hermes / tools /clarify_tool.py
lenson78's picture
initial upload: v2026.3.23 with HF Spaces deployment
9aa5185 verified
#!/usr/bin/env python3
"""
Clarify Tool Module - Interactive Clarifying Questions
Allows the agent to present structured multiple-choice questions or open-ended
prompts to the user. In CLI mode, choices are navigable with arrow keys. On
messaging platforms, choices are rendered as a numbered list.
The actual user-interaction logic lives in the platform layer (cli.py for CLI,
gateway/run.py for messaging). This module defines the schema, validation, and
a thin dispatcher that delegates to a platform-provided callback.
"""
import json
from typing import Dict, Any, List, Optional, Callable
# Maximum number of predefined choices the agent can offer.
# A 5th "Other (type your answer)" option is always appended by the UI.
MAX_CHOICES = 4
def clarify_tool(
question: str,
choices: Optional[List[str]] = None,
callback: Optional[Callable] = None,
) -> str:
"""
Ask the user a question, optionally with multiple-choice options.
Args:
question: The question text to present.
choices: Up to 4 predefined answer choices. When omitted the
question is purely open-ended.
callback: Platform-provided function that handles the actual UI
interaction. Signature: callback(question, choices) -> str.
Injected by the agent runner (cli.py / gateway).
Returns:
JSON string with the user's response.
"""
if not question or not question.strip():
return json.dumps({"error": "Question text is required."}, ensure_ascii=False)
question = question.strip()
# Validate and trim choices
if choices is not None:
if not isinstance(choices, list):
return json.dumps({"error": "choices must be a list of strings."}, ensure_ascii=False)
choices = [str(c).strip() for c in choices if str(c).strip()]
if len(choices) > MAX_CHOICES:
choices = choices[:MAX_CHOICES]
if not choices:
choices = None # empty list → open-ended
if callback is None:
return json.dumps(
{"error": "Clarify tool is not available in this execution context."},
ensure_ascii=False,
)
try:
user_response = callback(question, choices)
except Exception as exc:
return json.dumps(
{"error": f"Failed to get user input: {exc}"},
ensure_ascii=False,
)
return json.dumps({
"question": question,
"choices_offered": choices,
"user_response": str(user_response).strip(),
}, ensure_ascii=False)
def check_clarify_requirements() -> bool:
"""Clarify tool has no external requirements -- always available."""
return True
# =============================================================================
# OpenAI Function-Calling Schema
# =============================================================================
CLARIFY_SCHEMA = {
"name": "clarify",
"description": (
"Ask the user a question when you need clarification, feedback, or a "
"decision before proceeding. Supports two modes:\n\n"
"1. **Multiple choice** — provide up to 4 choices. The user picks one "
"or types their own answer via a 5th 'Other' option.\n"
"2. **Open-ended** — omit choices entirely. The user types a free-form "
"response.\n\n"
"Use this tool when:\n"
"- The task is ambiguous and you need the user to choose an approach\n"
"- You want post-task feedback ('How did that work out?')\n"
"- You want to offer to save a skill or update memory\n"
"- A decision has meaningful trade-offs the user should weigh in on\n\n"
"Do NOT use this tool for simple yes/no confirmation of dangerous "
"commands (the terminal tool handles that). Prefer making a reasonable "
"default choice yourself when the decision is low-stakes."
),
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to present to the user.",
},
"choices": {
"type": "array",
"items": {"type": "string"},
"maxItems": MAX_CHOICES,
"description": (
"Up to 4 answer choices. Omit this parameter entirely to "
"ask an open-ended question. When provided, the UI "
"automatically appends an 'Other (type your answer)' option."
),
},
},
"required": ["question"],
},
}
# --- Registry ---
from tools.registry import registry
registry.register(
name="clarify",
toolset="clarify",
schema=CLARIFY_SCHEMA,
handler=lambda args, **kw: clarify_tool(
question=args.get("question", ""),
choices=args.get("choices"),
callback=kw.get("callback")),
check_fn=check_clarify_requirements,
emoji="❓",
)