langchain/libs/partners/together/tests/unit_tests/test_chat_models.py
Hassan El Mghari d6ef5fe86a
together: add chat models, use openai base (#21337)
**Description:** Adding chat completions to the Together AI package,
which is our most popular API. Also staying backwards compatible with
the old API so folks can continue to use the completions API as well.
Also moved the embedding API to use the OpenAI library to standardize it
further.

**Twitter handle:** @nutlope

- [x] **Add tests and docs**: If you're adding a new integration, please
include
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-05-06 17:47:06 -07:00

193 lines
5.6 KiB
Python

import json
from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from langchain_core.messages import (
AIMessage,
FunctionMessage,
HumanMessage,
SystemMessage,
ToolMessage,
)
from langchain_openai.chat_models.base import (
_convert_dict_to_message,
_convert_message_to_dict,
)
from langchain_together import ChatTogether
def test_initialization() -> None:
"""Test chat model initialization."""
ChatTogether()
def test_together_model_param() -> None:
llm = ChatTogether(model="foo")
assert llm.model_name == "foo"
llm = ChatTogether(model_name="foo")
assert llm.model_name == "foo"
def test_function_dict_to_message_function_message() -> None:
content = json.dumps({"result": "Example #1"})
name = "test_function"
result = _convert_dict_to_message(
{
"role": "function",
"name": name,
"content": content,
}
)
assert isinstance(result, FunctionMessage)
assert result.name == name
assert result.content == content
def test_convert_dict_to_message_human() -> None:
message = {"role": "user", "content": "foo"}
result = _convert_dict_to_message(message)
expected_output = HumanMessage(content="foo")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test__convert_dict_to_message_human_with_name() -> None:
message = {"role": "user", "content": "foo", "name": "test"}
result = _convert_dict_to_message(message)
expected_output = HumanMessage(content="foo", name="test")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test_convert_dict_to_message_ai() -> None:
message = {"role": "assistant", "content": "foo"}
result = _convert_dict_to_message(message)
expected_output = AIMessage(content="foo")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test_convert_dict_to_message_ai_with_name() -> None:
message = {"role": "assistant", "content": "foo", "name": "test"}
result = _convert_dict_to_message(message)
expected_output = AIMessage(content="foo", name="test")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test_convert_dict_to_message_system() -> None:
message = {"role": "system", "content": "foo"}
result = _convert_dict_to_message(message)
expected_output = SystemMessage(content="foo")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test_convert_dict_to_message_system_with_name() -> None:
message = {"role": "system", "content": "foo", "name": "test"}
result = _convert_dict_to_message(message)
expected_output = SystemMessage(content="foo", name="test")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
def test_convert_dict_to_message_tool() -> None:
message = {"role": "tool", "content": "foo", "tool_call_id": "bar"}
result = _convert_dict_to_message(message)
expected_output = ToolMessage(content="foo", tool_call_id="bar")
assert result == expected_output
assert _convert_message_to_dict(expected_output) == message
@pytest.fixture
def mock_completion() -> dict:
return {
"id": "chatcmpl-7fcZavknQda3SQ",
"object": "chat.completion",
"created": 1689989000,
"model": "meta-llama/Llama-3-8b-chat-hf",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Bab",
"name": "KimSolar",
},
"finish_reason": "stop",
}
],
}
def test_together_invoke(mock_completion: dict) -> None:
llm = ChatTogether()
mock_client = MagicMock()
completed = False
def mock_create(*args: Any, **kwargs: Any) -> Any:
nonlocal completed
completed = True
return mock_completion
mock_client.create = mock_create
with patch.object(
llm,
"client",
mock_client,
):
res = llm.invoke("bab")
assert res.content == "Bab"
assert completed
async def test_together_ainvoke(mock_completion: dict) -> None:
llm = ChatTogether()
mock_client = AsyncMock()
completed = False
async def mock_create(*args: Any, **kwargs: Any) -> Any:
nonlocal completed
completed = True
return mock_completion
mock_client.create = mock_create
with patch.object(
llm,
"async_client",
mock_client,
):
res = await llm.ainvoke("bab")
assert res.content == "Bab"
assert completed
def test_together_invoke_name(mock_completion: dict) -> None:
llm = ChatTogether()
mock_client = MagicMock()
mock_client.create.return_value = mock_completion
with patch.object(
llm,
"client",
mock_client,
):
messages = [
HumanMessage(content="Foo", name="Zorba"),
]
res = llm.invoke(messages)
call_args, call_kwargs = mock_client.create.call_args
assert len(call_args) == 0 # no positional args
call_messages = call_kwargs["messages"]
assert len(call_messages) == 1
assert call_messages[0]["role"] == "user"
assert call_messages[0]["content"] == "Foo"
assert call_messages[0]["name"] == "Zorba"
# check return type has name
assert res.content == "Bab"
assert res.name == "KimSolar"