4 repository-uri
Techniques for processing multi-rate data streams using masks to maintain internal state for asynchronous entries.
Distinguishing note: The candidates refer to image segmentation masks or data privacy masking; this is about computational execution masks for batching.
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Moshi is a real-time voice foundation model and speech-to-speech framework designed for bidirectional, low-latency conversations. It functions as a full-duplex voice interface that processes audio and text concurrently in a single stream, enabling natural human-machine dialogue without sequential processing delays. The system utilizes a neural audio codec to compress high-fidelity audio into low-bitrate tokens for efficient transmission. To manage complex responses and reasoning, it employs internal monologue modeling, which generates a hidden stream of thought tokens alongside audible speech
Uses binary execution masks to process asynchronous data streams at varying rates while protecting internal state.
p-queue este o coadă de promisiuni JavaScript și un scheduler de sarcini concurente conceput pentru a limita numărul de operațiuni asincrone active. Acesta servește ca un limitator de rată asincron și manager al ciclului de viață al promisiunilor pentru a preveni epuizarea resurselor. Proiectul se distinge prin programarea sarcinilor bazată pe prioritate și limitarea ratei de tip token-bucket pentru a controla frecvența de execuție. Se integrează cu semnale de abort pentru anularea sarcinilor și oferă mecanisme pentru a întrerupe, relua și șterge operațiunile în așteptare. Instrumentul acoperă capabilități mai largi de gestionare a traficului, inclusiv timeout-uri pentru operațiuni și limitarea concurenței. Include, de asemenea, primitive de monitorizare pentru a urmări starea cozii și numărul de sarcini în așteptare, precum și sincronizare pentru starea de repaus a cozii.
Enables processing large sets of asynchronous jobs in controlled chunks to avoid overloading memory or database connections.
openai-go is an LLM SDK for Go and a client for interacting with OpenAI services. It provides type-safe bindings to generate text, images, and audio via REST endpoints, enabling the integration of large language models and AI assistant orchestration into Go applications. The library serves as an agent orchestration tool for managing stateful conversation threads and autonomous agents with integrated tool calling and file search. It also functions as an asynchronous batch processing client for monitoring large-scale request groups and fine-tuning jobs, alongside a management SDK for controllin
Enables creation and tracking of asynchronous processing jobs for large-scale API request groups.
This is a Python SDK for interacting with large language models via API. It serves as a client library to generate text, process messages, and manage conversational states, while providing a specialized interface for connecting to models hosted across different cloud infrastructure providers. The SDK includes a tool-calling framework that maps Python functions to JSON schemas, allowing models to execute external tools. It also features a built-in token counting utility to estimate input size before transmission and a server-sent events client for receiving model tokens in real time. The libr
Submits arrays of requests for asynchronous background processing and retrieves aggregated results.