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* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
157 lines
5.2 KiB
Python
157 lines
5.2 KiB
Python
"""
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Tests for litellm.acount_tokens() public API.
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"""
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import asyncio
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import os
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from unittest.mock import AsyncMock, patch
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import litellm
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from litellm.types.utils import TokenCountResponse
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def test_acount_tokens_routes_to_openai():
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"""Test that acount_tokens routes to OpenAI token counter for openai/ models."""
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with patch(
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"litellm.llms.openai.responses.count_tokens.token_counter.openai_count_tokens_handler.handle_count_tokens_request",
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new_callable=AsyncMock,
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return_value={"input_tokens": 15},
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):
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result = asyncio.run(
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litellm.acount_tokens(
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model="openai/gpt-4o",
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messages=[{"role": "user", "content": "Hello, how are you?"}],
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api_key="sk-test-key",
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)
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)
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assert result.total_tokens == 15
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assert result.tokenizer_type == "openai_api"
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assert result.request_model == "openai/gpt-4o"
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def test_acount_tokens_routes_to_anthropic():
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"""Test that acount_tokens routes to Anthropic token counter for anthropic/ models."""
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with patch(
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"litellm.llms.anthropic.count_tokens.token_counter.anthropic_count_tokens_handler.handle_count_tokens_request",
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new_callable=AsyncMock,
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return_value={"input_tokens": 20},
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):
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result = asyncio.run(
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litellm.acount_tokens(
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model="anthropic/claude-3-5-sonnet-20241022",
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messages=[{"role": "user", "content": "Hello Claude!"}],
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api_key="sk-ant-test-key",
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)
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)
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assert result.total_tokens == 20
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assert result.tokenizer_type == "anthropic_api"
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assert result.request_model == "anthropic/claude-3-5-sonnet-20241022"
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def test_acount_tokens_fallback_to_local():
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"""Test that unsupported providers fall back to local tiktoken counting."""
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result = asyncio.run(
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litellm.acount_tokens(
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model="together_ai/meta-llama/Llama-3-8b-chat-hf",
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messages=[{"role": "user", "content": "Hello"}],
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)
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)
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assert result.total_tokens > 0
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assert result.tokenizer_type == "local_tokenizer"
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def test_acount_tokens_with_tools():
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"""Test that tools are passed through to the token counter."""
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"description": "Get weather info",
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"parameters": {
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"type": "object",
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"properties": {"city": {"type": "string"}},
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},
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},
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}
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]
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with patch(
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"litellm.llms.openai.responses.count_tokens.token_counter.openai_count_tokens_handler.handle_count_tokens_request",
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new_callable=AsyncMock,
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return_value={"input_tokens": 30},
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) as mock_handler:
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result = asyncio.run(
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litellm.acount_tokens(
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model="openai/gpt-4o",
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messages=[{"role": "user", "content": "What's the weather?"}],
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tools=tools,
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api_key="sk-test-key",
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)
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)
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assert result.total_tokens == 30
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mock_handler.assert_called_once()
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call_kwargs = mock_handler.call_args
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assert call_kwargs.kwargs.get("tools") == tools
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def test_acount_tokens_with_system():
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"""Test that system messages are passed through."""
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with patch(
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"litellm.llms.openai.responses.count_tokens.token_counter.openai_count_tokens_handler.handle_count_tokens_request",
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new_callable=AsyncMock,
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return_value={"input_tokens": 25},
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):
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result = asyncio.run(
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litellm.acount_tokens(
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model="openai/gpt-4o",
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messages=[{"role": "user", "content": "Hello"}],
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system="You are a helpful assistant.",
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api_key="sk-test-key",
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)
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)
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assert result.total_tokens == 25
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def test_acount_tokens_api_error_falls_back():
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"""Test that API errors in token counting return error response."""
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from litellm.llms.openai.common_utils import OpenAIError
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with patch(
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"litellm.llms.openai.responses.count_tokens.token_counter.openai_count_tokens_handler.handle_count_tokens_request",
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new_callable=AsyncMock,
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side_effect=OpenAIError(status_code=401, message="Invalid API key"),
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):
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result = asyncio.run(
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litellm.acount_tokens(
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model="openai/gpt-4o",
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messages=[{"role": "user", "content": "Hello"}],
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api_key="sk-bad-key",
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)
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)
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# Should fall back to local tokenizer when provider API errors
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assert result.error is False
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assert result.tokenizer_type == "local_tokenizer"
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assert result.total_tokens > 0
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def test_acount_tokens_no_api_key_falls_back(monkeypatch):
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"""Test that missing API key falls back to local counting."""
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monkeypatch.delenv("OPENAI_API_KEY", raising=False)
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result = asyncio.run(
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litellm.acount_tokens(
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model="openai/gpt-4o",
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messages=[{"role": "user", "content": "Hello"}],
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)
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)
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# Should fall back to local tokenizer since no API key
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assert result.total_tokens > 0
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assert result.tokenizer_type == "local_tokenizer"
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