agent: Preserve thinking blocks between requests (#29055)
Looks like the required backend component of this was deployed. https://github.com/zed-industries/monorepo/actions/runs/14541199197 Release Notes: - N/A --------- Co-authored-by: Antonio Scandurra <me@as-cii.com> Co-authored-by: Agus Zubiaga <hi@aguz.me> Co-authored-by: Richard Feldman <oss@rtfeldman.com> Co-authored-by: Nathan Sobo <nathan@zed.dev>
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Bennet Bo Fenner
GitHub
parent
f737c4d01e
commit
bafc086d27
13 changed files with 236 additions and 68 deletions
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@ -336,6 +336,12 @@ pub fn count_anthropic_tokens(
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MessageContent::Text(text) => {
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string_contents.push_str(&text);
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}
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MessageContent::Thinking { .. } => {
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// Thinking blocks are not included in the input token count.
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}
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MessageContent::RedactedThinking(_) => {
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// Thinking blocks are not included in the input token count.
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}
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MessageContent::Image(image) => {
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tokens_from_images += image.estimate_tokens();
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}
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@ -515,6 +521,29 @@ pub fn into_anthropic(
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None
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}
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}
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MessageContent::Thinking {
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text: thinking,
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signature,
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} => {
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if !thinking.is_empty() {
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Some(anthropic::RequestContent::Thinking {
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thinking,
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signature: signature.unwrap_or_default(),
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cache_control,
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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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MessageContent::RedactedThinking(data) => {
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if !data.is_empty() {
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Some(anthropic::RequestContent::RedactedThinking {
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data: String::from_utf8(data).ok()?,
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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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MessageContent::Image(image) => Some(anthropic::RequestContent::Image {
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source: anthropic::ImageSource {
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source_type: "base64".to_string(),
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@ -637,7 +666,10 @@ pub fn map_to_language_model_completion_events(
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}
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ResponseContent::Thinking { thinking } => {
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return Some((
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vec![Ok(LanguageModelCompletionEvent::Thinking(thinking))],
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vec![Ok(LanguageModelCompletionEvent::Thinking {
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text: thinking,
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signature: None,
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})],
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state,
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));
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}
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@ -665,11 +697,22 @@ pub fn map_to_language_model_completion_events(
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}
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ContentDelta::ThinkingDelta { thinking } => {
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return Some((
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vec![Ok(LanguageModelCompletionEvent::Thinking(thinking))],
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vec![Ok(LanguageModelCompletionEvent::Thinking {
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text: thinking,
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signature: None,
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})],
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state,
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));
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}
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ContentDelta::SignatureDelta { signature } => {
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return Some((
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vec![Ok(LanguageModelCompletionEvent::Thinking {
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text: "".to_string(),
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signature: Some(signature),
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})],
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state,
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));
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}
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ContentDelta::SignatureDelta { .. } => {}
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ContentDelta::InputJsonDelta { partial_json } => {
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if let Some(tool_use) = state.tool_uses_by_index.get_mut(&index) {
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tool_use.input_json.push_str(&partial_json);
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@ -742,9 +742,10 @@ pub fn get_bedrock_tokens(
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for content in message.content {
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match content {
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MessageContent::Text(text) => {
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MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
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string_contents.push_str(&text);
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}
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MessageContent::RedactedThinking(_) => {}
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MessageContent::Image(image) => {
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tokens_from_images += image.estimate_tokens();
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}
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@ -830,25 +831,36 @@ pub fn map_to_language_model_completion_events(
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redacted,
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) => {
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let thinking_event =
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LanguageModelCompletionEvent::Thinking(
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String::from_utf8(
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LanguageModelCompletionEvent::Thinking {
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text: String::from_utf8(
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redacted.into_inner(),
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)
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.unwrap_or("REDACTED".to_string()),
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);
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signature: None,
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};
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return Some((
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Some(Ok(thinking_event)),
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state,
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));
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}
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ReasoningContentBlockDelta::Signature(_sig) => {
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ReasoningContentBlockDelta::Signature(
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signature,
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) => {
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return Some((
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Some(Ok(LanguageModelCompletionEvent::Thinking {
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text: "".to_string(),
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signature: Some(signature)
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})),
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state,
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));
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}
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ReasoningContentBlockDelta::Text(thoughts) => {
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let thinking_event =
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LanguageModelCompletionEvent::Thinking(
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thoughts.to_string(),
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);
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LanguageModelCompletionEvent::Thinking {
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text: thoughts.to_string(),
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signature: None
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};
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return Some((
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Some(Ok(thinking_event)),
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@ -424,8 +424,11 @@ impl CopilotChatLanguageModel {
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let text_content = {
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let mut buffer = String::new();
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for string in message.content.iter().filter_map(|content| match content {
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MessageContent::Text(text) => Some(text.as_str()),
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MessageContent::Text(text) | MessageContent::Thinking { text, .. } => {
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Some(text.as_str())
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}
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MessageContent::ToolUse(_)
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| MessageContent::RedactedThinking(_)
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| MessageContent::ToolResult(_)
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| MessageContent::Image(_) => None,
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}) {
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@ -368,13 +368,15 @@ pub fn into_google(
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content
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.into_iter()
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.filter_map(|content| match content {
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language_model::MessageContent::Text(text) => {
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language_model::MessageContent::Text(text)
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| language_model::MessageContent::Thinking { text, .. } => {
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if !text.is_empty() {
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Some(Part::TextPart(google_ai::TextPart { text }))
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} else {
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None
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}
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}
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language_model::MessageContent::RedactedThinking(_) => None,
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language_model::MessageContent::Image(_) => None,
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language_model::MessageContent::ToolUse(tool_use) => {
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Some(Part::FunctionCallPart(google_ai::FunctionCallPart {
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@ -342,14 +342,16 @@ pub fn into_open_ai(
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for message in request.messages {
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for content in message.content {
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match content {
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MessageContent::Text(text) => messages.push(match message.role {
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Role::User => open_ai::RequestMessage::User { content: text },
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Role::Assistant => open_ai::RequestMessage::Assistant {
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content: Some(text),
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tool_calls: Vec::new(),
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},
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Role::System => open_ai::RequestMessage::System { content: text },
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}),
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MessageContent::Text(text) | MessageContent::Thinking { text, .. } => messages
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.push(match message.role {
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Role::User => open_ai::RequestMessage::User { content: text },
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Role::Assistant => open_ai::RequestMessage::Assistant {
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content: Some(text),
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tool_calls: Vec::new(),
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},
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Role::System => open_ai::RequestMessage::System { content: text },
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}),
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MessageContent::RedactedThinking(_) => {}
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MessageContent::Image(_) => {}
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MessageContent::ToolUse(tool_use) => {
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let tool_call = open_ai::ToolCall {
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