自述文件
Nexus Raven 是一款为函数调用任务设计的 130 亿参数模型。
更新至 NexusRaven-V2，此模型是一个更新的开源且可商用的函数调用模型。
- 多功能函数调用能力：能够在许多具有挑战性的情况下生成单个函数调用、嵌套调用和并行调用。
- 完全可解释：能够为其生成的函数调用生成非常详细的解释。此行为可以关闭，以在推理过程中节省代币。
- 性能亮点：在涉及嵌套和复合函数的人工生成用例中，函数调用成功率比 GPT-4 高出 7%。
- 对未见过的函数的泛化：从未在评估中使用的函数上进行过训练。
- 商业许可：训练不涉及 GPT-4 等专有 LLM 生成的任何数据。在商业应用中部署模型时，您拥有对模型的完全控制权。
示例提示
Function:
def get_weather_data(coordinates):
"""
Fetches weather data from the Open-Meteo API for the given latitude and longitude.
Args:
coordinates (tuple): The latitude of the location.
Returns:
float: The current temperature in the coordinates you've asked for
"""
Function:
def get_coordinates_from_city(city_name):
"""
Fetches the latitude and longitude of a given city name using the Maps.co Geocoding API.
Args:
city_name (str): The name of the city.
Returns:
tuple: The latitude and longitude of the city.
"""
User Query: {query}<human_end>
这将生成类似于以下的响应
Call: get_weather_data(coordinates=get_coordinates_from_city(city_name='Seattle'))<bot_end>
Thought: The function call `get_weather_data(coordinates=get_coordinates_from_city(city_name='Seattle'))` answers the question "What's the weather like in Seattle right now?" by following these steps:
1. `get_coordinates_from_city(city_name='Seattle')`: This function call fetches the latitude and longitude of the city "Seattle" using the Maps.co Geocoding API.
2. `get_weather_data(coordinates=...)`: This function call fetches the current weather data for the coordinates returned by the previous function call.
Therefore, the function call `get_weather_data(coordinates=get_coordinates_from_city(city_name='Seattle'))` answers the question "What's the weather like in Seattle right now?" by first fetching the coordinates of the city "Seattle" and then fetching the current weather data for those coordinates.