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litellm/tests/test_litellm/llms/watsonx/test_watsonx.py
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Python

import json
import os
import sys
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
from typing import Optional
from unittest.mock import Mock, patch
import pytest
import litellm
from litellm import completion
from litellm.llms.custom_httpx.http_handler import HTTPHandler
@pytest.fixture
def watsonx_chat_completion_call():
def _call(
model="watsonx/my-test-model",
messages=None,
api_key="test_api_key",
space_id: Optional[str] = None,
headers=None,
client=None,
patch_token_call=True,
):
if messages is None:
messages = [{"role": "user", "content": "Hello, how are you?"}]
if client is None:
client = HTTPHandler()
if patch_token_call:
mock_response = Mock()
mock_response.json.return_value = {
"access_token": "mock_access_token",
"expires_in": 3600,
}
mock_response.raise_for_status = Mock() # No-op to simulate no exception
with patch.object(client, "post") as mock_post, patch.object(
litellm.module_level_client, "post", return_value=mock_response
) as mock_get:
try:
completion(
model=model,
messages=messages,
api_key=api_key,
headers=headers or {},
client=client,
space_id=space_id,
)
except Exception as e:
print(e)
return mock_post, mock_get
else:
with patch.object(client, "post") as mock_post:
try:
completion(
model=model,
messages=messages,
api_key=api_key,
headers=headers or {},
client=client,
space_id=space_id,
)
except Exception as e:
print(e)
return mock_post, None
return _call
def test_watsonx_deployment_model_id_not_in_payload(
monkeypatch, watsonx_chat_completion_call
):
"""Test that deployment models do not include 'model_id' in the request payload"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx/deployment/test-deployment-id"
messages = [{"role": "user", "content": "Test message"}]
mock_post, _ = watsonx_chat_completion_call(model=model, messages=messages)
assert mock_post.call_count == 1
json_data = json.loads(mock_post.call_args.kwargs["data"])
# Ensure model_id is not in the payload for deployment models
assert "model_id" not in json_data or json_data["model_id"] is None
# Ensure project_id is also not in the payload for deployment models
assert "project_id" not in json_data or json_data["project_id"] is None
def test_watsonx_regular_model_includes_model_id(
monkeypatch, watsonx_chat_completion_call
):
"""Test that regular models include 'model_id' in the request payload"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx/regular-model"
messages = [{"role": "user", "content": "Test message"}]
mock_post, _ = watsonx_chat_completion_call(model=model, messages=messages)
assert mock_post.call_count == 1
json_data = json.loads(mock_post.call_args.kwargs["data"])
# Ensure model_id is included in the payload for regular models
assert "model_id" in json_data
assert json_data["model_id"] == "regular-model" # Provider prefix is stripped
# Ensure project_id is also included for regular models
assert "project_id" in json_data
@pytest.fixture
def watsonx_completion_call():
def _call(
model="watsonx_text/my-test-model",
prompt="Hello, how are you?",
api_key="test_api_key",
space_id: Optional[str] = None,
headers=None,
client=None,
patch_token_call=True,
):
if client is None:
client = HTTPHandler()
if patch_token_call:
mock_response = Mock()
mock_response.json.return_value = {
"access_token": "mock_access_token",
"expires_in": 3600,
}
mock_response.raise_for_status = Mock()
with patch.object(client, "post") as mock_post, patch.object(
litellm.module_level_client, "post", return_value=mock_response
) as mock_get:
try:
litellm.text_completion(
model=model,
prompt=prompt,
api_key=api_key,
headers=headers or {},
client=client,
space_id=space_id,
)
except Exception as e:
print(e)
return mock_post, mock_get
else:
with patch.object(client, "post") as mock_post:
try:
litellm.text_completion(
model=model,
prompt=prompt,
api_key=api_key,
headers=headers or {},
client=client,
space_id=space_id,
)
except Exception as e:
print(e)
return mock_post, None
return _call
def test_watsonx_completion_deployment_model_id_not_in_payload(
monkeypatch, watsonx_completion_call
):
"""Test that deployment models do not include 'model_id' in completion request payload"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx_text/deployment/test-deployment-id"
prompt = "Test prompt"
mock_post, _ = watsonx_completion_call(model=model, prompt=prompt)
assert mock_post.call_count == 1
json_data = json.loads(mock_post.call_args.kwargs["data"])
# Ensure model_id is not in the payload for deployment models
assert "model_id" not in json_data
# Ensure project_id is also not in the payload for deployment models
assert "project_id" not in json_data
def test_watsonx_completion_regular_model_includes_model_id(
monkeypatch, watsonx_completion_call
):
"""Test that regular models include 'model_id' in completion request payload"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx_text/regular-model"
prompt = "Test prompt"
mock_post, _ = watsonx_completion_call(model=model, prompt=prompt)
assert mock_post.call_count == 1
json_data = json.loads(mock_post.call_args.kwargs["data"])
# Ensure model_id is included in the payload for regular models
assert "model_id" in json_data
assert json_data["model_id"] == "regular-model" # Provider prefix is stripped
# Ensure project_id is also included for regular models
assert "project_id" in json_data
@pytest.mark.asyncio
async def test_watsonx_gpt_oss_prompt_transformation(monkeypatch):
"""
Test that gpt-oss-120b model transforms messages to proper format instead of simple concatenation.
This test starts from litellm.acompletion and verifies what gets sent in the final POST request body.
Input messages should be transformed using the HuggingFace chat template from openai/gpt-oss-120b,
not just concatenated as "You are chatgpt Hi there".
"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
# Test with gpt-oss model using watsonx_text provider (text generation endpoint)
model = "watsonx_text/openai/gpt-oss-120b"
# Input messages
messages = [
{"role": "system", "content": "You are chatgpt"},
{"role": "user", "content": "Hi there"},
]
# Mock the HTTP client
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
client = AsyncHTTPHandler()
# Mock the token call
mock_token_response = Mock()
mock_token_response.json.return_value = {
"access_token": "mock_access_token",
"expires_in": 3600,
}
mock_token_response.raise_for_status = Mock()
# Mock the completion call
mock_completion_response = Mock()
mock_completion_response.status_code = 200
mock_completion_response.json.return_value = {
"results": [
{
"generated_text": "Hello! How can I help you?",
"generated_token_count": 10,
"input_token_count": 5,
"stop_reason": "stop", # Required field for response transformation
}
],
"model_id": "openai/gpt-oss-120b",
}
# Mock HuggingFace template fetch to make test deterministic and avoid network flakiness.
# The test verifies that prompt transformation occurs (not simple concatenation), not the exact
# HuggingFace template format. Using a mock template that produces the correct format is sufficient.
from unittest.mock import patch
# Mock template that produces gpt-oss-120b-like format.
# Note: This is a simplified version of the actual template. The real template is more complex
# (adds metadata, handles tools, thinking messages, etc.), but this captures the key aspects:
# - Converts system role to developer (matching real template behavior)
# - Uses the same tag structure (<|start|>, <|message|>, <|end|>)
# - Preserves message content
mock_tokenizer_config = {
"status": "success",
"tokenizer": {
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}<|start|>developer<|message|>{% else %}<|start|>{{ message['role'] }}<|message|>{% endif %}{{ message['content'] }}<|end|>{% endfor %}",
"bos_token": None,
"eos_token": None,
},
}
async def mock_aget_tokenizer_config(hf_model_name: str):
return mock_tokenizer_config
async def mock_aget_chat_template_file(hf_model_name: str):
# Return failure to use tokenizer_config instead
return {"status": "failure"}
# Clear any cached tokenizer config for this model to ensure fresh fetch
hf_model = "openai/gpt-oss-120b"
if hf_model in litellm.known_tokenizer_config:
del litellm.known_tokenizer_config[hf_model]
with patch.object(client, "post") as mock_post, patch.object(
litellm.module_level_client, "post", return_value=mock_token_response
), patch(
"litellm.litellm_core_utils.prompt_templates.huggingface_template_handler._aget_tokenizer_config",
side_effect=mock_aget_tokenizer_config,
), patch(
"litellm.litellm_core_utils.prompt_templates.huggingface_template_handler._aget_chat_template_file",
side_effect=mock_aget_chat_template_file,
):
# Set the mock to return the completion response
mock_post.return_value = mock_completion_response
try:
# Call acompletion with messages
await litellm.acompletion(
model=model,
messages=messages,
api_key="test_api_key",
client=client,
)
except Exception as e:
# May fail due to incomplete mocking, but we should have captured the request
print(f"Exception (may be expected): {e}")
# Verify the POST was called
assert (
mock_post.call_count >= 1
), f"POST should have been called at least once, got {mock_post.call_count}"
# Get the request body from the first call
# Use call_args_list to be more robust - get the first call's arguments
assert len(mock_post.call_args_list) > 0, "mock_post should have at least one call"
call_args = mock_post.call_args_list[0]
assert call_args is not None, "call_args should not be None"
assert "data" in call_args.kwargs, "call_args.kwargs should contain 'data'"
json_data = json.loads(call_args.kwargs["data"])
print(f"\n{'='*80}")
print(f"Input messages to litellm.acompletion:")
print(json.dumps(messages, indent=2))
print(f"\n{'='*80}")
print(f"Final POST request body:")
print(json.dumps(json_data, indent=2))
print(f"{'='*80}\n")
# Verify the transformed input is in the request
assert "input" in json_data, "Request should have 'input' field"
transformed_prompt = json_data["input"]
# Verify transformation occurred
assert transformed_prompt is not None, (
"Prompt transformation failed - the template should have been applied to transform "
"messages into the correct format for gpt-oss-120b."
)
print(f"Transformed prompt: {repr(transformed_prompt)}")
print(f"Prompt length: {len(transformed_prompt)}")
# Verify it's NOT simple concatenation
simple_concat = "You are chatgpt Hi there"
assert transformed_prompt != simple_concat, (
f"Prompt should not be simple concatenation.\n"
f"Expected: Chat template with <|start|> tags\n"
f"Got: {transformed_prompt}"
)
# Verify it contains proper chat template formatting
assert "<|start|>" in transformed_prompt, "Prompt should contain <|start|> tag"
assert "<|message|>" in transformed_prompt, "Prompt should contain <|message|> tag"
assert "<|end|>" in transformed_prompt, "Prompt should contain <|end|> tag"
assert (
"You are chatgpt" in transformed_prompt
), "Prompt should contain system message content"
assert (
"Hi there" in transformed_prompt
), "Prompt should contain user message content"
@pytest.mark.asyncio
async def test_watsonx_gpt_oss_uses_async_http_handler():
"""
Test that verifies async HTTP client is used when fetching HuggingFace templates.
"""
from unittest.mock import AsyncMock, MagicMock, patch
from litellm.litellm_core_utils.prompt_templates.huggingface_template_handler import (
_aget_chat_template_file,
)
# Mock the async HTTP client
mock_async_client = MagicMock()
mock_get = AsyncMock()
mock_async_client.get = mock_get
# Create mock response for chat template file
mock_response = MagicMock()
mock_response.status_code = 200
mock_response.content = b"test template content"
mock_get.return_value = mock_response
# Test the async function directly
with patch(
"litellm.litellm_core_utils.prompt_templates.huggingface_template_handler.get_async_httpx_client",
return_value=mock_async_client,
):
result = await _aget_chat_template_file(hf_model_name="test/model")
# Verify async HTTP client was called
assert mock_get.called, "Async HTTP client's get method should be called"
assert mock_get.await_count > 0, "Async HTTP client's get should be awaited"
# Verify it was called with HuggingFace URL
call_args = mock_get.call_args
assert call_args is not None, "get should have been called with arguments"
called_url = call_args.kwargs.get("url", "")
assert (
"huggingface.co/test/model" in called_url
), f"Should call HuggingFace API for test/model, got: {called_url}"
assert result["status"] == "success", "Should return success status"
def test_watsonx_chat_completion_with_reasoning_effort(monkeypatch):
"""
Test that 'reasoning_effort' is correctly passed through to the WatsonX API payload.
"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx/openai/gpt-oss-120b"
messages = [{"role": "user", "content": "Test message"}]
client = HTTPHandler()
# Mock the token generation call
mock_token_response = Mock()
mock_token_response.json.return_value = {
"access_token": "mock_access_token",
"expires_in": 3600,
}
mock_token_response.raise_for_status = Mock()
# Call litellm.completion with the new parameter
with patch.object(client, "post") as mock_post, patch.object(
litellm.module_level_client, "post", return_value=mock_token_response
):
try:
completion(
model=model,
messages=messages,
api_key="test_api_key",
client=client,
reasoning_effort="low",
)
except Exception as e:
print(f"Caught expected exception: {e}")
# Verify the parameter is in the final request payload
assert (
mock_post.call_count == 1
), "The completion endpoint should have been called once."
# Get the JSON data sent in the POST request
request_kwargs = mock_post.call_args.kwargs
json_data = json.loads(request_kwargs["data"])
print("\nRequest payload sent to WatsonX API:")
print(json.dumps(json_data, indent=2))
# Check for the parameter at the top level of the payload
assert (
"reasoning_effort" in json_data
), "'reasoning_effort' should be at the top level of the payload."
assert (
json_data["reasoning_effort"] == "low"
), "The value of 'reasoning_effort' should be 'low'."
def test_watsonx_zen_api_key_from_client(monkeypatch, watsonx_chat_completion_call):
"""
Test that zen_api_key can be passed from client code and is used in Authorization header.
"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
model = "watsonx/ibm/granite-3-3-8b-instruct"
messages = [{"role": "user", "content": "What is your favorite color?"}]
client = HTTPHandler()
zen_api_key = "U1ZDLWQo="
# No need to patch token call since zen_api_key should skip token generation
with patch.object(client, "post") as mock_post:
try:
completion(
model=model,
messages=messages,
api_key="test_api_key",
client=client,
zen_api_key=zen_api_key,
)
except Exception as e:
print(f"Caught expected exception: {e}")
# Verify the request was made
assert mock_post.call_count == 1, "The completion endpoint should have been called once."
# Get the headers sent in the POST request
request_kwargs = mock_post.call_args.kwargs
headers = request_kwargs["headers"]
print("\nHeaders sent to WatsonX API:")
print(json.dumps(dict(headers), indent=2))
# Verify Authorization header uses ZenApiKey format
assert "Authorization" in headers, "Authorization header should be present."
assert headers["Authorization"] == f"ZenApiKey {zen_api_key}", (
f"Authorization header should use ZenApiKey format. "
f"Expected: 'ZenApiKey {zen_api_key}', Got: '{headers['Authorization']}'"
)
def test_watsonx_zen_api_key_from_env(monkeypatch, watsonx_chat_completion_call):
"""
Test that zen_api_key from environment variable is used in Authorization header.
"""
monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
monkeypatch.setenv("WATSONX_API_BASE", "https://test-api.watsonx.ai")
zen_api_key = "U1ZDLWxpdG--==="
monkeypatch.setenv("WATSONX_ZENAPIKEY", zen_api_key)
model = "watsonx/ibm/granite-3-3-8b-instruct"
messages = [{"role": "user", "content": "What is your favorite color?"}]
client = HTTPHandler()
# No need to patch token call since zen_api_key should skip token generation
with patch.object(client, "post") as mock_post:
try:
completion(
model=model,
messages=messages,
api_key="test_api_key",
client=client,
)
except Exception as e:
print(f"Caught expected exception: {e}")
# Verify the request was made
assert mock_post.call_count == 1, "The completion endpoint should have been called once."
# Get the headers sent in the POST request
request_kwargs = mock_post.call_args.kwargs
headers = request_kwargs["headers"]
print("\nHeaders sent to WatsonX API:")
print(json.dumps(dict(headers), indent=2))
# Verify Authorization header uses ZenApiKey format
assert "Authorization" in headers, "Authorization header should be present."
assert headers["Authorization"] == f"ZenApiKey {zen_api_key}", (
f"Authorization header should use ZenApiKey format. "
f"Expected: 'ZenApiKey {zen_api_key}', Got: '{headers['Authorization']}'"
)