New revision of the Assistant Panel (#10870)
This is a crate only addition of a new version of the AssistantPanel. We'll be putting this behind a feature flag while we iron out the new experience. Release Notes: - N/A --------- Co-authored-by: Nathan Sobo <nathan@zed.dev> Co-authored-by: Antonio Scandurra <me@as-cii.com> Co-authored-by: Conrad Irwin <conrad@zed.dev> Co-authored-by: Marshall Bowers <elliott.codes@gmail.com> Co-authored-by: Antonio Scandurra <antonio@zed.dev> Co-authored-by: Nate Butler <nate@zed.dev> Co-authored-by: Nate Butler <iamnbutler@gmail.com> Co-authored-by: Max Brunsfeld <maxbrunsfeld@gmail.com> Co-authored-by: Max <max@zed.dev>
This commit is contained in:
Kyle Kelley
GitHub
parent
e0c83a1d32
commit
68a1ad89bb
55 changed files with 2989 additions and 262 deletions
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@ -5,7 +5,8 @@
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"maxbrunsfeld",
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"iamnbutler",
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"mikayla-maki",
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"JosephTLyons"
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"JosephTLyons",
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"rgbkrk"
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],
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"channels": ["zed"],
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"number_of_users": 100
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@ -1,5 +1,6 @@
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use anyhow::{anyhow, Result};
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use anyhow::{anyhow, Context as _, Result};
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use rpc::proto;
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use util::ResultExt as _;
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pub fn language_model_request_to_open_ai(
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request: proto::CompleteWithLanguageModel,
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@ -9,24 +10,83 @@ pub fn language_model_request_to_open_ai(
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messages: request
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.messages
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.into_iter()
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.map(|message| {
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.map(|message: proto::LanguageModelRequestMessage| {
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let role = proto::LanguageModelRole::from_i32(message.role)
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.ok_or_else(|| anyhow!("invalid role {}", message.role))?;
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Ok(open_ai::RequestMessage {
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role: match role {
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proto::LanguageModelRole::LanguageModelUser => open_ai::Role::User,
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proto::LanguageModelRole::LanguageModelAssistant => {
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open_ai::Role::Assistant
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}
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proto::LanguageModelRole::LanguageModelSystem => open_ai::Role::System,
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let openai_message = match role {
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proto::LanguageModelRole::LanguageModelUser => open_ai::RequestMessage::User {
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content: message.content,
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},
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content: message.content,
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})
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proto::LanguageModelRole::LanguageModelAssistant => {
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open_ai::RequestMessage::Assistant {
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content: Some(message.content),
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tool_calls: message
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.tool_calls
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.into_iter()
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.filter_map(|call| {
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Some(open_ai::ToolCall {
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id: call.id,
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content: match call.variant? {
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proto::tool_call::Variant::Function(f) => {
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open_ai::ToolCallContent::Function {
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function: open_ai::FunctionContent {
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name: f.name,
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arguments: f.arguments,
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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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.collect(),
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}
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}
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proto::LanguageModelRole::LanguageModelSystem => {
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open_ai::RequestMessage::System {
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content: message.content,
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}
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}
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proto::LanguageModelRole::LanguageModelTool => open_ai::RequestMessage::Tool {
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tool_call_id: message
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.tool_call_id
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.ok_or_else(|| anyhow!("tool message is missing tool call id"))?,
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content: message.content,
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},
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};
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Ok(openai_message)
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})
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.collect::<Result<Vec<open_ai::RequestMessage>>>()?,
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stream: true,
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stop: request.stop,
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temperature: request.temperature,
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tools: request
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.tools
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.into_iter()
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.filter_map(|tool| {
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Some(match tool.variant? {
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proto::chat_completion_tool::Variant::Function(f) => {
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open_ai::ToolDefinition::Function {
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function: open_ai::FunctionDefinition {
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name: f.name,
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description: f.description,
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parameters: if let Some(params) = &f.parameters {
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Some(
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serde_json::from_str(params)
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.context("failed to deserialize tool parameters")
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.log_err()?,
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)
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} else {
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None
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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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.collect(),
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tool_choice: request.tool_choice,
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})
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}
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@ -58,6 +118,9 @@ pub fn language_model_request_message_to_google_ai(
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proto::LanguageModelRole::LanguageModelUser => google_ai::Role::User,
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proto::LanguageModelRole::LanguageModelAssistant => google_ai::Role::Model,
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proto::LanguageModelRole::LanguageModelSystem => google_ai::Role::User,
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proto::LanguageModelRole::LanguageModelTool => {
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Err(anyhow!("we don't handle tool calls with google ai yet"))?
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}
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},
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})
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}
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@ -775,9 +775,7 @@ impl Server {
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Box::new(move |envelope, session| {
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let envelope = envelope.into_any().downcast::<TypedEnvelope<M>>().unwrap();
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let received_at = envelope.received_at;
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tracing::info!(
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"message received"
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);
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tracing::info!("message received");
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let start_time = Instant::now();
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let future = (handler)(*envelope, session);
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async move {
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@ -786,12 +784,24 @@ impl Server {
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let processing_duration_ms = start_time.elapsed().as_micros() as f64 / 1000.0;
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let queue_duration_ms = total_duration_ms - processing_duration_ms;
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let payload_type = M::NAME;
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match result {
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Err(error) => {
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// todo!(), why isn't this logged inside the span?
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tracing::error!(%error, total_duration_ms, processing_duration_ms, queue_duration_ms, payload_type, "error handling message")
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tracing::error!(
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?error,
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total_duration_ms,
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processing_duration_ms,
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queue_duration_ms,
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payload_type,
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"error handling message"
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)
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}
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Ok(()) => tracing::info!(total_duration_ms, processing_duration_ms, queue_duration_ms, "finished handling message"),
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Ok(()) => tracing::info!(
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total_duration_ms,
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processing_duration_ms,
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queue_duration_ms,
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"finished handling message"
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),
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}
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}
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.boxed()
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@ -4098,7 +4108,7 @@ async fn complete_with_open_ai(
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crate::ai::language_model_request_to_open_ai(request)?,
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)
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.await
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.context("open_ai::stream_completion request failed")?;
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.context("open_ai::stream_completion request failed within collab")?;
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while let Some(event) = completion_stream.next().await {
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let event = event?;
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@ -4113,8 +4123,32 @@ async fn complete_with_open_ai(
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open_ai::Role::User => LanguageModelRole::LanguageModelUser,
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open_ai::Role::Assistant => LanguageModelRole::LanguageModelAssistant,
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open_ai::Role::System => LanguageModelRole::LanguageModelSystem,
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open_ai::Role::Tool => LanguageModelRole::LanguageModelTool,
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} as i32),
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content: choice.delta.content,
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tool_calls: choice
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.delta
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.tool_calls
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.into_iter()
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.map(|delta| proto::ToolCallDelta {
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index: delta.index as u32,
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id: delta.id,
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variant: match delta.function {
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Some(function) => {
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let name = function.name;
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let arguments = function.arguments;
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Some(proto::tool_call_delta::Variant::Function(
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proto::tool_call_delta::FunctionCallDelta {
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name,
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arguments,
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},
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))
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}
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None => None,
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},
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})
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.collect(),
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}),
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finish_reason: choice.finish_reason,
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})
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@ -4165,6 +4199,8 @@ async fn complete_with_google_ai(
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})
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.collect(),
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),
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// Tool calls are not supported for Google
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tool_calls: Vec::new(),
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}),
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finish_reason: candidate.finish_reason.map(|reason| reason.to_string()),
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})
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@ -4187,24 +4223,28 @@ async fn complete_with_anthropic(
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let messages = request
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.messages
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.into_iter()
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.filter_map(|message| match message.role() {
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LanguageModelRole::LanguageModelUser => Some(anthropic::RequestMessage {
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role: anthropic::Role::User,
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content: message.content,
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}),
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LanguageModelRole::LanguageModelAssistant => Some(anthropic::RequestMessage {
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role: anthropic::Role::Assistant,
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content: message.content,
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}),
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// Anthropic's API breaks system instructions out as a separate field rather
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// than having a system message role.
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LanguageModelRole::LanguageModelSystem => {
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if !system_message.is_empty() {
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system_message.push_str("\n\n");
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}
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system_message.push_str(&message.content);
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.filter_map(|message| {
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match message.role() {
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LanguageModelRole::LanguageModelUser => Some(anthropic::RequestMessage {
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role: anthropic::Role::User,
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content: message.content,
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}),
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LanguageModelRole::LanguageModelAssistant => Some(anthropic::RequestMessage {
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role: anthropic::Role::Assistant,
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content: message.content,
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}),
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// Anthropic's API breaks system instructions out as a separate field rather
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// than having a system message role.
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LanguageModelRole::LanguageModelSystem => {
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if !system_message.is_empty() {
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system_message.push_str("\n\n");
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}
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system_message.push_str(&message.content);
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None
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None
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}
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// We don't yet support tool calls for Anthropic
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LanguageModelRole::LanguageModelTool => None,
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}
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})
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.collect();
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@ -4248,6 +4288,7 @@ async fn complete_with_anthropic(
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delta: Some(proto::LanguageModelResponseMessage {
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role: Some(current_role as i32),
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content: Some(text),
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tool_calls: Vec::new(),
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}),
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finish_reason: None,
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}],
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@ -4264,6 +4305,7 @@ async fn complete_with_anthropic(
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delta: Some(proto::LanguageModelResponseMessage {
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role: Some(current_role as i32),
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content: Some(text),
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tool_calls: Vec::new(),
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}),
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finish_reason: None,
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}],
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