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* feat: port NPA psychographic profiling system into IronClaw
Port the complete psychographic profiling system from NPA into IronClaw,
including enriched profile schema, conversational onboarding, profile
evolution, and three-tier prompt augmentation.
Personal onboarding moved from wizard Step 9 to first assistant
interaction per maintainer feedback — the First Contact system prompt
block now instructs the LLM to conduct a natural onboarding conversation
that builds the psychographic profile via memory_write.
Changes:
- Enrich profile.rs with 5 new structs, 9-dimension analysis framework,
custom deserializers for backward compatibility, and rendering methods
- Add conversational onboarding engine with one-step-removed questioning
technique, personality framework, and confidence-scored profile generation
- Add profile evolution with confidence gating, analysis metadata tracking,
and weekly update routine
- Replace thin interaction style injection with three-tier system gated on
confidence > 0.6 and profile recency
- Replace wizard Step 9 with First Contact system prompt block that drives
conversational onboarding during the user's first interaction
- Add autonomy progression to SOUL.md seed and personality framework to
AGENTS.md seed
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* feat: replace chat-based onboarding with bootstrap greeting and workspace seeds
Remove the interactive onboarding_chat.rs engine in favor of a simpler
bootstrap flow: fresh workspaces get a proactive LLM greeting that
naturally profiles the user. Identity files are now seeded from
src/workspace/seeds/ instead of being hardcoded. Also removes the
identity-file write protection (seeds are now managed), adds routine
advisor integration, and includes an e2e trace for bootstrap greeting.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* feat(safety): sanitize identity file writes via Sanitizer to prevent prompt injection
Identity files (SOUL.md, AGENTS.md, USER.md, IDENTITY.md) are injected into
every system prompt. Rather than hard-blocking writes (which broke onboarding),
scan content through the existing Sanitizer and reject writes with High/Critical
severity injection patterns. Medium/Low warnings are logged but allowed.
Also clarifies AGENTS.md identity file roles (USER.md = user info, IDENTITY.md =
agent identity) and adds IDENTITY.md setup as an explicit bootstrap step.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* docs: update profile_onboarding_completed comment to reflect current wiring
The field is now actively used by the agent loop to suppress BOOTSTRAP.md
injection — remove the stale "not yet wired" TODO.
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(setup): use env_or_override for NEARAI_API_KEY in model fetch config
When the user authenticates via NEAR AI Cloud API key (option 4),
api_key_login() stores the key via set_runtime_env(). But
build_nearai_model_fetch_config() was using std::env::var() which
doesn't check the runtime overlay — so model listing fell back to
session-token auth and re-triggered the interactive NEAR AI
authentication menu.
Switch to env_or_override() which checks both real env vars and the
runtime overlay.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(agent): correct channel/user_id in bootstrap greeting persist call
persist_assistant_response was called with channel="default",
user_id="system" but the assistant thread was created via
get_or_create_assistant_conversation("default", "gateway") which owns
the conversation as user_id="default", channel="gateway". The mismatch
caused ensure_writable_conversation to reject the write with:
WARN Rejected write for unavailable thread id user=system channel=default
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(web): remove all inline event handlers for CSP compliance
The Content-Security-Policy header (added in f48fe95) blocks inline JS
via script-src 'self'. All onclick/onchange attributes in index.html
are replaced with getElementById().addEventListener() calls. Dynamic
inline handlers in app.js (jobs, routines, memory breadcrumb, code
blocks, TEE report) are replaced with data-action attributes and a
single delegated click handler on document.
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(agent): align bootstrap message user/channel and update fixture schema field
- Bootstrap IncomingMessage now uses ("default", "gateway") consistently
with persist and session registration calls
- Update bootstrap_greeting.json fixture: schema_version → version to
match current PROFILE_JSON_SCHEMA
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* style: cargo fmt
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(safety): address PR review — expand injection scanning and harden profile sync
- BOOTSTRAP.md: fix target "profile" → "context/profile.json" so the
write hits the correct path and triggers profile sync
- IDENTITY_FILES: add context/assistant-directives.md to the scanned
set since it is also injected into the system prompt
- sync_profile_documents(): scan derived USER.md and assistant-directives
content through Sanitizer before writing, rejecting High/Critical
injection patterns
- profile_evolution_prompt(): wrap recent_messages_summary in <user_data>
delimiters with untrusted-data instruction to mitigate indirect
prompt injection
- routine-advisor skill: update cron examples from 6-field to standard
5-field format for consistency with routine_create tool docs
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* style: cargo fmt
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 <[email protected]>
* fix(setup): detect env-provided LLM keys during quick-mode onboarding
Quick-mode wizard now checks LLM_BACKEND, NEARAI_API_KEY,
ANTHROPIC_API_KEY, and OPENAI_API_KEY env vars to pre-populate
the provider setting, so users aren't re-prompted for credentials
they already supplied. Also teaches setup_nearai() to recognize
NEARAI_API_KEY from env (previously only checked session tokens).
Includes web UI cleanup (remove duplicate event listeners) and
e2e test response count adjustment.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix(test): update routine_create_list to expect 7-field normalized cron
The cron normalizer now always expands to 7-field format, so the
stored schedule is "0 0 9 * * * *" not "0 0 9 * * *".
[skip-regression-check]
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* feat(setup): skip LLM provider prompts when NEARAI_API_KEY is present
In quick mode, if NEARAI_API_KEY is set in the environment and the
backend was auto-detected as nearai, skip the interactive inference
provider and model selection steps. The API key is persisted to the
secrets store and a default model is set automatically.
Also simplify the static fallback model list for nearai to a single
default entry.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: unify default model, static bootstrap greeting, and web UI cleanup
- Add DEFAULT_MODEL const and default_models() fallback list in
llm/nearai_chat.rs; use from config, wizard, and .env.example so the
default model is defined in one place
- Restore multi-model fallback list in setup wizard (was reduced to 1)
- Move BOOTSTRAP_GREETING to module-level const (out of run() body)
- Replace LLM-based bootstrap with static greeting (persist to DB before
channels start, then broadcast — eliminates startup LLM call and race)
- Fix double env::var read for NEARAI_API_KEY in quick setup path
- Move thread sidebar buttons into threads-section-header (web UI)
- Remove orphaned .thread-sidebar-header CSS and fix double blank line
- Update bootstrap e2e test for static greeting (no LLM trace needed)
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix(safety): move prompt injection scanning into Workspace write/append
Addresses PR #927 review comments (#1, #3) — identity file write
protection and unsanitized profile fields in system prompt.
Instead of scanning at the tool layer (memory.rs) or the sync layer
(sync_profile_documents), injection scanning now lives in
Workspace::write() and Workspace::append() for all files that are
injected into the system prompt. This ensures every code path that
writes to these files is protected, including future ones.
- Add SYSTEM_PROMPT_FILES const and reject_if_injected() in workspace
- Add WorkspaceError::InjectionRejected variant
- Add map_write_err() in memory.rs to convert InjectionRejected to
ToolError::NotAuthorized
- Remove redundant IDENTITY_FILES/Sanitizer from memory.rs
- Remove redundant sanitizer calls from sync_profile_documents()
- Move sanitization tests to workspace::tests
- Existing integration test (test_memory_write_rejects_injection)
continues to pass through the new path
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: cargo fmt
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: address Copilot review — merge marker order, orphan thread, stale fixture
- merge_profile_section: search for END marker after BEGIN position to
avoid matching a stray END earlier in the file
- Bootstrap phase 2: use get_or_create_session + Thread::with_id instead
of resolve_thread(None) to avoid creating an orphan thread
- setup_nearai: use env_or_override for NEARAI_API_KEY consistency with
runtime overlay
- Delete orphaned bootstrap_greeting.json fixture (no test references it)
- Add test_merge_end_marker_must_follow_begin regression test
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: cargo fmt
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: fmt agent_loop.rs (CI stable rustfmt)
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: lazy-init sanitizer, check profile non-empty before skipping bootstrap
Address Copilot review:
- Use LazyLock<Sanitizer> to avoid rebuilding Aho-Corasick + regexes
on every workspace write
- has_profile check now requires non-empty content, not just file
existence, to prevent empty profile.json from suppressing onboarding
- Add seed_tests integration tests (libsql-backed) verifying:
- Empty profile.json does not suppress BOOTSTRAP.md seeding
- Non-empty profile.json correctly suppresses bootstrap for upgrades
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: cargo fmt
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: duplicate language handler, empty LLM_BACKEND, test_rig style
Address Copilot review on PR #927:
- Remove duplicate language-option click listeners (delegated
data-action handler already covers them)
- Guard LLM_BACKEND env prefill against empty string to prevent
suppressing API-key-based auto-detection
- Use destructured local `keep_bootstrap` instead of `self.keep_bootstrap`
in test_rig for consistency after destructure
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: update stale BOOTSTRAP.md write-protection comment [skip-regression-check]
BOOTSTRAP.md is now in SYSTEM_PROMPT_FILES and gets injection scanning
on write. The old comment incorrectly stated it was not write-protected.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: replace debug_assert panics with graceful error returns [skip-regression-check]
debug_assert! in execute_tool_with_safety and JobContext::transition_to
panicked in test builds before the graceful error path could run.
Existing tests (test_cancel_job_completed, test_execute_empty_tool_name_returns_not_found)
already cover these paths — they were the ones failing.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: address Copilot review — schema label, env var check, path normalization, profile validation
1. Label ANALYSIS_FRAMEWORK and PROFILE_JSON_SCHEMA sections separately
in bootstrap prompt so the LLM knows which blob is the target structure.
2. Wizard quick-mode backend auto-detection now rejects empty env vars
(std::env::var().is_ok_and(|v| !v.is_empty())) to avoid selecting the
wrong backend when e.g. NEARAI_API_KEY="" is set.
3. Normalize the target path before comparing with paths::PROFILE in
memory_write so non-canonical variants like "context//profile.json"
still trigger profile sync.
4. seed_if_empty now requires valid JSON parse of context/profile.json
before treating it as a populated profile. Corrupted content no longer
permanently suppresses bootstrap seeding.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* style: cargo fmt
* fix: address Copilot review — append scan, profile validation, env_or_override
1. Workspace::append() now scans the combined content (existing + new)
for prompt injection, not just the appended chunk. Prevents split-
injection evasion across multiple appends.
2. seed_if_empty() now deserializes into PsychographicProfile instead of
serde_json::Value for profile validation. Stray/legacy JSON that
doesn't match the expected schema no longer suppresses bootstrap.
3. Wizard quick-mode backend auto-detection now uses env_or_override()
to honor runtime overlays and injected secrets. LLM_BACKEND value
is trimmed before storage.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* test: add bootstrap_onboarding_clears_bootstrap E2E trace test
Exercises the full onboarding flow end-to-end:
1. Bootstrap greeting fires automatically on fresh workspace
2. User converses for 3 turns (name, tools, work style)
3. Agent writes psychographic profile to context/profile.json
4. Profile sync generates USER.md and assistant-directives.md
5. Agent writes IDENTITY.md (chosen persona)
6. Agent clears BOOTSTRAP.md via memory_write(target: "bootstrap")
Verifies:
- BOOTSTRAP.md is non-empty before onboarding, empty after
- bootstrap_completed flag is set
- Profile contains expected user data (name, profession, interests)
- USER.md contains profile-derived content (name, tone, profession)
- Assistant-directives.md references user and communication style
- IDENTITY.md contains agent's chosen persona name
- All memory_write calls succeed
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: address Copilot review — slash collapse, env_or_override, cron trim [skip-regression-check]
1. memory.rs path normalization now uses the same char-by-char loop as
Workspace::normalize_path() to fully collapse consecutive slashes
(e.g. "context///profile.json" → "context/profile.json").
2. Quick-mode NEARAI_API_KEY check (line 239) now uses env_or_override()
consistently with the backend auto-detection block above it.
3. normalize_cron_expression() trims input before field counting so the
passthrough branch (7+ fields) also strips whitespace.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: Jay Zalowitz <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
794 lines
30 KiB
Rust
794 lines
30 KiB
Rust
//! TestRig -- a builder for wiring a real Agent with a replay LLM and test channel.
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//!
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//! Constructs a full `Agent` with real tools but a `TraceLlm` (or custom LLM)
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//! and a `TestChannel`, runs the agent in a background tokio task, and provides
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//! methods to inject messages, wait for responses, and inspect tool calls.
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#![allow(dead_code)] // Public API consumed by later test modules (Task 4+).
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use std::sync::Arc;
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use std::time::{Duration, Instant};
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use ironclaw::agent::{Agent, AgentDeps};
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use ironclaw::app::{AppBuilder, AppBuilderFlags};
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use ironclaw::channels::web::log_layer::LogBroadcaster;
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use ironclaw::channels::{OutgoingResponse, StatusUpdate};
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use ironclaw::config::Config;
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use ironclaw::db::Database;
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use ironclaw::llm::{LlmProvider, SessionConfig, SessionManager};
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use ironclaw::tools::Tool;
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use crate::support::instrumented_llm::InstrumentedLlm;
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use crate::support::metrics::{ToolInvocation, TraceMetrics};
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use crate::support::test_channel::{TestChannel, TestChannelHandle};
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use crate::support::trace_llm::{LlmTrace, TraceLlm};
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use ironclaw::llm::recording::{HttpExchange, ReplayingHttpInterceptor};
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// ---------------------------------------------------------------------------
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// TestRig
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// ---------------------------------------------------------------------------
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/// A running test agent with methods to inject messages and inspect results.
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pub struct TestRig {
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/// The test channel for sending messages and reading captures.
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channel: Arc<TestChannel>,
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/// Instrumented LLM for collecting token/call metrics.
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instrumented_llm: Arc<InstrumentedLlm>,
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/// When the rig was created (for wall-time measurement).
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start_time: Instant,
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/// Maximum tool-call iterations per agentic loop (for count-based limit detection).
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max_tool_iterations: usize,
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/// Handle to the background agent task (wrapped in Option so Drop can take it).
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agent_handle: Option<tokio::task::JoinHandle<()>>,
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/// Database handle for direct queries in tests.
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#[cfg(feature = "libsql")]
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db: Arc<dyn Database>,
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/// Workspace handle for direct memory operations in tests.
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#[cfg(feature = "libsql")]
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workspace: Option<Arc<ironclaw::workspace::Workspace>>,
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/// The underlying TraceLlm for inspecting captured requests.
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#[cfg(feature = "libsql")]
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trace_llm: Option<Arc<TraceLlm>>,
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/// Extension manager for direct extension operations in tests.
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#[cfg(feature = "libsql")]
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extension_manager: Option<Arc<ironclaw::extensions::ExtensionManager>>,
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/// Temp directory guard -- keeps the libSQL database file alive.
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#[cfg(feature = "libsql")]
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_temp_dir: tempfile::TempDir,
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}
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impl TestRig {
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/// Inject a user message into the agent.
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pub async fn send_message(&self, content: &str) {
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self.channel.send_message(content).await;
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}
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/// Inject a raw `IncomingMessage` (for tests that need attachments, etc.).
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pub async fn send_incoming(&self, msg: ironclaw::channels::IncomingMessage) {
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self.channel.send_incoming(msg).await;
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}
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/// Return all message lists that were sent to the LLM provider.
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///
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/// Only available when the rig was built with a `TraceLlm` (i.e., via `.with_trace()`).
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pub fn captured_llm_requests(&self) -> Vec<Vec<ironclaw::llm::ChatMessage>> {
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self.trace_llm
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.as_ref()
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.map(|t| t.captured_requests())
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.unwrap_or_default()
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}
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/// Return the extension manager for direct extension operations in tests.
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pub fn extension_manager(&self) -> Option<&Arc<ironclaw::extensions::ExtensionManager>> {
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self.extension_manager.as_ref()
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}
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/// Wait until at least `n` responses have been captured, or `timeout` elapses.
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pub async fn wait_for_responses(&self, n: usize, timeout: Duration) -> Vec<OutgoingResponse> {
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self.channel.wait_for_responses(n, timeout).await
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}
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/// Return the names of all `ToolStarted` events captured so far.
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pub fn tool_calls_started(&self) -> Vec<String> {
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self.channel.tool_calls_started()
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}
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/// Return `(name, success)` for all `ToolCompleted` events captured so far.
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pub fn tool_calls_completed(&self) -> Vec<(String, bool)> {
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self.channel.tool_calls_completed()
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}
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/// Return `(name, preview)` for all `ToolResult` events captured so far.
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pub fn tool_results(&self) -> Vec<(String, String)> {
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self.channel.tool_results()
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}
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/// Return `(name, duration_ms)` for all completed tools with timing data.
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pub fn tool_timings(&self) -> Vec<(String, u64)> {
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self.channel.tool_timings()
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}
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/// Return a snapshot of all captured status events.
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pub fn captured_status_events(&self) -> Vec<StatusUpdate> {
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self.channel.captured_status_events()
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}
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/// Clear all captured responses and status events.
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pub async fn clear(&self) {
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self.channel.clear().await;
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}
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/// Number of LLM calls made so far.
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pub fn llm_call_count(&self) -> u32 {
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self.instrumented_llm.call_count()
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}
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/// Total input tokens across all LLM calls.
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pub fn total_input_tokens(&self) -> u32 {
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self.instrumented_llm.total_input_tokens()
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}
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/// Total output tokens across all LLM calls.
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pub fn total_output_tokens(&self) -> u32 {
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self.instrumented_llm.total_output_tokens()
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}
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/// Estimated total cost in USD.
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pub fn estimated_cost_usd(&self) -> f64 {
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self.instrumented_llm.estimated_cost_usd()
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}
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/// Wall-clock time since rig creation.
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pub fn elapsed_ms(&self) -> u64 {
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self.start_time.elapsed().as_millis() as u64
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}
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/// Collect a complete `TraceMetrics` snapshot from all captured data.
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///
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/// Call this after `wait_for_responses()` to get the full metrics for the
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/// scenario. The `turns` count is based on the number of captured responses.
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pub async fn collect_metrics(&self) -> TraceMetrics {
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let completed = self.tool_calls_completed();
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// Build ToolInvocation records from ToolStarted/ToolCompleted pairs,
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// matching each completion with its captured timing data.
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let timings = self.tool_timings();
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let mut timing_iter_by_name: std::collections::HashMap<&str, Vec<u64>> =
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std::collections::HashMap::new();
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for (name, ms) in &timings {
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timing_iter_by_name
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.entry(name.as_str())
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.or_default()
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.push(*ms);
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}
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let tool_invocations: Vec<ToolInvocation> = completed
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.iter()
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.map(|(name, success)| {
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let duration_ms = timing_iter_by_name
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.get_mut(name.as_str())
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.and_then(|v| {
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if v.is_empty() {
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None
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} else {
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Some(v.remove(0))
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}
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})
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.unwrap_or(0);
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ToolInvocation {
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name: name.clone(),
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duration_ms,
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success: *success,
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}
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})
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.collect();
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// Detect if iteration limit was hit by comparing completed tool-call count
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// against the configured max_tool_iterations threshold.
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let hit_iteration_limit = completed.len() >= self.max_tool_iterations;
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// Count turns as the number of captured responses.
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let responses = self.channel.captured_responses();
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let turns = responses.len() as u32;
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TraceMetrics {
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wall_time_ms: self.elapsed_ms(),
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llm_calls: self.instrumented_llm.call_count(),
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input_tokens: self.instrumented_llm.total_input_tokens(),
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output_tokens: self.instrumented_llm.total_output_tokens(),
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estimated_cost_usd: self.instrumented_llm.estimated_cost_usd(),
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tool_calls: tool_invocations,
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turns,
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hit_iteration_limit,
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hit_timeout: false, // Caller can set this based on wait_for_responses result.
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}
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}
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/// Run a complete multi-turn trace, injecting user messages from the trace
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/// and waiting for responses after each turn.
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///
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/// Returns a `Vec` of response lists, one per turn. Status events and tool
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/// call data accumulate across all turns (no clearing between turns), so
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/// post-run assertions like `tool_calls_started()` reflect the whole trace.
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pub async fn run_trace(
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&self,
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trace: &LlmTrace,
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timeout: Duration,
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) -> Vec<Vec<OutgoingResponse>> {
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let mut all_responses: Vec<Vec<OutgoingResponse>> = Vec::new();
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let mut total_responses = 0usize;
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for turn in &trace.turns {
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self.send_message(&turn.user_input).await;
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let responses = self.wait_for_responses(total_responses + 1, timeout).await;
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// Extract only the new responses from this turn.
|
|
let turn_responses: Vec<OutgoingResponse> =
|
|
responses.into_iter().skip(total_responses).collect();
|
|
total_responses += turn_responses.len();
|
|
all_responses.push(turn_responses);
|
|
}
|
|
all_responses
|
|
}
|
|
|
|
/// Run a trace, then verify all declarative `expects` (top-level and per-turn).
|
|
///
|
|
/// Returns the per-turn response lists for additional manual assertions.
|
|
pub async fn run_and_verify_trace(
|
|
&self,
|
|
trace: &LlmTrace,
|
|
timeout: Duration,
|
|
) -> Vec<Vec<OutgoingResponse>> {
|
|
use crate::support::assertions::verify_expects;
|
|
|
|
let all_responses = self.run_trace(trace, timeout).await;
|
|
|
|
// Verify top-level expects against all accumulated data.
|
|
if !trace.expects.is_empty() {
|
|
let all_response_strings: Vec<String> = all_responses
|
|
.iter()
|
|
.flat_map(|turn| turn.iter().map(|r| r.content.clone()))
|
|
.collect();
|
|
let started = self.tool_calls_started();
|
|
let completed = self.tool_calls_completed();
|
|
let mut results = self.tool_results();
|
|
for status in self.channel.captured_status_events() {
|
|
if let ironclaw::channels::StatusUpdate::ToolCompleted {
|
|
name,
|
|
success: false,
|
|
error,
|
|
parameters,
|
|
} = status
|
|
{
|
|
let detail = format!(
|
|
"error={}; params={}",
|
|
error.unwrap_or_else(|| "unknown".to_string()),
|
|
parameters.unwrap_or_else(|| "{}".to_string())
|
|
);
|
|
results.push((name, detail));
|
|
}
|
|
}
|
|
verify_expects(
|
|
&trace.expects,
|
|
&all_response_strings,
|
|
&started,
|
|
&completed,
|
|
&results,
|
|
"top-level",
|
|
);
|
|
}
|
|
|
|
all_responses
|
|
}
|
|
|
|
/// Verify top-level `expects` from a trace against already-captured data.
|
|
///
|
|
/// Call this after `send_message()` + `wait_for_responses()` for flat-format
|
|
/// traces. For multi-turn traces, use `run_and_verify_trace()` instead.
|
|
pub fn verify_trace_expects(&self, trace: &LlmTrace, responses: &[OutgoingResponse]) {
|
|
use crate::support::assertions::verify_expects;
|
|
|
|
if trace.expects.is_empty() {
|
|
return;
|
|
}
|
|
let response_strings: Vec<String> = responses.iter().map(|r| r.content.clone()).collect();
|
|
let started = self.tool_calls_started();
|
|
let completed = self.tool_calls_completed();
|
|
let mut results = self.tool_results();
|
|
for status in self.channel.captured_status_events() {
|
|
if let ironclaw::channels::StatusUpdate::ToolCompleted {
|
|
name,
|
|
success: false,
|
|
error,
|
|
parameters,
|
|
} = status
|
|
{
|
|
let detail = format!(
|
|
"error={}; params={}",
|
|
error.unwrap_or_else(|| "unknown".to_string()),
|
|
parameters.unwrap_or_else(|| "{}".to_string())
|
|
);
|
|
results.push((name, detail));
|
|
}
|
|
}
|
|
verify_expects(
|
|
&trace.expects,
|
|
&response_strings,
|
|
&started,
|
|
&completed,
|
|
&results,
|
|
"top-level",
|
|
);
|
|
}
|
|
|
|
/// Signal the channel to shut down and abort the background agent task.
|
|
pub fn shutdown(mut self) {
|
|
self.channel.signal_shutdown();
|
|
if let Some(handle) = self.agent_handle.take() {
|
|
handle.abort();
|
|
}
|
|
}
|
|
}
|
|
|
|
impl Drop for TestRig {
|
|
fn drop(&mut self) {
|
|
if let Some(handle) = self.agent_handle.take()
|
|
&& !handle.is_finished()
|
|
{
|
|
handle.abort();
|
|
}
|
|
}
|
|
}
|
|
|
|
// ---------------------------------------------------------------------------
|
|
// TestRigBuilder
|
|
// ---------------------------------------------------------------------------
|
|
|
|
/// Builder for constructing a `TestRig`.
|
|
pub struct TestRigBuilder {
|
|
trace: Option<LlmTrace>,
|
|
llm: Option<Arc<dyn LlmProvider>>,
|
|
max_tool_iterations: usize,
|
|
injection_check: bool,
|
|
auto_approve_tools: Option<bool>,
|
|
enable_skills: bool,
|
|
enable_routines: bool,
|
|
http_exchanges: Vec<HttpExchange>,
|
|
extra_tools: Vec<Arc<dyn Tool>>,
|
|
keep_bootstrap: bool,
|
|
}
|
|
|
|
impl TestRigBuilder {
|
|
/// Create a new builder with defaults.
|
|
pub fn new() -> Self {
|
|
Self {
|
|
trace: None,
|
|
llm: None,
|
|
max_tool_iterations: 10,
|
|
injection_check: false,
|
|
auto_approve_tools: Some(true),
|
|
enable_skills: false,
|
|
enable_routines: false,
|
|
http_exchanges: Vec::new(),
|
|
extra_tools: Vec::new(),
|
|
keep_bootstrap: false,
|
|
}
|
|
}
|
|
|
|
/// Set the LLM trace to replay.
|
|
pub fn with_trace(mut self, trace: LlmTrace) -> Self {
|
|
self.trace = Some(trace);
|
|
self
|
|
}
|
|
|
|
/// Override the LLM provider directly (takes precedence over trace).
|
|
pub fn with_llm(mut self, llm: Arc<dyn LlmProvider>) -> Self {
|
|
self.llm = Some(llm);
|
|
self
|
|
}
|
|
|
|
/// Set the maximum number of tool iterations per agentic loop invocation.
|
|
pub fn with_max_tool_iterations(mut self, n: usize) -> Self {
|
|
self.max_tool_iterations = n;
|
|
self
|
|
}
|
|
|
|
/// Register additional custom tools (e.g. stub tools for testing).
|
|
pub fn with_extra_tools(mut self, tools: Vec<Arc<dyn Tool>>) -> Self {
|
|
self.extra_tools = tools;
|
|
self
|
|
}
|
|
|
|
/// Enable prompt injection detection in the safety layer.
|
|
///
|
|
/// When enabled, tool outputs are scanned for injection patterns
|
|
/// (e.g., "ignore previous instructions", special tokens like `<|endoftext|>`)
|
|
/// and critical patterns are escaped before reaching the LLM.
|
|
pub fn with_injection_check(mut self, enable: bool) -> Self {
|
|
self.injection_check = enable;
|
|
self
|
|
}
|
|
|
|
/// Override agent-level automatic approval of `UnlessAutoApproved` tools.
|
|
pub fn with_auto_approve_tools(mut self, enable: bool) -> Self {
|
|
self.auto_approve_tools = Some(enable);
|
|
self
|
|
}
|
|
|
|
/// Enable skill discovery and registration for this test rig.
|
|
pub fn with_skills(mut self) -> Self {
|
|
self.enable_skills = true;
|
|
self
|
|
}
|
|
|
|
/// Enable the routines system so the scheduler is wired with a `RoutineEngine`,
|
|
/// allowing routine jobs to actually execute. Routine tools are always registered
|
|
/// but require the engine to dispatch jobs.
|
|
pub fn with_routines(mut self) -> Self {
|
|
self.enable_routines = true;
|
|
self
|
|
}
|
|
|
|
/// Keep `bootstrap_pending` so the proactive greeting fires on startup.
|
|
pub fn with_bootstrap(mut self) -> Self {
|
|
self.keep_bootstrap = true;
|
|
self
|
|
}
|
|
|
|
/// Add pre-recorded HTTP exchanges for the `ReplayingHttpInterceptor`.
|
|
///
|
|
/// When set, all `http` tool calls will return these responses in order
|
|
/// instead of making real network requests.
|
|
pub fn with_http_exchanges(mut self, exchanges: Vec<HttpExchange>) -> Self {
|
|
self.http_exchanges = exchanges;
|
|
self
|
|
}
|
|
|
|
/// Build the test rig, creating a real agent and spawning it in the background.
|
|
///
|
|
/// Uses `AppBuilder::build_all()` to get the same component set as the real
|
|
/// binary, with only the LLM swapped for TraceLlm.
|
|
///
|
|
/// Requires the `libsql` feature for the embedded test database.
|
|
#[cfg(feature = "libsql")]
|
|
pub async fn build(self) -> TestRig {
|
|
use ironclaw::channels::ChannelManager;
|
|
use ironclaw::db::libsql::LibSqlBackend;
|
|
|
|
// Destructure self up front to avoid partial-move issues.
|
|
let TestRigBuilder {
|
|
trace,
|
|
llm,
|
|
max_tool_iterations,
|
|
injection_check,
|
|
auto_approve_tools,
|
|
enable_skills,
|
|
enable_routines,
|
|
http_exchanges: explicit_http_exchanges,
|
|
extra_tools,
|
|
keep_bootstrap,
|
|
} = self;
|
|
|
|
// 1. Create temp dir + libSQL database + run migrations.
|
|
let temp_dir = tempfile::tempdir().expect("failed to create temp dir");
|
|
let db_path = temp_dir.path().join("test_rig.db");
|
|
let backend = LibSqlBackend::new_local(&db_path)
|
|
.await
|
|
.expect("failed to create test LibSqlBackend");
|
|
backend
|
|
.run_migrations()
|
|
.await
|
|
.expect("failed to run migrations");
|
|
let db: Arc<dyn ironclaw::db::Database> = Arc::new(backend);
|
|
|
|
// 2. Build Config::for_testing().
|
|
let skills_dir = temp_dir.path().join("skills");
|
|
let installed_skills_dir = temp_dir.path().join("installed_skills");
|
|
let _ = std::fs::create_dir_all(&skills_dir);
|
|
let _ = std::fs::create_dir_all(&installed_skills_dir);
|
|
let mut config = Config::for_testing(db_path, skills_dir, installed_skills_dir);
|
|
config.agent.max_tool_iterations = max_tool_iterations;
|
|
config.safety.injection_check_enabled = injection_check;
|
|
config.skills.enabled = enable_skills;
|
|
if let Some(v) = auto_approve_tools {
|
|
config.agent.auto_approve_tools = v;
|
|
}
|
|
|
|
// 3. Create SessionManager + LogBroadcaster.
|
|
let session = Arc::new(SessionManager::new(SessionConfig::default()));
|
|
let log_broadcaster = Arc::new(LogBroadcaster::new());
|
|
|
|
// 4. Create TraceLlm + InstrumentedLlm, extract HTTP exchanges for replay.
|
|
let trace_http_exchanges = trace
|
|
.as_ref()
|
|
.map(|t| t.http_exchanges.clone())
|
|
.unwrap_or_default();
|
|
|
|
let mut trace_llm_ref: Option<Arc<TraceLlm>> = None;
|
|
let base_llm: Arc<dyn LlmProvider> = if let Some(llm) = llm {
|
|
llm
|
|
} else if let Some(trace) = trace {
|
|
let tlm = Arc::new(TraceLlm::from_trace(trace));
|
|
trace_llm_ref = Some(Arc::clone(&tlm));
|
|
tlm
|
|
} else {
|
|
let trace = LlmTrace::single_turn(
|
|
"test-rig-default",
|
|
"(default)",
|
|
vec![crate::support::trace_llm::TraceStep {
|
|
request_hint: None,
|
|
response: crate::support::trace_llm::TraceResponse::Text {
|
|
content: "Hello from test rig!".to_string(),
|
|
input_tokens: 10,
|
|
output_tokens: 5,
|
|
},
|
|
expected_tool_results: Vec::new(),
|
|
}],
|
|
);
|
|
let tlm = Arc::new(TraceLlm::from_trace(trace));
|
|
trace_llm_ref = Some(Arc::clone(&tlm));
|
|
tlm
|
|
};
|
|
let instrumented = Arc::new(InstrumentedLlm::new(base_llm));
|
|
let llm: Arc<dyn LlmProvider> = Arc::clone(&instrumented) as Arc<dyn LlmProvider>;
|
|
|
|
// 5. Build AppComponents via AppBuilder with injected DB and LLM.
|
|
let mut builder = AppBuilder::new(
|
|
config,
|
|
AppBuilderFlags::default(),
|
|
None,
|
|
session,
|
|
log_broadcaster,
|
|
);
|
|
builder.with_database(Arc::clone(&db));
|
|
builder.with_llm(llm);
|
|
let mut components = builder
|
|
.build_all()
|
|
.await
|
|
.expect("AppBuilder::build_all() failed in test rig");
|
|
|
|
// Clear bootstrap flag so tests don't get an unexpected proactive greeting
|
|
// (unless the test explicitly wants to test the bootstrap flow).
|
|
if !keep_bootstrap && let Some(ref ws) = components.workspace {
|
|
ws.take_bootstrap_pending();
|
|
}
|
|
|
|
// AppBuilder may re-resolve config from env/TOML and override test defaults.
|
|
// Force test-rig agent flags to the requested deterministic values.
|
|
components.config.agent.auto_approve_tools = auto_approve_tools.unwrap_or(true);
|
|
components.config.agent.allow_local_tools = true;
|
|
|
|
let scheduler_slot: ironclaw::tools::builtin::SchedulerSlot =
|
|
Arc::new(tokio::sync::RwLock::new(None));
|
|
|
|
// 6. Register job tools, routine tools, and extra tools.
|
|
{
|
|
// Ensure filesystem/shell dev tools are always available in the
|
|
// test rig, even if upstream builder flags/config disable local tools.
|
|
components.tools.register_dev_tools();
|
|
|
|
components.tools.register_job_tools(
|
|
Arc::clone(&components.context_manager),
|
|
Some(scheduler_slot.clone()),
|
|
None,
|
|
components.db.clone(),
|
|
None,
|
|
None,
|
|
None,
|
|
None,
|
|
);
|
|
|
|
// Routine tools: create a RoutineEngine with the LLM and workspace.
|
|
if let (Some(db_arc), Some(ws)) = (&components.db, &components.workspace) {
|
|
use ironclaw::agent::routine_engine::RoutineEngine;
|
|
use ironclaw::config::RoutineConfig;
|
|
|
|
let routine_config = RoutineConfig::default();
|
|
let (notify_tx, _notify_rx) = tokio::sync::mpsc::channel(16);
|
|
let engine = Arc::new(RoutineEngine::new(
|
|
routine_config,
|
|
Arc::clone(db_arc),
|
|
components.llm.clone(),
|
|
Arc::clone(ws),
|
|
notify_tx,
|
|
None,
|
|
components.tools.clone(),
|
|
components.safety.clone(),
|
|
ironclaw::agent::SandboxReadiness::Available, // tests don't use real Docker
|
|
));
|
|
components
|
|
.tools
|
|
.register_routine_tools(Arc::clone(db_arc), engine);
|
|
}
|
|
|
|
// Skills tools: ensure tests use temp skill dirs (sandbox-safe) even if
|
|
// AppBuilder did not wire them for this environment.
|
|
if enable_skills {
|
|
let registry = Arc::new(std::sync::RwLock::new(
|
|
ironclaw::skills::SkillRegistry::new(temp_dir.path().join("skills"))
|
|
.with_installed_dir(temp_dir.path().join("installed_skills")),
|
|
));
|
|
let catalog = ironclaw::skills::catalog::shared_catalog();
|
|
components
|
|
.tools
|
|
.register_skill_tools(Arc::clone(®istry), Arc::clone(&catalog));
|
|
components.skill_registry = Some(registry);
|
|
components.skill_catalog = Some(catalog);
|
|
}
|
|
|
|
// Register any extra test-specific tools.
|
|
for tool in extra_tools {
|
|
components.tools.register(tool).await;
|
|
}
|
|
}
|
|
|
|
// Save references for test accessors.
|
|
let db_ref = components.db.clone().expect("test rig requires a database");
|
|
let workspace_ref = components.workspace.clone();
|
|
let ext_mgr_ref = components.extension_manager.clone();
|
|
|
|
// 7. Construct AgentDeps from AppComponents (mirrors main.rs).
|
|
let deps = AgentDeps {
|
|
owner_id: components.config.owner_id.clone(),
|
|
store: components.db,
|
|
llm: components.llm,
|
|
cheap_llm: components.cheap_llm,
|
|
safety: components.safety,
|
|
tools: components.tools,
|
|
workspace: components.workspace,
|
|
extension_manager: components.extension_manager,
|
|
skill_registry: components.skill_registry,
|
|
skill_catalog: components.skill_catalog,
|
|
skills_config: components.config.skills.clone(),
|
|
hooks: components.hooks,
|
|
cost_guard: components.cost_guard,
|
|
sse_tx: None,
|
|
http_interceptor: {
|
|
// Prefer explicit exchanges from with_http_exchanges(), fall back to trace.
|
|
let exchanges = if explicit_http_exchanges.is_empty() {
|
|
trace_http_exchanges
|
|
} else {
|
|
explicit_http_exchanges
|
|
};
|
|
if exchanges.is_empty() {
|
|
None
|
|
} else {
|
|
Some(Arc::new(ReplayingHttpInterceptor::new(exchanges))
|
|
as Arc<dyn ironclaw::llm::recording::HttpInterceptor>)
|
|
}
|
|
},
|
|
transcription: None,
|
|
document_extraction: None,
|
|
sandbox_readiness: ironclaw::agent::SandboxReadiness::Available, // tests don't use real Docker
|
|
builder: None,
|
|
};
|
|
|
|
// 7. Create TestChannel and ChannelManager.
|
|
// When testing bootstrap, the channel must be named "gateway" because
|
|
// the bootstrap greeting targets only the gateway channel.
|
|
let test_channel = if keep_bootstrap {
|
|
Arc::new(TestChannel::new().with_name("gateway"))
|
|
} else {
|
|
Arc::new(TestChannel::new())
|
|
};
|
|
let handle = TestChannelHandle::new(Arc::clone(&test_channel));
|
|
let channel_manager = ChannelManager::new();
|
|
channel_manager.add(Box::new(handle)).await;
|
|
let channels = Arc::new(channel_manager);
|
|
|
|
// 7b. Register message tool so routines can send messages to channels.
|
|
deps.tools
|
|
.register_message_tools(Arc::clone(&channels), deps.extension_manager.clone())
|
|
.await;
|
|
|
|
// 8. Create Agent.
|
|
let routine_config = if enable_routines {
|
|
Some(ironclaw::config::RoutineConfig {
|
|
enabled: true,
|
|
cron_check_interval_secs: 60,
|
|
max_concurrent_routines: 3,
|
|
default_cooldown_secs: 300,
|
|
max_lightweight_tokens: 4096,
|
|
lightweight_tools_enabled: true,
|
|
lightweight_max_iterations: 3,
|
|
})
|
|
} else {
|
|
None
|
|
};
|
|
let agent = Agent::new(
|
|
components.config.agent.clone(),
|
|
deps,
|
|
channels,
|
|
None, // heartbeat_config
|
|
None, // hygiene_config
|
|
routine_config,
|
|
Some(Arc::clone(&components.context_manager)),
|
|
None, // session_manager
|
|
);
|
|
|
|
// Match main.rs: fill the scheduler slot once Agent::new has created it.
|
|
*scheduler_slot.write().await = Some(agent.scheduler());
|
|
|
|
// 9. Spawn agent in background task.
|
|
let agent_handle = tokio::spawn(async move {
|
|
if let Err(e) = agent.run().await {
|
|
eprintln!("[TestRig] Agent exited with error: {e}");
|
|
}
|
|
});
|
|
|
|
// 10. Wait for the agent to call channel.start() (up to 5 seconds).
|
|
if let Some(rx) = test_channel.take_ready_rx().await {
|
|
let _ = tokio::time::timeout(Duration::from_secs(5), rx).await;
|
|
}
|
|
|
|
TestRig {
|
|
channel: test_channel,
|
|
instrumented_llm: instrumented,
|
|
start_time: Instant::now(),
|
|
max_tool_iterations,
|
|
agent_handle: Some(agent_handle),
|
|
db: db_ref,
|
|
workspace: workspace_ref,
|
|
trace_llm: trace_llm_ref,
|
|
extension_manager: ext_mgr_ref,
|
|
_temp_dir: temp_dir,
|
|
}
|
|
}
|
|
}
|
|
|
|
impl Default for TestRigBuilder {
|
|
fn default() -> Self {
|
|
Self::new()
|
|
}
|
|
}
|
|
|
|
impl TestRig {
|
|
/// Get the database handle for direct queries.
|
|
#[cfg(feature = "libsql")]
|
|
pub fn database(&self) -> &Arc<dyn Database> {
|
|
&self.db
|
|
}
|
|
|
|
/// Get the workspace handle for direct memory operations.
|
|
#[cfg(feature = "libsql")]
|
|
pub fn workspace(&self) -> Option<&Arc<ironclaw::workspace::Workspace>> {
|
|
self.workspace.as_ref()
|
|
}
|
|
|
|
/// Get the underlying TraceLlm for inspecting captured requests.
|
|
#[cfg(feature = "libsql")]
|
|
pub fn trace_llm(&self) -> Option<&Arc<TraceLlm>> {
|
|
self.trace_llm.as_ref()
|
|
}
|
|
|
|
/// Check if any captured status events contain safety/injection warnings.
|
|
pub fn has_safety_warnings(&self) -> bool {
|
|
self.captured_status_events().iter().any(|s| {
|
|
matches!(s, StatusUpdate::Status(msg) if msg.contains("sanitiz") || msg.contains("inject") || msg.contains("warning"))
|
|
})
|
|
}
|
|
}
|
|
|
|
// ---------------------------------------------------------------------------
|
|
// Convenience: run a recorded trace fixture end-to-end
|
|
// ---------------------------------------------------------------------------
|
|
|
|
/// Load a recorded trace fixture, build a rig, run and verify expects, then shut down.
|
|
///
|
|
/// `filename` is relative to `tests/fixtures/llm_traces/recorded/`.
|
|
#[cfg(feature = "libsql")]
|
|
pub async fn run_recorded_trace(filename: &str) {
|
|
let path = format!(
|
|
"{}/tests/fixtures/llm_traces/recorded/{filename}",
|
|
env!("CARGO_MANIFEST_DIR")
|
|
);
|
|
let trace = LlmTrace::from_file(&path)
|
|
.unwrap_or_else(|e| panic!("failed to load trace {filename}: {e}"));
|
|
let rig = TestRigBuilder::new()
|
|
.with_trace(trace.clone())
|
|
.build()
|
|
.await;
|
|
rig.run_and_verify_trace(&trace, Duration::from_secs(30))
|
|
.await;
|
|
rig.shutdown();
|
|
}
|