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adk-python/contributing/samples/litellm_inline_tool_call/agent.py
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George Weale 2367901ec5 chore: Upgrade to headers to 2026
Co-authored-by: George Weale <gweale@google.com>
PiperOrigin-RevId: 858763407
2026-01-20 14:50:09 -08:00

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5.0 KiB
Python

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations
import datetime
import json
import re
from typing import Any
from zoneinfo import ZoneInfo
from zoneinfo import ZoneInfoNotFoundError
from google.adk.agents.llm_agent import Agent
from google.adk.models.lite_llm import LiteLlm
from google.adk.models.lite_llm import LiteLLMClient
class InlineJsonToolClient(LiteLLMClient):
"""LiteLLM client that emits inline JSON tool calls for testing."""
async def acompletion(self, model, messages, tools, **kwargs):
del tools, kwargs # Only needed for API parity.
tool_message = _find_last_role(messages, role="tool")
if tool_message:
tool_summary = _coerce_to_text(tool_message.get("content"))
return {
"id": "mock-inline-tool-final-response",
"model": model,
"choices": [{
"message": {
"role": "assistant",
"content": (
f"The instrumentation tool responded with: {tool_summary}"
),
},
"finish_reason": "stop",
}],
"usage": {
"prompt_tokens": 60,
"completion_tokens": 12,
"total_tokens": 72,
},
}
timezone = _extract_timezone(messages) or "Asia/Taipei"
inline_call = json.dumps(
{
"name": "get_current_time",
"arguments": {"timezone_str": timezone},
},
separators=(",", ":"),
)
return {
"id": "mock-inline-tool-call",
"model": model,
"choices": [{
"message": {
"role": "assistant",
"content": (
f"{inline_call}\nLet me double-check the clock for you."
),
},
"finish_reason": "tool_calls",
}],
"usage": {
"prompt_tokens": 45,
"completion_tokens": 15,
"total_tokens": 60,
},
}
def _find_last_role(
messages: list[dict[str, Any]], role: str
) -> dict[str, Any]:
"""Returns the last message with the given role."""
for message in reversed(messages):
if message.get("role") == role:
return message
return {}
def _coerce_to_text(content: Any) -> str:
"""Best-effort conversion from OpenAI message content to text."""
if isinstance(content, str):
return content
if isinstance(content, dict):
return _coerce_to_text(content.get("text"))
if isinstance(content, list):
texts = []
for part in content:
if isinstance(part, dict):
texts.append(part.get("text") or "")
elif isinstance(part, str):
texts.append(part)
return " ".join(text for text in texts if text)
return ""
_TIMEZONE_PATTERN = re.compile(r"([A-Za-z]+/[A-Za-z_]+)")
def _extract_timezone(messages: list[dict[str, Any]]) -> str | None:
"""Extracts an IANA timezone string from the last user message."""
user_message = _find_last_role(messages, role="user")
text = _coerce_to_text(user_message.get("content"))
if not text:
return None
match = _TIMEZONE_PATTERN.search(text)
if match:
return match.group(1)
lowered = text.lower()
if "taipei" in lowered:
return "Asia/Taipei"
if "new york" in lowered:
return "America/New_York"
if "london" in lowered:
return "Europe/London"
if "tokyo" in lowered:
return "Asia/Tokyo"
return None
def get_current_time(timezone_str: str) -> dict[str, str]:
"""Returns mock current time for the provided timezone."""
try:
tz = ZoneInfo(timezone_str)
except ZoneInfoNotFoundError as exc:
return {
"status": "error",
"report": f"Unable to parse timezone '{timezone_str}': {exc}",
}
now = datetime.datetime.now(tz)
return {
"status": "success",
"report": (
f"The current time in {timezone_str} is"
f" {now.strftime('%Y-%m-%d %H:%M:%S %Z')}."
),
}
_mock_model = LiteLlm(
model="mock/inline-json-tool-calls",
llm_client=InlineJsonToolClient(),
)
root_agent = Agent(
name="litellm_inline_tool_tester",
model=_mock_model,
description=(
"Demonstrates LiteLLM inline JSON tool-call parsing without an external"
" VLLM deployment."
),
instruction=(
"You are a deterministic clock assistant. Always call the"
" get_current_time tool before answering user questions. After the tool"
" responds, summarize what it returned."
),
tools=[get_current_time],
)