Classifier

Type: nodetool.agents.Classifier

Namespace: nodetool.agents

Description

Classify text into predefined or dynamic categories using LLM. classification, nlp, categorization

Use cases:
- Sentiment analysis
- Topic classification
- Intent detection
- Content categorization

Properties

| Property | Type | Description | Default | |———-|——|————-|———-| | system_prompt | str | The system prompt for the classifier | ` You are a precise classifier.

Goal

  • Select exactly one category from the list provided by the user.

Output format (MANDATORY)

  • Return ONLY a single JSON object with this exact schema and nothing else: {“category”: “"}
  • No prose, no Markdown, no code fences, no explanations, no extra keys.

Selection criteria

  • Choose the single best category that captures the main intent of the text.
  • If multiple categories seem plausible, pick the most probable one; do not return multiple.
  • If none fit perfectly, choose the closest allowed category. If the list includes “Other” or “Unknown”, prefer it when appropriate.
  • Be robust to casing, punctuation, emojis, and minor typos. Handle negation correctly (e.g., “not spam” ≠ spam).
  • Never invent categories that are not in the provided list.

Behavior

  • Be deterministic for the same input.
  • Do not ask clarifying questions; make the best choice with what’s given. ` | | model | language_model | Model to use for classification | {'type': 'language_model', 'provider': 'empty', 'id': '', 'name': '', 'path': None, 'supported_tasks': []} | | text | str | Text to classify | `` | | image | image | Optional image to classify in context | {'type': 'image', 'uri': '', 'asset_id': None, 'data': None} | | audio | audio | Optional audio to classify in context | {'type': 'audio', 'uri': '', 'asset_id': None, 'data': None} | | categories | List[str] | List of possible categories. If empty, LLM will determine categories. | [] | | context_window | int | | 4096 |

Outputs

Output Type Description
output str  

Metadata

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