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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.
if self.example_instruction:
schema_str = json.dumps(reduced_schema)
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
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