ChatGPT plugin
OpenAI plugins connect
ChatGPT
to third-party applications. These plugins enableChatGPT
to interact with APIs defined by developers, enhancingChatGPT's
capabilities and allowing it to perform a wide range of actions.
Plugins allow
ChatGPT
to do things like:
- Retrieve real-time information; e.g., sports scores, stock prices, the latest news, etc.
- Retrieve knowledge-base information; e.g., company docs, personal notes, etc.
- Perform actions on behalf of the user; e.g., booking a flight, ordering food, etc.
This notebook shows how to use the ChatGPT Retriever Plugin within LangChain.
# STEP 1: Load
# Load documents using LangChain's DocumentLoaders
# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html
from langchain_community.document_loaders import CSVLoader
loader = CSVLoader(
file_path="../../document_loaders/examples/example_data/mlb_teams_2012.csv"
)
data = loader.load()
# STEP 2: Convert
# Convert Document to format expected by https://github.com/openai/chatgpt-retrieval-plugin
import json
from typing import List
from langchain_community.docstore.document import Document
def write_json(path: str, documents: List[Document]) -> None:
results = [{"text": doc.page_content} for doc in documents]
with open(path, "w") as f:
json.dump(results, f, indent=2)
write_json("foo.json", data)
# STEP 3: Use
# Ingest this as you would any other json file in https://github.com/openai/chatgpt-retrieval-plugin/tree/main/scripts/process_json
Using the ChatGPT Retriever Pluginโ
Okay, so we've created the ChatGPT Retriever Plugin, but how do we actually use it?
The below code walks through how to do that.
We want to use ChatGPTPluginRetriever
so we have to get the OpenAI API Key.
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
OpenAI API Key: ยทยทยทยทยทยทยทยท
from langchain_community.retrievers import (
ChatGPTPluginRetriever,
)
API Reference:
retriever = ChatGPTPluginRetriever(url="http://0.0.0.0:8000", bearer_token="foo")
retriever.invoke("alice's phone number")
[Document(page_content="This is Alice's phone number: 123-456-7890", lookup_str='', metadata={'id': '456_0', 'metadata': {'source': 'email', 'source_id': '567', 'url': None, 'created_at': '1609592400.0', 'author': 'Alice', 'document_id': '456'}, 'embedding': None, 'score': 0.925571561}, lookup_index=0),
Document(page_content='This is a document about something', lookup_str='', metadata={'id': '123_0', 'metadata': {'source': 'file', 'source_id': 'https://example.com/doc1', 'url': 'https://example.com/doc1', 'created_at': '1609502400.0', 'author': 'Alice', 'document_id': '123'}, 'embedding': None, 'score': 0.6987589}, lookup_index=0),
Document(page_content='Team: Angels "Payroll (millions)": 154.49 "Wins": 89', lookup_str='', metadata={'id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631_0', 'metadata': {'source': None, 'source_id': None, 'url': None, 'created_at': None, 'author': None, 'document_id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631'}, 'embedding': None, 'score': 0.697888613}, lookup_index=0)]