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AI Execution Context API Guide

Learn how to manage AI execution contexts using the Wacht Rust SDK. Execution contexts provide isolated environments for running AI agents with specific system instructions and configurations.

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Prerequisites

Before using any API methods, you must initialize the SDK: 
use wacht::init_from_env;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Initialize from environment variables
    // Requires: WACHT_API_KEY and WACHT_FRONTEND_HOST
    init_from_env().await?;

    // Now you can use the API
    Ok(())
}

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List Execution Contexts

Get all execution contexts in your deployment.

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Basic List

use wacht::api::ai;

// Fetch all contexts (default pagination)
let contexts = ai::fetch_execution_contexts(None)
    .await?;

for ctx in contexts.data {
    println!("{}: {}", ctx.title, ctx.status.as_ref().unwrap_or(&"unknown".to_string()));
}

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With Filters

use wacht::api::ai;

// Fetch contexts with builder pattern
let contexts = ai::list_execution_contexts()
    .limit(50)
    .offset(0)
    .status("active")
    .context_group("support")
    .send()
    .await?;

for ctx in contexts.data {
    println!("{} (group: {})", ctx.title, ctx.context_group.as_ref().unwrap_or(&"default".to_string()));
}

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Create Execution Context

Create a new execution context for AI operations. 
use wacht::api::ai;
use wacht::models::CreateAiExecutionContextRequest;

let context = ai::create_execution_context(CreateAiExecutionContextRequest {
    title: "Customer Support Context".to_string(),
    system_instructions: Some("You are a helpful customer support assistant.".to_string()),
    context_group: Some("support".to_string()),
    status: Some("active".to_string()),
})
.await?;

println!("Created context: {}", context.id);

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Update Execution Context

Modify an existing execution context. 
use wacht::api::ai;

let context = ai::update_execution_context_builder("ctx_123")
    .with_title("Updated Support Context")
    .with_system_instructions("You are a senior customer support specialist.")
    .with_status("active")
    .send()
    .await?;

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Execute Agent

Run an AI agent within a specific execution context. 
use wacht::api::ai;
use wacht::models::ExecuteAgentRequest;

let result = ai::execute_agent_builder(
    "ctx_123",
    ExecuteAgentRequest {
        agent_name: "support-bot".to_string(),
        execution_type: ExecuteAgentRequestType::NewMessage {
            message: "Help me reset my password".to_string(),
            files: None,
        },
    }
)
.send()
.await?;

println!("Agent response: {:?}", result.response);

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Builder Methods

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ListExecutionContextsBuilder

  • limit(i32) - Number of results to return (max 100)
  • offset(i32) - Number of results to skip
  • status(&str) - Filter by status
  • context_group(&str) - Filter by context group

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UpdateExecutionContextBuilder

  • with_title(&str) - Update context title
  • with_system_instructions(&str) - Update system instructions
  • with_context_group(&str) - Update context group
  • with_status(&str) - Update status

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Request Models

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CreateAiExecutionContextRequest

  • title (String) - Context title (required)
  • system_instructions (Option<String>) - System instructions for the AI
  • context_group (Option<String>) - Group identifier for the context
  • status (Option<String>) - Context status (e.g., “active”, “inactive”)

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ExecuteAgentRequest

  • agent_name (String) - Name of the agent to execute (required)
  • execution_type (ExecuteAgentRequestType) - Type of execution (required)

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ExecuteAgentRequestType

Variants for different execution types:
  • NewMessage { message: String, files: Option&lt;Vec&lt;String&gt;&gt; } - Execute with a new message
  • Continue { files: Option&lt;Vec&lt;String&gt;&gt; } - Continue previous conversation
  • Stream { message: String, files: Option&lt;Vec&lt;String&gt;&gt; } - Stream response

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Context States

Execution contexts can have different states:
  • active - Context is active and ready for execution
  • inactive - Context is disabled
  • archived - Context is archived

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System Instructions

System instructions define the behavior and personality of the AI within the context: 
CreateAiExecutionContextRequest {
    title: "Support Agent".to_string(),
    system_instructions: Some(
        "You are a customer support agent for Wacht. \
         Be polite, concise, and helpful. \
         Always prioritize customer satisfaction.".to_string()
    ),
    context_group: Some("support".to_string()),
    status: Some("active".to_string()),
}

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Context Groups

Context groups help organize related execution contexts: 
// Create contexts for different departments
let sales_context = ai::create_execution_context(CreateAiExecutionContextRequest {
    title: "Sales Context".to_string(),
    system_instructions: Some("You are a sales assistant.".to_string()),
    context_group: Some("sales".to_string()),
    status: Some("active".to_string()),
}).await?;

let support_context = ai::create_execution_context(CreateAiExecutionContextRequest {
    title: "Support Context".to_string(),
    system_instructions: Some("You are a support assistant.".to_string()),
    context_group: Some("support".to_string()),
    status: Some("active".to_string()),
}).await?;

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Error Handling

All SDK methods return a Result<T, Error>: 
use wacht::{Error, api::ai};

match ai::fetch_execution_contexts(None).await {
    Ok(contexts) => {
        for ctx in contexts.data {
            println!("Context: {}", ctx.title);
        }
    }
    Err(Error::Api { status, message, .. }) => {
        eprintln!("API Error {}: {}", status, message);
    }
    Err(Error::Request(e)) => {
        eprintln!("Network error: {}", e);
    }
    Err(e) => {
        eprintln!("Other error: {}", e);
    }
}