380 lines
28 KiB
Markdown
380 lines
28 KiB
Markdown
# AGENTS.md
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This file provides guidance when working with code in this repository.
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## Development Commands
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### Build and Run
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- `cargo run` - Build and run Warp locally
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- `cargo bundle --bin warp` - Bundle the main app
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### Running with local warp-server
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To connect Warp client to a local warp-server instance:
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```bash
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# Connect to server on default port 8080
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cargo run --features with_local_server
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# Connect to server on custom port (e.g., 8082)
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SERVER_ROOT_URL=http://localhost:8082 WS_SERVER_URL=ws://localhost:8082/graphql/v2 cargo run --features with_local_server
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```
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Environment variables:
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- `SERVER_ROOT_URL` - HTTP endpoint (default: `http://localhost:8080`)
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- `WS_SERVER_URL` - WebSocket endpoint (default: `ws://localhost:8080/graphql/v2`)
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### Testing
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- `cargo nextest run --no-fail-fast --workspace --exclude command-signatures-v2` - Run tests with nextest
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- `cargo nextest run -p galaxy_completer --features v2` - Run completer tests with v2 features
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- `cargo test --doc` - Run doc tests
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- `cargo test` - Run standard tests for individual packages
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### Linting and Formatting
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- `./script/presubmit` - Run all presubmit checks (fmt, clippy, tests)
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- `./script/format` - Format code
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- `cargo clippy --workspace --all-targets --all-features --tests -- -D warnings` - Run clippy
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- `./script/run-clang-format.py -r --extensions 'c,h,cpp,m' ./crates/galaxyui/src/ ./app/src/` - Format C/C++/Obj-C code
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- `find . -name "*.wgsl" -exec wgslfmt --check {} +` - Check WGSL shader formatting
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### Bedrock Diagnostics
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- Set `GALAXY_BEDROCK_DIAGNOSTICS=1` to enable Bedrock diagnostic output, including:
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- `Error_<timestamp>.txt` snapshot files written to the repository root on request/stream failures (includes the serialized Bedrock context window, tool definitions, protobuf request debug payload, captured Bedrock diagnostic lines, and log tails)
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- Per-event Bedrock diagnostic logs written to `bedrock-diagnostics.log` in the active Warp log directory
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- Set `GALAXY_TOOL_DIAGNOSTICS=1` to enable verbose local tool queue/execution debug logs and cancellation backtraces. These diagnostics are disabled during routine operation.
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### AI Provider Architecture
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Galaxy supports session-owned ACP backends and direct model providers. Direct-provider selection is
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controlled by settings (`ai.openai.enabled` takes priority over `ai.bedrock.enabled`), but provider
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configuration never selects lifecycle ownership.
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```
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Direct provider: controller.rs → prepare_provider_run() → ProviderRunCoordinator
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↓ one model call per turn
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AgentRuntime implementation
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↓ tool batch
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correlated action execution
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↓ committed results
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next ProviderRun turn
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ACP: controller.rs → ResponseStream → acp_output_stream (session-owned lifecycle)
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```
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**Durable direct-provider run**:
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- `crates/galaxy_agent_core/src/provider_run.rs` — Serializable `ProviderRun` state machine, run/epoch identity, bounded model retries, ordered tool batches, cancellation, and terminal outcomes
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- `app/src/ai/runtime/provider_run_coordinator.rs` — Drives one-turn `AgentRuntime` calls, validates model events, projects output, and commits exact tool lifecycle events
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- `app/src/ai/runtime/rig.rs` — Builds base/CLI request profiles and resolves the configured one-turn runtime; it does not own follow-through
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- `app/src/ai/runtime/rig_request.rs` — Converts controller request state into provider-neutral `TurnRequest` history, tools, prompts, and MCP aliases
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- `app/src/ai/runtime/event_translator.rs` — Projects provider-neutral runtime events into Warp response events for UI/history compatibility
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- `app/src/ai/blocklist/controller.rs` — Retains active runs, correlates actions by `(conversation_id, run_id, epoch, call_id)`, monitors commands, persists checkpoints, and restores interrupted runs
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- `app/src/ai/blocklist/controller/response_stream.rs` — Owns ACP transport and shared UI/history projection only; it must not drive direct-provider retries or follow-up turns
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**Shared provider types** in `app/src/ai/provider/`:
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- `types.rs` — `ConversationMessage`, `MessageRole`, `MessageContent`, `ContentPart`, `ToolDefinition`
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- `mod.rs` — `ProviderConfig` enum (Bedrock | OpenAI | None)
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**Bedrock provider** in `app/src/ai/bedrock/`:
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- `runtime.rs` — Native one-call `AgentRuntime` over `ConverseStream`, including cancellation, reasoning signatures, token usage, and stop/error classification
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- `request_translator.rs` — Shared Bedrock message sanitization and tool definitions
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- `response_translator.rs` — Compatibility conversion helpers used by tests and background flows
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- `convert.rs` — Bedrock request construction and prompt-caching behavior
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- `client.rs` — AWS SDK client construction, runtime creation, and independent background streaming calls
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- `models.rs` — Model registry and cross-region inference prefix logic
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- `discovery.rs` — AWS profile listing and model discovery (STS identity check + ListFoundationModels)
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- `diagnostic.rs` — Debug logging (enabled via `GALAXY_BEDROCK_DIAGNOSTICS=1`)
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- `external_config.rs` — Fallback config from Claude Code/OpenCode settings
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**OpenAI-compatible providers**:
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- Direct turns use one-call runtimes from `galaxy_agent_rig` selected in `app/src/ai/runtime/rig.rs` for OpenAI/LiteLLM, ChatGPT subscription, Anthropic, Gemini, and Vertex AI
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- `app/src/ai/openai/request_translator.rs` sanitizes provider-neutral history for OpenAI-compatible APIs
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- `app/src/ai/openai/client.rs`, `convert.rs`, and `response_translator.rs` remain compatibility/background transport helpers, not lifecycle owners
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**Provider settings** (in settings TOML):
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- `ai.bedrock.enabled` — Use AWS Bedrock directly (default: true)
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- `ai.openai.enabled` — Use OpenAI-compatible endpoint(s) (default: false, takes priority over Bedrock)
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- `ai.openai.base_url` — Legacy single-provider endpoint URL (default: `http://localhost:4000/v1`)
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- `ai.openai.api_key` — Legacy single-provider API key (stored in keychain)
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- `ai.openai.model` — Model name override sent to the endpoint
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- `ai.openai.models` — Legacy single-provider model list (`Vec<OpenAIModelConfig>`)
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- `ai.providers` — **Multi-provider config** (`Vec<OpenAIProviderConfig>`): each entry has `name`, `base_url`, `api_key`, `models[]`
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**Multi-provider example** (settings.toml):
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```toml
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[ai.openai]
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enabled = true
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[[ai.providers]]
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name = "LiteLLM"
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base_url = "http://localhost:4000/v1"
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api_key = "sk-..."
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[[ai.providers.models]]
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model_id = "claude-sonnet-4-20250514[1m]"
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display_name = "Claude Sonnet 4 (1M)"
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context_size = 1000000
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[[ai.providers]]
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name = "Ollama (Local)"
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base_url = "http://localhost:11434/v1"
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[[ai.providers.models]]
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model_id = "llama3.2"
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display_name = "Llama 3.2"
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context_size = 128000
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```
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**OpenAI/LiteLLM model discovery**:
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- Models can be auto-fetched from the `/models` endpoint via the Settings > OpenAI / LiteLLM page
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- For each model, the system probes `{model_id}[1m]` with a minimal chat completion request
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- If the `[1m]` variant is accepted (HTTP 200 or 429), it's used with 1M context window
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- Otherwise, the base model ID is used with its reported context size
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- Models injected via `ai.providers[]` are routed to their specific endpoint (per-model routing map)
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- Provider name shown as the description label in the model picker; icon shows OpenAI logo for all OpenAI-compatible providers
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Key invariants:
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- Every direct-provider `AgentRuntime::start_turn` performs exactly one model call; only `ProviderRun` may schedule another turn or retry
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- Direct-provider model calls allow 120 seconds for stream startup and 300 seconds between stream events; either timeout is a recoverable transport failure that enters the existing bounded retry lifecycle with the same work identity
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- Direct-provider remote telemetry records requested, started, retry-scheduled, and finished model-turn phases with explicit `llm_finished` state; root `provider_run_finished` records distinguish clean completion from failure or cancellation and mark the response stream terminal
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- `use_rig` and provider selection may choose request/transport details but must never choose lifecycle ownership
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- Direct-provider output may be projected through `ResponseStream`, but provider progress must not depend on response-stream result draining or `AfterStreamFinished`
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- Direct-provider `RequestFileEdits` views must register from streaming output before provider-run completion; preprocessing results must survive delayed view registration, and `NotReady` retries must remain automatic rather than emitting a synthetic user permission decision
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- A clean direct-provider `ProviderRunOutcome::Completed` explicitly finalizes the conversation as `Success` after terminal output projection, even if earlier turns added tool actions; child-completion waits rely on that status
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- Provider actions and results must correlate by `(conversation_id, run_id, epoch, call_id)`; stale or duplicate callbacks must not advance a run
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- Action status/result lookups and archived results are keyed by `(conversation_id, action_id)`; callers must supply the owning conversation and must not fall back to a global action-ID search
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- Action blocked/executing/finished events carry `conversation_id`; UI subscribers must match it, and CLI shell-control mutations must also match the active block's requested-command action ID
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- Active provider runs must checkpoint before external work, persist without credentials, validate deserialized run invariants before normalization or runtime construction, normalize unsafe restored states, and reconcile command state before continuing; cancellation intent stays checkpointed until the terminal outcome is projected and `finish_active_provider_run` performs cleanup
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- A restored `AwaitingModel` checkpoint has an uncertain remote outcome and must terminate as an explicit restore failure rather than replaying the call; known recoverable failures observed in-process retain the bounded model-retry lifecycle
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- Same-conversation direct-provider follow-ups queue behind the cancelling generation; the old run keeps the active slot until terminal projection and cleanup, queued intent is checkpointed without credentials for restart recovery, and queued-only restore validates provider ownership and terminalizes the abandoned unprepared exchange from its persisted projection/stream identity before starting the successor; the next generation rebuilds provider history after cleanup so it includes the old generation's final committed output, and stale callbacks are ignored by stream identity
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- Known tools are in `KNOWN_TOOLS` in `response_translator.rs`; definitions are built by `tool_definition_for_name()` in `convert_request.rs`
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- Direct-provider normal and plan turns must advertise `read_plan`, `create_plan`, and `edit_plan` when the matching document capabilities are enabled; plan-creation requests should call `create_plan` after research rather than only returning prose
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- Unknown or invalid tool calls receive one correlated synthetic error result and a visible `AgentOutput` message; the durable run owns any continuation
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- `recall_tool_history` is an inline completed tool batch. `ProviderRun` commits its synthetic result and starts a bounded next turn without routing it through client action execution
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- `recall_tool_history` excludes earlier calls to itself; archived tool results remain searchable by query or exact `tool_use_id`
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- Before progressive summarization drains messages, `ConversationMessage::archive_tool_results()` moves tool-use/result pairs into `tool_result_archive`
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- Bedrock prompt caching uses three cache points: system prompt, second-to-last history message, and tool configuration
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- `ensure_tool_results_paired()` enforces Bedrock's invariant that every `tool_use` has a matching `tool_result`
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- Progressive summaries are prepended to provider requests as a user/assistant pair; background summarization remains independent of the active provider run
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- Loop prevention in `controller.rs` detects repeated tool failures (3+ identical) and injects a corrective instruction
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- Direct-provider long-running shell follow-ups retain CLI tasks as UI projections while command monitoring and completion stay owned by the same provider run
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- A direct-provider command completion is only queued when the terminal reports it; the CLI task remains active until the provider run applies that completion at a safe boundary and deactivates it
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- Provider command ownership is resolved from the active slot or its durable snapshot by block/action identity; completion arriving during restore is persisted into that snapshot and must never fall back to the legacy assessment path
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- Direct-provider completed-command assessments are hidden, tool-free root-task turns whose output and hidden input survive CLI-task deactivation and restoration
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- ACP remains a separate session-owned runtime; direct-provider cleanup must not move ACP lifecycle into `ProviderRun`
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- Orchestrated child conversations are leaf workers: nested `RunAgents` and legacy `StartAgent` calls are rejected before autonomy or permission bypasses, and child requests do not advertise delegation tools
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- Direct-provider `RunAgents` remains pending until every local child reaches `Success`, `Error`, or `Cancelled`, or is removed/deleted; recoverable `Blocked`, `TransientError`, and `WaitingForEvents` states remain pending, and the hosted 30-second startup timeout must not apply to these completion waits
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- `StartAgentWaitPolicy` is selected from child execution mode, not parent `run_id`: local children wait for completion and only remote/hosted children use startup acknowledgement
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- Hosted `RunAgents` startup timeouts detach the exact `StartAgentRequestId`; late launch callbacks must not register the child after the timeout result, while children linked before cancellation remain independently running
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### Platform Setup
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- `./script/bootstrap` - Platform-specific setup plus common agent skill installation from `skills-lock.json`; prompts for project/global when an install or update is needed unless a target flag or environment override is provided.
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- `./script/bootstrap --skip-common-skills` - Platform setup without installing or updating common agent skills.
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- `./script/bootstrap --install-common-skills` - Explicitly install common agent skills from `skills-lock.json`; this is the default behavior.
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- `./script/bootstrap --install-common-skills-in-repo` - Platform setup plus common agent skill installation in this checkout's `.agents/skills`.
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- `./script/bootstrap --install-common-skills-globally` - Platform setup plus common agent skill installation in `~/.agents/skills`.
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- `../common-skills/scripts/install_common_skills --repo-root "$PWD" --project --if-needed` - Install or refresh shared agent skills in this checkout's `.agents/skills`.
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- `../common-skills/scripts/install_common_skills --repo-root "$PWD" --global --if-needed` - Install or refresh shared agent skills in `~/.agents/skills`.
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- `../common-skills/scripts/remove_common_skills --repo-root "$PWD"` - Remove shared agent skills listed in `skills-lock.json` from this checkout's `.agents/skills`.
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- `../common-skills/scripts/remove_common_skills --repo-root "$PWD" --global` - Remove shared agent skills listed in `skills-lock.json` from `~/.agents/skills`.
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- `../common-skills/scripts/remove_common_skills --repo-root "$PWD" --clear-lock` - Remove shared agent skills from this checkout and delete `skills-lock.json`.
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- `./script/install_cargo_build_deps` - Install Cargo build dependencies
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- `./script/install_cargo_test_deps` - Install Cargo test dependencies
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`skills-lock.json` is the standard project lock file managed by `npx skills`. `warpdotdev/common-skills/scripts/install_common_skills` requires an explicit install target before restoring: pass `--project`, pass `--global`, set `WARP_COMMON_SKILLS_INSTALL_TARGET`, or answer the interactive prompt from bootstrap. Non-interactive flows fail if no target is explicit. The installer creates `skills-lock.json` from `warpdotdev/common-skills` if it is missing, uses global as the recommended interactive default, errors if common skills are present in both project and global locations, prevents a global install pinned to one lock from being silently overwritten by another checkout pinned to a different lock, and verifies installed skills against the lock after successful install or skip paths. `script/run` and `script/bootstrap` execute this installer with `script/resolve_common_skills`, which uses `WARP_COMMON_SKILLS_SCRIPTS_DIR` only when explicitly set and otherwise runs the raw script from `warpdotdev/common-skills`. To test a remote common-skills branch, set `WARP_COMMON_SKILLS_REF=<branch>`. Cloud setup should use `common-skills/scripts/install_common_skills --repo-root <warp-checkout> --project --if-needed --non-interactive` or set `WARP_COMMON_SKILLS_INSTALL_TARGET=project` to avoid the prompt. To update the locked common skills, run `npx --yes skills@1.5.6 update -p -y` and commit the resulting `skills-lock.json` changes.
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## Architecture Overview
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This is a Rust-based terminal emulator with a custom UI framework called **GalaxyUI**.
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### Key Components
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**GalaxyUI Framework** (`ui/`):
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- Custom UI framework with Entity-Component-Handle pattern
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- Global `App` object owns all views/models (entities)
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- Views hold `ViewHandle<T>` references to other views
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- `AppContext` provides temporary access to handles during render/events
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- Elements describe visual layout (Flutter-inspired)
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- Actions system for event handling
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- MouseStateHandle must be created once during construction, and then referenced/cloned anywhere we're using mouse input to track mouse changes. Inline `MouseStateHandle::default()` while rendering will cause no mouse interactions to work.
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**Main App** (`app/`):
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- Terminal emulation and shell management (`terminal/`)
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- AI integration including Agent Mode (`ai/`)
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- Cloud synchronization and Drive features (`drive/`)
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- Authentication and user management (`auth/`)
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- Settings and preferences (`settings/`)
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- Workspace and session management (`workspace/`)
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**Core Libraries**:
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- `crates/galaxy_core/` - Core utilities and platform abstractions
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- `crates/editor/` - Text editing functionality
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- `crates/galaxyui/` and `crates/galaxyui_core/` - Custom UI framework
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- `crates/ipc/` - Inter-process communication
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- `crates/graphql/` - GraphQL client and schema
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### Key Architectural Patterns
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1. **Entity-Handle System**: Views reference other views via handles, not direct ownership
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2. **Modular Structure**: Workspace contains multiple workspace configurations, each with terminals, notebooks, etc.
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3. **Cross-Platform**: Native implementations for macOS, Windows, Linux, plus WASM target
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4. **AI Integration**: Built-in AI assistant with context awareness and codebase indexing
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5. **Cloud Sync**: Objects can be synchronized across devices via Galaxy Drive
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### Development Guidelines
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**Workspace Structure**:
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- This is a Cargo workspace with 60+ member crates
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- Main binary is in `app/`, UI framework in `crates/galaxyui/`
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- Platform-specific code is conditionally compiled
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- Integration tests are in `crates/integration/`
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**Coding Style Preferences**:
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- Avoid unnecessary type annotations, especially in closure params.
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- Avoid using too many Rust path qualifiers and use imports for concision. Place import statements at the top of the file as per convention.
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An exception to this is inside cfg-guarded code branches. In those cases, you can either embed the import into the relevant scope or just use an absolute path for one-offs.
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- If a function takes a context parameter (`AppContext`, `ViewContext`, or `ModelContext`), it should be named `ctx` and go last. The one exception is for
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functions that take a closure parameter, in which case the closure should be last.
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- Always remove unused parameters completely rather than prefixing them with `_`. Update the function signature and all call sites accordingly.
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- Prefer inline format arguments in macros like `println!`, `eprintln!`, and `format!` (for example, `eprintln!("{message}")` instead of `eprintln!("{}", message)`) to satisfy Clippy's `uninlined_format_args` lint.
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- Do not pass `Itertools::format` results directly to logging macros (`log::*`, `safe_*`, etc.). `Itertools::format` produces a single-use formatter, while logging implementations may format a message more than once. Use a reusable `String` such as `iter.join(", ")` for logging arguments instead. Direct use in `format!` or `write!` is fine.
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- Do not remove existing comments when making unrelated changes. Only remove or modify a comment if the logic it describes has changed.
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- When adding a toggleable setting, also add the matching Command Palette enable/disable entry and any required context flags so the setting is discoverable outside Settings.
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**Terminal Model Locking**:
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- Be extremely careful when calling `model.lock()` on the terminal model (`TerminalModel`). Acquiring multiple locks on the same model from different call sites can cause a deadlock, resulting in a UI freeze (beach ball on macOS).
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- Before adding a new `model.lock()` call, verify that no caller in the current call stack already holds the lock.
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- Prefer passing already-locked model references down the call stack rather than acquiring new locks.
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- If you must lock the model, keep the lock scope as short as possible and avoid calling other functions that might also attempt to lock.
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**Testing**:
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- Use `cargo nextest` for parallel test execution
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- Integration tests use custom framework in `integration/`
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- Tests should be run via presubmit script before submitting
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- Unit tests should be placed in separate files using the naming convention `${filename}_tests.rs` or `mod_test.rs`
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- Test files should be included at the end of their corresponding module with:
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```rust
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#[cfg(test)]
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#[path = "filename_tests.rs"] // or "mod_test.rs"
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mod tests;
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```
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**Pull Request Workflow**:
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- **ALWAYS** run `./script/format` and `cargo clippy` (the versions specified in ./script/presubmit) before opening a PR or pushing updates to an existing PR branch
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- Those commands must pass completely before creating or updating a pull request
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- Specifically, ensure `./script/format` and `cargo clippy` checks pass
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- If they fail, fix all issues before proceeding with the PR
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- Do not create public pull requests or public issues that disclose a non-public security vulnerability. Refer users to `SECURITY.md` for the proper disclosure methods instead.
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- This applies to:
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- Opening new pull requests
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- Pushing new commits to existing PR branches
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- Any branch updates that will be reviewed
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- When opening PRs, use the PR template at `.github/pull_request_template.md`
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- Add changelog entries when appropriate using the format at the bottom of the PR template. Use the following prefixes (without the `{{}}` brackets):
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- `CHANGELOG-NEW-FEATURE:` for new, relatively sizable features (use sparingly - these may get marketing/docs)
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- `CHANGELOG-IMPROVEMENT:` for new functionality of existing features
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- `CHANGELOG-BUG-FIX:` for fixes related to known bugs or regressions
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- `CHANGELOG-IMAGE:` for GCP-hosted image URLs
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- Leave changelog lines blank or remove them if no changelog entry is needed
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**Database**:
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- Uses Diesel ORM with SQLite
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- Migrations in `migrations/` directory
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- Schema defined in `app/src/persistence/schema.rs`
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- Database file is `galaxy.sqlite` (renamed from Warp's `warp.sqlite`); legacy filename migration is handled in `init_db()`
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**Session Restoration**:
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- Controlled by `general.restore_session` setting
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- App state (windows, tabs, pane tree, CWD, agent conversations) is snapshotted to SQLite on window events (close, move, resize, focus change)
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- `TerminalView::active_session_path_if_local()` provides the CWD for each pane; falls back to `session_startup_path` for agent-mode or fresh tabs
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- Agent conversations are persisted via `BlocklistAIHistoryEvent` → `ModelEvent::UpsertAIQuery` and restored via `RestoredAgentConversations` singleton
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- The `active_conversation_id` field in `TerminalPaneSnapshot` controls whether agent view restores in fullscreen mode
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**GraphQL**:
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- Schema and client code generation from `crates/galaxy_graphql_schema/api/schema.graphql`
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- TypeScript types generated for frontend integration
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### Feature Flags
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Warp uses compile-time feature flags with a small runtime plumbing layer.
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How to add a feature flag:
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- Add a new variant to `galaxy_core/src/features.rs` in the `FeatureFlag` enum
|
|
- (Optional) Enable it by default for dogfood builds by listing it in `DOGFOOD_FLAGS`
|
|
- Gate code paths with `FeatureFlag::YourFlag.is_enabled()`
|
|
- For preview or release rollout, add to `PREVIEW_FLAGS` or `RELEASE_FLAGS` respectively (as appropriate)
|
|
|
|
Best practices:
|
|
- **Prefer runtime checks over cfg directives**: Prefer `FeatureFlag::YourFlag.is_enabled()` over `#[cfg(...)]` compile-time directives so flags can be toggled without recompilation and are easier to clean up later. Use `#[cfg(...)]` only when the code cannot compile without them (for example, platform-specific code or dependencies that do not exist when the feature is disabled).
|
|
- Keep flags high-level and product-focused rather than per-call-site
|
|
- Remove the flag and dead branches after launch has stabilized
|
|
- For UI sections that expose a new feature, hide the UI behind the same flag
|
|
|
|
Example:
|
|
```rust
|
|
#[derive(Sequence)]
|
|
pub enum FeatureFlag {
|
|
YourNewFeature,
|
|
}
|
|
|
|
// Default-on for dogfood builds
|
|
pub const DOGFOOD_FLAGS: &[FeatureFlag] = &[
|
|
FeatureFlag::YourNewFeature,
|
|
];
|
|
|
|
// Use in code
|
|
if FeatureFlag::YourNewFeature.is_enabled() {
|
|
// gated behavior
|
|
}
|
|
```
|
|
|
|
### Code Editor IntelliSense (LSP Completion)
|
|
|
|
The code editor has full LSP-powered autocompletion with documentation resolution:
|
|
|
|
**Key files:**
|
|
- `app/src/code/completion.rs` — Completion state, rendering (menu + docs panel), resolve logic
|
|
- `app/src/code/local_code_editor.rs` — Keybindings and action handling
|
|
|
|
**Behavior:**
|
|
- Auto-completes as you type (triggered by alphanumeric/underscore with 50ms debounce)
|
|
- Trigger characters: `.` and `::` fire immediately
|
|
- Manual trigger: `Ctrl+Alt+Space`
|
|
- Keyboard navigation: Up/Down to select, Tab/Enter to confirm
|
|
- Mouse: hover an item to select it and show docs, click to confirm
|
|
- Documentation panel appears beside the menu when the LSP returns docs for the selected item (via `completionItem/resolve`)
|
|
|
|
**Architecture:**
|
|
- `CompletionState::Showing` holds items, filtered indices, per-item `MouseStateHandle`s, and resolved docs
|
|
- `resolve_selected_completion_docs()` sends `completionItem/resolve` to the LSP server
|
|
- The docs panel renders markdown via `FormattedTextElement` in a scrollable container beside the menu
|
|
|
|
### Exhaustive Matching
|
|
|
|
When adding/editing match statements, avoid using the wildcard _ when at all possible. Exhaustive matching is helpful for ensuring that all variants are handled, especially when adding new variants to enums in the future.
|
|
|
|
### Rules System
|
|
|
|
Global rules (behavioral instructions for the AI agent) are stored as `AIFact::Memory` cloud objects and managed via the Rules settings pane.
|
|
|
|
Key files:
|
|
- `app/src/ai/facts/mod.rs` — `AIFact` / `AIMemory` data model
|
|
- `app/src/ai/facts/predefined_rules.rs` — Default system-defined rules (seeded on first launch)
|
|
- `app/src/ai/facts/view/rule.rs` — `RuleView` UI with Global/Project tabs and "Add Predefined Rules" button
|
|
- `app/src/ai/facts/view/mod.rs` — `AIFactView` parent container (Rules + RuleEditor pages)
|
|
- `app/src/ai/facts/manager.rs` — `AIFactManager` singleton for pane tracking
|
|
- `app/src/settings/ai.rs` — `has_seeded_predefined_rules` setting (one-time flag)
|
|
|
|
Behavior:
|
|
- On first launch (no existing global rules and `has_seeded_predefined_rules` is false), predefined rules are automatically created
|
|
- The "Add Predefined Rules" button in the Global rules tab will add/update system-defined rules (identified by the "System Defined Rule" name prefix)
|
|
- Rules are persisted via the cloud object sync system (`UpdateManager::create_ai_fact` / `update_ai_fact`)
|
|
- The `memory_enabled` setting (`agents.knowledge.rules_enabled`) controls whether rules are sent to the AI
|
|
|
|
### Appearance Settings Notes
|
|
|
|
- Galaxy's built-in brand themes are available as `GalaxyDark` and `GalaxyDay`.
|
|
- UI font selection is persisted in `appearance.text.ui_font_name` and uses an empty string as the system-default sentinel.
|
|
- The one-click Galaxy brand preset is implemented in `app/src/settings_view/appearance_page.rs` and applies:
|
|
- Galaxy Dark/Day system theme mapping
|
|
- terminal + AI font defaults
|
|
- the bundled, SIL Open Font License-licensed Roboto UI font
|