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Created by
Sachin Gaikwad
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LangChain
An open-source framework for
creating
applications
using LLMs with ease.
Key components of LangChain
Schema
Models
Prompts
Indexes
Memory
Chains
Agents
Schema
Defines the data types within LangChain, including Text, ChatMessages, Examples, and Document.
Models
Interact with LLMs to generate vector embeddings, submit prompts, and open chat sessions.
Prompts
This feature enables the use of placeholders to parameterize common prompts with real-time data, thereby enhancing efficiency.
Indexes
This helps to find useful information from different data sources in order to enhance LLM responses.
Memory
This feature allows LLMs to retain the context of previous interactions and recall pertinent information in subsequent interactions.
Chains
:
Links together multiple LangChain components, automating the sequence of LLM calls and actions.
Agents can take
actions
and make
decisions
based on their environment using the Retrieval Augmented Generation (RAG) pattern.