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LangChain

User input + base prompt = Prompt Template

Chain

Achieve a specific task by linking multiple components together.

Chains allow us to combine multiple components together to create a single, coherent application. For example, we can create a chain that takes user input, formats it with a PromptTemplate, and then passes the formatted response to an LLM. We can build more complex chains by combining multiple chains together, or by combining chains with other components.

Embedding Path (or Indexing)

  1. Document loaders - extract text from the source documents
  2. Text splitters - split long pieces of text into chunks
  3. Embedding models - convert text to numbers, such that similar meaning texts are closer in numbers to each other
  4. Vector stores - numbers are stored in a database called Vector Database

Retrieval Process

Prompt Retrieval Process

Prompt Retrieval Architecture

FlowiseAI