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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
278 lines
10 KiB
Python
278 lines
10 KiB
Python
import traceback
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import asyncio
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from dotenv import load_dotenv
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from fastapi import Request
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from datetime import datetime
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from litellm import Router
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import pytest
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import litellm
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from unittest.mock import patch, MagicMock, AsyncMock
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from create_mock_standard_logging_payload import create_standard_logging_payload
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from litellm.types.utils import StandardLoggingPayload
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import unittest
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from pydantic import BaseModel
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from litellm.router_utils.prompt_caching_cache import PromptCachingCache
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class ExampleModel(BaseModel):
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field1: str
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field2: int
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def test_serialize_pydantic_object():
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model = ExampleModel(field1="value", field2=42)
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serialized = PromptCachingCache.serialize_object(model)
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assert serialized == {"field1": "value", "field2": 42}
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def test_serialize_dict():
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obj = {"b": 2, "a": 1}
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serialized = PromptCachingCache.serialize_object(obj)
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assert serialized == '{"a":1,"b":2}' # JSON string with sorted keys
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def test_serialize_nested_dict():
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obj = {"z": {"b": 2, "a": 1}, "x": [1, 2, {"c": 3}]}
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serialized = PromptCachingCache.serialize_object(obj)
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expected = '{"x":[1,2,{"c":3}],"z":{"a":1,"b":2}}' # JSON string with sorted keys
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assert serialized == expected
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def test_serialize_list():
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obj = ["item1", {"a": 1, "b": 2}, 42]
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serialized = PromptCachingCache.serialize_object(obj)
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expected = ["item1", '{"a":1,"b":2}', 42]
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assert serialized == expected
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def test_serialize_fallback():
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obj = 12345 # Simple non-serializable object
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serialized = PromptCachingCache.serialize_object(obj)
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assert serialized == 12345
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def test_serialize_non_serializable():
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class CustomClass:
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def __str__(self):
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return "custom_object"
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obj = CustomClass()
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serialized = PromptCachingCache.serialize_object(obj)
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assert serialized == "custom_object" # Fallback to string conversion
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@pytest.mark.asyncio
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async def test_router_prompt_caching_same_cacheable_prefix_routes_to_same_deployment():
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"""
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End-to-end test to validate prompt caching routing through LiteLLM Router.
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Tests that requests with same cacheable content but different user messages
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route to the same deployment (for prompt caching).
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This reproduces the issue where requests with same cacheable prefix but different
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user messages should route to the same deployment, but previously didn't because
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the cache key included the entire messages array instead of just the cacheable prefix.
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"""
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from litellm.types.llms.openai import AllMessageValues
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def create_messages(user_content: str) -> list[AllMessageValues]:
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"""
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Create messages matching the user's exact scenario.
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Message structure:
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- BLOCK 1: System message, first content block (no cache_control)
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→ INCLUDED (comes before the last cacheable block)
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- BLOCK 2: System message, second content block (WITH cache_control)
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→ INCLUDED (this IS the last cacheable block)
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- USER MESSAGE: User message (no cache_control)
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→ NOT included (comes after last cacheable block)
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"""
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return [
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{
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"role": "system",
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"content": [
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# BLOCK 1: No cache_control → INCLUDED (all blocks up to last cacheable are included)
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{
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"type": "text",
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"text": "You are an AI assistant tasked with analyzing legal documents.",
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},
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# BLOCK 2: Has cache_control → INCLUDED (this is the last cacheable block)
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{
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"type": "text",
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"text": "Here 3 is the full text of a complex legal agreement"
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* 400,
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"cache_control": {"type": "ephemeral"},
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},
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],
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},
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{
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"role": "user",
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# USER MESSAGE: No cache_control → NOT included (comes after last cacheable block)
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"content": user_content,
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},
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]
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# Create router with multiple deployments
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router = Router(
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model_list=[
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{
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"model_name": "test-model",
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"litellm_params": {
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"model": "gpt-5-mini",
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"api_base": "https://exampleopenaiendpoint-production-0ee2.up.railway.app/v1",
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"api_key": f"test-key-{i}",
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},
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"model_info": {"id": f"deployment-{i}"},
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}
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for i in range(1, 4)
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],
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routing_strategy="simple-shuffle",
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optional_pre_call_checks=["prompt_caching"],
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)
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# Create test messages matching user's exact scenario
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# Same cacheable prefix (system blocks 1+2) but different user messages
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messages1 = create_messages(
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"what are the key terms and conditions in this agreement?"
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)
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messages2 = create_messages("how many words are there?")
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messages3 = create_messages("how many sentences are there?")
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cache = PromptCachingCache(cache=router.cache)
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# Test 1: Cache keys should be same (same cacheable prefix, different user messages)
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key1 = PromptCachingCache.get_prompt_caching_cache_key(messages1, None)
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key2 = PromptCachingCache.get_prompt_caching_cache_key(messages2, None)
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key3 = PromptCachingCache.get_prompt_caching_cache_key(messages3, None)
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assert key1 is not None, "Cache key should not be None"
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assert (
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key1 == key2 == key3
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), "Cache keys should be the same for same cacheable prefix"
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# Make first request
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try:
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response1 = await router.acompletion(model="test-model", messages=messages1)
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model_id_1 = response1._hidden_params.get("model_id", "unknown")
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except Exception:
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# If API call fails, we can still test the cache key logic
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model_id_1 = "unknown"
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await asyncio.sleep(1) # Wait for cache write
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# Test 2: Cache lookup should work for messages2 (same cacheable prefix)
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cached_2 = await cache.async_get_model_id(messages2, None)
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# Cache should be found if first request succeeded
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if model_id_1 != "unknown":
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assert (
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cached_2 is not None
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), "Cache lookup should work for same cacheable prefix"
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# Make second request
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try:
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response2 = await router.acompletion(model="test-model", messages=messages2)
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model_id_2 = response2._hidden_params.get("model_id", "unknown")
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except Exception:
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model_id_2 = "unknown"
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await asyncio.sleep(1) # Wait for cache write
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# Make third request
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try:
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response3 = await router.acompletion(model="test-model", messages=messages3)
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model_id_3 = response3._hidden_params.get("model_id", "unknown")
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except Exception:
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model_id_3 = "unknown"
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# Test 3: All requests should route to same deployment (if API calls succeeded)
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if model_id_1 != "unknown" and model_id_2 != "unknown" and model_id_3 != "unknown":
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assert (
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model_id_1 == model_id_2 == model_id_3
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), f"All requests should route to same deployment, but got: {model_id_1}, {model_id_2}, {model_id_3}"
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def test_extract_cacheable_prefix_with_string_content_and_message_level_cache_control():
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"""
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Test that extract_cacheable_prefix correctly handles messages where:
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- content is a string (not a list of content blocks)
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- cache_control is a sibling key at the message level
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This is a valid message format per LiteLLM's ChatCompletionUserMessage type:
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{"role": "user", "content": "...", "cache_control": {"type": "ephemeral"}}
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Regression test for issue #19228.
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"""
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# Test case 1: Single message with string content and message-level cache_control
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messages_string_content = [
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{"role": "system", "content": "You are a helpful assistant"},
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{
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"role": "user",
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"content": "This is a large message that should be cached",
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"cache_control": {"type": "ephemeral", "ttl": "5m"},
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},
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]
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result = PromptCachingCache.extract_cacheable_prefix(messages_string_content)
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# Should return both messages (system + user with cache_control)
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assert len(result) == 2, f"Expected 2 messages, got {len(result)}"
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assert result[0]["role"] == "system"
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assert result[1]["role"] == "user"
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assert result[1]["content"] == "This is a large message that should be cached"
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assert result[1].get("cache_control") == {"type": "ephemeral", "ttl": "5m"}
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def test_extract_cacheable_prefix_with_string_content_no_cache_control():
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"""
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Test that extract_cacheable_prefix returns empty list when:
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- content is a string
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- no cache_control is present
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"""
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messages_no_cache = [
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{"role": "system", "content": "You are a helpful assistant"},
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{"role": "user", "content": "Hello"},
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]
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result = PromptCachingCache.extract_cacheable_prefix(messages_no_cache)
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# Should return empty list (no cacheable content)
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assert len(result) == 0, f"Expected 0 messages, got {len(result)}"
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def test_extract_cacheable_prefix_mixed_string_and_list_content():
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"""
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Test that extract_cacheable_prefix handles messages with a mix of:
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- String content with message-level cache_control
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- List content with block-level cache_control
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The last cache_control (regardless of format) should determine the cacheable prefix.
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"""
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# Message with string content + cache_control, followed by message with list content + cache_control
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messages_mixed = [
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{"role": "system", "content": "You are a helpful assistant"},
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{
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"role": "user",
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"content": "First cached message",
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"cache_control": {"type": "ephemeral"},
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},
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "Second cached message in list format",
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"cache_control": {"type": "ephemeral"},
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}
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],
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},
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{"role": "user", "content": "This should not be in the prefix"},
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]
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result = PromptCachingCache.extract_cacheable_prefix(messages_mixed)
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# Should include first 3 messages (up to and including the last cache_control)
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assert len(result) == 3, f"Expected 3 messages, got {len(result)}"
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assert result[0]["role"] == "system"
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assert result[1]["content"] == "First cached message"
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assert isinstance(result[2]["content"], list)
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