Closes#459. Reported by @jasonftl with a precise smoking gun: incoming ChannelMessage has channel="discord" (TYPE label) and conversation_id=<numeric channel id>, but the reply code was using cm.channel as the destination — Discord saw /channels/discord/messages and 404'd silently, blackholing every reply.
The bug was two field-mappings in channel_agent.py:_process_message (the happy path + the exception path):
self._channel.send(
msg.channel, # WRONG — TYPE label
reply,
conversation_id=msg.conversation_id, # WRONG — channel id used as msg-ref-id
)
The existing DiscordChannel.send() contract — proved by the existing test_send_with_conversation_id test — is:
- first positional `channel` = native destination ID (Discord channel id)
- `conversation_id` kwarg = native message ID for reply threading
Fix: swap both fields to the correct ones from ChannelMessage:
self._channel.send(
msg.conversation_id, # Discord channel id
reply,
conversation_id=msg.message_id, # message id for threading
)
Plus a defensive guard in discord_channel.py: when channel is empty, refuse fast with a clear warning instead of POSTing to /channels//messages and silently 404'ing.
3 new tests, 38 affected pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* rlm: expose real tool calls inside the repl
* rlm: wrap long TypeError message in repl
* style(rlm): collapse over-wrapped TypeError to satisfy ruff format
The cherry-picked RLM tool-call work left a `raise TypeError(\n message\n)`
that `ruff format --check` rejects (the PR's own lint-fix commit broke
format). Collapse to `raise TypeError(message)`. No behavior change.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Eddie Richter <eddie.richter@amd.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The real `jarvis ask --agent opencode` path passes an InstrumentedEngine
(telemetry wrapper) whose underlying engine — and its `_host` — lives at
`_inner`. The base-URL derivation only checked the top object, so it returned
"", no provider was registered, and opencode 500'd on `openjarvis/<model>`.
Direct construction with a raw engine masked this; only the CLI path exposed
it.
- _derive_openai_base_url now unwraps up to 6 wrapper layers
(`_inner`/`_engine`/`_wrapped`) to find `_host`/`base_url`.
- run() resolves the provider/model spec up front and, when it genuinely
can't (no base URL + bare model name), returns a clear actionable error
instead of letting opencode 500.
Tests: wrapper-unwrap derivation + unresolvable-provider guard. 20 passed,
ruff clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Two hardening fixes for headless use, found while verifying real runs:
- Permissions: opencode's interactive default *asks* before some actions (and
`plan` asks before bash), which would block forever with no TTY. The agent
now writes an explicit permission policy: `build` allows edit+bash, `plan`
denies them (read-only), overridable via a `permission` kwarg. Verified: a
bash task completes without hanging and plan mode refuses to create files.
- Config no longer written into the user's workspace. We now write provider +
permission config to a private temp file referenced via `OPENCODE_CONFIG`
(confirmed honored by opencode), keeping the workspace clean while opencode
still operates there as cwd.
Tests updated to cover `_build_config` (provider presence, per-mode
permission, custom override, no-pollution). 18 passed, ruff clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
A real-model E2E (Ollama qwen3:8b) exposed what unit tests with synthetic
parts missed: `POST /session/{id}/message` returns only the final assistant
message (text/reasoning), while ToolParts live in intermediate assistant
messages. The parser was reading the wrong message, so tool_results was always
empty even when opencode actually edited files.
- run(): after the prompt POST, GET /session/{id}/message and collect parts
across the whole turn for tool extraction (content still comes from the
final message). Verified against a live opencode session.
- _extract_tool_results: success now keys on opencode's state.status ==
"completed" (states: completed | error | running | pending).
- Test now feeds the real full-turn message shape and asserts the write tool
is recovered.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds an `OpenCodeAgent` (registry key `opencode`) that delegates coding tasks
to opencode (https://opencode.ai, MIT) while keeping inference local-first:
OpenJarvis's engine backs opencode via an OpenAI-compatible provider.
How it works:
- Derives an OpenAI-compatible base URL from the engine (e.g. Ollama/vLLM at
`<host>/v1`) and writes an `opencode.json` registering it as an
`@ai-sdk/openai-compatible` provider (`openjarvis/<model>`).
- Spawns a headless `opencode serve` (loopback, random port), waits for
`/global/health`, then drives a session: `POST /session` →
`POST /session/{id}/message` with `model={providerID,modelID}` + agent
(`build`/`plan`) → parses message `parts` (text → content, tool → tool_results)
into an `AgentResult`. `close()` disposes the server.
- opencode is an external binary (not bundled); `run()` returns a clear,
actionable error when it's missing, mirroring ClaudeCodeAgent's degradation.
Verified end-to-end against the real opencode binary wired to a stub
OpenAI-compatible engine: opencode called the local endpoint and the agent
parsed the response (content/finish/model) correctly. Unit tests cover part
parsing, base-URL derivation, provider-config writing (incl. merge), binary
detection, graceful degradation, and run() parsing with a mocked client — 15
passed, ruff clean. Registered via the standard try/except import in
agents/__init__.py; documented in docs/user-guide/agents.md.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
SystemPromptBuilder (which loads the SOUL/MEMORY/USER persona files) was wired
only into the one-shot `jarvis ask` path, so persistent agents run through
AgentExecutor ignored persona entirely. The naive "pass prompt_builder" fix is
insufficient: `prompt_builder` was dropped at every __init__ hop
(ToolUsingAgent never accepted/forwarded it), and monitor_operative/operative
assemble their own system prompt and never consult `_prompt_builder` — so they
would silently ignore it even if it arrived.
Fix:
- `SystemPromptBuilder.persona_sections()` returns just the SOUL/MEMORY/USER
sections (no agent template), for agents that build their own prompt and want
to *append* persona rather than have it replace their instructions.
- `BaseAgent._apply_persona()` appends persona to a self-assembled prompt
(no-op without a builder or persona files).
- Thread `prompt_builder` through the __init__ chain: ToolUsingAgent now
accepts and forwards it to BaseAgent; monitor_operative and operative forward
it and call `_apply_persona()` on their assembled system prompt.
- AgentExecutor constructs a SystemPromptBuilder from config and passes it to
any agent whose __init__ accepts it (same gating as session_store /
memory_backend). Agents that override __init__ without forwarding (e.g.
orchestrator) opt out automatically and keep their own machinery.
Specialized prompts are preserved — persona is appended, not substituted. The
one-shot path is unchanged.
Verified: persona_sections() excludes the template but build() still includes
both; monitor_operative/operative receive the builder through the chain and
their assembled prompt includes the SOUL content. New tests in
tests/agents/test_persona_persistent.py (11 passed; ruff clean).
Closes#376
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Closes#164 — Qwen and other models with baked-in corporate identities
would claim to be cloud services when running locally. Adds a
configurable default_system_prompt to AgentConfig that is injected as a
fallback when no other system prompt is provided. The default tells the
model it is running locally through OpenJarvis. Users can override or
clear it via config.toml.
Tests were storing digests with local time but get_today() filters
by UTC date, causing failures when local date != UTC date.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- test_deep_research_prompt.py (8 tests): date injection, time, day of week,
dynamic generation, response types, tool descriptions, /no_think, Jarvis name
- test_slack_messaging.py (7 tests): connect with/without tokens, error state,
disconnect, handler registration, send without token
- test_connector_health.py (44 tests): all 11 connectors instantiate, have
required methods, report not-connected without creds, have metadata.
Plus KnowledgeStore data presence checks.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Resolve tool names from config["tools"] into actual tool instances
using ToolRegistry, inject runtime deps, and pass them to the agent
constructor instead of hardcoded tools=[].
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Merge main into fix/ssrf-check, keeping both the auto-recover
logic for error-state agents and the async streaming support
for the send_message endpoint.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds tests/agents/test_channel_agent_integration.py covering the full
stack from KnowledgeStore + IngestionPipeline through TwoStageRetriever,
KnowledgeSearchTool, and DeepResearchAgent into ChannelAgent/FakeChannel:
- test_quick_query_inline_response: asserts inline reply with meeting info
and no openjarvis:// escalation link
- test_deep_query_escalation_link: asserts openjarvis:// link is present
when engine issues a tool call and returns a long report
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds classify_query() heuristic (quick vs deep) and ChannelAgent that
bridges BaseChannel messages to any agent, delivering inline replies for
quick/short responses and preview+openjarvis:// escalation links for deep
or long responses. 18 tests cover classifier cases and agent behaviour
including non-blocking handler and error recovery.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Tests the full path from multi-source Document ingestion through
IngestionPipeline -> KnowledgeStore -> TwoStageRetriever ->
KnowledgeSearchTool -> DeepResearchAgent to a cited report, and
verifies cross-platform retrieval returns results from >= 2 sources.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Multi-hop research agent that uses native function calling (OpenAI
tool_calls format) to search personal data across sources via
KnowledgeSearchTool, cross-references results, and produces narrative
answers with inline source citations.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Add optional prompt_builder parameter to BaseAgent. When provided,
_build_messages() uses builder.build() output instead of raw system_prompt.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: add interactive agent confirmation mode and fix tool loading
- Add `interactive` and `confirm_callback` params to ToolUsingAgent and
NativeReActAgent so CLI sessions can prompt user before tool execution
- Fix tool resolution in `ask` and `chat` commands to fall back to
config.tools.enabled when no --tools flag is provided
- Register shell_exec tool in tools/__init__.py auto-discovery
- Add dspy and gepa as optional learning extras (learning-dspy, learning-gepa)
- Fix openjarvis-rust lock version (1.0.0 → 0.1.0)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(cli): support configured tool defaults and confirmations
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
