Abstract: In various examples, systems and methods are disclosed that relate to managing interactions with generative artificial intelligence models. For example, a system can receive data associated with a system prompt, the system prompt including a first string of text. The system can then receive data associated with a task prompt, the task prompt including a second string of text configured to cause a large language model (LLM) to generate an output. The system can generate a model prompt including a third string of text based at least on the first string of text and the second string of text. In examples, the system can provide the model prompt to the LLM to cause the LLM to generate the output, the output including an answer that is determined based at least on a context associated with the third string of text.

Abstract: In various examples, systems and techniques are provided that encapsulate indexing and query operations into an application programming interface (API) that automates and coordinates calls to various local and cloud-based services. When a user has a document(s) to add to a retrieval augmented generation (RAG) database, the API may offer to the user multiple document processing pipelines (DPPs) having pre-set indexing configurations. Similarly, when a user query is received, the API may generate calls to implement query processing that does not require the user to manually configure retrieval and processing of the embeddings. The API may further implement calls that locate a relevant embedding store and provide the stored embeddings, together with the query embeddings, to a search engine that identifies the most relevant matches. The API may then access the embedding-to-text indexing and identify relevant text segments and documents to a prompt generator.

Abstract: In some embodiments, an apparatus includes a memory of a dispatch server and a processor of the dispatch server communicatively coupled to the memory. The processor is configured to receive an indication of a blockchain transaction to monitor; the blockchain transaction having not yet been finalized by a blockchain. The processor is configured to store the indication of the blockchain transaction in a state monitor cache communicatively coupled to the blockchain such that a state monitor queries the blockchain for a status of the blockchain transaction based on the indication of the blockchain transaction being stored within the state monitor cache. The processor is configured to provide the status of the blockchain transaction to a user in response to receiving an indication of the status of the blockchain transaction.