mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
09462ba80c
* Add cohere v2/rerank support (#8421) * Support v2 endpoint cohere rerank * Add tests and docs * Make v1 default if old params used * Update docs * Update docs pt 2 * Update tests * Add e2e test * Clean up code * Use inheritence for new config * Fix linting issues (#8608) * Fix cohere v2 failing test + linting (#8672) * Fix test and unused imports * Fix tests * fix: fix linting errors * test: handle tgai instability * fix: skip service unavailable err * test: print logs for unstable test * test: skip unreliable tests --------- Co-authored-by: vibhavbhat <vibhavb00@gmail.com>
483 lines
15 KiB
Python
483 lines
15 KiB
Python
import asyncio
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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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import os
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from typing import Optional, Dict
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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 os
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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import litellm
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from litellm.types.rerank import RerankResponse
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from litellm import RateLimitError, Timeout, completion, completion_cost, embedding
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from litellm.integrations.custom_logger import CustomLogger
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
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def assert_response_shape(response, custom_llm_provider):
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expected_response_shape = {"id": str, "results": list, "meta": dict}
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expected_results_shape = {
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"index": int,
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"relevance_score": float,
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"document": Optional[Dict[str, str]],
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}
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expected_meta_shape = {"api_version": dict, "billed_units": dict}
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expected_api_version_shape = {"version": str}
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expected_billed_units_shape = {"search_units": int}
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assert isinstance(response.id, expected_response_shape["id"])
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assert isinstance(response.results, expected_response_shape["results"])
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for result in response.results:
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assert isinstance(result["index"], expected_results_shape["index"])
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assert isinstance(
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result["relevance_score"], expected_results_shape["relevance_score"]
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)
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if "document" in result:
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assert isinstance(result["document"], Dict)
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assert isinstance(result["document"]["text"], str)
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assert isinstance(response.meta, expected_response_shape["meta"])
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if custom_llm_provider == "cohere":
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assert isinstance(
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response.meta["api_version"], expected_meta_shape["api_version"]
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)
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assert isinstance(
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response.meta["api_version"]["version"],
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expected_api_version_shape["version"],
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)
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assert isinstance(
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response.meta["billed_units"], expected_meta_shape["billed_units"]
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)
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assert isinstance(
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response.meta["billed_units"]["search_units"],
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expected_billed_units_shape["search_units"],
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)
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.flaky(retries=3, delay=1)
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async def test_basic_rerank(sync_mode):
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litellm.set_verbose = True
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if sync_mode is True:
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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else:
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("async re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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print("response", response.model_dump_json(indent=4))
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.skip(reason="Skipping test due to 503 Service Temporarily Unavailable")
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async def test_basic_rerank_together_ai(sync_mode):
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try:
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if sync_mode is True:
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response = litellm.rerank(
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model="together_ai/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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else:
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response = await litellm.arerank(
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model="together_ai/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("async re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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except Exception as e:
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if "Service unavailable" in str(e):
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pytest.skip("Skipping test due to 503 Service Temporarily Unavailable")
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raise e
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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async def test_basic_rerank_azure_ai(sync_mode):
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import os
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litellm.set_verbose = True
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if sync_mode is True:
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response = litellm.rerank(
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model="azure_ai/Cohere-rerank-v3-multilingual-ko",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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api_key=os.getenv("AZURE_AI_COHERE_API_KEY"),
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api_base=os.getenv("AZURE_AI_COHERE_API_BASE"),
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)
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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else:
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response = await litellm.arerank(
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model="azure_ai/Cohere-rerank-v3-multilingual-ko",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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api_key=os.getenv("AZURE_AI_COHERE_API_KEY"),
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api_base=os.getenv("AZURE_AI_COHERE_API_BASE"),
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)
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print("async re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("version", ["v1", "v2"])
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async def test_rerank_custom_api_base(version):
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mock_response = AsyncMock()
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litellm.cohere_key = "test_api_key"
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def return_val():
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return {
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"id": "cmpl-mockid",
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"results": [{"index": 0, "relevance_score": 0.95}],
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"meta": {
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"api_version": {"version": "1.0"},
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"billed_units": {"search_units": 1},
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},
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}
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mock_response.json = return_val
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mock_response.headers = {"key": "value"}
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mock_response.status_code = 200
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expected_payload = {
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"model": "Salesforce/Llama-Rank-V1",
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"query": "hello",
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"top_n": 3,
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"documents": ["hello", "world"],
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}
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api_base = "https://exampleopenaiendpoint-production.up.railway.app/"
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if version == "v1":
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api_base += "v1/rerank"
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with patch(
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"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
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return_value=mock_response,
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) as mock_post:
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response = await litellm.arerank(
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model="cohere/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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api_base=api_base,
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)
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print("async re rank response: ", response)
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# Assert
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mock_post.assert_called_once()
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print("call args", mock_post.call_args)
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args_to_api = mock_post.call_args.kwargs["data"]
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_url = mock_post.call_args.kwargs["url"]
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print("Arguments passed to API=", args_to_api)
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print("url = ", _url)
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assert (
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_url
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== f"https://exampleopenaiendpoint-production.up.railway.app/{version}/rerank"
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)
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request_data = json.loads(args_to_api)
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assert request_data["query"] == expected_payload["query"]
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assert request_data["documents"] == expected_payload["documents"]
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assert request_data["top_n"] == expected_payload["top_n"]
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assert request_data["model"] == expected_payload["model"]
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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class TestLogger(CustomLogger):
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def __init__(self):
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self.kwargs = None
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self.response_obj = None
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super().__init__()
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async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
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print("in success event for rerank, kwargs = ", kwargs)
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print("in success event for rerank, response_obj = ", response_obj)
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self.kwargs = kwargs
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self.response_obj = response_obj
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@pytest.mark.asyncio()
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async def test_rerank_custom_callbacks():
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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custom_logger = TestLogger()
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litellm.callbacks = [custom_logger]
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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await asyncio.sleep(5)
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print("async re rank response: ", response)
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assert custom_logger.kwargs is not None
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assert custom_logger.kwargs.get("response_cost") > 0.0
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assert custom_logger.response_obj is not None
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assert custom_logger.response_obj.results is not None
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def test_complete_base_url_cohere():
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from litellm.llms.custom_httpx.http_handler import HTTPHandler
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client = HTTPHandler()
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litellm.api_base = "http://localhost:4000"
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litellm.cohere_key = "test_api_key"
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litellm.set_verbose = True
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text = "Hello there!"
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list_texts = ["Hello there!", "How are you?", "How do you do?"]
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rerank_model = "rerank-multilingual-v3.0"
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with patch.object(client, "post") as mock_post:
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try:
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litellm.rerank(
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model=rerank_model,
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query=text,
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documents=list_texts,
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custom_llm_provider="cohere",
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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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print("mock_post.call_args", mock_post.call_args)
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mock_post.assert_called_once()
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# Default to the v2 client when calling the base /rerank
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assert "http://localhost:4000/v2/rerank" in mock_post.call_args.kwargs["url"]
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.parametrize(
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"top_n_1, top_n_2, expect_cache_hit",
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[
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(3, 3, True),
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(3, None, False),
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],
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)
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@pytest.mark.flaky(retries=3, delay=1)
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async def test_basic_rerank_caching(sync_mode, top_n_1, top_n_2, expect_cache_hit):
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from litellm.caching.caching import Cache
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litellm.set_verbose = True
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litellm.cache = Cache(type="local")
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if sync_mode is True:
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for idx in range(2):
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if idx == 0:
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top_n = top_n_1
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else:
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top_n = top_n_2
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=top_n,
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)
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else:
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for idx in range(2):
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if idx == 0:
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top_n = top_n_1
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else:
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top_n = top_n_2
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=top_n,
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)
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await asyncio.sleep(1)
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if expect_cache_hit is True:
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assert "cache_key" in response._hidden_params
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else:
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assert "cache_key" not in response._hidden_params
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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def test_rerank_response_assertions():
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r = RerankResponse(
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**{
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"id": "ab0fcca0-b617-11ef-b292-0242ac110002",
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"results": [
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{"index": 2, "relevance_score": 0.9958819150924683},
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{"index": 0, "relevance_score": 0.001293411129154265},
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{
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"index": 1,
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"relevance_score": 7.641685078851879e-05,
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},
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{
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"index": 3,
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"relevance_score": 7.621097756782547e-05,
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},
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],
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"meta": {
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"api_version": None,
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"billed_units": None,
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"tokens": None,
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"warnings": None,
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},
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}
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)
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assert_response_shape(r, custom_llm_provider="custom")
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def test_cohere_rerank_v2_client():
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from litellm.llms.custom_httpx.http_handler import HTTPHandler
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client = HTTPHandler()
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litellm.api_base = "http://localhost:4000"
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litellm.set_verbose = True
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text = "Hello there!"
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list_texts = ["Hello there!", "How are you?", "How do you do?"]
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rerank_model = "rerank-multilingual-v3.0"
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with patch.object(client, "post") as mock_post:
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mock_response = MagicMock()
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mock_response.text = json.dumps(
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{
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"id": "cmpl-mockid",
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"results": [
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{"index": 0, "relevance_score": 0.95},
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{"index": 1, "relevance_score": 0.75},
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{"index": 2, "relevance_score": 0.65},
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],
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"usage": {"prompt_tokens": 100, "total_tokens": 150},
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}
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)
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mock_response.status_code = 200
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mock_response.headers = {"Content-Type": "application/json"}
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mock_response.json = lambda: json.loads(mock_response.text)
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mock_post.return_value = mock_response
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response = litellm.rerank(
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model=rerank_model,
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query=text,
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documents=list_texts,
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custom_llm_provider="cohere",
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max_tokens_per_doc=3,
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top_n=2,
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api_key="fake-api-key",
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client=client,
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)
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# Ensure Cohere API is called with the expected params
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mock_post.assert_called_once()
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assert mock_post.call_args.kwargs["url"] == "http://localhost:4000/v2/rerank"
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request_data = json.loads(mock_post.call_args.kwargs["data"])
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assert request_data["model"] == rerank_model
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assert request_data["query"] == text
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assert request_data["documents"] == list_texts
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assert request_data["max_tokens_per_doc"] == 3
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assert request_data["top_n"] == 2
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# Ensure litellm response is what we expect
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assert response["results"] == mock_response.json()["results"]
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@pytest.mark.flaky(retries=3, delay=1)
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def test_rerank_cohere_api():
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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return_documents=True,
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top_n=3,
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)
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print("rerank response", response)
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assert response.results[0]["document"] is not None
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assert response.results[0]["document"]["text"] is not None
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assert response.results[0]["document"]["text"] == "hello"
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assert response.results[1]["document"]["text"] == "world"
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