I’m unable to identify or verify any specific “public agent E57 Lenka” based on available information. It’s possible this refers to a fictional character, an internal designation, or a misunderstood reference.
| Feature | What It Does | When to Use It | Example Call | |---------|--------------|----------------|--------------| | | Conversational Q&A, multi‑turn context. | Customer support, help desks. | client.chat(messages=[…]) | | Structured Extraction | Returns JSON with typed fields (dates, amounts, IDs). | Data ingestion, form parsing. | client.extract(text, schema) | | Decision Engine | Accepts a scenario and a set of rules → returns ranked actions. | Incident triage, ops automation. | client.decide(scenario, rules) | | Realtime Streaming | WebSocket that pushes tokens as they’re generated. | UI chat widgets, low‑latency bots. | client.stream_chat(messages=[…]) | | Knowledge‑Base Integration | Attach a vector store (e.g., Pinecone) to let Lenka ground responses in your docs. | Internal SOPs, product manuals. | client.query_knowledge(query, index_id) | | Safety Guardrails | Built‑in profanity filter, PII redaction, compliance tags. | Public‑facing apps. | client.chat(..., safety_level="high") | | Self‑Healing Prompt Manager | Monitors token usage & relevance, auto‑tunes prompt templates. | Large‑scale deployments (≥ 10k req/min). | Configured via dashboard → Prompt Optimizer . | public agent e57 lenka
The blends three core technologies: