wehub-resource-sync
74 lines
2.9 KiB
Python
74 lines
2.9 KiB
Python
from __future__ import annotations
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from typing import Any
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from livekit.agents import llm
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from livekit.agents.llm.utils import function_arguments_to_pydantic_model
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def parse_tools(tools: list[llm.FunctionTool | llm.RawFunctionTool]) -> list[dict[str, Any]]:
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"""Prepare tools for sending to Ultravox. https://docs.ultravox.ai/essentials/tools#creating-your-first-custom-tool"""
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results: list[dict[str, Any]] = []
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for tool in tools:
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if isinstance(tool, llm.RawFunctionTool):
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raw_fnc_info = tool.info
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name = raw_fnc_info.name
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description = raw_fnc_info.raw_schema.get("description", None)
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parameters = raw_fnc_info.raw_schema.get("parameters", {})
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elif isinstance(tool, llm.FunctionTool):
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fnc_info = tool.info
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model = function_arguments_to_pydantic_model(tool)
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name = fnc_info.name
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description = fnc_info.description
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parameters = model.model_json_schema()
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def _extract_type(prop: dict[str, Any]) -> str:
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"""Best-effort guess of a parameter's primitive type."""
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if "type" in prop:
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assert isinstance(prop["type"], str)
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return prop["type"]
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if "enum" in prop:
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return "string"
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if "items" in prop:
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return "array"
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for key in ("anyOf", "oneOf"):
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if key in prop:
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for variant in prop[key]:
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if isinstance(variant, dict) and "type" in variant:
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assert isinstance(variant["type"], str)
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return variant["type"]
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# Fallback to string
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return "string"
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results.append(
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{
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"temporaryTool": {
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"modelToolName": name,
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"description": description,
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"dynamicParameters": [
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{
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"name": pn,
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"location": "PARAMETER_LOCATION_BODY",
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"schema": (
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p
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if "type" in p
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else { # fallback minimal schema for enum/anyOf etc.
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"type": _extract_type(p),
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**(
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{"description": p.get("description")}
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if p.get("description")
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else {}
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),
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}
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),
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"required": pn in parameters.get("required", []),
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}
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for pn, p in parameters["properties"].items()
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],
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"client": {},
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}
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}
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)
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return results
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