Browsing: applications

Voice agents, live captioning, contact center analytics, and accessibility tools all depend on real-time speech-to-text, where your application streams audio in and receives transcription back simultaneously…

Building end-to-end live streaming applications with real-time voice interaction presents several challenges: network bandwidth constraints can cause high latency and quality degradation in time-critical applications. Language…

banner(“Part 5 — Streaming”) mem.attribution(entity_id=”[email protected]”, process_id=”personal-assistant”) stream = client.chat.completions.create( model=MODEL, messages=[{“role”: “user”, “content”: “In two sentences, what do you remember about me?”}], stream=True, ) print(“[stream] “,…

Most agentic applications today have a memory problem. Every time a user opens a new session, the agent starts from zero. There is no recollection of…

Image by Author   # Introduction  Building large language model (LLM) applications is very different from using consumer-facing tools like Claude Code, ChatGPT, or Codex. Those products…

Image by Editor   # Introduction  Python decorators are tailor-made solutions that are designed to help simplify complex software logic in a variety of applications, including LLM-based…

Organizations can face two critical challenges with conversational AI. First, users need answers where they work—in their CRM, support console, or analytics portal—not in separate tools.…

Alibaba’s Qwen team has released the Qwen3.5 Small Model Series, a collection of Large Language Models (LLMs) ranging from 0.8B to 9B parameters. While the industry…

Are you struggling to balance generative AI safety with accuracy, performance, and costs? Many organizations face this challenge when deploying generative AI applications to production. A…

def normalize_ws(s: str) -> str: return re.sub(r”\s+”, ” “, s).strip() RAW_DOCS = [ { “doc_id”: “trulens_core”, “title”: “TruLens core idea”, “text”: “TruLens is used to track…