hf_inference.nlp.sentiment
Classify the sentiment of a text using a HuggingFace NLP model via the Inference API. Returns a predicted label (positive, negative, or neutral) with a confidence score, plus scores for all classes. Default model (cardiffnlp/twitter-roberta-base-sentiment-latest) is optimized for social media and...
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What hf_inference.nlp.sentiment does on Apibase
AI agents call hf_inference.nlp.sentiment to retrieve information from Apibase without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
text | string | Yes | Input text to process. Maximum ~10,000 characters depending on model context window. |
model | string | — | HuggingFace model ID to use for sentiment classification. Default: "cardiffnlp/twitter-roberta-base-sentiment-latest" (3-class: positive/neutral/negative). Alte |
Parameters from the server's own tool schema.
Why hf_inference.nlp.sentiment is rated Low
Tool only analyzes and returns sentiment classification; no data modification or side effects.
From the tool's definition Classify sentiment of text, returns predicted label with confidence score
Attacks that exploit this kind of access
The rule that runs hf_inference.nlp.sentiment safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Apibase, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For hf_inference.nlp.sentiment, this is the rule to start with:
hf_inference.nlp.sentiment is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Apibase, apply this rule, and every hf_inference.nlp.sentiment call is checked against it from then on.
Questions about hf_inference.nlp.sentiment
Classify the sentiment of a text using a HuggingFace NLP model via the Inference API. Returns a predicted label (positive, negative, or neutral) with a confidence score, plus scores for all classes. Default model (cardiffnlp/twitter-roberta-base-sentiment-latest) is optimized for social media and short-form text. Supports custom model override. Useful for customer feedback analysis, social media monitoring, and review classification. It is categorised as a Read tool in the Apibase MCP Server, which means it retrieves data without modifying state.
hf_inference.nlp.sentiment accepts 2 parameters: text, model. Required: text. The full parameter table on this page comes from the server's own tool schema.
Register the Apibase MCP server in PolicyLayer and add a rule for hf_inference.nlp.sentiment: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Apibase. Nothing to install.
hf_inference.nlp.sentiment is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the hf_inference.nlp.sentiment rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for hf_inference.nlp.sentiment. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
hf_inference.nlp.sentiment is provided by the Apibase MCP server (apibase-mcp-client). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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