Langchain-Chatchat/model-providers/model_providers/__main__.py

import os
from typing import Generator, cast

from model_providers.core.model_manager import ModelManager
from model_providers.core.model_runtime.entities.llm_entities import (
    LLMResultChunk,
    LLMResultChunkDelta,
)
from model_providers.core.model_runtime.entities.message_entities import (
    AssistantPromptMessage,
    UserPromptMessage,
)
from model_providers.core.model_runtime.entities.model_entities import ModelType

if __name__ == "__main__":
    # 基于配置管理器创建的模型实例
    provider_manager = ModelManager(
        provider_name_to_provider_records_dict={
            "openai": {
                "openai_api_key": "sk-4M9LYF",
            }
        },
        provider_name_to_provider_model_records_dict={},
    )

    #
    # Invoke model
    model_instance = provider_manager.get_model_instance(
        provider="openai", model_type=ModelType.LLM, model="gpt-4"
    )

    response = model_instance.invoke_llm(
        prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")],
        model_parameters={
            "temperature": 0.7,
            "top_p": 1.0,
            "top_k": 1,
            "plugin_web_search": True,
        },
        stop=["you"],
        stream=True,
        user="abc-123",
    )

    assert isinstance(response, Generator)
    total_message = ""
    for chunk in response:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        total_message += chunk.delta.message.content
        assert (
            len(chunk.delta.message.content) > 0
            if not chunk.delta.finish_reason
            else True
        )
    print(total_message)
    assert "参考资料" in total_message