JSON

Let's look at how to load files with the .json extension using a loader.

• Author: leebeanbin

• Peer Review : syshin0116, Teddy Lee

• Proofread : JaeJun Shim

• This is a part of LangChain Open Tutorial

Overview

This tutorial demonstrates how to use LangChain's JSONLoader to load and process JSON files. We'll explore how to extract specific data from structured JSON files using jq-style queries.

Table of Contents

• Environment Set up

• JSON

• Overview

• Generate JSON Data

• JSONLoader

When you want to extract values under the content field within the message key of JSON data, you can easily do this using JSONLoader as shown below.

References

• https://python.langchain.com/docs/how_to/document_loader_json/

---

Environment Setup

Set up the environment. You may refer to Environment Setup for more details.

[Note]

• langchain-opentutorial is a package that provides a set of easy-to-use environment setup, useful functions and utilities for tutorials.

• You can check out the langchain-opentutorial for more details.

%%capture --no-stderr
%pip install langchain-opentutorial

# Install required packages
from langchain_opentutorial import package

package.install(
    [
        "langsmith",
        "langchain",
        "langchain_community",
        "langchain_openai"
    ],
    verbose=False,
    upgrade=False,
)

%pip install rq

Requirement already satisfied: rq in /Users/leejungbin/Library/Caches/pypoetry/virtualenvs/langchain-opentutorial-LGorndcz-py3.11/lib/python3.11/site-packages (2.1.0)

    Requirement already satisfied: click>=5 in /Users/leejungbin/Library/Caches/pypoetry/virtualenvs/langchain-opentutorial-LGorndcz-py3.11/lib/python3.11/site-packages (from rq) (8.1.8)

    Requirement already satisfied: redis>=3.5 in /Users/leejungbin/Library/Caches/pypoetry/virtualenvs/langchain-opentutorial-LGorndcz-py3.11/lib/python3.11/site-packages (from rq) (5.2.1)

    Note: you may need to restart the kernel to use updated packages.

# Set environment variables
from langchain_opentutorial import set_env

set_env(
    {
        "OPENAI_API_KEY": "",
        "LANGCHAIN_API_KEY": "",
        "LANGCHAIN_TRACING_V2": "true",
        "LANGCHAIN_ENDPOINT": "https://api.smith.langchain.com",
        "LANGCHAIN_PROJECT": "09-JSONLoader",
    }
)

You can alternatively set OPENAI_API_KEY in .env file and load it.

[Note] This is not necessary if you've already set OPENAI_API_KEY in previous steps.

# Load environment variables
# Reload any variables that need to be overwritten from the previous cell

from dotenv import load_dotenv

load_dotenv(override=True)

Generate JSON Data

---

If you want to generate JSON data, you can use the following code.

from langchain import PromptTemplate
from langchain_openai import ChatOpenAI
from pathlib import Path
from dotenv import load_dotenv
from pprint import pprint
import json
import os

# Load .env file
load_dotenv()

# Initialize ChatOpenAI
llm = ChatOpenAI(
    model="gpt-4o-mini",
    temperature=0.7,
    model_kwargs={"response_format": {"type": "json_object"}}
)

# Create prompt template
prompt = PromptTemplate(
    input_variables=[],
    template="""Generate a JSON array containing detailed personal information for 5 people. 
        Include various fields like name, age, contact details, address, personal preferences, and any other interesting information you think would be relevant."""
)

# Create and invoke runnable sequence using the new pipe syntax
response = (prompt | llm).invoke({})
generated_data = json.loads(response.content)

# Save to JSON file
current_dir = Path().absolute()
data_dir = current_dir / "data"
data_dir.mkdir(exist_ok=True)

file_path = data_dir / "people.json"
with open(file_path, "w", encoding="utf-8") as f:
    json.dump(generated_data, f, ensure_ascii=False, indent=2)

print("Generated and saved JSON data:")
pprint(generated_data)

Generated and saved JSON data:
    {'people': [{'address': {'city': 'Springfield',
                             'country': 'USA',
                             'state': 'IL',
                             'street': '123 Maple St',
                             'zip': '62701'},
                 'age': 28,
                 'contact_details': {'email': '[e-mail]',
                                     'phone': '[phone]'},
                 'interesting_information': {'pet': {'breed': 'Golden Retriever',
                                                     'name': 'Buddy',
                                                     'type': 'dog'},
                                             'travel_history': [{'country': 'Japan',
                                                                 'year': 2019},
                                                                {'country': 'Italy',
                                                                 'year': 2021}]},
                 'name': 'Alice Johnson',
                 'personal_preferences': {'favorite_food': 'sushi',
                                          'hobbies': ['reading',
                                                      'hiking',
                                                      'photography'],
                                          'music_genres': ['jazz',
                                                           'classical',
                                                           'indie']}},
                {'address': {'city': 'Denver',
                             'country': 'USA',
                             'state': 'CO',
                             'street': '456 Oak Ave',
                             'zip': '80202'},
                 'age': 34,
                 'contact_details': {'email': '[e-mail]',
                                     'phone': '[phone]'},
                 'interesting_information': {'pet': {'breed': 'Siamese',
                                                     'name': 'Whiskers',
                                                     'type': 'cat'},
                                             'volunteering': {'organization': 'Local '
                                                                              'Food '
                                                                              'Bank',
                                                              'years_active': 5}},
                 'name': 'Michael Smith',
                 'personal_preferences': {'favorite_food': 'pizza',
                                          'hobbies': ['cycling',
                                                      'cooking',
                                                      'gaming'],
                                          'music_genres': ['rock',
                                                           'pop',
                                                           'hip-hop']}},
                {'address': {'city': 'Austin',
                             'country': 'USA',
                             'state': 'TX',
                             'street': '789 Pine Rd',
                             'zip': '73301'},
                 'age': 22,
                 'contact_details': {'email': '[e-mail]',
                                     'phone': '[phone]'},
                 'interesting_information': {'pet': None,
                                             'study': {'graduation_year': 2024,
                                                       'major': 'Fine Arts',
                                                       'university': 'University '
                                                                     'of Texas'}},
                 'name': 'Emily Davis',
                 'personal_preferences': {'favorite_food': 'tacos',
                                          'hobbies': ['painting',
                                                      'traveling',
                                                      'yoga'],
                                          'music_genres': ['country',
                                                           'folk',
                                                           'dance']}},
                {'address': {'city': 'Seattle',
                             'country': 'USA',
                             'state': 'WA',
                             'street': '101 Birch Blvd',
                             'zip': '98101'},
                 'age': 45,
                 'contact_details': {'email': '[e-mail]',
                                     'phone': '[phone]'},
                 'interesting_information': {'career': {'job_title': 'Software '
                                                                     'Engineer',
                                                        'years_experience': 20},
                                             'pet': {'breed': 'Canary',
                                                     'name': 'Tweety',
                                                     'type': 'bird'}},
                 'name': 'David Brown',
                 'personal_preferences': {'favorite_food': 'steak',
                                          'hobbies': ['golf', 'reading', 'fishing'],
                                          'music_genres': ['blues',
                                                           'classic rock',
                                                           'jazz']}},
                {'address': {'city': 'Miami',
                             'country': 'USA',
                             'state': 'FL',
                             'street': '202 Cedar Ct',
                             'zip': '33101'},
                 'age': 39,
                 'contact_details': {'email': '[e-mail]',
                                     'phone': '[phone]'},
                 'interesting_information': {'pet': {'breed': 'Bulldog',
                                                     'name': 'Max',
                                                     'type': 'dog'},
                                             'travel_history': [{'country': 'Spain',
                                                                 'year': 2018},
                                                                {'country': 'Brazil',
                                                                 'year': 2020}]},
                 'name': 'Sophia Wilson',
                 'personal_preferences': {'favorite_food': 'paella',
                                          'hobbies': ['dancing',
                                                      'gardening',
                                                      'cooking'],
                                          'music_genres': ['latin',
                                                           'pop',
                                                           'salsa']}}]}

The case of loading JSON data is as follows when you want to load your own JSON data.

import json
from pathlib import Path
from pprint import pprint


file_path = "data/people.json"
data = json.loads(Path(file_path).read_text())

pprint(data)

{'people': [{'address': {'city': 'Springfield',
                             'country': 'USA',
                             'state': 'IL',
                             'street': '123 Maple St',
                             'zip': '62704'},
                 'age': 28,
                 'contact': {'email': '[e-mail]',
                             'phone': '[phone]',
                             'social_media': {'linkedin': 'linkedin.com/in/alicejohnson',
                                              'twitter': '@alice_j'}},
                 'interesting_fact': 'Alice has traveled to over 15 countries and '
                                     'speaks 3 languages.',
                 'name': {'first': 'Alice', 'last': 'Johnson'},
                 'personal_preferences': {'favorite_food': 'Italian',
                                          'hobbies': ['Reading',
                                                      'Hiking',
                                                      'Cooking'],
                                          'music_genre': 'Jazz',
                                          'travel_destinations': ['Japan',
                                                                  'Italy',
                                                                  'Canada']}},
                {'address': {'city': 'Metropolis',
                             'country': 'USA',
                             'state': 'NY',
                             'street': '456 Oak Ave',
                             'zip': '10001'},
                 'age': 34,
                 'contact': {'email': '[e-mail]',
                             'phone': '[phone]',
                             'social_media': {'linkedin': 'linkedin.com/in/bobsmith',
                                              'twitter': '@bobsmith34'}},
                 'interesting_fact': 'Bob is an avid gamer and has competed in '
                                     'several national tournaments.',
                 'name': {'first': 'Bob', 'last': 'Smith'},
                 'personal_preferences': {'favorite_food': 'Mexican',
                                          'hobbies': ['Photography',
                                                      'Cycling',
                                                      'Video Games'],
                                          'music_genre': 'Rock',
                                          'travel_destinations': ['Brazil',
                                                                  'Australia',
                                                                  'Germany']}},
                {'address': {'city': 'Gotham',
                             'country': 'USA',
                             'state': 'NJ',
                             'street': '789 Pine Rd',
                             'zip': '07001'},
                 'age': 45,
                 'contact': {'email': '[e-mail]',
                             'phone': '[phone]',
                             'social_media': {'linkedin': 'linkedin.com/in/charliedavis',
                                              'twitter': '@charliedavis45'}},
                 'interesting_fact': 'Charlie has a small farm where he raises '
                                     'chickens and grows organic vegetables.',
                 'name': {'first': 'Charlie', 'last': 'Davis'},
                 'personal_preferences': {'favorite_food': 'Barbecue',
                                          'hobbies': ['Gardening',
                                                      'Fishing',
                                                      'Woodworking'],
                                          'music_genre': 'Country',
                                          'travel_destinations': ['Canada',
                                                                  'New Zealand',
                                                                  'Norway']}},
                {'address': {'city': 'Star City',
                             'country': 'USA',
                             'state': 'CA',
                             'street': '234 Birch Blvd',
                             'zip': '90001'},
                 'age': 22,
                 'contact': {'email': '[e-mail]',
                             'phone': '[phone]',
                             'social_media': {'linkedin': 'linkedin.com/in/danalee',
                                              'twitter': '@danalee22'}},
                 'interesting_fact': 'Dana is a dance instructor and has won '
                                     'several local competitions.',
                 'name': {'first': 'Dana', 'last': 'Lee'},
                 'personal_preferences': {'favorite_food': 'Thai',
                                          'hobbies': ['Dancing',
                                                      'Sketching',
                                                      'Traveling'],
                                          'music_genre': 'Pop',
                                          'travel_destinations': ['Thailand',
                                                                  'France',
                                                                  'Spain']}},
                {'address': {'city': 'Central City',
                             'country': 'USA',
                             'state': 'TX',
                             'street': '345 Cedar St',
                             'zip': '75001'},
                 'age': 31,
                 'contact': {'email': '[e-mail]',
                             'phone': '[phone]',
                             'social_media': {'linkedin': 'linkedin.com/in/ethangarcia',
                                              'twitter': '@ethangarcia31'}},
                 'interesting_fact': 'Ethan runs a popular travel blog where he '
                                     'shares his adventures and culinary '
                                     'experiences.',
                 'name': {'first': 'Ethan', 'last': 'Garcia'},
                 'personal_preferences': {'favorite_food': 'Indian',
                                          'hobbies': ['Running',
                                                      'Travel Blogging',
                                                      'Cooking'],
                                          'music_genre': 'Hip-Hop',
                                          'travel_destinations': ['India',
                                                                  'Italy',
                                                                  'Mexico']}}]}

print(type(data))

JSONLoader

---

When you want to extract values under the content field within the message key of JSON data, you can easily do this using JSONLoader as shown below.

Basic Usage

This usage shows off how to execute load JSON and print what I get from

from langchain_community.document_loaders import JSONLoader

# Create JSONLoader
loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[]",  # Access each item in the people array
    text_content=False,
)

# Load documents
docs = loader.load()
pprint(docs)

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "age": 28, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "123 Maple St", "city": "Springfield", "state": "IL", "zip": "62701", "country": "USA"}, "personal_preferences": {"hobbies": ["reading", "hiking", "photography"], "favorite_food": "sushi", "music_genres": ["jazz", "classical", "indie"]}, "interesting_information": {"pet": {"type": "dog", "name": "Buddy", "breed": "Golden Retriever"}, "travel_history": [{"country": "Japan", "year": 2019}, {"country": "Italy", "year": 2021}]}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "age": 34, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "456 Oak Ave", "city": "Denver", "state": "CO", "zip": "80202", "country": "USA"}, "personal_preferences": {"hobbies": ["cycling", "cooking", "gaming"], "favorite_food": "pizza", "music_genres": ["rock", "pop", "hip-hop"]}, "interesting_information": {"pet": {"type": "cat", "name": "Whiskers", "breed": "Siamese"}, "volunteering": {"organization": "Local Food Bank", "years_active": 5}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "age": 22, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "789 Pine Rd", "city": "Austin", "state": "TX", "zip": "73301", "country": "USA"}, "personal_preferences": {"hobbies": ["painting", "traveling", "yoga"], "favorite_food": "tacos", "music_genres": ["country", "folk", "dance"]}, "interesting_information": {"pet": null, "study": {"major": "Fine Arts", "university": "University of Texas", "graduation_year": 2024}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "age": 45, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "101 Birch Blvd", "city": "Seattle", "state": "WA", "zip": "98101", "country": "USA"}, "personal_preferences": {"hobbies": ["golf", "reading", "fishing"], "favorite_food": "steak", "music_genres": ["blues", "classic rock", "jazz"]}, "interesting_information": {"pet": {"type": "bird", "name": "Tweety", "breed": "Canary"}, "career": {"job_title": "Software Engineer", "years_experience": 20}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "age": 39, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "202 Cedar Ct", "city": "Miami", "state": "FL", "zip": "33101", "country": "USA"}, "personal_preferences": {"hobbies": ["dancing", "gardening", "cooking"], "favorite_food": "paella", "music_genres": ["latin", "pop", "salsa"]}, "interesting_information": {"pet": {"type": "dog", "name": "Max", "breed": "Bulldog"}, "travel_history": [{"country": "Spain", "year": 2018}, {"country": "Brazil", "year": 2020}]}}')]

Loading Each Person as a Separate Document

We can load each person object from people.json as an individual document using the jq_schema=".people[]"

loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[]",
    text_content=False,
)

data = loader.load()
data

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "age": 28, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "123 Maple St", "city": "Springfield", "state": "IL", "zip": "62701", "country": "USA"}, "personal_preferences": {"hobbies": ["reading", "hiking", "photography"], "favorite_food": "sushi", "music_genres": ["jazz", "classical", "indie"]}, "interesting_information": {"pet": {"type": "dog", "name": "Buddy", "breed": "Golden Retriever"}, "travel_history": [{"country": "Japan", "year": 2019}, {"country": "Italy", "year": 2021}]}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "age": 34, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "456 Oak Ave", "city": "Denver", "state": "CO", "zip": "80202", "country": "USA"}, "personal_preferences": {"hobbies": ["cycling", "cooking", "gaming"], "favorite_food": "pizza", "music_genres": ["rock", "pop", "hip-hop"]}, "interesting_information": {"pet": {"type": "cat", "name": "Whiskers", "breed": "Siamese"}, "volunteering": {"organization": "Local Food Bank", "years_active": 5}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "age": 22, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "789 Pine Rd", "city": "Austin", "state": "TX", "zip": "73301", "country": "USA"}, "personal_preferences": {"hobbies": ["painting", "traveling", "yoga"], "favorite_food": "tacos", "music_genres": ["country", "folk", "dance"]}, "interesting_information": {"pet": null, "study": {"major": "Fine Arts", "university": "University of Texas", "graduation_year": 2024}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "age": 45, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "101 Birch Blvd", "city": "Seattle", "state": "WA", "zip": "98101", "country": "USA"}, "personal_preferences": {"hobbies": ["golf", "reading", "fishing"], "favorite_food": "steak", "music_genres": ["blues", "classic rock", "jazz"]}, "interesting_information": {"pet": {"type": "bird", "name": "Tweety", "breed": "Canary"}, "career": {"job_title": "Software Engineer", "years_experience": 20}}}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "age": 39, "contact_details": {"email": "[e-mail]", "phone": "[phone]"}, "address": {"street": "202 Cedar Ct", "city": "Miami", "state": "FL", "zip": "33101", "country": "USA"}, "personal_preferences": {"hobbies": ["dancing", "gardening", "cooking"], "favorite_food": "paella", "music_genres": ["latin", "pop", "salsa"]}, "interesting_information": {"pet": {"type": "dog", "name": "Max", "breed": "Bulldog"}, "travel_history": [{"country": "Spain", "year": 2018}, {"country": "Brazil", "year": 2020}]}}')]

Using content_key within jq_schema

To load documents from a JSON file using content_key within the jq_schema, set is_content_key_jq_parsable=True. Ensure that content_key is compatible and can be parsed using the jq_schema.

loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[]",
    content_key="name",
    text_content=False
)

data = loader.load()
data

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='Alice Johnson'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='Michael Smith'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='Emily Davis'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='David Brown'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='Sophia Wilson')]

Extracting Metadata from people.json

Let's define a metadata_func to extract relevant information like name, age, and city from each person object.

def metadata_func(record: dict, metadata: dict) -> dict:
    metadata["name"] = record.get("name")
    metadata["age"] = record.get("age")
    metadata["city"] = record.get("address", {}).get("city")
    return metadata

loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[]",
    content_key="name",
    metadata_func=metadata_func,
    text_content=False
)

data = loader.load()
data

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1, 'name': 'Alice Johnson', 'age': 28, 'city': 'Springfield'}, page_content='Alice Johnson'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2, 'name': 'Michael Smith', 'age': 34, 'city': 'Denver'}, page_content='Michael Smith'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3, 'name': 'Emily Davis', 'age': 22, 'city': 'Austin'}, page_content='Emily Davis'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4, 'name': 'David Brown', 'age': 45, 'city': 'Seattle'}, page_content='David Brown'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5, 'name': 'Sophia Wilson', 'age': 39, 'city': 'Miami'}, page_content='Sophia Wilson')]

Understanding JSON Query Syntax

Let's explore the basic syntax of jq-style queries used in JSONLoader:

Basic Selectors

• . : Current object

• .key : Access specific key in object

• .[] : Iterate over array elements

Pipe Operator

• | : Pass result of left expression as input to right expression

Object Construction

• {key: value} : Create new object

Example JSON:

{
  "people": [
    {"name": "Alice", "age": 30, "contactDetails": {"email": "[e-mail]", "phone": "123-456-7890"}},
    {"name": "Bob", "age": 25, "contactDetails": {"email": "[e-mail]", "phone": "098-765-4321"}}
  ]
}

Common Query Patterns:

• .people[] : Access each array element

• .people[].name : Get all names

• .people[] | {name: .name} : Create new object with name

• .people[] | {name, email: .contact.email} : Extract nested data

[Note]

• Always use text_content=False when working with complex JSON data

• This ensures proper handling of non-string values (objects, arrays, numbers)

Advanced Queries

Here are examples of extracting specific information using different jq schemas:

# Extract only contact details
contact_loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[] | {name: .name, contact: .contactDetails}",
    text_content=False
)

docs = contact_loader.load()
docs

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "contact": null}')]

# Extract nested data
hobbies_loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[] | {name: .name, hobbies: .personalPreferences.hobbies}",
    text_content=False
)

docs = hobbies_loader.load()
docs

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "hobbies": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "hobbies": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "hobbies": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "hobbies": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "hobbies": null}')]

# Get all interesting facts
facts_loader = JSONLoader(
    file_path="data/people.json",
    jq_schema=".people[] | {name: .name, facts: .interestingFacts}",
    text_content=False
)

docs = facts_loader.load()
docs

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "facts": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "facts": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "facts": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "facts": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "facts": null}')]

# Extract email and phone together
contact_info = JSONLoader(
    file_path="data/people.json",
    jq_schema='.people[] | {name: .name, email: .contactDetails.email, phone: .contactDetails.phone}',
    text_content=False
)

docs = contact_loader.load()
docs

[Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 1}, page_content='{"name": "Alice Johnson", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "Michael Smith", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Davis", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "David Brown", "contact": null}'),
     Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sophia Wilson", "contact": null}')]

These examples demonstrate the flexibility of jq queries in fetching data in various ways.