Getting Started
Introduction to Prism
Prism is an innovative platform designed to simplify the integration of Retrieval Augmented Generation (RAG) capabilities into your applications. RAG combines the power of large language models with the ability to retrieve and incorporate information from knowledge sources seamlessly. It enhances the text generated by AI models, such as ChatGPT, Bard or Claude, by incorporating real-world knowledge.
RAG is a groundbreaking approach in the field of AI that allows developers to tap into the vast knowledge available in databases, websites, and files. By integrating this knowledge, developers can create AI systems that provide accurate and contextually relevant information. RAG is particularly valuable in tasks such as document search, question-answering, and chatbots, where understanding context and retrieving relevant information are crucial.
Vector embeddings, a key component of RAG systems, play a crucial role in capturing the semantic meaning of words and phrases. These embeddings transform text into high-dimensional numerical representations, enabling AI models to compare and identify similar information effectively. Vector embeddings have been instrumental in advancing RAG systems by providing a nuanced understanding of information and improving search capabilities.
Vector Embeddings are not Enough! Prism takes RAG to the next level by offering powerful Multidimensional Index Structures, Named Entity Recognition and subsequent Knowledge-Graph Retrieval, and more. Through Prism's intuitive API and libraries available in multiple languages, including Python and JavaScript, developers can quickly integrate RAG capabilities into their applications. Whether you are an expert or just getting started with language models, Prism's user-friendly platform simplifies the process of incorporating real-world knowledge into your AI applications.
API Use
We have designed Prism's API to be as simple as possible to use, with packages for Python and JavaScript/TypeScript.
You can purchase additional API credits at the Upgrade page.
Model Pricing (per 1k tokens)
| Model | Input Price | Output Price |
|---|---|---|
| Llama3 (Meta) | 13.5 | 13.5 |
| Mixtral-8x7B (Mistral) | 4.05 | 4.05 |
| Mistral Medium | 40.5 | 121.5 |
| Mistral Large | 120 | 360 |
| Claude 3 Haiku | 3.75 | 18.75 |
| Claude 3 Sonnet | 45 | 225 |
| Claude 3 Opus | 225 | 1125 |
| GPT3.5 (OpenAI) | 7.5 | 22.5 |
| GPT4 (OpenAI) | 150 | 450 |
| PaLM 2 (Google) | 3.75 | 7.5 |
| Gemini (Google) | 1.875 | 5.625 |
- Input Price is charged against the prompt and the context automatically generated from the knowledge base.
- Output Price is charged against the generated text.
- These prices may not be current. Last updated 30 April 2024.