If you are finding it tricky to write programs using ChatGPT due to its September 2021 cut-off date. You might be interested in these new tutorials created by developers Greg Kamradt (Data Indy) Shweta Lodha. Lodha combines OpenAI’s ChatGPT model with Langchain to build a search engine that can be used to answer questions about current events using any search queries that might take your interest. While Kamradt provides a great introduction to Langchain and how you can start using it to connect services.
If you are not familiar with LangChain it is a framework for developing applications powered by language models. The LangChain framework is designed around these principles : Data-aware: connect a language model to other sources of data and Agentic: allow a language model to interact with its environment.
What is Langchain
LangChain is a comprehensive framework designed for developing applications that are powered by language models. The LangChain framework is structured around several core modules, each serving as a building block for any language model-powered application. These modules include Models, Prompts, Memory, Indexes, Chains, Agents, and Callbacks. Each module comes with standard, extendable interfaces, and LangChain provides external integrations and end-to-end implementations for immediate use.
LangChain is versatile and can be used in a variety of use cases. Some of the common use cases include Autonomous Agents, Agent Simulations, Personal Assistants, Question Answering, Chatbots, Querying Tabular Data, Code Understanding, Interacting with APIs, Extraction, Summarization, and Evaluation.
Other articles you may find of interest on the subject of ChatGPT:
- What is Chat GPT?
- OpenAI Playgrounds vs ChatGPT what are the differences
- AI alternatives to ChatGPT
- How to use DALL·E the Chat GPT image creator
- How to use ChatGPT API to write programs
- Chat GPT detectors and how to bypass them
- ChatGPT plugins what can they do?
How to use Langchain
The Langchain framework integrates with a wide range of language models, systems, and products. It offers full documentation on all methods, classes, installation methods, and integration setups, making it a robust tool for developers looking to leverage the power of language models in their applications.
To learn more about using Langchain and Python to carry out searches referencing current events jump over to the Quickstart guide for LangChain on its.
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