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litellm/tests/unit/llms/snowflake/test_snowflake_native_endpoints.py
yuneng-jiang 5e6dc89ba1
test: move tests/test_litellm/llms into tests/unit/llms (#43191) 
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* ci: rename fork-flag to unit-flag now that it applies on every event

* test: move tests/test_litellm root and small trees into tests/unit

Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.

* test: carry tests/test_litellm conftest isolation into tests/unit

Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.

* test: merge, split and prune the moved root and small-tree tests

Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.

* ci: run the moved root and small-tree tests under their legacy flags

Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.

* test: make the new tests/unit directories packages

tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.

* test: scope the unit socket block to tests/unit in shared sessions

The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.

* test: move tests/test_litellm/llms into tests/unit/llms

Rename-only. Moves the provider tests and the fine-tuning fixtures they
load, mirroring the old paths. Follow-up commits merge, split and wire them.

* test: merge, split and prune the moved llms tests

Merges the Databricks chat transformation tests into the existing unit
file, keeps the tests that need real keys or the network in
tests/test_litellm, deletes the audited tests a stronger unit test
already covers, and points imports at tests.unit.llms.

* ci: run the moved llms tests under their legacy flags

The Vertex AI and All Other Providers shards keep their legacy test-path
for the retained files and add the llm-vertex-ai and llm-other-providers
unit selections. CircleCI gets matching unit jobs.

* test: make the tests/unit/llms directories packages

Adds __init__.py to the moved dirs and drops the legacy ones whose
directories no longer hold tests.

* test: drop script runners and path hacks the llms split left dangling

The __main__ runners in the split openai_like files and the Databricks e2e
runner called tests that now live in the other half of the split or were
deleted. The retained legacy halves also no longer need sys.path edits.

* test: give the shard-script tests their own GITHUB_OUTPUT

They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.

* test: point the router and module-deletion checks at tests/unit

router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.

* test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path

The Databricks e2e file is a manual script whose main() calls the tests
that were pruned, so pruning them broke the documented run. It is back to
its main version. The SageMaker Nova docstring now points at the file's
real location in tests/local_testing.

* test: keep the job's UNIT_FLAG out of the shard-script tests

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-25 12:43:23 -07:00

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"""
Tests for Snowflake Cortex native endpoint migration.
Covers:
- SnowflakeConfig with auto-routing:
- Non-Claude models → /chat/completions (OpenAI format)
- Claude models → /messages (Anthropic format)
Run:
pytest tests/unit/llms/snowflake/test_snowflake_native_endpoints.py -v
"""
import json
from unittest.mock import MagicMock, patch
import httpx
import pytest
from litellm.llms.snowflake.chat.transformation import (
SnowflakeConfig,
_is_claude_model,
)
from litellm.types.utils import ModelResponse
# ─── Fixtures ──────────────────────────────────────────────────────────────
ACCOUNT_ID = "myaccount"
API_BASE = f"https://{ACCOUNT_ID}.snowflakecomputing.com"
PAT_TOKEN = "pat/my-secret-pat-token"
JWT_TOKEN = "eyJhbGciOiJSUzI1NiJ9.test"
def _mock_logging():
m = MagicMock()
m.post_call = MagicMock()
return m
def _make_openai_response(content: str = "Hello!") -> httpx.Response:
body = {
"id": "chatcmpl-abc123",
"object": "chat.completion",
"model": "llama3.1-70b",
"choices": [
{
"index": 0,
"message": {"role": "assistant", "content": content},
"finish_reason": "stop",
}
],
"usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
}
return httpx.Response(200, json=body)
def _make_anthropic_response(content: str = "Hello!") -> httpx.Response:
body = {
"id": "msg_abc123",
"type": "message",
"role": "assistant",
"model": "claude-sonnet-4-5",
"content": [{"type": "text", "text": content}],
"stop_reason": "end_turn",
"usage": {"input_tokens": 10, "output_tokens": 5},
}
return httpx.Response(200, json=body)
# ─── SnowflakeConfig (OpenAI-compatible) ───────────────────────────────────
class TestSnowflakeConfigURL:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_url_with_account_id_in_optional_params(self):
optional_params = {"account_id": ACCOUNT_ID}
url = self.cfg.get_complete_url(
api_base=None,
api_key=JWT_TOKEN,
model="snowflake/llama3.1-70b",
optional_params=optional_params,
litellm_params={},
)
assert url == f"https://{ACCOUNT_ID}.snowflakecomputing.com/api/v2/cortex/v1/chat/completions"
def test_url_with_explicit_api_base(self):
url = self.cfg.get_complete_url(
api_base=API_BASE,
api_key=JWT_TOKEN,
model="snowflake/llama3.1-70b",
optional_params={},
litellm_params={},
)
assert url.endswith("/api/v2/cortex/v1/chat/completions")
assert "cortex/inference:complete" not in url
def test_url_never_uses_legacy_endpoint(self):
url = self.cfg.get_complete_url(
api_base=API_BASE,
api_key=JWT_TOKEN,
model="snowflake/llama3.1-70b",
optional_params={},
litellm_params={},
)
assert "inference:complete" not in url
assert "/v1/chat/completions" in url
def test_url_works_for_claude_models(self):
url = self.cfg.get_complete_url(
api_base=API_BASE,
api_key=JWT_TOKEN,
model="snowflake/claude-sonnet-4-5",
optional_params={},
litellm_params={},
)
assert "/cortex/v1/messages" in url
def test_url_works_for_llama_models(self):
url = self.cfg.get_complete_url(
api_base=API_BASE,
api_key=JWT_TOKEN,
model="snowflake/llama3.1-70b",
optional_params={},
litellm_params={},
)
assert "/cortex/v1/chat/completions" in url
class TestSnowflakeConfigAuth:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_pat_auth_strips_prefix_and_sets_header(self):
headers = self.cfg.validate_environment(
headers={},
model="snowflake/llama3.1-70b",
messages=[],
optional_params={},
litellm_params={},
api_key=PAT_TOKEN,
)
assert headers["X-Snowflake-Authorization-Token-Type"] == "PROGRAMMATIC_ACCESS_TOKEN"
assert headers["Authorization"] == "Bearer my-secret-pat-token"
def test_jwt_auth_sets_keypair_header(self):
headers = self.cfg.validate_environment(
headers={},
model="snowflake/llama3.1-70b",
messages=[],
optional_params={},
litellm_params={},
api_key=JWT_TOKEN,
)
assert headers["X-Snowflake-Authorization-Token-Type"] == "KEYPAIR_JWT"
assert headers["Authorization"] == f"Bearer {JWT_TOKEN}"
def test_missing_api_key_raises(self):
with pytest.raises(ValueError, match="Missing Snowflake JWT key"):
self.cfg.validate_environment(
headers={},
model="snowflake/llama3.1-70b",
messages=[],
optional_params={},
litellm_params={},
api_key=None,
)
class TestSnowflakeConfigRequest:
def setup_method(self):
self.cfg = SnowflakeConfig()
self.messages = [{"role": "user", "content": "hello"}]
def test_request_uses_openai_tool_format(self):
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather",
"parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
},
}
]
body = self.cfg.transform_request(
model="snowflake/llama3.1-70b",
messages=self.messages,
optional_params={"tools": tools},
litellm_params={},
headers={},
)
assert body["tools"] == tools
assert "tool_spec" not in json.dumps(body)
def test_stream_defaults_to_false(self):
body = self.cfg.transform_request(
model="snowflake/llama3.1-70b",
messages=self.messages,
optional_params={},
litellm_params={},
headers={},
)
assert body["stream"] is False
def test_stream_true_passes_through(self):
body = self.cfg.transform_request(
model="snowflake/llama3.1-70b",
messages=self.messages,
optional_params={"stream": True},
litellm_params={},
headers={},
)
assert body["stream"] is True
def test_supported_params_includes_stream(self):
params = self.cfg.get_supported_openai_params("snowflake/llama3.1-70b")
assert "stream" in params
def test_no_content_list_in_request(self):
body = self.cfg.transform_request(
model="snowflake/llama3.1-70b",
messages=self.messages,
optional_params={},
litellm_params={},
headers={},
)
assert "content_list" not in body
class TestSnowflakeConfigResponse:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_standard_response_parsed(self):
raw = _make_openai_response("Hello from Snowflake!")
result = self.cfg.transform_response(
model="snowflake/llama3.1-70b",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[{"role": "user", "content": "hi"}],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.choices[0].message.content == "Hello from Snowflake!"
assert result.model.startswith("snowflake/")
def test_model_prefixed_with_snowflake(self):
raw = _make_openai_response()
result = self.cfg.transform_response(
model="snowflake/llama3.1-70b",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.model.startswith("snowflake/")
# ─── SnowflakeConfig ────────────────────────────────────────
class TestAnthropicConfigURL:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_url_routes_to_messages_endpoint(self):
url = self.cfg.get_complete_url(
api_base=API_BASE,
api_key=PAT_TOKEN,
model="snowflake/claude-sonnet-4-5",
optional_params={},
litellm_params={},
)
assert url.endswith("/api/v2/cortex/v1/messages")
assert "chat/completions" not in url
assert "inference:complete" not in url
def test_url_with_account_id(self):
url = self.cfg.get_complete_url(
api_base=None,
api_key=PAT_TOKEN,
model="snowflake/claude-sonnet-4-5",
optional_params={"account_id": ACCOUNT_ID},
litellm_params={},
)
assert f"https://{ACCOUNT_ID}.snowflakecomputing.com/api/v2/cortex/v1/messages" == url
class TestAnthropicConfigAuth:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_anthropic_version_header_set(self):
headers = self.cfg.validate_environment(
headers={},
model="snowflake/claude-sonnet-4-5",
messages=[],
optional_params={},
litellm_params={},
api_key=PAT_TOKEN,
)
assert headers["anthropic-version"] == "2023-06-01"
def test_pat_auth_and_anthropic_version_combined(self):
headers = self.cfg.validate_environment(
headers={},
model="snowflake/claude-sonnet-4-5",
messages=[],
optional_params={},
litellm_params={},
api_key=PAT_TOKEN,
)
assert headers["X-Snowflake-Authorization-Token-Type"] == "PROGRAMMATIC_ACCESS_TOKEN"
assert headers["anthropic-version"] == "2023-06-01"
assert "Bearer" in headers["Authorization"]
class TestAnthropicConfigRequest:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_system_message_extracted_to_top_level(self):
messages = [
{"role": "system", "content": "You are helpful."},
{"role": "user", "content": "Hello"},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
assert body["system"] == [{"type": "text", "text": "You are helpful."}]
assert all(m["role"] != "system" for m in body["messages"])
assert body["messages"][0] == {"role": "user", "content": "Hello"}
def test_model_prefix_stripped(self):
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=[{"role": "user", "content": "hi"}],
optional_params={},
litellm_params={},
headers={},
)
assert body["model"] == "claude-sonnet-4-5"
assert "snowflake/" not in body["model"]
def test_max_tokens_defaulted_when_missing(self):
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=[{"role": "user", "content": "hi"}],
optional_params={},
litellm_params={},
headers={},
)
assert "max_tokens" in body
assert body["max_tokens"] == 4096
def test_max_tokens_not_overridden_when_provided(self):
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=[{"role": "user", "content": "hi"}],
optional_params={"max_tokens": 500},
litellm_params={},
headers={},
)
assert body["max_tokens"] == 500
def test_no_system_key_when_no_system_message(self):
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=[{"role": "user", "content": "hi"}],
optional_params={},
litellm_params={},
headers={},
)
assert "system" not in body
class TestAnthropicConfigResponse:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_anthropic_response_to_openai_format(self):
raw = _make_anthropic_response("Hi there!")
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-5",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[{"role": "user", "content": "hi"}],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.choices[0].message.content == "Hi there!"
assert result.choices[0].finish_reason == "stop"
def test_usage_tokens_mapped(self):
raw = _make_anthropic_response()
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-5",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.usage.prompt_tokens == 10
assert result.usage.completion_tokens == 5
assert result.usage.total_tokens == 15
def test_prompt_cache_usage_is_surfaced(self):
"""Cortex reports cache creation/read counts; dropping them hides caching and bills cached input at full price."""
raw = httpx.Response(
200,
json={
"id": "msg_1",
"model": "claude-sonnet-4-6",
"content": [{"type": "text", "text": "hi"}],
"stop_reason": "end_turn",
"usage": {"input_tokens": 18, "cache_creation_input_tokens": 1323, "cache_read_input_tokens": 0},
},
)
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-6",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.usage.prompt_tokens == 1341
assert result.usage.prompt_tokens_details.cache_creation_tokens == 1323
assert result.usage.prompt_tokens_details.cached_tokens == 0
def test_thinking_block_and_signature_are_preserved(self):
"""The signature must survive so a client can echo the thinking block on the next turn."""
raw = httpx.Response(
200,
json={
"id": "msg_1",
"model": "claude-sonnet-4-6",
"content": [
{"type": "thinking", "thinking": "391", "signature": "Eto"},
{"type": "text", "text": "391"},
],
"stop_reason": "end_turn",
"usage": {"input_tokens": 10, "output_tokens": 5},
},
)
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-6",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
message = result.choices[0].message
assert message.content == "391"
assert message.reasoning_content == "391"
assert message.thinking_blocks[0]["signature"] == "Eto"
def test_stop_reason_end_turn_maps_to_stop(self):
raw = _make_anthropic_response()
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-5",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.choices[0].finish_reason == "stop"
def test_tool_use_block_mapped_to_tool_calls(self):
body = {
"id": "msg_tool",
"type": "message",
"role": "assistant",
"model": "claude-sonnet-4-5",
"content": [
{
"type": "tool_use",
"id": "toolu_01",
"name": "get_weather",
"input": {"city": "Paris"},
}
],
"stop_reason": "tool_use",
"usage": {"input_tokens": 20, "output_tokens": 10},
}
raw = httpx.Response(200, json=body)
result = self.cfg.transform_response(
model="snowflake/claude-sonnet-4-5",
raw_response=raw,
model_response=ModelResponse(),
logging_obj=_mock_logging(),
request_data={},
messages=[],
optional_params={},
litellm_params={},
encoding=None,
)
assert result.choices[0].finish_reason == "tool_calls"
tool_calls = result.choices[0].message.tool_calls
assert len(tool_calls) == 1
assert tool_calls[0].function.name == "get_weather"
assert json.loads(tool_calls[0].function.arguments) == {"city": "Paris"}
# ─── Model detection helper ────────────────────────────────────────────────
class TestIsClaudeModel:
def test_claude_model_detected(self):
assert _is_claude_model("snowflake/claude-sonnet-4-5") is True
assert _is_claude_model("claude-3-haiku") is True
assert _is_claude_model("snowflake/claude-opus-4") is True
def test_non_claude_not_detected(self):
assert _is_claude_model("snowflake/llama3.1-70b") is False
assert _is_claude_model("snowflake/mistral-large") is False
assert _is_claude_model("snowflake/deepseek-r1") is False
assert _is_claude_model("snowflake/snowflake-arctic") is False
# ─── Anthropic Tool Transformation Tests ──────────────────────────────────
class TestAnthropicToolTransformation:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_openai_tools_converted_to_anthropic_format(self):
messages = [{"role": "user", "content": "What's the weather?"}]
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather",
"parameters": {
"type": "object",
"properties": {"city": {"type": "string"}},
"required": ["city"],
},
},
}
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={"tools": tools},
litellm_params={},
headers={},
)
assert len(body["tools"]) == 1
tool = body["tools"][0]
assert tool["name"] == "get_weather"
assert tool["description"] == "Get current weather"
assert "input_schema" in tool
assert tool["input_schema"]["properties"]["city"]["type"] == "string"
assert "function" not in tool
assert "type" not in tool
def test_tools_already_in_anthropic_format_pass_through(self):
messages = [{"role": "user", "content": "hi"}]
tools = [{"name": "my_tool", "input_schema": {"type": "object", "properties": {}}}]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={"tools": tools},
litellm_params={},
headers={},
)
assert body["tools"] == tools
class TestAnthropicMultiTurnToolMessages:
def setup_method(self):
self.cfg = SnowflakeConfig()
def test_assistant_tool_calls_converted_to_tool_use_blocks(self):
messages = [
{"role": "user", "content": "What's the weather in Paris?"},
{
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_123",
"type": "function",
"function": {
"name": "get_weather",
"arguments": '{"city": "Paris"}',
},
}
],
},
{
"role": "tool",
"tool_call_id": "call_123",
"content": "Sunny, 22°C",
},
{"role": "user", "content": "Thanks!"},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
msgs = body["messages"]
assert msgs[0] == {"role": "user", "content": "What's the weather in Paris?"}
assistant_msg = msgs[1]
assert assistant_msg["role"] == "assistant"
assert isinstance(assistant_msg["content"], list)
assert assistant_msg["content"][0]["type"] == "tool_use"
assert assistant_msg["content"][0]["id"] == "call_123"
assert assistant_msg["content"][0]["name"] == "get_weather"
assert assistant_msg["content"][0]["input"] == {"city": "Paris"}
tool_result_msg = msgs[2]
assert tool_result_msg["role"] == "user"
assert tool_result_msg["content"][0]["type"] == "tool_result"
assert tool_result_msg["content"][0]["tool_use_id"] == "call_123"
assert tool_result_msg["content"][0]["content"] == "Sunny, 22°C"
assert msgs[3] == {"role": "user", "content": "Thanks!"}
def test_assistant_with_text_and_tool_calls(self):
messages = [
{"role": "user", "content": "Check weather"},
{
"role": "assistant",
"content": "Let me check that for you.",
"tool_calls": [
{
"id": "call_456",
"type": "function",
"function": {
"name": "get_weather",
"arguments": '{"city": "London"}',
},
}
],
},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
assistant_msg = body["messages"][1]
assert assistant_msg["content"][0] == {"type": "text", "text": "Let me check that for you."}
assert assistant_msg["content"][1]["type"] == "tool_use"
assert assistant_msg["content"][1]["name"] == "get_weather"
def test_tool_role_never_in_output(self):
messages = [
{"role": "user", "content": "hi"},
{
"role": "assistant",
"content": None,
"tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "{}"}}],
},
{"role": "tool", "tool_call_id": "c1", "content": "result"},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
for msg in body["messages"]:
assert msg["role"] != "tool"
def test_malformed_json_in_tool_arguments_handled_gracefully(self):
messages = [
{"role": "user", "content": "hi"},
{
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_bad",
"type": "function",
"function": {"name": "broken_tool", "arguments": "not valid json{{{"},
}
],
},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
assistant_msg = body["messages"][1]
tool_use_block = assistant_msg["content"][0]
assert tool_use_block["type"] == "tool_use"
assert tool_use_block["name"] == "broken_tool"
assert tool_use_block["input"] == {}
def test_non_string_tool_arguments_pass_through(self):
messages = [
{"role": "user", "content": "hi"},
{
"role": "assistant",
"content": None,
"tool_calls": [
{
"id": "call_dict",
"type": "function",
"function": {"name": "dict_tool", "arguments": {"already": "parsed"}},
}
],
},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
tool_use_block = body["messages"][1]["content"][0]
assert tool_use_block["input"] == {"already": "parsed"}
def test_tool_result_with_non_string_content(self):
messages = [
{"role": "user", "content": "hi"},
{
"role": "assistant",
"content": None,
"tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "{}"}}],
},
{"role": "tool", "tool_call_id": "c1", "content": {"result_key": "result_value"}},
]
body = self.cfg.transform_request(
model="snowflake/claude-sonnet-4-5",
messages=messages,
optional_params={},
litellm_params={},
headers={},
)
tool_result = body["messages"][2]["content"][0]
assert tool_result["type"] == "tool_result"
assert json.loads(tool_result["content"]) == {"result_key": "result_value"}
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