hermes-agent/skills/mlops/training/hermes-atropos-environments/references/agentresult-fields.md
teknium1 6ab3ebf195 Add hermes-atropos-environments skill (bundled)
Add comprehensive skill for building, testing, and debugging Hermes Agent
RL environments for Atropos training. Includes:

- SKILL.md: Full guide covering HermesAgentBaseEnv interface, required
  methods, config class, CLI modes (serve/process/evaluate), reward
  function patterns, common pitfalls, and minimum implementation checklist
- New 'Inference Setup' section: instructs the agent to always ask the
  user for their inference provider (OpenRouter + model choice, self-hosted
  VLLM endpoint, or other OpenAI-compatible API) before running tests
- references/agentresult-fields.md: AgentResult dataclass field reference
- references/atropos-base-env.md: Atropos BaseEnv API reference
- references/usage-patterns.md: Step-by-step patterns for process,
  evaluate, serve, and smoke test modes

Will be auto-synced to ~/.hermes/skills/ via skills_sync.
2026-03-09 23:04:17 -07:00

2 KiB

AgentResult Fields Reference

AgentResult is defined in environments/agent_loop.py as a dataclass.

Fields

Field Type Description
messages List[Dict[str, Any]] Full conversation history in OpenAI message format
managed_state Optional[Dict] ManagedServer.get_state() if Phase 2, else None
turns_used int Number of LLM calls made during the loop
finished_naturally bool True if model stopped calling tools on its own
reasoning_per_turn List[Optional[str]] Extracted reasoning content per turn
tool_errors List[ToolError] Tool errors encountered during the loop

ToolError Fields

Field Type Description
turn int Which turn the error occurred
tool_name str Name of the tool that failed
arguments str Arguments passed to the tool
error str Error message
tool_result str The result returned to the model

Extracting Data from Messages

Messages follow OpenAI format. Common patterns:

# Get final assistant response
for msg in reversed(result.messages):
    if msg.get("role") == "assistant" and msg.get("content"):
        final_response = msg["content"]
        break

# Get all tool names used
tools = []
for msg in result.messages:
    if msg.get("role") == "assistant" and msg.get("tool_calls"):
        for tc in msg["tool_calls"]:
            fn = tc.get("function", {}) if isinstance(tc, dict) else {}
            tools.append(fn.get("name", ""))

# Get tool results
for msg in result.messages:
    if msg.get("role") == "tool":
        tool_output = msg.get("content", "")
        call_id = msg.get("tool_call_id", "")

Fields that DO NOT EXIST

These are common mistakes — AgentResult does NOT have:

  • final_response — extract from messages
  • tool_calls — extract from messages
  • tools_used — extract from messages
  • output — extract from messages
  • response — extract from messages