Discover how to leverage OpenAI’s powerful embedding capabilities to transform your Salesforce data into insightful, actionable embeddings. This guide provides a step-by-step process, complet …
Here are highlights from article Talk to Salesforce Data Using OpenAI, Langchain & Chroma
1. Using Open AI embedding with Langchain and Chroma vector database:
– Demonstrates how to use Open AI embedding with Langchain and Chroma vector database.
– Langchain is used to enrich prompts based on the embedding data available in Chroma database.
– This approach helps in saving API costs from Open AI.
2. Retrieval-Augmented Generation (RAG) concept:
– RAG concept is utilized in this demo.
– RAG combines retrieval-based models with language generation models.
– OpenAI uses the enriched prompt to answer questions.
3. Steps involved in the demo:
– Data from Salesforce is retrieved and saved in a text file.
– The text file is then converted into embedding vectors using Open AI embedding.
– The embedding vectors are stored in the Chroma vector database.
– When prompted, Langchain is used to enrich the prompt based on the embedding data in Chroma database.
4. Benefits of using Chroma vector database:
– Using Chroma vector database helps in saving API costs from Open AI.
– The database stores the embedding vectors, allowing for easier retrieval and enrichment of prompts.
5. Source code and video tutorial:
– The source code for this demo is provided.
– A video tutorial is also available, explaining the process step-by-step.
You can read it here: https://sfdc.blog/QZkAO
Source from jitendrazaa(dot)com