", toolset.len());

    let agent = openai
        .agent("gpt-4o")
        .preamble("You have access to API tools. Use them when asked.")
        .tools(toolset.into_tools())
        .build();

    let response: String = agent
        .prompt("Use the API tool to get user 1 and summarize the result.")
        .await?;

    println!("{response}");

    Ok(())
}

pub fn from_spec_str(spec_str: &str) -> Result<Self>

Parse an OpenAPI spec from a YAML or JSON string.

pub fn builder(spec_str: &str) -> OpenApiToolsetBuilder

Start building a toolset from a YAML or JSON string with configuration options.

pub fn builder_from_file( path: impl AsRef<Path>, ) -> Result<OpenApiToolsetBuilder>

Start building a toolset from a file with configuration options.

Examples found in repository

examples/petstore.rs (line 12)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    // Parse once at startup — reuse across requests
    let toolset = OpenApiToolset::builder_from_file("examples/petstore.json")?
        .base_url("https://petstore3.swagger.io/api/v3")
        .build()?;

    println!("Loaded {} tools from Petstore spec\n", toolset.len());

    // Simulate a per-request context (e.g. from a logged-in user session)
    let visible_ctx = HashMap::from([
        ("username".to_string(), "user1".to_string()),
        ("preferred_status".to_string(), "available".to_string()),
    ]);
    let context_preamble = OpenApiToolset::context_preamble(&visible_ctx);

    let preamble = format!(
        "You have access to the Swagger Petstore API. \
         Use the available tools to answer questions about the pet store.\n\n\
         {context_preamble}"
    );

    // Create agent with per-request tools (cheap clone)
    let agent = openai
        .agent("gpt-4o")
        .preamble(&preamble)
        .tools(toolset.tools_with_context(&HashMap::new()))
        .build();

    let prompts = [
        "What pets are currently available in the store? Show me the first 3.",
        "Get the store inventory and tell me the status counts.",
        "Look up my user profile and summarize it.",
    ];

    for prompt in prompts {
        println!(">>> {prompt}");
        let response: String = agent.prompt(prompt).await?;
        println!("{response}\n");
    }

    Ok(())
}

pub fn len(&self) -> usize

Return the number of tools parsed from the spec.

Examples found in repository

examples/jsonplaceholder.rs (line 10)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    let toolset = OpenApiToolset::from_file("examples/openapi.yaml")?;
    println!("Loaded {} tools from OpenAPI spec", toolset.len());

    let agent = openai
        .agent("gpt-4o")
        .preamble("You have access to API tools. Use them when asked.")
        .tools(toolset.into_tools())
        .build();

    let response: String = agent
        .prompt("Use the API tool to get user 1 and summarize the result.")
        .await?;

    println!("{response}");

    Ok(())
}

examples/petstore.rs (line 16)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    // Parse once at startup — reuse across requests
    let toolset = OpenApiToolset::builder_from_file("examples/petstore.json")?
        .base_url("https://petstore3.swagger.io/api/v3")
        .build()?;

    println!("Loaded {} tools from Petstore spec\n", toolset.len());

    // Simulate a per-request context (e.g. from a logged-in user session)
    let visible_ctx = HashMap::from([
        ("username".to_string(), "user1".to_string()),
        ("preferred_status".to_string(), "available".to_string()),
    ]);
    let context_preamble = OpenApiToolset::context_preamble(&visible_ctx);

    let preamble = format!(
        "You have access to the Swagger Petstore API. \
         Use the available tools to answer questions about the pet store.\n\n\
         {context_preamble}"
    );

    // Create agent with per-request tools (cheap clone)
    let agent = openai
        .agent("gpt-4o")
        .preamble(&preamble)
        .tools(toolset.tools_with_context(&HashMap::new()))
        .build();

    let prompts = [
        "What pets are currently available in the store? Show me the first 3.",
        "Get the store inventory and tell me the status counts.",
        "Look up my user profile and summarize it.",
    ];

    for prompt in prompts {
        println!(">>> {prompt}");
        let response: String = agent.prompt(prompt).await?;
        println!("{response}\n");
    }

    Ok(())
}

pub fn is_empty(&self) -> bool

Returns true if no operations were found in the spec.

pub fn into_tools(self) -> Vec<Box<dyn ToolDyn>>

Consume the toolset and return tools for use with rig’s AgentBuilder::tools().

Examples found in repository

examples/jsonplaceholder.rs (line 15)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    let toolset = OpenApiToolset::from_file("examples/openapi.yaml")?;
    println!("Loaded {} tools from OpenAPI spec", toolset.len());

    let agent = openai
        .agent("gpt-4o")
        .preamble("You have access to API tools. Use them when asked.")
        .tools(toolset.into_tools())
        .build();

    let response: String = agent
        .prompt("Use the API tool to get user 1 and summarize the result.")
        .await?;

    println!("{response}");

    Ok(())
}

pub fn tools_with_context( &self, context: &HashMap<String, String>, ) -> Vec<Box<dyn ToolDyn>>

Clone the tools with per-request context injected as hidden parameters. The LLM will not see these parameters in tool schemas, but they will be auto-injected into every tool call at execution time.

This is the primary way to add per-request state (user ID, session info, etc.) while reusing the parsed toolset across requests.

Examples found in repository

examples/petstore.rs (line 35)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    // Parse once at startup — reuse across requests
    let toolset = OpenApiToolset::builder_from_file("examples/petstore.json")?
        .base_url("https://petstore3.swagger.io/api/v3")
        .build()?;

    println!("Loaded {} tools from Petstore spec\n", toolset.len());

    // Simulate a per-request context (e.g. from a logged-in user session)
    let visible_ctx = HashMap::from([
        ("username".to_string(), "user1".to_string()),
        ("preferred_status".to_string(), "available".to_string()),
    ]);
    let context_preamble = OpenApiToolset::context_preamble(&visible_ctx);

    let preamble = format!(
        "You have access to the Swagger Petstore API. \
         Use the available tools to answer questions about the pet store.\n\n\
         {context_preamble}"
    );

    // Create agent with per-request tools (cheap clone)
    let agent = openai
        .agent("gpt-4o")
        .preamble(&preamble)
        .tools(toolset.tools_with_context(&HashMap::new()))
        .build();

    let prompts = [
        "What pets are currently available in the store? Show me the first 3.",
        "Get the store inventory and tell me the status counts.",
        "Look up my user profile and summarize it.",
    ];

    for prompt in prompts {
        println!(">>> {prompt}");
        let response: String = agent.prompt(prompt).await?;
        println!("{response}\n");
    }

    Ok(())
}

pub fn context_preamble(context: &HashMap<String, String>) -> String

Generate a preamble snippet describing the visible context for the LLM. Include this in your agent’s .preamble() so the LLM knows about available context values it can use when calling tools.

Examples found in repository

examples/petstore.rs (line 23)

async fn main() -> anyhow::Result<()> {
    let openai = rig::providers::openai::Client::from_env();

    // Parse once at startup — reuse across requests
    let toolset = OpenApiToolset::builder_from_file("examples/petstore.json")?
        .base_url("https://petstore3.swagger.io/api/v3")
        .build()?;

    println!("Loaded {} tools from Petstore spec\n", toolset.len());

    // Simulate a per-request context (e.g. from a logged-in user session)
    let visible_ctx = HashMap::from([
        ("username".to_string(), "user1".to_string()),
        ("preferred_status".to_string(), "available".to_string()),
    ]);
    let context_preamble = OpenApiToolset::context_preamble(&visible_ctx);

    let preamble = format!(
        "You have access to the Swagger Petstore API. \
         Use the available tools to answer questions about the pet store.\n\n\
         {context_preamble}"
    );

    // Create agent with per-request tools (cheap clone)
    let agent = openai
        .agent("gpt-4o")
        .preamble(&preamble)
        .tools(toolset.tools_with_context(&HashMap::new()))
        .build();

    let prompts = [
        "What pets are currently available in the store? Show me the first 3.",
        "Get the store inventory and tell me the status counts.",
        "Look up my user profile and summarize it.",
    ];

    for prompt in prompts {
        println!(">>> {prompt}");
        let response: String = agent.prompt(prompt).await?;
        println!("{response}\n");
    }

    Ok(())
}