tjdify/api/tests/integration_tests/model_runtime/cohere/test_llm.py

import os
from collections.abc import Generator

import pytest

from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.cohere.llm.llm import CohereLargeLanguageModel


def test_validate_credentials_for_chat_model():
    model = CohereLargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(model="command-light-chat", credentials={"api_key": "invalid_key"})

    model.validate_credentials(model="command-light-chat", credentials={"api_key": os.environ.get("COHERE_API_KEY")})


def test_validate_credentials_for_completion_model():
    model = CohereLargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(model="command-light", credentials={"api_key": "invalid_key"})

    model.validate_credentials(model="command-light", credentials={"api_key": os.environ.get("COHERE_API_KEY")})


def test_invoke_completion_model():
    model = CohereLargeLanguageModel()

    credentials = {"api_key": os.environ.get("COHERE_API_KEY")}

    result = model.invoke(
        model="command-light",
        credentials=credentials,
        prompt_messages=[UserPromptMessage(content="Hello World!")],
        model_parameters={"temperature": 0.0, "max_tokens": 1},
        stream=False,
        user="abc-123",
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0
    assert model._num_tokens_from_string("command-light", credentials, result.message.content) == 1


def test_invoke_stream_completion_model():
    model = CohereLargeLanguageModel()

    result = model.invoke(
        model="command-light",
        credentials={"api_key": os.environ.get("COHERE_API_KEY")},
        prompt_messages=[UserPromptMessage(content="Hello World!")],
        model_parameters={"temperature": 0.0, "max_tokens": 100},
        stream=True,
        user="abc-123",
    )

    assert isinstance(result, Generator)

    for chunk in result:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True


def test_invoke_chat_model():
    model = CohereLargeLanguageModel()

    result = model.invoke(
        model="command-light-chat",
        credentials={"api_key": os.environ.get("COHERE_API_KEY")},
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Hello World!"),
        ],
        model_parameters={
            "temperature": 0.0,
            "p": 0.99,
            "presence_penalty": 0.0,
            "frequency_penalty": 0.0,
            "max_tokens": 10,
        },
        stop=["How"],
        stream=False,
        user="abc-123",
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0


def test_invoke_stream_chat_model():
    model = CohereLargeLanguageModel()

    result = model.invoke(
        model="command-light-chat",
        credentials={"api_key": os.environ.get("COHERE_API_KEY")},
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Hello World!"),
        ],
        model_parameters={"temperature": 0.0, "max_tokens": 100},
        stream=True,
        user="abc-123",
    )

    assert isinstance(result, Generator)

    for chunk in result:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
        if chunk.delta.finish_reason is not None:
            assert chunk.delta.usage is not None
            assert chunk.delta.usage.completion_tokens > 0


def test_get_num_tokens():
    model = CohereLargeLanguageModel()

    num_tokens = model.get_num_tokens(
        model="command-light",
        credentials={"api_key": os.environ.get("COHERE_API_KEY")},
        prompt_messages=[UserPromptMessage(content="Hello World!")],
    )

    assert num_tokens == 3

    num_tokens = model.get_num_tokens(
        model="command-light-chat",
        credentials={"api_key": os.environ.get("COHERE_API_KEY")},
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Hello World!"),
        ],
    )

    assert num_tokens == 15


def test_fine_tuned_model():
    model = CohereLargeLanguageModel()

    # test invoke
    result = model.invoke(
        model="85ec47be-6139-4f75-a4be-0f0ec1ef115c-ft",
        credentials={"api_key": os.environ.get("COHERE_API_KEY"), "mode": "completion"},
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Hello World!"),
        ],
        model_parameters={"temperature": 0.0, "max_tokens": 100},
        stream=False,
        user="abc-123",
    )

    assert isinstance(result, LLMResult)


def test_fine_tuned_chat_model():
    model = CohereLargeLanguageModel()

    # test invoke
    result = model.invoke(
        model="94f2d55a-4c79-4c00-bde4-23962e74b170-ft",
        credentials={"api_key": os.environ.get("COHERE_API_KEY"), "mode": "chat"},
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Hello World!"),
        ],
        model_parameters={"temperature": 0.0, "max_tokens": 100},
        stream=False,
        user="abc-123",
    )

    assert isinstance(result, LLMResult)