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9ddebbfca97877cbe386b4fa445b1b118d8f51c6
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4 Commits
Author SHA1 Message Date
Jon Saad-FalconandClaude Opus 4.6 9ec402ab4a Enrich agent tool awareness, normalize engine tool_calls, add telemetry and eval config 
- Add build_tool_descriptions() shared builder for enriched agent system
  prompts (NativeReAct, NativeOpenHands, RLM, Orchestrator structured mode)
- Normalize tool_calls to flat {id, name, arguments} across CloudEngine
  (OpenAI/Anthropic/Google), LiteLLM, and Ollama
- Add Anthropic tool_use extraction and input_schema conversion
- Add Google function_call extraction
- Make ReAct/OpenHands parsing case-insensitive
- Add telemetry efficiency, GPU monitor, and vLLM metrics modules
- Add TOML-based eval suite config system
- Update documentation and changelog

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-02-25 01:58:18 +00:00
Jon Saad-FalconandClaude Opus 4.6 68091dd90b Refactor agent hierarchy: extract BaseAgent/ToolUsingAgent helpers, add native ReAct/OpenHands 
- Pull shared boilerplate (event emission, message building, generation,
  think-tag stripping) into BaseAgent concrete helpers and ToolUsingAgent
  intermediate base class with tool-call loop
- Add NativeReActAgent and NativeOpenHandsAgent as clean implementations
  built on the new base classes
- Simplify SimpleAgent, OrchestratorAgent, ReActAgent, OpenHandsAgent,
  and RLMAgent to use inherited helpers instead of duplicated logic
- Remove CustomAgent (superseded by BaseAgent subclassing)
- Add backward-compat tests, base agent tests, native agent tests

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-02-24 03:59:24 +00:00
Jon Saad-FalconandClaude Opus 4.6 852259f18b Restructure codebase into 5-pillar architecture with MCP tool management, composition layer, and structured learning 
Phase 1: Move RoutingContext to core/types.py, add RouterPolicy and QueryAnalyzer ABCs to intelligence/_stubs.py
Phase 2: Move memory backends to tools/storage/, convert memory/ to backward-compat shims
Phase 3: Add MCPToolAdapter, storage MCP tools, upgrade MCP server to spec 2025-11-25
Phase 4: Add SystemBuilder + JarvisSystem composition layer (system.py)
Phase 5: Add InstrumentedEngine for opt-in telemetry, simplify all agents
Phase 6: Add LearningPolicy ABC taxonomy with SFTPolicy, AgentAdvisorPolicy, ICLUpdaterPolicy
Phase 7: Update config schema (ToolsConfig, MCPConfig, TracesConfig, per-pillar learning policies)

Also: update all docs, README (DSPy-inspired), CLAUDE.md, and add logo assets.
1391 tests pass, 32 skipped. Zero new lint errors. Full backward compatibility via shims.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-02-22 05:57:13 +00:00
Jon Saad-FalconandClaude Opus 4.6 990d7d8a79 Expand test suite to 1031 tests: new agents, tools, MCP layer, model catalog 
Add ReAct and OpenHands agents, WebSearch and CodeInterpreter tools,
full MCP protocol layer (server/client/transport), Gemini cloud engine
support, 12 new model specs (4 local MoE + 8 cloud), trace system,
and comprehensive test coverage across all dimensions (hardware, engine,
memory, agents, tools, MCP, integration).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-02-21 04:59:11 +00:00