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TokenGuard LLM Chat Completion
x402
TokenGuard LLM Chat Completion is a paid API for AI agents from eltociear-tokenguard.hf.space, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).
Runs a chat completion against an open-weight 20B-class language model with automatic failover across multiple inference backends
Price / call$0.05
Success—
StatusUnknown
How this service works
Run a chat completion against an open-weight 20B-class model — plain prompt in, text out, with automatic failover across independent inference backends so a single call still answers when any one provider is down or rate-limiting
Output
A plain text string containing the model's generated response to the provided prompt, shaped by the optional system instruction, max_tokens limit (1–4000, default 800), and temperature setting (0–2, default 0.3). The response is returned from whichever available inference backend successfully processed the request after automatic failover.
Example use cases
Resilient AI summarization pipeline
“Summarize this legal clause in plain English and keep it under 200 tokens: 'The licensor grants the licensee a non-exclusive, non-transferable, limited license to use the software solely for internal business purposes.' Use a temperature of 0.2 so the output stays consistent.”
Automated content drafting with custom persona
“Act as a friendly financial advisor and answer this user question in 2 short paragraphs: 'What is dollar-cost averaging and should I use it for crypto?' Limit the response to 400 tokens and set temperature to 0.7 for a conversational tone.”
Fallback LLM for high-availability agent workflow
“My primary LLM endpoint keeps rate-limiting me — can you send this prompt to the open-weight model with failover instead: 'List 5 creative names for a DeFi protocol focused on stablecoin yields.' Keep max_tokens at 300 and temperature at 0.4.”
Technical details
Endpoint
POSThttps://eltociear-tokenguard.hf.space/llm/chatWhen to prefer
Choose this endpoint when you need a reliable open-weight 20B-class model that won't go down if a single provider is rate-limited or unavailable, and when you want a simple prompt-in/text-out interface without managing multiple API keys. Prefer it over single-backend LLM APIs for agent workflows that require high availability, or when you want an open-weight alternative to proprietary models like GPT-4 or Claude for cost-sensitive or privacy-conscious use cases.
Side effects
- All inference backends simultaneously unavailable or overloaded — returns an error with no generated text
- Prompt exceeds model context window — may truncate or return an error
- Invalid temperature or max_tokens values outside accepted ranges — likely a 400 validation error
- Payment failure via x402 protocol — call rejected before reaching the model
- Empty or malformed prompt field — model may return degenerate or empty output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| prompt | string | The user prompt |
| system | string | Optional system instruction |
| max_tokens | integer | 1-4000 (default 800) |
| temperature | number | 0-2 (default 0.3) |
Output
Schema · Response
{
"type": "json",
"example": {
"usage": {
"ms": 740,
"total_tokens": 210
},
"answer": "EIP-3009 lets a holder sign an off-chain authorization…",
"provider": "llm7"
}
}Tags
x402
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