Exemplos de Amazon Bedrock Runtime usando SDK para Rust - AWS SDKExemplos de código

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Exemplos de Amazon Bedrock Runtime usando SDK para Rust

Os exemplos de código a seguir mostram como realizar ações e implementar cenários comuns usando o AWS SDK for Rust com o Amazon Bedrock Runtime.

Cada exemplo inclui um link para o código-fonte completo, onde você pode encontrar instruções sobre como configurar e executar o código no contexto.

Anthropic Claude

O exemplo de código a seguir mostra como enviar uma mensagem de texto para Anthropic Claude usando o Converse do Bedrock. API

SDKpara Rust
nota

Tem mais sobre GitHub. Encontre o exemplo completo e saiba como configurar e executar no Repositório de exemplos de código da AWS.

Envie uma mensagem de texto para Anthropic Claude, usando o Converse do Bedrock. API

#[tokio::main] async fn main() -> Result<(), BedrockConverseError> { tracing_subscriber::fmt::init(); let sdk_config = aws_config::defaults(BehaviorVersion::latest()) .region(CLAUDE_REGION) .load() .await; let client = Client::new(&sdk_config); let response = client .converse() .model_id(MODEL_ID) .messages( Message::builder() .role(ConversationRole::User) .content(ContentBlock::Text(USER_MESSAGE.to_string())) .build() .map_err(|_| "failed to build message")?, ) .send() .await; match response { Ok(output) => { let text = get_converse_output_text(output)?; println!("{}", text); Ok(()) } Err(e) => Err(e .as_service_error() .map(BedrockConverseError::from) .unwrap_or_else(|| BedrockConverseError("Unknown service error".into()))), } } fn get_converse_output_text(output: ConverseOutput) -> Result<String, BedrockConverseError> { let text = output .output() .ok_or("no output")? .as_message() .map_err(|_| "output not a message")? .content() .first() .ok_or("no content in message")? .as_text() .map_err(|_| "content is not text")? .to_string(); Ok(text) }

Use instruções, utilitário de erro e constantes.

use aws_config::BehaviorVersion; use aws_sdk_bedrockruntime::{ operation::converse::{ConverseError, ConverseOutput}, types::{ContentBlock, ConversationRole, Message}, Client, }; // Set the model ID, e.g., Claude 3 Haiku. const MODEL_ID: &str = "anthropic.claude-3-haiku-20240307-v1:0"; const CLAUDE_REGION: &str = "us-east-1"; // Start a conversation with the user message. const USER_MESSAGE: &str = "Describe the purpose of a 'hello world' program in one line."; #[derive(Debug)] struct BedrockConverseError(String); impl std::fmt::Display for BedrockConverseError { fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { write!(f, "Can't invoke '{}'. Reason: {}", MODEL_ID, self.0) } } impl std::error::Error for BedrockConverseError {} impl From<&str> for BedrockConverseError { fn from(value: &str) -> Self { BedrockConverseError(value.to_string()) } } impl From<&ConverseError> for BedrockConverseError { fn from(value: &ConverseError) -> Self { BedrockConverseError::from(match value { ConverseError::ModelTimeoutException(_) => "Model took too long", ConverseError::ModelNotReadyException(_) => "Model is not ready", _ => "Unknown", }) } }
  • Para API obter detalhes, consulte Converse in AWS SDKpara referência sobre Rust API.

O exemplo de código a seguir mostra como enviar uma mensagem de texto para Anthropic Claude usando o Converse da Bedrock API e processar o fluxo de resposta em tempo real.

SDKpara Rust
nota

Tem mais sobre GitHub. Encontre o exemplo completo e saiba como configurar e executar no Repositório de exemplos de código da AWS.

Envie uma mensagem de texto para Anthropic Claude e transmita tokens de resposta usando o Bedrock's. ConverseStream API

#[tokio::main] async fn main() -> Result<(), BedrockConverseStreamError> { tracing_subscriber::fmt::init(); let sdk_config = aws_config::defaults(BehaviorVersion::latest()) .region(CLAUDE_REGION) .load() .await; let client = Client::new(&sdk_config); let response = client .converse_stream() .model_id(MODEL_ID) .messages( Message::builder() .role(ConversationRole::User) .content(ContentBlock::Text(USER_MESSAGE.to_string())) .build() .map_err(|_| "failed to build message")?, ) .send() .await; let mut stream = match response { Ok(output) => Ok(output.stream), Err(e) => Err(BedrockConverseStreamError::from( e.as_service_error().unwrap(), )), }?; loop { let token = stream.recv().await; match token { Ok(Some(text)) => { let next = get_converse_output_text(text)?; print!("{}", next); Ok(()) } Ok(None) => break, Err(e) => Err(e .as_service_error() .map(BedrockConverseStreamError::from) .unwrap_or(BedrockConverseStreamError( "Unknown error receiving stream".into(), ))), }? } println!(); Ok(()) } fn get_converse_output_text( output: ConverseStreamOutputType, ) -> Result<String, BedrockConverseStreamError> { Ok(match output { ConverseStreamOutputType::ContentBlockDelta(event) => match event.delta() { Some(delta) => delta.as_text().cloned().unwrap_or_else(|_| "".into()), None => "".into(), }, _ => "".into(), }) }

Use instruções, utilitário de erro e constantes.

use aws_config::BehaviorVersion; use aws_sdk_bedrockruntime::{ error::ProvideErrorMetadata, operation::converse_stream::ConverseStreamError, types::{ error::ConverseStreamOutputError, ContentBlock, ConversationRole, ConverseStreamOutput as ConverseStreamOutputType, Message, }, Client, }; // Set the model ID, e.g., Claude 3 Haiku. const MODEL_ID: &str = "anthropic.claude-3-haiku-20240307-v1:0"; const CLAUDE_REGION: &str = "us-east-1"; // Start a conversation with the user message. const USER_MESSAGE: &str = "Describe the purpose of a 'hello world' program in one line."; #[derive(Debug)] struct BedrockConverseStreamError(String); impl std::fmt::Display for BedrockConverseStreamError { fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { write!(f, "Can't invoke '{}'. Reason: {}", MODEL_ID, self.0) } } impl std::error::Error for BedrockConverseStreamError {} impl From<&str> for BedrockConverseStreamError { fn from(value: &str) -> Self { BedrockConverseStreamError(value.into()) } } impl From<&ConverseStreamError> for BedrockConverseStreamError { fn from(value: &ConverseStreamError) -> Self { BedrockConverseStreamError( match value { ConverseStreamError::ModelTimeoutException(_) => "Model took too long", ConverseStreamError::ModelNotReadyException(_) => "Model is not ready", _ => "Unknown", } .into(), ) } } impl From<&ConverseStreamOutputError> for BedrockConverseStreamError { fn from(value: &ConverseStreamOutputError) -> Self { match value { ConverseStreamOutputError::ValidationException(ve) => BedrockConverseStreamError( ve.message().unwrap_or("Unknown ValidationException").into(), ), ConverseStreamOutputError::ThrottlingException(te) => BedrockConverseStreamError( te.message().unwrap_or("Unknown ThrottlingException").into(), ), value => BedrockConverseStreamError( value .message() .unwrap_or("Unknown StreamOutput exception") .into(), ), } } }
  • Para API obter detalhes, consulte ConverseStreama AWS SDKAPIreferência do Rust.

O exemplo de código a seguir mostra como criar uma interação típica entre um aplicativo, um modelo generativo de IA e ferramentas conectadas ou como APIs mediar interações entre a IA e o mundo externo. Ele usa o exemplo de conectar um clima externo API ao modelo de IA para que possa fornecer informações meteorológicas em tempo real com base na entrada do usuário.

SDKpara Rust
nota

Tem mais sobre GitHub. Encontre o exemplo completo e saiba como configurar e executar no Repositório de exemplos de código da AWS.

O cenário principal e a lógica da demonstração. Isso orquestra a conversa entre o usuário, o Amazon Bedrock Converse e uma ferramenta API meteorológica.

#[derive(Debug)] #[allow(dead_code)] struct InvokeToolResult(String, ToolResultBlock); struct ToolUseScenario { client: Client, conversation: Vec<Message>, system_prompt: SystemContentBlock, tool_config: ToolConfiguration, } impl ToolUseScenario { fn new(client: Client) -> Self { let system_prompt = SystemContentBlock::Text(SYSTEM_PROMPT.into()); let tool_config = ToolConfiguration::builder() .tools(Tool::ToolSpec( ToolSpecification::builder() .name(TOOL_NAME) .description(TOOL_DESCRIPTION) .input_schema(ToolInputSchema::Json(make_tool_schema())) .build() .unwrap(), )) .build() .unwrap(); ToolUseScenario { client, conversation: vec![], system_prompt, tool_config, } } async fn run(&mut self) -> Result<(), ToolUseScenarioError> { loop { let input = get_input().await?; if input.is_none() { break; } let message = Message::builder() .role(User) .content(ContentBlock::Text(input.unwrap())) .build() .map_err(ToolUseScenarioError::from)?; self.conversation.push(message); let response = self.send_to_bedrock().await?; self.process_model_response(response).await?; } Ok(()) } async fn send_to_bedrock(&mut self) -> Result<ConverseOutput, ToolUseScenarioError> { debug!("Sending conversation to bedrock"); self.client .converse() .model_id(MODEL_ID) .set_messages(Some(self.conversation.clone())) .system(self.system_prompt.clone()) .tool_config(self.tool_config.clone()) .send() .await .map_err(ToolUseScenarioError::from) } async fn process_model_response( &mut self, mut response: ConverseOutput, ) -> Result<(), ToolUseScenarioError> { let mut iteration = 0; while iteration < MAX_RECURSIONS { iteration += 1; let message = if let Some(ref output) = response.output { if output.is_message() { Ok(output.as_message().unwrap().clone()) } else { Err(ToolUseScenarioError( "Converse Output is not a message".into(), )) } } else { Err(ToolUseScenarioError("Missing Converse Output".into())) }?; self.conversation.push(message.clone()); match response.stop_reason { StopReason::ToolUse => { response = self.handle_tool_use(&message).await?; } StopReason::EndTurn => { print_model_response(&message.content[0])?; return Ok(()); } _ => (), } } Err(ToolUseScenarioError( "Exceeded MAX_ITERATIONS when calling tools".into(), )) } async fn handle_tool_use( &mut self, message: &Message, ) -> Result<ConverseOutput, ToolUseScenarioError> { let mut tool_results: Vec<ContentBlock> = vec![]; for block in &message.content { match block { ContentBlock::Text(_) => print_model_response(block)?, ContentBlock::ToolUse(tool) => { let tool_response = self.invoke_tool(tool).await?; tool_results.push(ContentBlock::ToolResult(tool_response.1)); } _ => (), }; } let message = Message::builder() .role(User) .set_content(Some(tool_results)) .build()?; self.conversation.push(message); self.send_to_bedrock().await } async fn invoke_tool( &mut self, tool: &ToolUseBlock, ) -> Result<InvokeToolResult, ToolUseScenarioError> { match tool.name() { TOOL_NAME => { println!( "\x1b[0;90mExecuting tool: {TOOL_NAME} with input: {:?}...\x1b[0m", tool.input() ); let content = fetch_weather_data(tool).await?; println!( "\x1b[0;90mTool responded with {:?}\x1b[0m", content.content() ); Ok(InvokeToolResult(tool.tool_use_id.clone(), content)) } _ => Err(ToolUseScenarioError(format!( "The requested tool with name {} does not exist", tool.name() ))), } } } #[tokio::main] async fn main() { tracing_subscriber::fmt::init(); let sdk_config = aws_config::defaults(BehaviorVersion::latest()) .region(CLAUDE_REGION) .load() .await; let client = Client::new(&sdk_config); let mut scenario = ToolUseScenario::new(client); header(); if let Err(err) = scenario.run().await { println!("There was an error running the scenario! {}", err.0) } footer(); }

A ferramenta meteorológica usada pela demonstração. Esse script define a especificação da ferramenta e implementa a lógica para recuperar dados meteorológicos usando o Open-Meteo. API

const ENDPOINT: &str = "https://api.open-meteo.com/v1/forecast"; async fn fetch_weather_data( tool_use: &ToolUseBlock, ) -> Result<ToolResultBlock, ToolUseScenarioError> { let input = tool_use.input(); let latitude = input .as_object() .unwrap() .get("latitude") .unwrap() .as_string() .unwrap(); let longitude = input .as_object() .unwrap() .get("longitude") .unwrap() .as_string() .unwrap(); let params = [ ("latitude", latitude), ("longitude", longitude), ("current_weather", "true"), ]; debug!("Calling {ENDPOINT} with {params:?}"); let response = reqwest::Client::new() .get(ENDPOINT) .query(&params) .send() .await .map_err(|e| ToolUseScenarioError(format!("Error requesting weather: {e:?}")))? .error_for_status() .map_err(|e| ToolUseScenarioError(format!("Failed to request weather: {e:?}")))?; debug!("Response: {response:?}"); let bytes = response .bytes() .await .map_err(|e| ToolUseScenarioError(format!("Error reading response: {e:?}")))?; let result = String::from_utf8(bytes.to_vec()) .map_err(|_| ToolUseScenarioError("Response was not utf8".into()))?; Ok(ToolResultBlock::builder() .tool_use_id(tool_use.tool_use_id()) .content(ToolResultContentBlock::Text(result)) .build()?) }

Utilitários para imprimir os blocos de conteúdo da mensagem

fn print_model_response(block: &ContentBlock) -> Result<(), ToolUseScenarioError> { if block.is_text() { let text = block.as_text().unwrap(); println!("\x1b[0;90mThe model's response:\x1b[0m\n{text}"); Ok(()) } else { Err(ToolUseScenarioError(format!( "Content block is not text ({block:?})" ))) } }

Use instruções, utilitário de erro e constantes.

use std::{collections::HashMap, io::stdin}; use aws_config::BehaviorVersion; use aws_sdk_bedrockruntime::{ error::{BuildError, SdkError}, operation::converse::{ConverseError, ConverseOutput}, types::{ ContentBlock, ConversationRole::User, Message, StopReason, SystemContentBlock, Tool, ToolConfiguration, ToolInputSchema, ToolResultBlock, ToolResultContentBlock, ToolSpecification, ToolUseBlock, }, Client, }; use aws_smithy_runtime_api::http::Response; use aws_smithy_types::Document; use tracing::debug; /// This demo illustrates a tool use scenario using Amazon Bedrock's Converse API and a weather tool. /// The script interacts with a foundation model on Amazon Bedrock to provide weather information based on user /// input. It uses the Open-Meteo API (https://open-meteo.com) to retrieve current weather data for a given location. // Set the model ID, e.g., Claude 3 Haiku. const MODEL_ID: &str = "anthropic.claude-3-haiku-20240307-v1:0"; const CLAUDE_REGION: &str = "us-east-1"; const SYSTEM_PROMPT: &str = "You are a weather assistant that provides current weather data for user-specified locations using only the Weather_Tool, which expects latitude and longitude. Infer the coordinates from the location yourself. If the user provides coordinates, infer the approximate location and refer to it in your response. To use the tool, you strictly apply the provided tool specification. - Explain your step-by-step process, and give brief updates before each step. - Only use the Weather_Tool for data. Never guess or make up information. - Repeat the tool use for subsequent requests if necessary. - If the tool errors, apologize, explain weather is unavailable, and suggest other options. - Report temperatures in °C (°F) and wind in km/h (mph). Keep weather reports concise. Sparingly use emojis where appropriate. - Only respond to weather queries. Remind off-topic users of your purpose. - Never claim to search online, access external data, or use tools besides Weather_Tool. - Complete the entire process until you have all required data before sending the complete response. "; // The maximum number of recursive calls allowed in the tool_use_demo function. // This helps prevent infinite loops and potential performance issues. const MAX_RECURSIONS: i8 = 5; const TOOL_NAME: &str = "Weather_Tool"; const TOOL_DESCRIPTION: &str = "Get the current weather for a given location, based on its WGS84 coordinates."; fn make_tool_schema() -> Document { Document::Object(HashMap::<String, Document>::from([ ("type".into(), Document::String("object".into())), ( "properties".into(), Document::Object(HashMap::from([ ( "latitude".into(), Document::Object(HashMap::from([ ("type".into(), Document::String("string".into())), ( "description".into(), Document::String("Geographical WGS84 latitude of the location.".into()), ), ])), ), ( "longitude".into(), Document::Object(HashMap::from([ ("type".into(), Document::String("string".into())), ( "description".into(), Document::String( "Geographical WGS84 longitude of the location.".into(), ), ), ])), ), ])), ), ( "required".into(), Document::Array(vec![ Document::String("latitude".into()), Document::String("longitude".into()), ]), ), ])) } #[derive(Debug)] struct ToolUseScenarioError(String); impl std::fmt::Display for ToolUseScenarioError { fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { write!(f, "Tool use error with '{}'. Reason: {}", MODEL_ID, self.0) } } impl From<&str> for ToolUseScenarioError { fn from(value: &str) -> Self { ToolUseScenarioError(value.into()) } } impl From<BuildError> for ToolUseScenarioError { fn from(value: BuildError) -> Self { ToolUseScenarioError(value.to_string().clone()) } } impl From<SdkError<ConverseError, Response>> for ToolUseScenarioError { fn from(value: SdkError<ConverseError, Response>) -> Self { ToolUseScenarioError(match value.as_service_error() { Some(value) => value.meta().message().unwrap_or("Unknown").into(), None => "Unknown".into(), }) } }
  • Para API obter detalhes, consulte Converse in AWS SDKpara referência sobre Rust API.