mirror of
https://github.com/open-jarvis/OpenJarvis.git
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Jon Saad-FalconandClaude Opus 4.6
8d538cd1b0
Major changes across parallel sessions: - Add orchestrator SFT & GRPO training subpackage (learning/orchestrator/) with episode types, multi-objective reward, prompt registry, policy model, RL environment, and registered learning policies - Add structured THOUGHT/TOOL/INPUT/FINAL_ANSWER mode to OrchestratorAgent - Add 15 channel backends (Discord, Slack, Telegram, Email, Webhook, IRC, Matrix, Teams, WhatsApp, Signal, Mattermost, BlueBubbles, Feishu, Google Chat, Webchat) with channel tools and config - Add LiteLLM engine backend for unified LLM provider access - Add RLM agent and REPL tool - Remove ToolLearningPolicy — learning taxonomy now only targets Intelligence (LM weights/routing) and Agents (logic/ICL/tool strategies) - Rename SFTPolicy to SFTRouterPolicy (backward-compat alias kept) - Remove OpenClaw agent infrastructure (openclaw*.py, openclaw_bridge.py) - Fix async streaming tests (asyncio.run vs deprecated get_event_loop) - Fix server channel route tests (pytest.importorskip for optional fastapi) - Track uv.lock for reproducibility - Update CLAUDE.md and docs to reflect all changes 1676 tests pass, 37 skipped. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
129 lines
4.1 KiB
Python
129 lines
4.1 KiB
Python
"""Tests for orchestrator RL environment."""
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from __future__ import annotations
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import pytest
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from openjarvis.core.types import ToolResult
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from openjarvis.learning.orchestrator.environment import (
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OrchestratorEnvironment,
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)
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from openjarvis.learning.orchestrator.types import OrchestratorAction
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from openjarvis.tools._stubs import BaseTool, ToolSpec
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# -- Mock tool ---------------------------------------------------------------
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class _MockCalculator(BaseTool):
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tool_id = "calculator"
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@property
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def spec(self) -> ToolSpec:
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return ToolSpec(
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name="calculator",
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description="mock calculator",
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parameters={
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"type": "object",
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"properties": {
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"expression": {
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"type": "string",
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"description": "math expression",
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},
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},
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},
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)
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def execute(self, **params) -> ToolResult:
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expr = params.get("expression", "")
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try:
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result = str(eval(expr)) # noqa: S307
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except Exception as e:
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return ToolResult(
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tool_name="calculator",
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content=f"Error: {e}",
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success=False,
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)
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return ToolResult(
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tool_name="calculator",
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content=result,
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success=True,
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)
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# -- Tests -------------------------------------------------------------------
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class TestOrchestratorEnvironment:
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def test_reset_creates_clean_state(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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state = env.reset("What is 2+2?")
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assert state.initial_prompt == "What is 2+2?"
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assert state.num_turns() == 0
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assert state.final_answer is None
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def test_step_executes_tool(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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state = env.reset("q")
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action = OrchestratorAction(
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thought="calc",
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tool_name="calculator",
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tool_input="2+2",
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)
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state, obs = env.step(state, action)
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assert state.num_turns() == 1
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assert obs.latency_seconds >= 0
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def test_is_done_on_final_answer(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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state = env.reset("q")
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action = OrchestratorAction(
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thought="done",
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tool_name="calculator",
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tool_input="2+2",
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is_final_answer=True,
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)
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state, obs = env.step(state, action)
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assert env.is_done(state) is True
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def test_is_done_on_max_turns(self):
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env = OrchestratorEnvironment(
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tools=[_MockCalculator()], max_turns=2
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)
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state = env.reset("q")
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for _ in range(2):
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action = OrchestratorAction(
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thought="go", tool_name="calculator", tool_input="1+1"
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)
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state, obs = env.step(state, action)
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assert env.is_done(state) is True
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def test_invalid_tool_raises(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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state = env.reset("q")
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action = OrchestratorAction(
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thought="t", tool_name="nonexistent", tool_input="x"
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)
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with pytest.raises(ValueError, match="not available"):
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env.step(state, action)
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def test_max_turns_exceeded_raises(self):
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env = OrchestratorEnvironment(
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tools=[_MockCalculator()], max_turns=1
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)
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state = env.reset("q")
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action = OrchestratorAction(
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thought="go", tool_name="calculator", tool_input="1+1"
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)
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state, _ = env.step(state, action)
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with pytest.raises(ValueError, match="exceeded"):
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env.step(state, action)
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def test_get_available_tools(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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assert env.get_available_tools() == ["calculator"]
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def test_not_done_initially(self):
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env = OrchestratorEnvironment(tools=[_MockCalculator()])
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state = env.reset("q")
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assert env.is_done(state) is False
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