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@ -1,10 +1,8 @@
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use super::claude::*;
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use super::prompt_format::*;
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use super::*;
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use crate::utils::{base64_decode, encode_uri, hex_encode, hmac_sha256, sha256};
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use anyhow::{anyhow, bail, Result};
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use anyhow::{bail, Context, Result};
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use async_trait::async_trait;
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use aws_smithy_eventstream::frame::{DecodedFrame, MessageFrameDecoder};
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use aws_smithy_eventstream::smithy::parse_response_headers;
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@ -41,9 +39,8 @@ impl Client for BedrockClient {
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client: &ReqwestClient,
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data: ChatCompletionsData,
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) -> Result<ChatCompletionsOutput> {
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let model_category = ModelCategory::from_str(self.model.name())?;
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let builder = self.chat_completions_builder(client, data, &model_category)?;
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chat_completions(builder, &model_category).await
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let builder = self.chat_completions_builder(client, data)?;
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chat_completions(builder).await
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}
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async fn chat_completions_streaming_inner(
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@ -52,9 +49,8 @@ impl Client for BedrockClient {
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handler: &mut SseHandler,
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data: ChatCompletionsData,
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) -> Result<()> {
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let model_category = ModelCategory::from_str(self.model.name())?;
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let builder = self.chat_completions_builder(client, data, &model_category)?;
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chat_completions_streaming(builder, handler, &model_category).await
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let builder = self.chat_completions_builder(client, data)?;
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chat_completions_streaming(builder, handler).await
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}
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}
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@ -83,7 +79,6 @@ impl BedrockClient {
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&self,
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client: &ReqwestClient,
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data: ChatCompletionsData,
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model_category: &ModelCategory,
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) -> Result<RequestBuilder> {
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let access_key_id = self.get_access_key_id()?;
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let secret_access_key = self.get_secret_access_key()?;
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@ -91,15 +86,15 @@ impl BedrockClient {
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let model_name = &self.model.name();
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let uri = if data.stream {
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format!("/model/{model_name}/invoke-with-response-stream")
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format!("/model/{model_name}/converse-stream")
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} else {
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format!("/model/{model_name}/invoke")
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format!("/model/{model_name}/converse")
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};
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let host = format!("bedrock-runtime.{region}.amazonaws.com");
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let headers = IndexMap::new();
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let mut body = build_chat_completions_body(data, &self.model, model_category)?;
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let mut body = build_chat_completions_body(data, &self.model)?;
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self.patch_chat_completions_body(&mut body);
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let builder = aws_fetch(
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@ -124,10 +119,7 @@ impl BedrockClient {
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}
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}
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async fn chat_completions(
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builder: RequestBuilder,
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model_category: &ModelCategory,
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) -> Result<ChatCompletionsOutput> {
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async fn chat_completions(builder: RequestBuilder) -> Result<ChatCompletionsOutput> {
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let res = builder.send().await?;
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let status = res.status();
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let data: Value = res.json().await?;
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@ -137,17 +129,12 @@ async fn chat_completions(
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}
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debug!("non-stream-data: {data}");
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match model_category {
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ModelCategory::Anthropic => claude_extract_chat_completions(&data),
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ModelCategory::MetaLlama3 => llama_extract_chat_completions(&data),
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ModelCategory::Mistral => mistral_extract_chat_completions(&data),
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}
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extract_chat_completions(&data)
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}
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async fn chat_completions_streaming(
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builder: RequestBuilder,
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handler: &mut SseHandler,
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model_category: &ModelCategory,
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) -> Result<()> {
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let res = builder.send().await?;
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let status = res.status();
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@ -156,6 +143,11 @@ async fn chat_completions_streaming(
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catch_error(&data, status.as_u16())?;
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bail!("Invalid response data: {data}");
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}
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let mut function_name = String::new();
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let mut function_arguments = String::new();
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let mut function_id = String::new();
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let mut stream = res.bytes_stream();
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let mut buffer = BytesMut::new();
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let mut decoder = MessageFrameDecoder::new();
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@ -167,31 +159,53 @@ async fn chat_completions_streaming(
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let message_type = response_headers.message_type.as_str();
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let smithy_type = response_headers.smithy_type.as_str();
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match (message_type, smithy_type) {
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("event", "chunk") => {
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let data: Value = decode_chunk(message.payload()).ok_or_else(|| {
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anyhow!("Invalid chunk data: {}", hex_encode(message.payload()))
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("event", _) => {
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let data: Value = serde_json::from_slice(message.payload())?;
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debug!("stream-data: {smithy_type} {data}");
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match smithy_type {
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"contentBlockStart" => {
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if let Some(tool_use) = data["start"]["toolUse"].as_object() {
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if let (Some(id), Some(name)) = (
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json_str_from_map(tool_use, "toolUseId"),
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json_str_from_map(tool_use, "name"),
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) {
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if !function_name.is_empty() {
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let arguments: Value =
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function_arguments.parse().with_context(|| {
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format!("Tool call '{function_name}' is invalid: arguments must be in valid JSON format")
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})?;
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debug!("stream-data: {data}");
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match model_category {
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ModelCategory::Anthropic => {
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if let Some(typ) = data["type"].as_str() {
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if typ == "content_block_delta" {
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if let Some(text) = data["delta"]["text"].as_str() {
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handler.text(text)?;
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handler.tool_call(ToolCall::new(
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function_name.clone(),
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arguments,
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Some(function_id.clone()),
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))?;
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}
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function_arguments.clear();
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function_name = name.into();
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function_id = id.into();
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}
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}
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}
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ModelCategory::MetaLlama3 => {
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if let Some(text) = data["generation"].as_str() {
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"contentBlockDelta" => {
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if let Some(text) = data["delta"]["text"].as_str() {
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handler.text(text)?;
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} else if let Some(input) = data["delta"]["toolUse"]["input"].as_str() {
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function_arguments.push_str(input);
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}
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}
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ModelCategory::Mistral => {
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if let Some(text) = data["outputs"][0]["text"].as_str() {
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handler.text(text)?;
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"contentBlockStop" => {
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if !function_name.is_empty() {
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let arguments: Value = function_arguments.parse().with_context(|| {
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format!("Tool call '{function_name}' is invalid: arguments must be in valid JSON format")
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})?;
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handler.tool_call(ToolCall::new(
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function_name.clone(),
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arguments,
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Some(function_id.clone()),
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))?;
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}
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}
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_ => {}
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}
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}
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("exception", _) => {
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@ -209,124 +223,195 @@ async fn chat_completions_streaming(
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Ok(())
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}
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fn build_chat_completions_body(
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data: ChatCompletionsData,
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model: &Model,
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model_category: &ModelCategory,
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) -> Result<Value> {
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match model_category {
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ModelCategory::Anthropic => {
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let mut body = claude_build_chat_completions_body(data, model)?;
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if let Some(body_obj) = body.as_object_mut() {
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body_obj.remove("model");
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body_obj.remove("stream");
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}
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body["anthropic_version"] = "bedrock-2023-05-31".into();
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Ok(body)
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}
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ModelCategory::MetaLlama3 => {
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meta_llama_build_chat_completions_body(data, model, LLAMA3_PROMPT_FORMAT)
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}
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ModelCategory::Mistral => mistral_build_chat_completions_body(data, model),
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}
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}
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fn meta_llama_build_chat_completions_body(
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data: ChatCompletionsData,
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model: &Model,
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pt: PromptFormat,
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) -> Result<Value> {
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fn build_chat_completions_body(data: ChatCompletionsData, model: &Model) -> Result<Value> {
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let ChatCompletionsData {
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messages,
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mut messages,
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temperature,
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top_p,
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functions: _,
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functions,
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stream: _,
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} = data;
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let prompt = generate_prompt(&messages, pt)?;
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let mut body = json!({ "prompt": prompt });
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let system_message = extract_system_message(&mut messages);
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let mut network_image_urls = vec![];
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let messages: Vec<Value> = messages
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.into_iter()
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.flat_map(|message| {
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let Message { role, content } = message;
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match content {
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MessageContent::Text(text) => vec![json!({
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"role": role,
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"content": [
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{
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"text": text,
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}
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],
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})],
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MessageContent::Array(list) => {
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let content: Vec<_> = list
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.into_iter()
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.map(|item| match item {
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MessageContentPart::Text { text } => {
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json!({"text": text})
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}
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MessageContentPart::ImageUrl {
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image_url: ImageUrl { url },
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} => {
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if let Some((mime_type, data)) = url
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.strip_prefix("data:")
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.and_then(|v| v.split_once(";base64,"))
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{
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json!({
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"image": {
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"format": mime_type.replace("image/", ""),
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"source": {
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"bytes": data,
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}
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}
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})
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} else {
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network_image_urls.push(url.clone());
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json!({ "url": url })
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}
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}
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})
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.collect();
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vec![json!({
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"role": role,
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"content": content,
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})]
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}
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MessageContent::ToolResults((tool_results, text)) => {
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let mut assistant_parts = vec![];
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let mut user_parts = vec![];
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if !text.is_empty() {
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assistant_parts.push(json!({
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"text": text,
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}))
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}
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for tool_result in tool_results {
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assistant_parts.push(json!({
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"toolUse": {
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"toolUseId": tool_result.call.id,
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"name": tool_result.call.name,
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"input": tool_result.call.arguments,
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}
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}));
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user_parts.push(json!({
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"toolResult": {
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"toolUseId": tool_result.call.id,
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"content": [
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{
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"json": tool_result.output,
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}
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]
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}
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}));
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}
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vec![
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json!({
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"role": "assistant",
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"content": assistant_parts,
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}),
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json!({
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"role": "user",
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"content": user_parts,
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}),
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]
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}
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}
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})
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.collect();
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if !network_image_urls.is_empty() {
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bail!(
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"The model does not support network images: {:?}",
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network_image_urls
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);
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}
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let mut body = json!({
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"inferenceConfig": {},
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"messages": messages,
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});
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if let Some(v) = system_message {
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body["system"] = json!([
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{
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"text": v,
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}
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])
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|
|
|
}
|
|
|
|
|
|
|
|
|
|
if let Some(v) = model.max_tokens_param() {
|
|
|
|
|
body["max_gen_len"] = v.into();
|
|
|
|
|
body["inferenceConfig"]["maxTokens"] = v.into();
|
|
|
|
|
}
|
|
|
|
|
if let Some(v) = temperature {
|
|
|
|
|
body["temperature"] = v.into();
|
|
|
|
|
body["inferenceConfig"]["temperature"] = v.into();
|
|
|
|
|
}
|
|
|
|
|
if let Some(v) = top_p {
|
|
|
|
|
body["top_p"] = v.into();
|
|
|
|
|
body["inferenceConfig"]["topP"] = v.into();
|
|
|
|
|
}
|
|
|
|
|
if let Some(functions) = functions {
|
|
|
|
|
let tools: Vec<_> = functions
|
|
|
|
|
.iter()
|
|
|
|
|
.map(|v| {
|
|
|
|
|
json!({
|
|
|
|
|
"toolSpec": {
|
|
|
|
|
"name": v.name,
|
|
|
|
|
"description": v.description,
|
|
|
|
|
"inputSchema": {
|
|
|
|
|
"json": v.parameters,
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
})
|
|
|
|
|
})
|
|
|
|
|
.collect();
|
|
|
|
|
body["toolConfig"] = json!({
|
|
|
|
|
"tools": tools,
|
|
|
|
|
})
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
Ok(body)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn mistral_build_chat_completions_body(data: ChatCompletionsData, model: &Model) -> Result<Value> {
|
|
|
|
|
let ChatCompletionsData {
|
|
|
|
|
messages,
|
|
|
|
|
temperature,
|
|
|
|
|
top_p,
|
|
|
|
|
functions: _,
|
|
|
|
|
stream: _,
|
|
|
|
|
} = data;
|
|
|
|
|
let prompt = generate_prompt(&messages, MISTRAL_PROMPT_FORMAT)?;
|
|
|
|
|
let mut body = json!({ "prompt": prompt });
|
|
|
|
|
|
|
|
|
|
if let Some(v) = model.max_tokens_param() {
|
|
|
|
|
body["max_tokens"] = v.into();
|
|
|
|
|
fn extract_chat_completions(data: &Value) -> Result<ChatCompletionsOutput> {
|
|
|
|
|
let mut texts = vec![];
|
|
|
|
|
let mut tool_calls = vec![];
|
|
|
|
|
if let Some(array) = data["output"]["message"]["content"].as_array() {
|
|
|
|
|
for item in array {
|
|
|
|
|
if let Some(text) = item["text"].as_str() {
|
|
|
|
|
texts.push(text);
|
|
|
|
|
} else if let Some(tool_use) = item["toolUse"].as_object() {
|
|
|
|
|
if let (Some(id), Some(name), Some(input)) = (
|
|
|
|
|
json_str_from_map(tool_use, "toolUseId"),
|
|
|
|
|
json_str_from_map(tool_use, "name"),
|
|
|
|
|
tool_use.get("input"),
|
|
|
|
|
) {
|
|
|
|
|
tool_calls.push(ToolCall::new(
|
|
|
|
|
name.to_string(),
|
|
|
|
|
input.clone(),
|
|
|
|
|
Some(id.to_string()),
|
|
|
|
|
))
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
if let Some(v) = temperature {
|
|
|
|
|
body["temperature"] = v.into();
|
|
|
|
|
}
|
|
|
|
|
if let Some(v) = top_p {
|
|
|
|
|
body["top_p"] = v.into();
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
Ok(body)
|
|
|
|
|
if texts.is_empty() && tool_calls.is_empty() {
|
|
|
|
|
bail!("Invalid response data: {data}");
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn llama_extract_chat_completions(data: &Value) -> Result<ChatCompletionsOutput> {
|
|
|
|
|
let text = data["generation"]
|
|
|
|
|
.as_str()
|
|
|
|
|
.ok_or_else(|| anyhow!("Invalid response data: {data}"))?;
|
|
|
|
|
let output = ChatCompletionsOutput {
|
|
|
|
|
text: text.to_string(),
|
|
|
|
|
tool_calls: vec![],
|
|
|
|
|
text: texts.join("\n\n"),
|
|
|
|
|
tool_calls,
|
|
|
|
|
id: None,
|
|
|
|
|
input_tokens: data["prompt_token_count"].as_u64(),
|
|
|
|
|
output_tokens: data["generation_token_count"].as_u64(),
|
|
|
|
|
input_tokens: data["usage"]["inputTokens"].as_u64(),
|
|
|
|
|
output_tokens: data["usage"]["outputTokens"].as_u64(),
|
|
|
|
|
};
|
|
|
|
|
Ok(output)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn mistral_extract_chat_completions(data: &Value) -> Result<ChatCompletionsOutput> {
|
|
|
|
|
let text = data["outputs"][0]["text"]
|
|
|
|
|
.as_str()
|
|
|
|
|
.ok_or_else(|| anyhow!("Invalid response data: {data}"))?;
|
|
|
|
|
Ok(ChatCompletionsOutput::new(text))
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
|
|
|
|
|
enum ModelCategory {
|
|
|
|
|
Anthropic,
|
|
|
|
|
MetaLlama3,
|
|
|
|
|
Mistral,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
impl FromStr for ModelCategory {
|
|
|
|
|
type Err = anyhow::Error;
|
|
|
|
|
|
|
|
|
|
fn from_str(s: &str) -> std::result::Result<Self, Self::Err> {
|
|
|
|
|
if s.starts_with("anthropic.") {
|
|
|
|
|
Ok(ModelCategory::Anthropic)
|
|
|
|
|
} else if s.starts_with("meta.llama3") {
|
|
|
|
|
Ok(ModelCategory::MetaLlama3)
|
|
|
|
|
} else if s.starts_with("mistral") {
|
|
|
|
|
Ok(ModelCategory::Mistral)
|
|
|
|
|
} else {
|
|
|
|
|
unsupported_model!(s)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
#[derive(Debug)]
|
|
|
|
|
struct AwsCredentials {
|
|
|
|
|
access_key_id: String,
|
|
|
|
|
@ -439,10 +524,3 @@ fn gen_signing_key(key: &str, date_stamp: &str, region: &str, service: &str) ->
|
|
|
|
|
let k_service = hmac_sha256(&k_region, service);
|
|
|
|
|
hmac_sha256(&k_service, "aws4_request")
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fn decode_chunk(data: &[u8]) -> Option<Value> {
|
|
|
|
|
let data = serde_json::from_slice::<Value>(data).ok()?;
|
|
|
|
|
let data = data["bytes"].as_str()?;
|
|
|
|
|
let data = base64_decode(data).ok()?;
|
|
|
|
|
serde_json::from_slice(&data).ok()
|
|
|
|
|
}
|
|
|
|
|
|
sigoden
3 months ago