There are more AWS SDK examples available in the AWS Doc SDK Examples
Amazon Bedrock Runtime examples using SDK for Rust
The following code examples show you how to perform actions and implement common scenarios by using the AWS SDK for Rust with Amazon Bedrock Runtime.
Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.
Topics
Anthropic Claude
The following code example shows how to send a text message to Anthropic Claude, using Bedrock's Converse API.
- SDK for Rust
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Send a text message to Anthropic Claude, using Bedrock's Converse 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 statements, Error utility, and constants.
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", }) } }
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For API details, see Converse
in AWS SDK for Rust API reference.
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The following code example shows how to send a text message to Anthropic Claude, using Bedrock's Converse API and process the response stream in real-time.
- SDK for Rust
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. Send a text message to Anthropic Claude and stream reply tokens, using 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 statements, Error utility, and constants.
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(), ), } } }
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For API details, see ConverseStream
in AWS SDK for Rust API reference.
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The following code example shows how to build a typical interaction between an application, a generative AI model, and connected tools or APIs to mediate interactions between the AI and the outside world. It uses the example of connecting an external weather API to the AI model so it can provide real-time weather information based on user input.
- SDK for Rust
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Note
There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository
. The primary scenario and logic for the demo. This orchestrates the conversation between the user, the Amazon Bedrock Converse API, and a weather tool.
#[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(); }
The weather tool used by the demo. This script defines the tool specification and implements the logic to retrieve weather data using from the 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(¶ms) .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()?) }
Utilities to print the Message Content Blocks.
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 statements, Error utility, and constants.
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(), }) } }
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For API details, see Converse
in AWS SDK for Rust API reference.
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