cecli/tests/basic/test_models.py at main · cecli-dev/cecli · GitHub

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from unittest.mock import ANY, MagicMock, patch

import pytest

from cecli.models import (

ANTHROPIC_BETA_HEADER,

Model,

ModelInfoManager,

register_models,

sanity_check_model,

sanity_check_models,

)

class TestModels:

@pytest.fixture(autouse=True)

def setup_and_teardown(self):

"""Reset MODEL_SETTINGS before each test and restore after"""

from cecli.models import MODEL_SETTINGS

self._original_settings = MODEL_SETTINGS.copy()

yield

MODEL_SETTINGS.clear()

MODEL_SETTINGS.extend(self._original_settings)

def test_get_model_info_nonexistent(self):

manager = ModelInfoManager()

info = manager.get_model_info("non-existent-model")

assert info == {}

def test_configured_provider_prefix_wins_over_litellm_provider(self, monkeypatch):

"""Provider settings resolve from the model's configured prefix.

litellm's model-cost table rewrites info's litellm_provider to the

upstream vendor for known model names, which previously made a

user-defined provider's supports_stream flag invisible.

"""

from cecli import models as models_module

provider_manager = MagicMock()

provider_manager.supports_provider.side_effect = lambda provider: provider == "my-provider"

provider_manager.get_provider_config.return_value = {

"litellm_provider": "my-provider",

"supports_stream": False,

}

provider_manager.get_provider_base_url.return_value = None

fake_info_manager = MagicMock()

fake_info_manager.provider_manager = provider_manager

monkeypatch.setattr(models_module, "model_info_manager", fake_info_manager)

model = object.__new__(Model)

model.name = "my-provider/gpt-4o"

model.info = {"litellm_provider": "openai", "supports_stream": True}

model.extra_params = {}

model.streaming = True

assert model._configured_provider() == "my-provider"

model._apply_provider_defaults()

assert model.litellm_provider == "my-provider"

assert model.streaming is False

# A bare model name still falls back to litellm's provider.

model.name = "gpt-4o"

assert model._configured_provider() == "openai"

def test_max_context_tokens(self):

model = Model("gpt-3.5-turbo")

assert model.info["max_input_tokens"] == 16385

model = Model("gpt-3.5-turbo-16k")

assert model.info["max_input_tokens"] == 16385

model = Model("gpt-3.5-turbo-1106")

assert model.info["max_input_tokens"] == 16385

model = Model("gpt-4")

assert model.info["max_input_tokens"] == 8 * 1024

model = Model("gpt-4-32k")

# gpt-4-32k might not have model info in litellm, use .get() to avoid KeyError

max_tokens = model.info.get("max_input_tokens")

if max_tokens is not None:

assert max_tokens == 32 * 1024

model = Model("gpt-4-0613")

assert model.info["max_input_tokens"] == 8 * 1024

@patch("os.environ")

async def test_sanity_check_model_all_set(self, mock_environ):

mock_environ.get.return_value = "dummy_value"

mock_io = MagicMock()

model = MagicMock()

model.name = "test-model"

model.missing_keys = ["API_KEY1", "API_KEY2"]

model.keys_in_environment = True

model.info = {"some": "info"}

await sanity_check_model(mock_io, model)

mock_io.tool_output.assert_called()

calls = mock_io.tool_output.call_args_list

assert "- API_KEY1: Set" in str(calls)

assert "- API_KEY2: Set" in str(calls)

@patch("os.environ")

async def test_sanity_check_model_not_set(self, mock_environ):

mock_environ.get.return_value = ""

mock_io = MagicMock()

model = MagicMock()

model.name = "test-model"

model.missing_keys = ["API_KEY1", "API_KEY2"]

model.keys_in_environment = True

model.info = {"some": "info"}

await sanity_check_model(mock_io, model)

mock_io.tool_output.assert_called()

calls = mock_io.tool_output.call_args_list

assert "- API_KEY1: Not set" in str(calls)

assert "- API_KEY2: Not set" in str(calls)

async def test_sanity_check_models_bogus_editor(self):

mock_io = MagicMock()

main_model = Model("gpt-4")

main_model.editor_model = Model("bogus-model")

result = await sanity_check_models(mock_io, main_model)

assert result

mock_io.tool_warning.assert_called_with(ANY)

warning_messages = [

warning_call.args[0] for warning_call in mock_io.tool_warning.call_args_list

]

print("Warning messages:", warning_messages)

assert mock_io.tool_warning.call_count >= 1

assert any(("bogus-model" in msg for msg in warning_messages))

@patch("cecli.models.check_for_dependencies")

async def test_sanity_check_model_calls_check_dependencies(self, mock_check_deps):

"""Test that sanity_check_model calls check_for_dependencies"""

mock_io = MagicMock()

model = MagicMock()

model.name = "test-model"

model.missing_keys = []

model.keys_in_environment = True

model.info = {"some": "info"}

await sanity_check_model(mock_io, model)

mock_check_deps.assert_called_once_with(mock_io, "test-model")

def test_model_aliases(self):

# Test common aliases

model = Model("4")

assert model.name == "gpt-4-0613"

model = Model("4o")

assert model.name == "gpt-4o"

model = Model("35turbo")

assert model.name == "gpt-3.5-turbo"

model = Model("35-turbo")

assert model.name == "gpt-3.5-turbo"

model = Model("3")

assert model.name == "gpt-3.5-turbo"

model = Model("sonnet")

assert model.name == "anthropic/claude-sonnet-4-20250514"

model = Model("haiku")

assert model.name == "claude-3-5-haiku-20241022"

model = Model("opus")

assert model.name == "claude-opus-4-20250514"

# Test non-alias passes through unchanged

model = Model("gpt-4")

assert model.name == "gpt-4"

def test_o1_use_temp_false(self):

model = Model("github/o1-mini")

assert model.name == "github/o1-mini"

assert model.use_temperature is False

model = Model("github/o1-preview")

assert model.name == "github/o1-preview"

assert model.use_temperature is False

def test_parse_token_value(self):

model = Model("gpt-4")

# Test integer inputs

assert model.parse_token_value(8096) == 8096

assert model.parse_token_value(1000) == 1000

# Test string inputs

assert model.parse_token_value("8096") == 8096

# Test k/K suffix (kilobytes)

assert model.parse_token_value("8k") == 8 * 1024

assert model.parse_token_value("8K") == 8 * 1024

assert model.parse_token_value("10.5k") == 10.5 * 1024

assert model.parse_token_value("0.5K") == 0.5 * 1024

# Test m/M suffix (megabytes)

assert model.parse_token_value("1m") == 1 * 1024 * 1024

assert model.parse_token_value("1M") == 1 * 1024 * 1024

assert model.parse_token_value("0.5M") == 0.5 * 1024 * 1024

# Test with spaces

assert model.parse_token_value(" 8k ") == 8 * 1024

# Test conversion from other types

assert model.parse_token_value(8.0) == 8

def test_set_thinking_tokens(self):

model = Model("gpt-4")

# Test with integer

model.set_thinking_tokens(8096)

assert model.extra_params["extra_body"]["thinking"]["budget_tokens"] == 8096

assert not model.use_temperature

# Test with string

model.set_thinking_tokens("10k")

assert model.extra_params["extra_body"]["thinking"]["budget_tokens"] == 10 * 1024

# Test with decimal value

model.set_thinking_tokens("0.5M")

assert model.extra_params["extra_body"]["thinking"]["budget_tokens"] == 0.5 * 1024 * 1024

@patch("cecli.models.check_pip_install_extra")

async def test_check_for_dependencies_bedrock(self, mock_check_pip):

"""Test that check_for_dependencies calls check_pip_install_extra for Bedrock models"""

from cecli.io import InputOutput

io = InputOutput()

from cecli.models import check_for_dependencies

await check_for_dependencies(io, "bedrock/anthropic.claude-3-sonnet-20240229-v1:0")

mock_check_pip.assert_called_once_with(

io, "boto3", "AWS Bedrock models require the boto3 package.", ["boto3"]

)

@patch("cecli.models.check_pip_install_extra")

async def test_check_for_dependencies_vertex_ai(self, mock_check_pip):

"""Test that check_for_dependencies calls check_pip_install_extra for Vertex AI models"""

from cecli.io import InputOutput

io = InputOutput()

from cecli.models import check_for_dependencies

await check_for_dependencies(io, "vertex_ai/gemini-1.5-pro")

mock_check_pip.assert_called_once_with(

io,

"google.cloud.aiplatform",

"Google Vertex AI models require the google-cloud-aiplatform package.",

["google-cloud-aiplatform"],

)

@patch("cecli.models.check_pip_install_extra")

async def test_check_for_dependencies_other_model(self, mock_check_pip):

"""Test that check_for_dependencies doesn't call check_pip_install_extra for other models"""

from cecli.io import InputOutput

io = InputOutput()

from cecli.models import check_for_dependencies

await check_for_dependencies(io, "gpt-4")

mock_check_pip.assert_not_called()

def test_get_repo_map_tokens(self):

# Test default case (no max_input_tokens in info)

model = Model("gpt-4")

model.info = {}

assert model.get_repo_map_tokens() == 1024

# Test minimum boundary (max_input_tokens < 8192)

model.info = {"max_input_tokens": 4096}

assert model.get_repo_map_tokens() == 1024

# Test middle range (max_input_tokens = 16384)

model.info = {"max_input_tokens": 16384}

assert model.get_repo_map_tokens() == 2048

# Test maximum boundary (max_input_tokens > 32768)

model.info = {"max_input_tokens": 65536}

assert model.get_repo_map_tokens() == 4096

# Test exact boundary values

model.info = {"max_input_tokens": 8192}

assert model.get_repo_map_tokens() == 1024

model.info = {"max_input_tokens": 32768}

assert model.get_repo_map_tokens() == 4096

def test_configure_model_settings(self):

# Test o3-mini case

model = Model("something/o3-mini")

assert model.edit_format == "diff"

assert model.use_repo_map

assert not model.use_temperature

# Test o1-mini case

model = Model("something/o1-mini")

assert model.use_repo_map

assert not model.use_temperature

assert not model.use_system_prompt

# Test o1-preview case

model = Model("something/o1-preview")

assert model.edit_format == "diff"

assert model.use_repo_map

assert not model.use_temperature

assert not model.use_system_prompt

# Test o1 case

model = Model("something/o1")

assert model.edit_format == "diff"

assert model.use_repo_map

assert not model.use_temperature

assert not model.streaming

# Test deepseek v3 case

model = Model("deepseek-v3")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.reminder == "sys"

assert model.examples_as_sys_msg

# Test deepseek reasoner case

model = Model("deepseek-r1")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.examples_as_sys_msg

assert not model.use_temperature

assert model.reasoning_tag == "think"

# Test provider/deepseek-r1 case

model = Model("someprovider/deepseek-r1")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.examples_as_sys_msg

assert not model.use_temperature

assert model.reasoning_tag == "think"

# Test provider/deepseek-v3 case

model = Model("anotherprovider/deepseek-v3")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.reminder == "sys"

assert model.examples_as_sys_msg

# Test llama3 70b case

model = Model("llama3-70b")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.send_undo_reply

assert model.examples_as_sys_msg

# Test gpt-4 case

model = Model("gpt-4")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.send_undo_reply

# Test gpt-3.5 case

model = Model("gpt-3.5")

assert model.reminder == "sys"

# Test 3.5-sonnet case

model = Model("claude-3.5-sonnet")

assert model.edit_format == "diff"

assert model.use_repo_map

assert model.examples_as_sys_msg

assert model.reminder == "user"

# Test o1- prefix case

model = Model("o1-something")

assert not model.use_system_prompt

assert not model.use_temperature

# Test qwen case

model = Model("qwen-coder-2.5-32b")

assert model.edit_format == "diff"

assert model.editor_edit_format == "editor-diff"

assert model.use_repo_map

def test_cecli_extra_model_settings(self):

import tempfile

import yaml

test_settings = [

{

"name": "cecli/extra_params",

"extra_params": {"extra_headers": {"Foo": "bar"}, "some_param": "some value"},

}

]

tmp = tempfile.mktemp(suffix=".yml")

try:

with open(tmp, "w") as f:

yaml.dump(test_settings, f)

register_models([tmp])

model = Model("claude-3-5-sonnet-20240620")

assert model.extra_params["extra_headers"]["Foo"] == "bar"

assert model.extra_params["extra_headers"]["anthropic-beta"] == ANTHROPIC_BETA_HEADER

assert model.extra_params["some_param"] == "some value"

assert model.extra_params["max_tokens"] == 8192

model = Model("gpt-4")

assert model.extra_params["extra_headers"]["Foo"] == "bar"

assert model.extra_params["some_param"] == "some value"

finally:

import os

try:

os.unlink(tmp)

except OSError:

pass

@patch("cecli.models.litellm.acompletion")

@patch.object(Model, "token_count")

async def test_ollama_num_ctx_set_when_missing(self, mock_token_count, mock_completion):

mock_token_count.return_value = 1000

model = Model("ollama/llama3")

model.extra_params = {}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

expected_ctx = int(1000 * 1.25) + 8192

mock_completion.assert_called_once_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

num_ctx=expected_ctx,

timeout=600,

keep_alive=-1,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

@patch("cecli.models.litellm.acompletion")

async def test_modern_tool_call_propagation(self, mock_completion):

model = Model("gpt-4")

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(

messages,

functions=None,

stream=False,

tools=[dict(type="function", function=dict(name="test"))],

)

mock_completion.assert_called_once()

call_kwargs = mock_completion.call_args.kwargs

assert call_kwargs["tools"] == [dict(type="function", function=dict(name="test"))]

assert call_kwargs["model"] == model.name

assert call_kwargs["stream"] is False

@patch("cecli.models.litellm.acompletion")

async def test_legacy_tool_call_propagation(self, mock_completion):

model = Model("gpt-4")

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=[dict(name="test")], stream=False)

mock_completion.assert_called_once()

call_kwargs = mock_completion.call_args.kwargs

assert call_kwargs["tools"] == [dict(type="function", function=dict(name="test"))]

assert call_kwargs["model"] == model.name

assert call_kwargs["stream"] is False

@patch("cecli.models.litellm.acompletion")

async def test_ollama_uses_existing_num_ctx(self, mock_completion):

model = Model("ollama/llama3")

model.extra_params = {"num_ctx": 4096}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_once_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

num_ctx=4096,

timeout=600,

keep_alive=-1,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

@patch("cecli.models.litellm.acompletion")

async def test_non_ollama_no_num_ctx(self, mock_completion):

model = Model("gpt-4")

model.extra_params = {}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_once_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

timeout=600,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

assert "num_ctx" not in mock_completion.call_args.kwargs

def test_use_temperature_settings(self):

# Test use_temperature=True (default) uses temperature=0

model = Model("gpt-4")

assert model.use_temperature

assert model.use_temperature is True

# Test use_temperature=False doesn't pass temperature

model = Model("github/o1-mini")

assert not model.use_temperature

# Test use_temperature as float value

model = Model("gpt-4")

model.use_temperature = 0.7

assert model.use_temperature == 0.7

@patch("cecli.models.litellm.acompletion")

async def test_use_temperature_false_omits_temperature(self, mock_completion):

model = Model("github/o1-mini")

model.extra_params = {}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(

messages, functions=None, stream=False, override_kwargs={"temperature": 0}

)

assert "temperature" not in mock_completion.call_args.kwargs

@patch("cecli.models.litellm.acompletion")

async def test_request_timeout_default(self, mock_completion):

model = Model("gpt-4")

model.extra_params = {}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

timeout=600,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

@patch("cecli.models.litellm.acompletion")

async def test_request_timeout_from_extra_params(self, mock_completion):

# Test timeout from extra_params overrides default

model = Model("gpt-4")

model.extra_params = {"timeout": 300}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

timeout=300,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

@patch("cecli.models.litellm.acompletion")

async def test_use_temperature_in_send_completion(self, mock_completion):

# Test use_temperature=True sends temperature=0

model = Model("gpt-4")

model.extra_params = {}

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0,

timeout=600,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

# Test use_temperature=False doesn't send temperature

model = Model("github/o1-mini")

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

assert "temperature" not in mock_completion.call_args.kwargs

# Test use_temperature as float sends that value

model = Model("gpt-4")

model.extra_params = {}

model.use_temperature = 0.7

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

mock_completion.assert_called_with(

model=model.name,

messages=ANY,

prompt_cache_key=ANY,

stream=False,

temperature=0.7,

timeout=600,

drop_params=True,

headers={"User-Agent": ANY},

cache_control_injection_points=ANY,

allowed_openai_params=["tools", "tool_choice"],

)

@patch("cecli.models.litellm.acompletion")

async def test_send_completion_retry_with_debug(self, mock_completion):

from cecli.io import InputOutput

from cecli.llm import litellm

io = InputOutput()

model = Model("gpt-4", io=io, debug=True)

model.extra_params = {}

mock_completion.side_effect = [

litellm.ServiceUnavailableError(

"Service unavailable", llm_provider="openai", model="gpt-4"

MagicMock(),

]

messages = [{"role": "user", "content": "Hello"}]

hash_obj, res = await model.send_completion(messages, functions=None, stream=False)

assert mock_completion.call_count == 2

def test_model_override_kwargs(self):

"""Test that override kwargs are applied to model extra_params."""

# Test with override kwargs

model = Model("gpt-4", override_kwargs={"temperature": 0.8, "top_p": 0.9})

assert "temperature" in model.extra_params

assert model.extra_params["temperature"] == 0.8

assert "top_p" in model.extra_params

assert model.extra_params["top_p"] == 0.9

# Test that override kwargs merge with existing extra_params

model = Model("gpt-4", override_kwargs={"extra_headers": {"X-Custom": "value"}})

assert "extra_headers" in model.extra_params

assert "X-Custom" in model.extra_params["extra_headers"]

assert model.extra_params["extra_headers"]["X-Custom"] == "value"

# Test nested dict merging

model = Model("gpt-4", override_kwargs={"extra_body": {"reasoning_effort": "high"}})

assert "extra_body" in model.extra_params

assert "reasoning_effort" in model.extra_params["extra_body"]

assert model.extra_params["extra_body"]["reasoning_effort"] == "high"

def test_model_override_kwargs_with_existing_extra_params(self):

"""Test that override kwargs merge correctly with existing extra_params."""

# Create a model with existing extra_params via model settings

import tempfile

import yaml

test_settings = [

{

"name": "gpt-4",

"extra_params": {"temperature": 0.5, "extra_headers": {"Existing": "header"}},

}

]

tmp = tempfile.mktemp(suffix=".yml")

try:

with open(tmp, "w") as f:

yaml.dump(test_settings, f)

register_models([tmp])

# Test that override kwargs take precedence

model = Model("gpt-4", override_kwargs={"temperature": 0.8, "top_p": 0.9})

assert model.extra_params["temperature"] == 0.8 # Override wins

assert model.extra_params["top_p"] == 0.9 # New param added

assert "extra_headers" in model.extra_params

assert model.extra_params["extra_headers"]["Existing"] == "header" # Existing preserved

# Test nested dict merging

model = Model("gpt-4", override_kwargs={"extra_headers": {"New": "value"}})

assert "Existing" in model.extra_params["extra_headers"]

assert "New" in model.extra_params["extra_headers"]

assert model.extra_params["extra_headers"]["Existing"] == "header"

assert model.extra_params["extra_headers"]["New"] == "value"

finally:

import os

try:

os.unlink(tmp)

except OSError:

pass

@patch("cecli.models.litellm.acompletion")

async def test_send_completion_with_override_kwargs(self, mock_completion):

"""Test that override kwargs are passed to acompletion."""

# Create model with override kwargs

model = Model("gpt-4", override_kwargs={"temperature": 0.8, "top_p": 0.9})

messages = [{"role": "user", "content": "Hello"}]

await model.send_completion(messages, functions=None, stream=False)

# Check that override kwargs are in the call

mock_completion.assert_called_once()

call_kwargs = mock_completion.call_args.kwargs

assert "temperature" in call_kwargs

assert call_kwargs["temperature"] == 0.8

assert "top_p" in call_kwargs

assert call_kwargs["top_p"] == 0.9

# Check that model name and other defaults are still there

assert call_kwargs["model"] == "gpt-4"

assert not call_kwargs["stream"]

@pytest.mark.parametrize(

"model_input,expected_base,expected_kwargs,description",

[

(

"gpt-4o:high",

"gpt-4o",

{"reasoning_effort": "high", "temperature": 0.7},

"valid suffix 'high'",

(

"gpt-4o:low",

"gpt-4o",

{"reasoning_effort": "low", "temperature": 0.2},

"valid suffix 'low'",

("gpt-4o", "gpt-4o", {}, "no suffix"),

("gpt-4o:unknown", "gpt-4o", {}, "unknown suffix"),

("unknown-model:high", "unknown-model", {}, "unknown model with suffix"),

("", "", {}, "empty model name"),

)

def test_parse_model_with_suffix(

self, model_input, expected_base, expected_kwargs, description

"""Test parse_model_with_suffix function handles model names with optional :suffix."""

def parse_model_with_suffix(model_name, overrides):

"""Parse model name with optional :suffix and apply overrides."""

if not model_name:

return (model_name, {})

if ":" in model_name:

base_model, suffix = model_name.rsplit(":", 1)

else:

base_model, suffix = (model_name, None)

override_kwargs = {}

if suffix and base_model in overrides and (suffix in overrides[base_model]):

override_kwargs = overrides[base_model][suffix].copy()

return (base_model, override_kwargs)

overrides = {

"gpt-4o": {

"high": {"reasoning_effort": "high", "temperature": 0.7},

"low": {"reasoning_effort": "low", "temperature": 0.2},

"claude-3-5-sonnet": {"fast": {"temperature": 0.3}, "creative": {"temperature": 0.9}},

}

base_model, kwargs = parse_model_with_suffix(model_input, overrides)

assert base_model == expected_base, f"Failed ({description}): base model mismatch"

assert kwargs == expected_kwargs, f"Failed ({description}): kwargs mismatch"

def test_print_matching_models_with_pricing(self):

"""Test that print_matching_models displays pricing information correctly."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock model_info_manager to return pricing data

with patch("cecli.models.model_info_manager") as mock_manager:

mock_manager.get_model_info.return_value = {

"input_cost_per_token": 0.000005, # $5 per 1M tokens

"output_cost_per_token": 0.000015, # $15 per 1M tokens

}

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "gpt-4")

# Check that the header was printed

mock_tool_output.assert_any_call('Models which match "gpt-4":')

# Check that pricing was included in the output

calls = [str(call) for call in mock_tool_output.call_args_list]

pricing_found = any("$5.00/1m/input" in call for call in calls)

output_pricing_found = any("$15.00/1m/output" in call for call in calls)

assert pricing_found, "Input pricing not found in output"

assert output_pricing_found, "Output pricing not found in output"

def test_print_matching_models_with_cache_pricing(self):

"""Test that print_matching_models displays cache pricing when available."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock model_info_manager to return pricing data with cache

with patch("cecli.models.model_info_manager") as mock_manager:

mock_manager.get_model_info.return_value = {

"input_cost_per_token": 0.000003, # $3 per 1M tokens

"output_cost_per_token": 0.000012, # $12 per 1M tokens

"cache_cost_per_token": 0.000001, # $1 per 1M tokens

}

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "claude-3-5-sonnet")

# Check that all pricing was included in the output

calls = [str(call) for call in mock_tool_output.call_args_list]

input_found = any("$3.00/1m/input" in call for call in calls)

output_found = any("$12.00/1m/output" in call for call in calls)

cache_found = any("$1.00/1m/cache" in call for call in calls)

assert input_found, "Input pricing not found in output"

assert output_found, "Output pricing not found in output"

assert cache_found, "Cache pricing not found in output"

def test_print_matching_models_without_pricing(self):

"""Test that print_matching_models works when no pricing info is available."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock model_info_manager to return no pricing data

with patch("cecli.models.model_info_manager") as mock_manager:

mock_manager.get_model_info.return_value = {}

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "gpt-4")

# Check that the header was printed

mock_tool_output.assert_any_call('Models which match "gpt-4":')

# Check that no pricing was included in the output

calls = [str(call) for call in mock_tool_output.call_args_list]

pricing_found = any("/1m/" in call for call in calls)

assert not pricing_found, "Pricing should not be in output when not available"

def test_print_matching_models_partial_pricing(self):

"""Test that print_matching_models displays only available pricing info."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock model_info_manager to return only input pricing

with patch("cecli.models.model_info_manager") as mock_manager:

mock_manager.get_model_info.return_value = {

"input_cost_per_token": 0.000002, # $2 per 1M tokens

# No output or cache pricing

}

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "gpt-3.5")

# Check that only input pricing was included

calls = [str(call) for call in mock_tool_output.call_args_list]

input_found = any("$2.00/1m/input" in call for call in calls)

output_found = any("/1m/output" in call for call in calls)

assert input_found, "Input pricing not found in output"

assert not output_found, "Output pricing should not be in output when not available"

def test_print_matching_models_no_matches(self):

"""Test that print_matching_models handles no matches correctly."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock fuzzy_match_models to return no matches

with patch("cecli.models.fuzzy_match_models") as mock_fuzzy:

mock_fuzzy.return_value = []

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "nonexistent-model")

# Check that the no matches message was printed

mock_tool_output.assert_called_once_with('No models match "nonexistent-model".')

def test_print_matching_models_price_formatting(self):

"""Test that pricing is formatted correctly with 2 decimal places."""

from cecli.io import InputOutput

from cecli.models import print_matching_models

# Mock fuzzy_match_models to return a test model

with patch("cecli.models.fuzzy_match_models") as mock_fuzzy:

mock_fuzzy.return_value = ["test-model"]

# Mock model_info_manager to return pricing with various values

with patch("cecli.models.model_info_manager") as mock_manager:

mock_manager.get_model_info.return_value = {

"input_cost_per_token": 0.0000025, # $2.50 per 1M tokens

"output_cost_per_token": 0.0000105, # $10.50 per 1M tokens

}

io = InputOutput(pretty=False, fancy_input=False, yes=True)

with patch.object(io, "tool_output") as mock_tool_output:

print_matching_models(io, "test-model")

# Check that pricing is formatted with 2 decimal places

calls = [str(call) for call in mock_tool_output.call_args_list]

input_found = any("$2.50/1m/input" in call for call in calls)

output_found = any("$10.50/1m/output" in call for call in calls)

assert input_found, "Input pricing format incorrect"

assert output_found, "Output pricing format incorrect"

@patch("cecli.models.litellm.acompletion")

async def test_tool_description_escaping(self, mock_acompletion):

"""

Test that tool descriptions with special characters are properly escaped.

"""

model = Model("gpt-4")

messages = [{"role": "user", "content": "Hello"}]

# A complex description with various special characters

complex_description = (

'This is a "test" description with `special` characters like \\, \n, and *.'

)

# Mock tool with the complex description

mock_tool = {

"type": "function",

"function": {

"name": "test_tool",

"description": complex_description,

"parameters": {

"type": "object",

"properties": {},

"required": [],

}

await model.send_completion(messages, functions=None, stream=False, tools=[mock_tool])

# Verify that acompletion was called

mock_acompletion.assert_called_once()

# Get the keyword arguments passed to acompletion

call_kwargs = mock_acompletion.call_args.kwargs

# Check that the 'tools' argument is present and correctly formatted

assert "tools" in call_kwargs

sent_tools = call_kwargs["tools"]

assert isinstance(sent_tools, list)

assert len(sent_tools) == 1

# Verify the description of the sent tool

sent_tool_function = sent_tools[0].get("function", {})

sent_description = sent_tool_function.get("description")

# The description should be a JSON-escaped string

# Expected: 'This is a \\"test\\" description with `special` characters like \\\\, \\n, and *.'

expected_escaped_description = (

'This is a \\"test\\" description with `special` characters like \\\\, \\n, and *.'

)

assert sent_description == expected_escaped_description

cecli/tests/basic/test_models.py at main · cecli-dev/cecli · GitHub

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