APR_Orchestrator.md

graph LR
    Document_Ingestion["Document Ingestion"]
    Text_Splitter["Text Splitter"]
    Vector_Store["Vector Store"]
    Embeddings_Model["Embeddings Model"]
    Language_Model_LLM_["Language Model (LLM)"]
    Retrieval_Chain["Retrieval Chain"]
    Unclassified["Unclassified"]
    Document_Ingestion -- "loads documents into" --> Text_Splitter
    Text_Splitter -- "splits text for" --> Embeddings_Model
    Embeddings_Model -- "generates embeddings for" --> Vector_Store
    Vector_Store -- "stores embeddings from" --> Embeddings_Model
    Vector_Store -- "retrieves context for" --> Retrieval_Chain
    Retrieval_Chain -- "uses" --> Language_Model_LLM_
    Language_Model_LLM_ -- "answers queries using" --> Retrieval_Chain

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Details

This graph represents the core functionality of a document processing and question-answering system. The main flow involves ingesting documents, processing them into a searchable format, and then using a language model to answer user queries based on the ingested content. Its purpose is to provide an intelligent interface for users to retrieve information from a collection of documents.

Document Ingestion

Handles the loading and initial processing of various document types.

Related Classes/Methods:

• langchain_community.document_loaders.pdf.PyPDFLoader
• langchain_community.document_loaders.csv_loader.CSVLoader

Text Splitter

Breaks down large documents into smaller, manageable chunks for efficient processing and embedding.

Related Classes/Methods:

• langchain.text_splitter.RecursiveCharacterTextSplitter

Vector Store

Stores and retrieves document embeddings, enabling semantic search.

Related Classes/Methods:

• langchain_community.vectorstores.chroma.Chroma

Embeddings Model

Generates numerical representations (embeddings) of text chunks.

Related Classes/Methods:

• langchain_community.embeddings.ollama.OllamaEmbeddings

Language Model (LLM)

Processes user queries and generates answers based on retrieved context.

Related Classes/Methods:

• langchain_community.llms.ollama.Ollama

Retrieval Chain

Orchestrates the retrieval of relevant document chunks and passes them to the LLM for answer generation.

Related Classes/Methods:

• langchain.chains.retrieval.create_retrieval_chain

Unclassified

Component for all unclassified files and utility functions (Utility functions/External Libraries/Dependencies)

Related Classes/Methods: None

FAQ