json_helpers.py

import re
import json
from pydantic import BaseModel, ValidationError
from typing import get_type_hints



def model_to_json(model_instance):
    """
    Converts a Pydantic model instance to a JSON string.

    Args:
        model_instance (YourModel): An instance of your Pydantic model.

    Returns:
        str: A JSON string representation of the model.
    """
    return model_instance.model_dump_json()


def extract_json(text_response):
    pattern = r'\{.*?\}'
    matches = re.finditer(pattern, text_response, re.DOTALL)
    json_objects = []

    for match in matches:
        json_str = extend_search_new(text_response, match.span())
        try:
            json_obj = json.loads(json_str)
            json_objects.append(json_obj)
        except json.JSONDecodeError:
            continue

    return json_objects if json_objects else None

def extend_search_new(text, span):
    start, end = span
    nest_count = 1  # Starts with 1 since we know '{' is at the start position
    for i in range(end, len(text)):
        if text[i] == '{':
            nest_count += 1
        elif text[i] == '}':
            nest_count -= 1
            if nest_count == 0:
                return text[start:i+1]
    return text[start:end] 


def extract_json_old(text_response):
    # This pattern matches a string that starts with '{' and ends with '}'
    pattern = r'\{[^{}]*\}'

    matches = re.finditer(pattern, text_response)
    json_objects = []

    for match in matches:
        json_str = match.group(0)
        try:
            # Validate if the extracted string is valid JSON
            json_obj = json.loads(json_str)
            json_objects.append(json_obj)
        except json.JSONDecodeError:
            # Extend the search for nested structures
            extended_json_str = extend_search(text_response, match.span())
            try:
                json_obj = json.loads(extended_json_str)
                json_objects.append(json_obj)
            except json.JSONDecodeError:
                # Handle cases where the extraction is not valid JSON
                continue

    if json_objects:
        return json_objects
    else:
        return None  # Or handle this case as you prefer

def extend_search(text, span):
    # Extend the search to try to capture nested structures
    start, end = span
    nest_count = 0
    for i in range(start, len(text)):
        if text[i] == '{':
            nest_count += 1
        elif text[i] == '}':
            nest_count -= 1
            if nest_count == 0:
                return text[start:i+1]
    return text[start:end]

def json_to_pydantic(model_class, json_data):
    try:
        model_instance = model_class(**json_data)
        return model_instance
    except ValidationError as e:
        print("Validation error:", e)
        return None

def validate_json_with_model(model_class, json_data):
    """
    Validates JSON data against a specified Pydantic model.

    Args:
        model_class (BaseModel): The Pydantic model class to validate against.
        json_data (dict or list): JSON data to validate. Can be a dict for a single JSON object, 
                                  or a list for multiple JSON objects.

    Returns:
        list: A list of validated JSON objects that match the Pydantic model.
        list: A list of errors for JSON objects that do not match the model.
    """
    validated_data = []
    validation_errors = []

    if isinstance(json_data, list):
        for item in json_data:
            try:
                model_instance = model_class(**item)
                validated_data.append(model_instance.dict())
            except ValidationError as e:
                validation_errors.append({"error": str(e), "data": item})
    elif isinstance(json_data, dict):
        try:
            model_instance = model_class(**json_data)
            validated_data.append(model_instance.dict())
        except ValidationError as e:
            validation_errors.append({"error": str(e), "data": json_data})
    else:
        raise ValueError("Invalid JSON data type. Expected dict or list.")

    return validated_data, validation_errors



# Example usage
# text_response = "Some text with JSON {\"key\": \"value\", \"nested\": {\"key2\": \"value2\"}} embedded in it."
# extracted_json = extract_json(text_response)
# print(extracted_json)