This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use a LangChain "Chain" to orchestrate steps required to query a vector database and submit the results of the query to Gemini to obtain results based on a knowledge base. To do so, you embed a query submitted in a session in order to perform a nearest neighbor search on the vector store. Once results are retrieved, they are added as contextual information when querying a large language model (LLM), in this case, Gemini.
Enhance Text Generation with RAG, LangChain, and Vertex AI
Enhance Text Generation with RAG, LangChain, and Vertex AI
Taught in English
Instructor: Google Cloud Training
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Project
Build in-demand job skills with step-by-step instructions
Intermediate level
Some related experience required
90 minutes
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
What you'll learn
Leverage Gemini python SDK to generate content without LangChain. Prepare a private knowledge base using DocArray to index embeddings of documents
Generate embeddings with Gemini.Use Gemini's embedding-001 model to create representations of text as vector data.Create query-based retrieval system
Implement RAG with Gemini: Provide relevant context with a query submitted to a LLM, in this case, the gemini-pro model to enhance generated results
Skills you'll practice
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Recently updated!
May 2024
Project
Build in-demand job skills with step-by-step instructions
Intermediate level
Some related experience required
90 minutes
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
See how employees at top companies are mastering in-demand skills
Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
About this project
Instructor
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How you'll learn
Hands-on, project-based learning
Practice new skills by completing job-related tasks with step-by-step instructions.
No downloads or installation required
Access the tools and resources you need in a cloud environment.
Available only on desktop
This project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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