mirror of
https://github.com/kennethreitz/instructor.git
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Jason Liu
112 lines
4.1 KiB
Python
112 lines
4.1 KiB
Python
# MIT License
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#
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# Copyright (c) 2023 Jason Liu
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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import json
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from functools import wraps
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from typing import Any, Callable
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from pydantic import validate_arguments, BaseModel
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def _remove_a_key(d, remove_key) -> None:
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"""Remove a key from a dictionary recursively"""
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if isinstance(d, dict):
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for key in list(d.keys()):
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if key == remove_key:
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del d[key]
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else:
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_remove_a_key(d[key], remove_key)
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class openai_function:
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def __init__(self, func: Callable) -> None:
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self.func = func
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self.validate_func = validate_arguments(func)
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parameters = self.validate_func.model.schema()
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parameters["properties"] = {
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k: v
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for k, v in parameters["properties"].items()
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if k not in ("v__duplicate_kwargs", "args", "kwargs")
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}
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parameters["required"] = sorted(
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parameters["properties"]
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) # bug workaround see lc
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_remove_a_key(parameters, "title")
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_remove_a_key(parameters, "additionalProperties")
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self.openai_schema = {
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"name": self.func.__name__,
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"description": self.func.__doc__,
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"parameters": parameters,
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}
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self.model = self.validate_func.model
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def __call__(self, *args: Any, **kwargs: Any) -> Any:
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@wraps(self.func)
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def wrapper(*args, **kwargs):
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return self.validate_func(*args, **kwargs)
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return wrapper(*args, **kwargs)
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def from_response(self, completion, throw_error=True):
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"""Execute the function from the response of an openai chat completion"""
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message = completion.choices[0].message
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if throw_error:
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assert "function_call" in message, "No function call detected"
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assert (
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message["function_call"]["name"] == self.openai_schema["name"]
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), "Function name does not match"
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function_call = message["function_call"]
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arguments = json.loads(function_call["arguments"])
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return self.validate_func(**arguments)
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class OpenAISchema(BaseModel):
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@classmethod
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@property
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def openai_schema(cls):
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schema = cls.schema()
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parameters = {
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k: v for k, v in schema.items() if k not in ("title", "description")
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}
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parameters["required"] = sorted(parameters["properties"])
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_remove_a_key(parameters, "title")
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return {
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"name": schema["title"],
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"description": schema["description"],
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"parameters": parameters,
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}
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@classmethod
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def from_response(cls, completion, throw_error=True):
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message = completion.choices[0].message
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if throw_error:
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assert "function_call" in message, "No function call detected"
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assert (
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message["function_call"]["name"] == cls.openai_schema["name"]
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), "Function name does not match"
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function_call = message["function_call"]
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arguments = json.loads(function_call["arguments"])
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return cls(**arguments)
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