AI Starter Kits

What Are AI Starter Kits?

Starter Kits Help You Build Fast – They bootstrap application development for common AI use cases with open-source Python code on SambaNova GitHub. They let you see how the code works and customize it to your needs, so you can prove the business value of AI.


How Do We Use Them?

We put AI to work for enterprise customers, developers, and ourselves, to speed up our work and learn the real-life capabilities of the technology, including building PoCs with customers, using a coding copilot that doesn’t leave the corporate network, and allowing enterprise knowledge to be retrieved in-context, like via Slack bots.


Featured Capabilities

Finance Assistant

Corporate financial performance analysis – Perform financial data analysis, combining function calling, web scraping, and retrieval-augmented generation (RAG) to query stock data, build SQL databases, scrape financial news, and analyze SEC filings, with options for generating PDF reports.
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(GitHub)

Enterprise Knowledge Retrieval

Document Q&A on PDF, TXT, DOC, and more – Bootstrap your document Q&A application with this sample implementation of a Retrieval Augmented Generation semantic search workflow using the SambaNova platform, built with Python and a Streamlit UI.
Screenshot 2024-08-20 at 9.30.40 AM

(Demo, GitHub)

Search Assistant

Include web search results in responses – Expand your application’s knowledge with this implementation of the semantic search workflow and prompt construction strategies, with configurable integrations with multiple SERP APIs.
(Demo, GitHub)

Function Calling

Integrate non-LLM capabilities – Easily enable business use cases by adding function calls into NLP applications that do more than understand text by querying databases, performing calculations, talking to other applications, searching the web, and more.
(GitHub)

Benchmarking

Compare model performance – Quickly determine which models meet your speed and quality needs by comparing model outputs, Time to First Token, End-to-End Latency, Throughput, Latency, and more with configuration options in a chat interface.
(Demo, GitHub)


Which Other Use Cases and Techniques are Covered?

Click an item below to view step-by-step instructions and download code.

Enterprise Use Cases

Recipes & Data Preparation


Let’s Get Building!

  • Getting Started – Complete the Getting Started tutorial on GitHub
  • Customize – Use AI Starter Kits to implement your own solution in your environment
  • Get Help – Let us help you build a solution to prove value; just post a message here!
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