DarkStar Python SDK
Most of AI and data sciences are written in python. We bring the best core technologies into the DarkStar AI Agents Python SDK.
Core Technology
The DarkStar SDK is the core library that integrates core open source technology to utilize the best python library resources. Open source that has been tested and well integrated reduces significant licensing cost. We bridge together technology that are not natively connected which our SDK does seemlessly. This allows the best from different technology to produce the best framework possible. Then we optimize it and make cloud native.
LangChain
LangChain is a Python framework for building applications with Large Language Models (LLMs). It offers modular components for chaining LLM calls, managing memory, integrating tools (e.g., APIs, databases), and enabling agents that make decisions based on user input and context. It's widely used for building chatbots, RAG (retrieval-augmented generation) systems, and workflow automation with LLMs.
CrewAI
CrewAI is an open-source framework that enables the creation of autonomous AI “crews” composed of specialized agents. Each agent has roles, goals, and tools, and they collaborate to complete workflows or tasks with minimal human intervention. It’s ideal for use cases like report generation, customer support, and business process automation, offering high customizability and efficient task division.
Autogen
Microsoft AutoGen is a framework for creating multi-agent systems powered by LLMs. It enables the design of collaborative AI agents that can autonomously plan, communicate, and execute complex tasks (e.g., coding, research, analysis) through structured conversations. It simplifies agent orchestration and allows integration with tools and human-in-the-loop workflows.
Llama Index
LlamaIndex is a data framework that connects LLMs to external data sources (like PDFs, SQL, Notion, and more). It provides tools for indexing, querying, and retrieving information efficiently using LLMs, making it a go-to choice for building RAG pipelines where context from private or structured data needs to be incorporated into model outputs.
Tools
The tools and databases used in our tech stack support our Agentic System. Here is a list of some of those tools and databases.
Weaviate
An open-source vector database that supports hybrid search (vector + keyword) and integrates easily with ML models via RESTful and GraphQL APIs. It’s designed for scalable semantic search and knowledge-based applications.
Neo4J
A graph database optimized for storing and querying complex relationships using the Cypher query language, ideal for recommendation systems, fraud detection, and network analysis.
React
React is a popular open-source JavaScript library developed by Meta for building interactive user interfaces, especially single-page applications. It uses a component-based architecture and a virtual DOM to efficiently update and render UI elements in response to data changes.
FastAPI
A modern, high-performance web framework for building APIs with Python, based on Pydantic and Starlette, known for its speed, type hints, and automatic documentation via Swagger/OpenAPI.
Pytorch
An open-source deep learning framework developed by Meta, favored for its dynamic computation graph and Pythonic design, widely used in research and production.
Tensor Flow
A powerful machine learning framework developed by Google, offering scalable tools for training and deploying deep learning models across platforms, with strong support for production and mobile inference.
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