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streaming-chat

Automate streaming and non-streaming AI inference across 0G Compute Network providers.

Updated Apr 26, 2026
Search Tags:#llm#sdk#streaming#chat#broker#ai-inference#compute-network
One-click install
npx skills add https://github.com/gabrielfior/ai-village-open-agents --skill streaming-chat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: streaming-chat
Source: https://github.com/gabrielfior/ai-village-open-agents/tree/main/.opencode/skills/streaming-chat
Command: npx skills add https://github.com/gabrielfior/ai-village-open-agents --skill streaming-chat

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables streaming and non-streaming AI inference across 0G Compute Network providers to support real-time chat experiences.

Core Features & Use Cases

  • Streaming chat support with live tokens and model metadata retrieval.
  • Non-streaming chat for traditional request-response workflows.
  • Multi-model compatibility across DeepSeek, Qwen, Gemma, and GPT-OSS for flexible deployments.

Quick Start

Send a user message to the streaming chat endpoint and observe the assistant responses in real time.

Frequently Asked Questions about streaming-chat

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement streaming chat with AI inference on a compute network?▼

Streaming chat is implemented by automating conversational AI inference requests to 0G Compute Network providers. The Skill orchestrates live token delivery and tracks usage accounting for real-time chat applications.

What problem does streaming AI inference solve for multi-model deployments?▼

Streaming AI inference solves the latency issue in multi-model deployments by enabling real-time chat experiences. It supports compatibility across models like DeepSeek, Qwen, Gemma, and GPT-OSS for flexible workflows.

Do I need Node.js to use the 0g-serving-broker for chat applications?▼

Yes, Node.js is required to use the @0glabs/0g-serving-broker library. This environment is necessary to authenticate providers, retrieve model metadata, and orchestrate streaming and non-streaming chat requests.

How do I get model metadata and authenticate providers for real-time chat?▼

Model metadata retrieval and provider authentication are automated during request orchestration via the 0g-serving-broker library. This ensures valid access to compute network providers for live chat token streaming.

Can I use non-streaming chat for traditional request-response workflows?▼

Yes, non-streaming chat is supported alongside streaming chat for traditional request-response workflows. This handles standard AI inference tasks without live token delivery when real-time updates are unnecessary.

What are the limitations of using 0G Compute Network for conversational AI?▼

Limitations include dependency on Node.js and the @0glabs/0g-serving-broker library for orchestration. Usage is constrained to compatible models and requires explicit provider authentication to track usage accounting.

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