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Fix cursor focus and selection in input box, add AWS env var warning box, and remove AWS Bedrock login banner

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This commit is contained in:
rkw6086
2026-07-02 14:54:15 -05:00
parent 4770ac06b5
commit 3769646ca6
1194 changed files with 5312 additions and 8032 deletions
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app/src/ai/agent/api/convert_conversation.rs
+5 -1
View File
@@ -14,8 +14,8 @@ use ai::agent::action_result::{
};
use ai::skills::{ParsedSkill, SkillPathOrigin};
use chrono::{DateTime, Local, TimeZone};
use persistence::model::AgentConversationData;
use galaxy_core::command::ExitCode;
use persistence::model::AgentConversationData;
use warp_multi_agent_api as api;
use warp_multi_agent_api::ask_user_question_result::answer_item::Answer as AskUserQuestionAnswer;
@@ -89,6 +89,8 @@ pub fn convert_conversation_data_to_ai_conversation(
autoexecute_override: None,
last_event_sequence: None,
pinned: false,
progressive_summary: None,
messages_summarized_up_to: 0,
},
RestorationMode::Continue => AgentConversationData {
server_conversation_token: Some(
@@ -110,6 +112,8 @@ pub fn convert_conversation_data_to_ai_conversation(
autoexecute_override: None,
last_event_sequence: None,
pinned: false,
progressive_summary: None,
messages_summarized_up_to: 0,
},
};
app/src/ai/agent/api/convert_conversation_tests.rs
+1
View File
@@ -31,6 +31,7 @@ fn test_server_metadata(
token_usage: vec![],
tool_usage_metadata: Default::default(),
context_window_segments: Vec::new(),
..Default::default()
},
metadata: ServerMetadata {
uid: ServerId::default(),
app/src/ai/agent/api/impl.rs
+63 -31
View File
@@ -8,11 +8,15 @@ use warp_multi_agent_api as api;
use super::convert_to::convert_input;
use super::{ConvertToAPITypeError, RequestParams, ResponseStream};
use crate::ai::agent::redaction;
use crate::server::server_api::{AIApiError, ServerApi};
use crate::ai::openai::translator as openai_translator;
use crate::ai::provider::ProviderConfig;
use crate::server::server_api::ai::AIClient;
use crate::server::server_api::AIApiError;
use crate::terminal::model::session::SessionType;
pub async fn generate_multi_agent_output(
provider_config: ProviderConfig,
server_api: Arc<dyn AIClient>,
mut params: RequestParams,
cancellation_rx: futures::channel::oneshot::Receiver<()>,
) -> Result<ResponseStream, ConvertToAPITypeError> {
@@ -65,9 +69,9 @@ pub async fn generate_multi_agent_output(
input: Some(convert_input(params.input)?),
settings: Some(api::request::Settings {
model_config: Some(api::request::settings::ModelConfig {
base: params.model.into(),
cli_agent: params.cli_agent_model.into(),
computer_use_agent: params.computer_use_model.into(),
base: params.model.clone().into(),
cli_agent: params.cli_agent_model.clone().into(),
computer_use_agent: params.computer_use_model.clone().into(),
base_model_context_window_limit: params.context_window_limit.unwrap_or(0),
..Default::default()
}),
@@ -136,24 +140,11 @@ pub async fn generate_multi_agent_output(
mcp_context: params.mcp_context.map(Into::into),
};
let response_stream =
warp_multi_agent_client::generate_multi_agent_output(server_api.as_ref(), &request).await;
match response_stream {
Ok(stream) => {
let output_stream = stream
.then(|result| async {
match result {
Ok(event) => Ok(event),
Err(error) => Err(convert_multi_agent_client_error(error).await),
}
})
.take_until(cancellation_rx);
Ok(Box::pin(output_stream))
}
match provider_config {
ProviderConfig::OpenAI(config) => {
let translator_request = openai_translator::TranslatorRequest {
config,
model_id,
model_id: params.model.as_str().to_string(),
root_task_id: params.root_task_id.clone(),
message_history: params.bedrock_message_history.clone(),
tool_result_archive: params.bedrock_tool_result_archive.clone(),
@@ -178,19 +169,60 @@ pub async fn generate_multi_agent_output(
}
}
}
ProviderConfig::Bedrock(config) => {
let translator_request = crate::ai::bedrock::translator::TranslatorRequest {
config,
model_id: params.model.as_str().to_string(),
root_task_id: params.root_task_id.clone(),
bedrock_message_history: params.bedrock_message_history.clone(),
bedrock_tool_result_archive: params.bedrock_tool_result_archive.clone(),
bedrock_progressive_summary: params.bedrock_progressive_summary.clone(),
bedrock_messages_sent: params.bedrock_messages_sent.clone(),
};
match crate::ai::bedrock::translator::execute(translator_request, &mut request).await {
Ok(stream) => {
let output_stream = stream.take_until(cancellation_rx);
Ok(Box::pin(output_stream))
}
Err(e) => {
log::error!("[bedrock] Translator error: {e}");
let err = Arc::new(crate::server::server_api::AIApiError::Stream {
stream_type: "bedrock",
source: anyhow::anyhow!("{e}"),
});
let (tx, rx) = async_channel::unbounded();
let _ = tx.send(Err(err)).await;
Ok(Box::pin(rx))
}
}
}
ProviderConfig::None => {
log::error!("No AI provider configured. Cannot process request.");
let err = Arc::new(crate::server::server_api::AIApiError::Stream {
stream_type: "provider_dispatch",
source: anyhow::anyhow!(
"No AI backend available. Please configure a provider in Settings > AI."
),
});
let (tx, rx) = async_channel::unbounded();
let _ = tx
.send(Err(convert_multi_agent_client_error(e).await))
.await;
Ok(Box::pin(rx))
let response_stream = warp_multi_agent_client::generate_multi_agent_output(
server_api.base_client().as_ref(),
&request,
)
.await;
match response_stream {
Ok(stream) => {
let output_stream = stream
.then(|result| async {
match result {
Ok(event) => Ok(event),
Err(error) => Err(convert_multi_agent_client_error(error).await),
}
})
.take_until(cancellation_rx);
Ok(Box::pin(output_stream))
}
Err(e) => {
let (tx, rx) = async_channel::unbounded();
let _ = tx
.send(Err(convert_multi_agent_client_error(e).await))
.await;
Ok(Box::pin(rx))
}
}
}
}
}