Azure/azure-sdk-for-python azure-ai-agentserver-optimization_1.0.0b1

on GitHub

1.0.0b1 (2026-05-24)

Features Added

• Initial beta release.
• load_config(*, config_dir) — single-call config loader with 4-priority resolution and graceful fallback.
• load_skills_from_dir(path) — load skills from a directory on demand (not loaded inline by load_config).
• OptimizationConfig with instructions, model, temperature, skills, skills_dir, tool_definitions, source, and candidate_id.
• OptimizationConfig.apply_tool_descriptions(tools) — patch __doc__, .description, and input_model parameter descriptions on @tool-decorated functions from optimized tool definitions.
• OptimizationConfig.compose_instructions() — append skill catalog to instructions.
• CandidateConfig — typed representation of the resolver API payload.
• Skill — learned skill model (name, description, body).
• 4-priority resolution order:
  1. Inline JSON via OPTIMIZATION_CONFIG env var.
  2. Resolver API via OPTIMIZATION_CANDIDATE_ID + OPTIMIZATION_RESOLVE_ENDPOINT (endpoint is the full job-scoped URL).
  3. Local directory layout (OPTIMIZATION_LOCAL_DIR or config_dir param, defaults to .agent_configs/).
  4. No config found → returns None.
• Local directory layout: metadata.yaml + instructions.md + tools.json + skills/ per candidate, with baseline/ fallback.
• Tool definitions use the OpenAI function-calling list format exclusively.
• Skill loading from SKILL.md files with YAML frontmatter.
• Resolver API persists fetched configs and skill files to local directory for offline use.
• Path traversal (zip-slip) protection on skill file downloads from the API.