Hello! How to use adk web with non google api model? (Deepinfra or local) #1719

Blynskyniki · 2025-06-27T17:48:50Z

Blynskyniki
Jun 27, 2025

omanandswami2005 · 2025-06-28T16:40:34Z

omanandswami2005
Jun 28, 2025

description ? or any code snippet ? (you can use LiteLLM library available in ADK)

1 reply

Blynskyniki Jul 1, 2025
Author

`import os
from datetime import date, datetime, timedelta

from dotenv import load_dotenv
from google.adk.agents import LlmAgent
from google.adk.models.lite_llm import LiteLlm
from google.adk.tools import ToolContext, FunctionTool
load_dotenv()

model1 = LiteLlm(
model="deepinfra/meta-llama/Llama-4-Scout-17B-16E-Instruct",
api_base="https://api.deepinfra.com/v1/openai",
extra_headers={"Authorization": f"Bearer {os.getenv('DEEPINFRA_API_KEY')}"},
)
model = LiteLlm(
model="deepinfra/Qwen/Qwen3-32B",
api_base="https://api.deepinfra.com/v1/openai",
extra_headers={"Authorization": f"Bearer {os.getenv('DEEPINFRA_API_KEY')}"},
)

def edit_duration(
code: str, new_duration: int, tool_context: ToolContext = None
) -> dict:
"""
Обновляет длительность задачи с заданным кодом.

Args:
    code (str): Уникальный код задачи, которую нужно обновить.
    new_duration (int): Новое значение длительности (в днях).
    tool_context (ToolContext): Контекст выполнения с доступом к state.


Returns:
    dict: Словарь с ключами 'status' и 'report' или 'error_message'.

Example:
     >>> edit_duration(code="1", new_duration=7)
    {'status': 'success', 'report': 'Длительность задачи 1 обновлена на 7 дней.'}
"""

print(f"[TOOL CALL] edit_duration called: code={code}, new_duration={new_duration}")
schedule = tool_context.state.get("project_schedule", [])
tool_context.actions.transfer_to_agent = "CoordinatorAgent"
for task in schedule:
    if task["code"] == code:
        task["duration_days"] = new_duration
        try:
            start_date = datetime.strptime(task["start_date"], "%Y-%m-%d")
            new_end_date = start_date + timedelta(days=new_duration)
            task["end_date"] = new_end_date.strftime("%Y-%m-%d")
        except Exception as e:
            return {
                "status": "error",
                "error_message": f"Ошибка при пересчёте даты: {e}",
            }
        tool_context.state["project_schedule"] = schedule
        return {
            "status": "success",
            "report": f" Длительность задачи {code} обновлена на {new_duration} дней.",
        }
return {"status": "error", "error_message": f" Задача с кодом {code} не найдена."}

def get_all(tool_context: ToolContext) -> dict:
"""
Возвращает текущий граф задач, сохранённый в state.
Args:
tool_context (ToolContext): Контекст выполнения с доступом к state.

Returns:
    dict: Словарь с ключами 'status' и 'report' или 'error_message'.

Example:
    >>> get_all(tool_context)
    {'status': 'success', 'report': '[{...}, {...}]'}
"""
schedule = tool_context.state.get("project_schedule", [])
if schedule:
    return {
        "status": "success",
        "report": f"{schedule}",
    }
return {"status": "error", "error_message": f" Задачи не найдены."}

duration_editor_agent = LlmAgent(
name="DurationEditorAgent",
model=model,
output_key="duration_editor_agent_result",
description="Изменяет длительность задачи",
instruction="""
Ты изменяешь длительность задачи. Когда пользователь просит увеличить или уменьшить длительность задачи,
вызови инструмент edit_duration(code, new_duration).
code : str
new_duration:int
Ты можешь получить полный список задач для понимая о чем речь, вызови инструмент get_all()

Всегда уточняй код задачи и число дней, если они указаны неявно (например, "на неделю" = 7, к 3 добавить 1 день =4).
""",
tools=[FunctionTool(func=get_all), FunctionTool(func=edit_duration)],
)
date_today = date.today()

--- Родительский агент ---

coordinator_agent = LlmAgent(
name="CoordinatorAgent",
model=model1,
description="Координирует агентов, анализирует запросы и вызывает нужных агентов",
global_instruction=(
f"""
You are Coordinator in Multi Agent System.
Todays date: {date_today}
Если пользователь задал вопрос, или попросил действие- подбери агента. После выполнения всех действий проинформируй пользователя
"""
),
sub_agents=[duration_editor_agent],
output_key="finish",
)
--> adk web --> input any symbols and enter -> {"error": "Missing key inputs argument! To use the Google AI API, provide (api_key) arguments. To use the Google Cloud API, provide (vertexai, project&location`) arguments."}

NewGenesis04 · 2025-06-28T23:07:26Z

NewGenesis04
Jun 28, 2025

description ? or any code snippet ? (you can use LiteLLM library available in ADK)

I tried and I got an error after the first output when I used tools. This is my code:

from google.adk.agents import LlmAgent, Agent
from google.genai import types
import os
from google.adk.models.lite_llm import LiteLlm
from pathlib import Path
import praw
from dotenv import load_dotenv
load_dotenv(dotenv_path=Path('.') / '.env')
from .prompts import SYSTEM_INSTRUCTION
api_key = os.getenv("OPENROUTER_API_KEY")

def get_reddit_ai_news(subreddit: str, limit: int = 5) -> dict[str, list[str]]:
"""
Fetches top post titles from a specified subreddit using the Reddit API.

Args:
    subreddit: The name of the subreddit to fetch news from (e.g., 'AINewsAndTrends').
    limit: The maximum number of top posts to fetch.

Returns:
    A dictionary with the subreddit name as key and a list of
    post titles as value. Returns an error message if credentials are
    missing, the subreddit is invalid, or an API error occurs.
"""

print(f"--- Tool called: Fetching from r/{subreddit} via Reddit API ---")
client_id = os.getenv("REDDIT_CLIENT_ID")
client_secret = os.getenv("REDDIT_CLIENT_SECRET")
user_agent = os.getenv("REDDIT_USER_AGENT")

if not all([client_id, client_secret, user_agent]):
    print("--- Tool error: Reddit API credentials missing in .env file. ---")
    return {subreddit: ["Error: Reddit API credentials not configured."]}

try:
    reddit = praw.Reddit(
        client_id=client_id,
        client_secret=client_secret,
        user_agent=user_agent
    )
    # Check if the subreddit exists
    reddit.subreddits.search_by_name(subreddit, exact=True)
    sub = reddit.subreddit(subreddit)
    top_posts = list(sub.hot(limit=limit)) # Fetch hot posts
    titles = [post.title for post in top_posts]
    if not titles:
         return {subreddit: [f"No recent hot posts found in r/{subreddit}."]}
    
    return {subreddit: titles}

except praw.exceptions.PRAWException as e:
    print(f"--- Tool error: {e} ---")
    return {subreddit: [f"Error fetching from r/{subreddit}: {str(e)}"]}

except Exception as e:
    print(f"--- Tool error: {e} ---")
    return {subreddit: [f"An unexpected error occurred: {str(e)}"]}

model = LiteLlm(
model="openrouter/mistralai/mistral-7b-instruct:free",
api_key=api_key
)

root_agent = LlmAgent(
name="reddit_news_agent",
description="Agent to help users find news articles on Reddit.",
model=model,
instruction=SYSTEM_INSTRUCTION,
tools=[get_reddit_ai_news],
output_key="summary"
)

1 reply

Blynskyniki Jul 1, 2025
Author

location) arguments.
Traceback (most recent call last):
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/cli/fast_api.py", line 809, in event_generator
async for event in runner.run_async(
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/runners.py", line 203, in run_async
async for event in invocation_context.agent.run_async(invocation_context):
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/agents/base_agent.py", line 147, in run_async
async for event in self._run_async_impl(ctx):
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/agents/llm_agent.py", line 275, in _run_async_impl
async for event in self._llm_flow.run_async(ctx):
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/flows/llm_flows/base_llm_flow.py", line 282, in run_async
async for event in self._run_one_step_async(invocation_context):
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/flows/llm_flows/base_llm_flow.py", line 314, in _run_one_step_async
async for llm_response in self._call_llm_async(
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/flows/llm_flows/base_llm_flow.py", line 539, in _call_llm_async
async for llm_response in llm.generate_content_async(
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/models/google_llm.py", line 88, in generate_content_async
self._preprocess_request(llm_request)
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/models/google_llm.py", line 267, in _preprocess_request
if self._api_backend == GoogleLLMVariant.GEMINI_API:
^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/functools.py", line 993, in get
val = self.func(instance)
^^^^^^^^^^^^^^^^^^^
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/models/google_llm.py", line 193, in _api_backend
if self.api_client.vertexai
^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/functools.py", line 993, in get
val = self.func(instance)
^^^^^^^^^^^^^^^^^^^
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/adk/models/google_llm.py", line 185, in api_client
return Client(
^^^^^^^
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/genai/client.py", line 219, in init
self._api_client = self._get_api_client(
^^^^^^^^^^^^^^^^^^^^^
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/genai/client.py", line 265, in _get_api_client
return BaseApiClient(
^^^^^^^^^^^^^^
File "/Users/niki/PycharmProjects/KSG/.venv/lib/python3.12/site-packages/google/genai/_api_client.py", line 531, in init
raise ValueError(
ValueError: Missing key inputs argument! To use the Google AI API, provide (api_key) arguments. To use the Google Cloud API, provide (vertexai, project & location) arguments.
`

omanandswami2005 · 2025-06-29T00:20:18Z

omanandswami2005
Jun 29, 2025

What was ur error? It's Working for me
Try pasting this code in same file in local installation of adk

0 replies

boyangsvl · 2025-06-30T17:25:54Z

boyangsvl
Jun 30, 2025
Maintainer

Thanks for the discussions. I will move this to the discussions section since it doesn't seems to be an issue of ADK iteself.

0 replies

Blynskyniki · 2025-06-30T17:31:05Z

Blynskyniki
Jun 30, 2025
Author

I'll try to send an example tomorrow

1 reply

Blynskyniki Jul 1, 2025
Author

`import os
from datetime import date, datetime, timedelta

from dotenv import load_dotenv
from google.adk.agents import LlmAgent
from google.adk.models.lite_llm import LiteLlm
from google.adk.tools import ToolContext, FunctionTool

load_dotenv()

model1 = LiteLlm(
model="deepinfra/meta-llama/Llama-4-Scout-17B-16E-Instruct",
api_base="https://api.deepinfra.com/v1/openai",
extra_headers={"Authorization": f"Bearer {os.getenv('DEEPINFRA_API_KEY')}"},
)
model = LiteLlm(
model="deepinfra/Qwen/Qwen3-32B",
api_base="https://api.deepinfra.com/v1/openai",
extra_headers={"Authorization": f"Bearer {os.getenv('DEEPINFRA_API_KEY')}"},
)

def edit_duration(
code: str, new_duration: int, tool_context: ToolContext = None
) -> dict:
"""
Обновляет длительность задачи с заданным кодом.

Args:
    code (str): Уникальный код задачи, которую нужно обновить.
    new_duration (int): Новое значение длительности (в днях).
    tool_context (ToolContext): Контекст выполнения с доступом к state.


Returns:
    dict: Словарь с ключами 'status' и 'report' или 'error_message'.

Example:
     >>> edit_duration(code="1", new_duration=7)
    {'status': 'success', 'report': ' Длительность задачи 1 обновлена на 7 дней.'}
"""

print(f"[TOOL CALL] edit_duration called: code={code}, new_duration={new_duration}")
schedule = tool_context.state.get("project_schedule", [])
tool_context.actions.transfer_to_agent = "CoordinatorAgent"
for task in schedule:
    if task["code"] == code:
        task["duration_days"] = new_duration
        try:
            start_date = datetime.strptime(task["start_date"], "%Y-%m-%d")
            new_end_date = start_date + timedelta(days=new_duration)
            task["end_date"] = new_end_date.strftime("%Y-%m-%d")
        except Exception as e:
            return {
                "status": "error",
                "error_message": f"Ошибка при пересчёте даты: {e}",
            }
        tool_context.state["project_schedule"] = schedule
        return {
            "status": "success",
            "report": f" Длительность задачи {code} обновлена на {new_duration} дней.",
        }
return {"status": "error", "error_message": f" Задача с кодом {code} не найдена."}

def get_all(tool_context: ToolContext) -> dict:
"""
Возвращает текущий граф задач, сохранённый в state.

Args:
    tool_context (ToolContext): Контекст выполнения с доступом к state.

Returns:
    dict: Словарь с ключами 'status' и 'report' или 'error_message'.

Example:
    >>> get_all(tool_context)
    {'status': 'success', 'report': '[{...}, {...}]'}
"""
schedule = tool_context.state.get("project_schedule", [])
if schedule:
    return {
        "status": "success",
        "report": f"{schedule}",
    }
return {"status": "error", "error_message": f" Задачи не найдены."}

duration_editor_agent = LlmAgent(
name="DurationEditorAgent",
model=model,
output_key="duration_editor_agent_result",
description="Изменяет длительность задачи",
instruction="""
Ты изменяешь длительность задачи. Когда пользователь просит увеличить или уменьшить длительность задачи,
вызови инструмент edit_duration(code, new_duration).
code : str
new_duration:int
Ты можешь получить полный список задач для понимая о чем речь, вызови инструмент get_all()

Всегда уточняй код задачи и число дней, если они указаны неявно (например, "на неделю" = 7, к 3 добавить 1 день =4).
""",
tools=[FunctionTool(func=get_all), FunctionTool(func=edit_duration)],
)
date_today = date.today()

coordinator_agent = LlmAgent(
name="CoordinatorAgent",
model=model1,
description="Координирует агентов, анализирует запросы и вызывает нужных агентов",
global_instruction=(
f"""
You are Coordinator in Multi Agent System.
Todays date: {date_today}
Если пользователь задал вопрос, или попросил действие- подбери агента. После выполнения всех действий проинформируй пользователя
"""
),
sub_agents=[duration_editor_agent],
output_key="finish",
)`

{"error": "Missing key inputs argument! To use the Google AI API, provide (api_key) arguments. To use the Google Cloud API, provide (vertexai, project&location) arguments."}

Hello! How to use adk web with non google api model? (Deepinfra or local) #1719

Uh oh!

Blynskyniki Jun 27, 2025

Replies: 5 comments · 3 replies

Uh oh!

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omanandswami2005 Jun 28, 2025

Uh oh!

Uh oh!

Blynskyniki Jul 1, 2025 Author

--- Родительский агент ---

Uh oh!

NewGenesis04 Jun 28, 2025

Uh oh!

Blynskyniki Jul 1, 2025 Author

Uh oh!

Uh oh!

omanandswami2005 Jun 29, 2025

Uh oh!

boyangsvl Jun 30, 2025 Maintainer

Uh oh!

Blynskyniki Jun 30, 2025 Author

Uh oh!

Uh oh!

Blynskyniki Jul 1, 2025 Author

Blynskyniki
Jun 27, 2025

Replies: 5 comments 3 replies

omanandswami2005
Jun 28, 2025

Blynskyniki Jul 1, 2025
Author

NewGenesis04
Jun 28, 2025

Blynskyniki Jul 1, 2025
Author

omanandswami2005
Jun 29, 2025

boyangsvl
Jun 30, 2025
Maintainer

Blynskyniki
Jun 30, 2025
Author

Blynskyniki Jul 1, 2025
Author