09-JSONLoader
Last updated
Last updated
Let's look at how to load files with the .json extension using a loader.
Author: leebeanbin
Design:
Peer Review : syshin0116, Teddy Lee
This is a part of LangChain Open Tutorial
Setting up your environment is the first step. See the Environment Setup guide for more details.
[Note]
The langchain-opentutorial is a bundle of easy-to-use environment setup guidance, useful functions and utilities for tutorials.
Check out the langchain-opentutorial for more details.
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.
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.
https://python.langchain.com/docs/how_to/document_loader_json/
You can set and load OPENAI_API_KEY from a .env file when you'd like to make new json file.
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Note: you may need to restart the kernel to use updated packages.if you want to generate JSON data, you can use the following code.
from langchain.prompts 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': '62704'},
'age': 28,
'contact': {'email': 'alice.johnson@example.com',
'phone': '+1-555-0123',
'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': 'bob.smith@example.com',
'phone': '+1-555-0456',
'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': 'charlie.davis@example.com',
'phone': '+1-555-0789',
'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': 'dana.lee@example.com',
'phone': '+1-555-0111',
'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': 'ethan.garcia@example.com',
'phone': '+1-555-0999',
'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']}}]}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': 'alice.johnson@example.com',
'phone': '+1-555-0123',
'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': 'bob.smith@example.com',
'phone': '+1-555-0456',
'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': 'charlie.davis@example.com',
'phone': '+1-555-0789',
'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': 'dana.lee@example.com',
'phone': '+1-555-0111',
'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': 'ethan.garcia@example.com',
'phone': '+1-555-0999',
'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))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.
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,
)
# Example: extract only contact_details
# loader = JSONLoader(
# file_path="data/people.json",
# jq_schema=".people[].contact_details",
# text_content=False,
# )
# Or extract only hobbies from personal_preferences
# loader = JSONLoader(
# file_path="data/people.json",
# jq_schema=".people[].personal_preferences.hobbies",
# 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 Smith", "age": 32, "contact": {"email": "alice.smith@example.com", "phone": "555-123-4567"}, "address": {"street": "123 Main St", "city": "New York", "state": "NY", "zip": "10001"}, "personal_preferences": {"favorite_color": "blue", "hobbies": ["reading", "yoga"], "favorite_food": "sushi"}}'),
Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 2}, page_content='{"name": "John Doe", "age": 45, "contact": {"email": "john.doe@example.com", "phone": "555-987-6543"}, "address": {"street": "456 Elm St", "city": "Los Angeles", "state": "CA", "zip": "90001"}, "personal_preferences": {"favorite_color": "green", "hobbies": ["hiking", "gardening"], "favorite_food": "pizza"}}'),
Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 3}, page_content='{"name": "Emily Johnson", "age": 28, "contact": {"email": "emily.johnson@example.com", "phone": "555-456-7890"}, "address": {"street": "789 Oak St", "city": "Chicago", "state": "IL", "zip": "60601"}, "personal_preferences": {"favorite_color": "pink", "hobbies": ["painting", "traveling"], "favorite_food": "tacos"}}'),
Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 4}, page_content='{"name": "Michael Brown", "age": 38, "contact": {"email": "michael.brown@example.com", "phone": "555-234-5678"}, "address": {"street": "321 Maple St", "city": "Houston", "state": "TX", "zip": "77001"}, "personal_preferences": {"favorite_color": "red", "hobbies": ["playing guitar", "cooking"], "favorite_food": "barbecue"}}'),
Document(metadata={'source': '/Users/leejungbin/Downloads/LangChain-OpenTutorial/06-DocumentLoader/data/people.json', 'seq_num': 5}, page_content='{"name": "Sarah Wilson", "age": 35, "contact": {"email": "sarah.wilson@example.com", "phone": "555-345-6789"}, "address": {"street": "654 Pine St", "city": "Miami", "state": "FL", "zip": "33101"}, "personal_preferences": {"favorite_color": "purple", "hobbies": ["photography", "dancing"], "favorite_food": "sushi"}}')]