Module agentCopy item path

use rig::{
    completion::{Chat, Completion, Prompt},
    providers::openai,
};

let openai = openai::Client::from_env();

// Configure the agent
let agent = openai.agent("gpt-4o")
    .preamble("System prompt")
    .context("Context document 1")
    .context("Context document 2")
    .tool(tool1)
    .tool(tool2)
    .temperature(0.8)
    .additional_params(json!({"foo": "bar"}))
    .build();

// Use the agent for completions and prompts
// Generate a chat completion response from a prompt and chat history
let chat_response = agent.chat("Prompt", chat_history)
    .await
    .expect("Failed to chat with Agent");

// Generate a prompt completion response from a simple prompt
let chat_response = agent.prompt("Prompt")
    .await
    .expect("Failed to prompt the Agent");

// Generate a completion request builder from a prompt and chat history. The builder
// will contain the agent's configuration (i.e.: preamble, context documents, tools,
// model parameters, etc.), but these can be overwritten.
let completion_req_builder = agent.completion("Prompt", chat_history)
    .await
    .expect("Failed to create completion request builder");

let response = completion_req_builder
    .temperature(0.9) // Overwrite the agent's temperature
    .send()
    .await
    .expect("Failed to send completion request");

use rig::{
    completion::Prompt,
    embeddings::EmbeddingsBuilder,
    providers::openai,
    vector_store::{in_memory_store::InMemoryVectorStore, VectorStore},
};

// Initialize OpenAI client
let openai = openai::Client::from_env();

// Initialize OpenAI embedding model
let embedding_model = openai.embedding_model(openai::TEXT_EMBEDDING_ADA_002);

// Create vector store, compute embeddings and load them in the store
let mut vector_store = InMemoryVectorStore::default();

let embeddings = EmbeddingsBuilder::new(embedding_model.clone())
    .simple_document("doc0", "Definition of a *flurbo*: A flurbo is a green alien that lives on cold planets")
    .simple_document("doc1", "Definition of a *glarb-glarb*: A glarb-glarb is a ancient tool used by the ancestors of the inhabitants of planet Jiro to farm the land.")
    .simple_document("doc2", "Definition of a *linglingdong*: A term used by inhabitants of the far side of the moon to describe humans.")
    .build()
    .await
    .expect("Failed to build embeddings");

vector_store.add_documents(embeddings)
    .await
    .expect("Failed to add documents");

// Create vector store index
let index = vector_store.index(embedding_model);

let agent = openai.agent(openai::GPT_4O)
    .preamble("
        You are a dictionary assistant here to assist the user in understanding the meaning of words.
        You will find additional non-standard word definitions that could be useful below.
    ")
    .dynamic_context(1, index)
    .build();

// Prompt the agent and print the response
let response = agent.prompt("What does \"glarb-glarb\" mean?").await
    .expect("Failed to prompt the agent");