Software Engineering
12 learners
Document Processing and Retrieval with LangChain in Python
Unlock the power of document intelligence with LangChain in Python. This course will teach you how to efficiently process and retrieve information from documents. Learn to load, split, and embed documents, and master the art of similarity search to extract relevant insights. Build a robust foundation for document-driven applications with cutting-edge techniques.
LangChain
OpenAI
Python
See path
4 lessons
18 practices
2 hours
Badge for RAG Systems and Vector Databases,
RAG Systems and Vector Databases
Lessons and practices
Lesson 1: Loading and Splitting Documents with LangChain
Loading and Inspecting PDF Documents
Switching to Text File Loading
Experiment with Document Splitting Parameters
Exploring Different Text Splitters
Loading and Splitting PDF Documents
Lesson 2: Generating Document Embeddings with OpenAI
Creating Document Embeddings with OpenAI
Experiment with Embedding Parameters
Fix the Embedding Model Bug
Exploring Embedding Dimensions
Lesson 3: Retrieving Relevant Information with Similarity Search
Exploring Vector Store Details
Formulate a Query for the Similarity Search
Adjusting Document Retrieval Quantity
Similarity Search with FAISS
Lesson 4: Asking Questions with Retrieved Context and Templates
Creating a Chat Prompt Template
Combining Document Chunks for Context
Crafting a Prompt Template with Retrieved Context
Integrating Chat Model with Context
Guiding Model Responses with System Message
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