mirror of
https://github.com/tiennm99/litellm.git
synced 2026-06-27 05:07:36 +00:00
Ishaan Jaff
265 lines
11 KiB
Python
265 lines
11 KiB
Python
"""
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This test ensures that the proxy can passthrough anthropic requests
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"""
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import pytest
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import anthropic
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import aiohttp
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import asyncio
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import json
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@pytest.mark.asyncio
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@pytest.mark.flaky(retries=3, delay=2)
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async def test_anthropic_basic_completion_with_headers():
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print("making basic completion request to anthropic passthrough with aiohttp")
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headers = {
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"Authorization": f"Bearer sk-1234",
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"Content-Type": "application/json",
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"Anthropic-Version": "2023-06-01",
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}
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payload = {
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"model": "claude-3-5-sonnet-20241022",
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"max_tokens": 10,
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"messages": [{"role": "user", "content": "Say 'hello test' and nothing else"}],
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"litellm_metadata": {
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"tags": ["test-tag-1", "test-tag-2"],
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},
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}
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async with aiohttp.ClientSession() as session:
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async with session.post(
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"http://0.0.0.0:4000/anthropic/v1/messages", json=payload, headers=headers
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) as response:
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response_text = await response.text()
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print(f"Response text: {response_text}")
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response_json = await response.json()
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response_headers = response.headers
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print(
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"non-streaming response",
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json.dumps(response_json, indent=4, default=str),
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)
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reported_usage = response_json.get("usage", None)
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anthropic_api_input_tokens = reported_usage.get("input_tokens", None)
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anthropic_api_output_tokens = reported_usage.get("output_tokens", None)
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litellm_call_id = response_headers.get("x-litellm-call-id")
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print(f"LiteLLM Call ID: {litellm_call_id}")
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# Wait for spend to be logged
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await asyncio.sleep(15)
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# Check spend logs for this specific request
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async with session.get(
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f"http://0.0.0.0:4000/spend/logs?request_id={litellm_call_id}",
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headers={"Authorization": "Bearer sk-1234"},
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) as spend_response:
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print("text spend response")
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print(f"Spend response: {spend_response}")
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spend_data = await spend_response.json()
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print(f"Spend data: {spend_data}")
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assert spend_data is not None, "Should have spend data for the request"
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log_entry = spend_data[
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0
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] # Get the first (and should be only) log entry
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# Basic existence checks
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assert spend_data is not None, "Should have spend data for the request"
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assert isinstance(log_entry, dict), "Log entry should be a dictionary"
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# Request metadata assertions
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assert (
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log_entry["request_id"] == litellm_call_id
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), "Request ID should match"
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assert (
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log_entry["call_type"] == "pass_through_endpoint"
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), "Call type should be pass_through_endpoint"
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assert (
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log_entry["api_base"] == "https://api.anthropic.com/v1/messages"
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), "API base should be Anthropic's endpoint"
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# Token and spend assertions
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assert log_entry["spend"] > 0, "Spend value should not be None"
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assert isinstance(
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log_entry["spend"], (int, float)
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), "Spend should be a number"
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assert log_entry["total_tokens"] > 0, "Should have some tokens"
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assert (
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log_entry["prompt_tokens"] == anthropic_api_input_tokens
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), f"Should have prompt tokens matching anthropic api. Expected {anthropic_api_input_tokens} but got {log_entry['prompt_tokens']}"
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assert (
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log_entry["completion_tokens"] == anthropic_api_output_tokens
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), f"Should have completion tokens matching anthropic api. Expected {anthropic_api_output_tokens} but got {log_entry['completion_tokens']}"
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assert (
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log_entry["total_tokens"]
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== log_entry["prompt_tokens"] + log_entry["completion_tokens"]
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), "Total tokens should equal prompt + completion"
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# Time assertions
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assert all(
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key in log_entry
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for key in ["startTime", "endTime", "completionStartTime"]
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), "Should have all time fields"
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assert (
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log_entry["startTime"] < log_entry["endTime"]
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), "Start time should be before end time"
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# Metadata assertions
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assert (
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str(log_entry["cache_hit"]).lower() != "true"
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), "Cache should be off"
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assert log_entry["request_tags"] == [
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"test-tag-1",
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"test-tag-2",
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], "Tags should match input"
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assert (
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"user_api_key" in log_entry["metadata"]
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), "Should have user API key in metadata"
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assert "claude" in log_entry["model"]
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assert log_entry["custom_llm_provider"] == "anthropic"
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@pytest.mark.asyncio
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async def test_anthropic_streaming_with_headers():
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print("making streaming request to anthropic passthrough with aiohttp")
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headers = {
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"Authorization": f"Bearer sk-1234",
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"Content-Type": "application/json",
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"Anthropic-Version": "2023-06-01",
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}
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payload = {
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"model": "claude-3-5-sonnet-20241022",
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"max_tokens": 10,
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"messages": [
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{"role": "user", "content": "Say 'hello stream test' and nothing else"}
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],
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"stream": True,
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"litellm_metadata": {
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"tags": ["test-tag-stream-1", "test-tag-stream-2"],
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"user": "test-user-1",
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},
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}
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async with aiohttp.ClientSession() as session:
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async with session.post(
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"http://0.0.0.0:4000/anthropic/v1/messages", json=payload, headers=headers
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) as response:
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print("response status")
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print(response.status)
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assert response.status == 200, "Response should be successful"
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response_headers = response.headers
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print(f"Response headers: {response_headers}")
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litellm_call_id = response_headers.get("x-litellm-call-id")
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print(f"LiteLLM Call ID: {litellm_call_id}")
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collected_output = []
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async for line in response.content:
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if line:
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text = line.decode("utf-8").strip()
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if text.startswith("data: "):
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collected_output.append(text[6:]) # Remove 'data: ' prefix
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print("Collected output:", "".join(collected_output))
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anthropic_api_usage_chunks = []
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for chunk in collected_output:
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chunk_json = json.loads(chunk)
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if "usage" in chunk_json:
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anthropic_api_usage_chunks.append(chunk_json["usage"])
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elif "message" in chunk_json and "usage" in chunk_json["message"]:
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anthropic_api_usage_chunks.append(chunk_json["message"]["usage"])
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print(
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"anthropic_api_usage_chunks",
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json.dumps(anthropic_api_usage_chunks, indent=4, default=str),
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)
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anthropic_api_input_tokens = sum(
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[usage.get("input_tokens", 0) for usage in anthropic_api_usage_chunks]
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)
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anthropic_api_output_tokens = max(
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[usage.get("output_tokens", 0) for usage in anthropic_api_usage_chunks]
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)
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print("anthropic_api_input_tokens", anthropic_api_input_tokens)
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print("anthropic_api_output_tokens", anthropic_api_output_tokens)
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# Wait for spend to be logged
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await asyncio.sleep(20)
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# Check spend logs for this specific request
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async with session.get(
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f"http://0.0.0.0:4000/spend/logs?request_id={litellm_call_id}",
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headers={"Authorization": "Bearer sk-1234"},
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) as spend_response:
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spend_data = await spend_response.json()
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print(f"Spend data: {spend_data}")
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assert spend_data is not None, "Should have spend data for the request"
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log_entry = spend_data[
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0
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] # Get the first (and should be only) log entry
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# Basic existence checks
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assert spend_data is not None, "Should have spend data for the request"
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assert isinstance(log_entry, dict), "Log entry should be a dictionary"
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# Request metadata assertions
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assert (
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log_entry["request_id"] == litellm_call_id
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), "Request ID should match"
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assert (
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log_entry["call_type"] == "pass_through_endpoint"
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), "Call type should be pass_through_endpoint"
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# assert (
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# log_entry["api_base"] == "https://api.anthropic.com/v1/messages"
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# ), "API base should be Anthropic's endpoint"
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# Token and spend assertions
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assert log_entry["spend"] > 0, "Spend value should not be None"
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assert isinstance(
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log_entry["spend"], (int, float)
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), "Spend should be a number"
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assert log_entry["total_tokens"] > 0, "Should have some tokens"
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assert (
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log_entry["prompt_tokens"] == anthropic_api_input_tokens
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), f"Should have prompt tokens matching anthropic api. Expected {anthropic_api_input_tokens} but got {log_entry['prompt_tokens']}"
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assert (
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log_entry["completion_tokens"] == anthropic_api_output_tokens
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), f"Should have completion tokens matching anthropic api. Expected {anthropic_api_output_tokens} but got {log_entry['completion_tokens']}"
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assert (
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log_entry["total_tokens"]
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== log_entry["prompt_tokens"] + log_entry["completion_tokens"]
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), "Total tokens should equal prompt + completion"
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# Time assertions
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assert all(
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key in log_entry
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for key in ["startTime", "endTime", "completionStartTime"]
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), "Should have all time fields"
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assert (
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log_entry["startTime"] < log_entry["endTime"]
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), "Start time should be before end time"
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# Metadata assertions
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assert (
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str(log_entry["cache_hit"]).lower() != "true"
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), "Cache should be off"
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assert log_entry["request_tags"] == [
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"test-tag-stream-1",
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"test-tag-stream-2",
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], "Tags should match input"
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assert (
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"user_api_key" in log_entry["metadata"]
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), "Should have user API key in metadata"
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assert "claude" in log_entry["model"]
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assert log_entry["end_user"] == "test-user-1"
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assert log_entry["custom_llm_provider"] == "anthropic"
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