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| """ | |
| https://github.com/langchain-ai/langchain/blob/master/docs/extras/modules/model_io/output_parsers/pydantic.ipynb | |
| Example 1. | |
| # Define your desired data structure. | |
| class Joke(BaseModel): | |
| setup: str = Field(description="question to set up a joke") | |
| punchline: str = Field(description="answer to resolve the joke") | |
| # You can add custom validation logic easily with Pydantic. | |
| @validator("setup") | |
| def question_ends_with_question_mark(cls, field): | |
| if field[-1] != "?": | |
| raise ValueError("Badly formed question!") | |
| return field | |
| Example 2. | |
| # Here's another example, but with a compound typed field. | |
| class Actor(BaseModel): | |
| name: str = Field(description="name of an actor") | |
| film_names: List[str] = Field(description="list of names of films they starred in") | |
| """ | |
| import json, re, logging | |
| PYDANTIC_FORMAT_INSTRUCTIONS = """The output should be formatted as a JSON instance that conforms to the JSON schema below. | |
| As an example, for the schema {{"properties": {{"foo": {{"title": "Foo", "description": "a list of strings", "type": "array", "items": {{"type": "string"}}}}}}, "required": ["foo"]}} | |
| the object {{"foo": ["bar", "baz"]}} is a well-formatted instance of the schema. The object {{"properties": {{"foo": ["bar", "baz"]}}}} is not well-formatted. | |
| Here is the output schema: | |
| ``` | |
| {schema} | |
| ```""" | |
| PYDANTIC_FORMAT_INSTRUCTIONS_SIMPLE = """The output should be formatted as a JSON instance that conforms to the JSON schema below. | |
| ``` | |
| {schema} | |
| ```""" | |
| class JsonStringError(Exception): ... | |
| class GptJsonIO(): | |
| def __init__(self, schema, example_instruction=True): | |
| self.pydantic_object = schema | |
| self.example_instruction = example_instruction | |
| self.format_instructions = self.generate_format_instructions() | |
| def generate_format_instructions(self): | |
| schema = self.pydantic_object.schema() | |
| # Remove extraneous fields. | |
| reduced_schema = schema | |
| if "title" in reduced_schema: | |
| del reduced_schema["title"] | |
| if "type" in reduced_schema: | |
| del reduced_schema["type"] | |
| # Ensure json in context is well-formed with double quotes. | |
| schema_str = json.dumps(reduced_schema) | |
| if self.example_instruction: | |
| return PYDANTIC_FORMAT_INSTRUCTIONS.format(schema=schema_str) | |
| else: | |
| return PYDANTIC_FORMAT_INSTRUCTIONS_SIMPLE.format(schema=schema_str) | |
| def generate_output(self, text): | |
| # Greedy search for 1st json candidate. | |
| match = re.search( | |
| r"\{.*\}", text.strip(), re.MULTILINE | re.IGNORECASE | re.DOTALL | |
| ) | |
| json_str = "" | |
| if match: json_str = match.group() | |
| json_object = json.loads(json_str, strict=False) | |
| final_object = self.pydantic_object.parse_obj(json_object) | |
| return final_object | |
| def generate_repair_prompt(self, broken_json, error): | |
| prompt = "Fix a broken json string.\n\n" + \ | |
| "(1) The broken json string need to fix is: \n\n" + \ | |
| "```" + "\n" + \ | |
| broken_json + "\n" + \ | |
| "```" + "\n\n" + \ | |
| "(2) The error message is: \n\n" + \ | |
| error + "\n\n" + \ | |
| "Now, fix this json string. \n\n" | |
| return prompt | |
| def generate_output_auto_repair(self, response, gpt_gen_fn): | |
| """ | |
| response: string containing canidate json | |
| gpt_gen_fn: gpt_gen_fn(inputs, sys_prompt) | |
| """ | |
| try: | |
| result = self.generate_output(response) | |
| except Exception as e: | |
| try: | |
| logging.info(f'Repairing json：{response}') | |
| repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e)) | |
| result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions)) | |
| logging.info('Repaire json success.') | |
| except Exception as e: | |
| # 没辙了，放弃治疗 | |
| logging.info('Repaire json fail.') | |
| raise JsonStringError('Cannot repair json.', str(e)) | |
| return result | |