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https://github.com/BerriAI/litellm.git
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* fix(core_helpers.py): return None, instead of raising kwargs is None error Closes https://github.com/BerriAI/litellm/issues/6500 * docs(cost_tracking.md): cleanup doc * fix(vertex_and_google_ai_studio.py): handle function call with no params passed in Closes https://github.com/BerriAI/litellm/issues/6495 * test(test_router_timeout.py): add test for router timeout + retry logic * test: update test to use module level values * (fix) Prometheus - Log Postgres DB latency, status on prometheus (#6484) * fix logging DB fails on prometheus * unit testing log to otel wrapper * unit testing for service logger + prometheus * use LATENCY buckets for service logging * fix service logging * docs clarify vertex vs gemini * (router_strategy/) ensure all async functions use async cache methods (#6489) * fix router strat * use async set / get cache in router_strategy * add coverage for router strategy * fix imports * fix batch_get_cache * use async methods for least busy * fix least busy use async methods * fix test_dual_cache_increment * test async_get_available_deployment when routing_strategy="least-busy" * (fix) proxy - fix when `STORE_MODEL_IN_DB` should be set (#6492) * set store_model_in_db at the top * correctly use store_model_in_db global * (fix) `PrometheusServicesLogger` `_get_metric` should return metric in Registry (#6486) * fix logging DB fails on prometheus * unit testing log to otel wrapper * unit testing for service logger + prometheus * use LATENCY buckets for service logging * fix service logging * fix _get_metric in prom services logger * add clear doc string * unit testing for prom service logger * bump: version 1.51.0 → 1.51.1 * Add `azure/gpt-4o-mini-2024-07-18` to model_prices_and_context_window.json (#6477) * Update utils.py (#6468) Fixed missing keys * (perf) Litellm redis router fix - ~100ms improvement (#6483) * docs(exception_mapping.md): add missing exception types Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183 * fix(main.py): register custom model pricing with specific key Ensure custom model pricing is registered to the specific model+provider key combination * test: make testing more robust for custom pricing * fix(redis_cache.py): instrument otel logging for sync redis calls ensures complete coverage for all redis cache calls * refactor: pass parent_otel_span for redis caching calls in router allows for more observability into what calls are causing latency issues * test: update tests with new params * refactor: ensure e2e otel tracing for router * refactor(router.py): add more otel tracing acrosss router catch all latency issues for router requests * fix: fix linting error * fix(router.py): fix linting error * fix: fix test * test: fix tests * fix(dual_cache.py): pass ttl to redis cache * fix: fix param * perf(cooldown_cache.py): improve cooldown cache, to store cache results in memory for 5s, prevents redis call from being made on each request reduces 100ms latency per call with caching enabled on router * fix: fix test * fix(cooldown_cache.py): handle if a result is None * fix(cooldown_cache.py): add debug statements * refactor(dual_cache.py): move to using an in-memory check for batch get cache, to prevent redis from being hit for every call * fix(cooldown_cache.py): fix linting erropr * refactor(prometheus.py): move to using standard logging payload for reading the remaining request / tokens Ensures prometheus token tracking works for anthropic as well * fix: fix linting error * fix(redis_cache.py): make sure ttl is always int (handle float values) Fixes issue where redis_client.ex was not working correctly due to float ttl * fix: fix linting error * test: update test * fix: fix linting error --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Xingyao Wang <xingyao@all-hands.dev> Co-authored-by: vibhanshu-ob <115142120+vibhanshu-ob@users.noreply.github.com>
180 lines
4.9 KiB
Python
180 lines
4.9 KiB
Python
import json
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import os
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import sys
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import io
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from unittest.mock import AsyncMock, MagicMock, patch
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import pytest
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import litellm
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from litellm import get_optional_params
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def test_completion_pydantic_obj_2():
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from pydantic import BaseModel
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from litellm.llms.custom_httpx.http_handler import HTTPHandler
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litellm.set_verbose = True
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class CalendarEvent(BaseModel):
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name: str
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date: str
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participants: list[str]
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class EventsList(BaseModel):
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events: list[CalendarEvent]
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messages = [
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{"role": "user", "content": "List important events from the 20th century."}
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]
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expected_request_body = {
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"contents": [
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{
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"role": "user",
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"parts": [{"text": "List important events from the 20th century."}],
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}
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],
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"generationConfig": {
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"response_mime_type": "application/json",
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"response_schema": {
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"properties": {
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"events": {
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"items": {
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"properties": {
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"name": {"type": "string"},
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"date": {"type": "string"},
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"participants": {
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"items": {"type": "string"},
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"type": "array",
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},
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},
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"required": [
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"name",
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"date",
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"participants",
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],
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"type": "object",
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},
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"type": "array",
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}
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},
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"required": [
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"events",
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],
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"type": "object",
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},
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},
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}
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client = HTTPHandler()
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with patch.object(client, "post", new=MagicMock()) as mock_post:
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mock_post.return_value = expected_request_body
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try:
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litellm.completion(
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model="gemini/gemini-1.5-pro",
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messages=messages,
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response_format=EventsList,
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client=client,
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)
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except Exception as e:
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print(e)
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mock_post.assert_called_once()
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print(mock_post.call_args.kwargs)
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assert mock_post.call_args.kwargs["json"] == expected_request_body
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def test_build_vertex_schema():
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from litellm.llms.vertex_ai_and_google_ai_studio.common_utils import (
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_build_vertex_schema,
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)
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import json
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schema = {
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"type": "object",
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"properties": {
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"recipes": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {"recipe_name": {"type": "string"}},
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"required": ["recipe_name"],
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},
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}
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},
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"required": ["recipes"],
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}
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new_schema = _build_vertex_schema(schema)
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print(f"new_schema: {new_schema}")
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assert new_schema["type"] == schema["type"]
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assert new_schema["properties"] == schema["properties"]
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assert "required" in new_schema and new_schema["required"] == schema["required"]
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@pytest.mark.parametrize(
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"tools, key",
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[
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([{"googleSearchRetrieval": {}}], "googleSearchRetrieval"),
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([{"code_execution": {}}], "code_execution"),
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],
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)
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def test_vertex_tool_params(tools, key):
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optional_params = get_optional_params(
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model="gemini-1.5-pro",
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custom_llm_provider="vertex_ai",
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tools=tools,
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)
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print(optional_params)
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assert optional_params["tools"][0][key] == {}
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@pytest.mark.parametrize(
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"tool, expect_parameters",
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[
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(
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{
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"name": "test_function",
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"description": "test_function_description",
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"parameters": {
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"type": "object",
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"properties": {"test_param": {"type": "string"}},
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},
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},
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True,
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),
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(
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{
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"name": "test_function",
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},
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False,
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),
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],
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)
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def test_vertex_function_translation(tool, expect_parameters):
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"""
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If param not set, don't set it in the request
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"""
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tools = [tool]
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optional_params = get_optional_params(
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model="gemini-1.5-pro",
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custom_llm_provider="vertex_ai",
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tools=tools,
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)
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print(optional_params)
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if expect_parameters:
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assert "parameters" in optional_params["tools"][0]["function_declarations"][0]
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else:
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assert (
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"parameters" not in optional_params["tools"][0]["function_declarations"][0]
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)
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