# Meeting Topic Local Text Classifier (Naive-Bayes)

> Meeting Topic Local Text Classifier (Naive-Bayes) is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Trains a local naive-Bayes text classifier on up to 200 labelled meeting-transcript records and classifies new query texts into planning, progress, decision, or review categories.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-local-classifier?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/meeting-topic-local-text-classifier-naive-bayes-09b6a4ff
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4lF90E8mG8P52y6bkfGY0

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability meeting-topic-local-text-classifier-naive-bayes-09b6a4ff -d '<json body>'
```

Example prompt: I have about 50 labelled meeting text snippets — some marked planning, some progress, some decision, and some review — can you train a local naive-Bayes classifier on them and then tell me what category these three new meeting notes fall into?

## When to prefer this

Choose this endpoint when you need a fast, cheap, interpretable text classification baseline for meeting topics using only your own labelled data — no hosted model, no foundation model API calls, no data leaving your control beyond this single bounded call. Ideal for prototyping, evaluation, or low-volume use cases where a naive-Bayes local classifier is sufficient and cost ($0.01 USDC) matters. Prefer alternatives if you need deep-learning accuracy, large-scale inference, or topic discovery on unlabelled data.

## Known failure modes

- Fewer than 2 records supplied (minItems violation)
- More than 200 records supplied (maxItems exceeded)
- Missing required fields (id, text, actual) on any record
- Invalid actual label value outside enum (planning/progress/decision/review)
- Text exceeds 1000-character limit per record
- No query_texts provided or query_texts exceeds 20 items
- Insufficient class diversity for a meaningful classifier (e.g. only one class represented)

## How this service works

Meeting topic - Train local text baseline and classify: Train local text baseline and classify for Meeting topic. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded train local text baseline and classify deliverable.

## Output

Returns per-query predicted meeting topic labels (planning, progress, decision, or review) derived from a locally-trained naive-Bayes text baseline fitted on the supplied labelled records, along with evaluation metadata about the trained model.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "planning",
       "progress",
       "decision",
       "review"
      ],
      "type": "string"
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "planning sample document number 0 for this supplied dataset.",
     "actual": "planning"
    },
    {
     "id": "example-0-1",
     "text": "planning sample document number 1 for this supplied dataset.",
     "actual": "planning"
    },
    {
     "id": "example-0-2",
     "text": "planning sample document number 2 for this supplied dataset.",
     "actual": "planning"
    },
    {
     "id": "example-1-0",
     "text": "progress sample document number 0 for this supplied dataset.",
     "actual": "progress"
    },
    {
     "id": "example-1-1",
     "text": "progress sample document number 1 for this supplied dataset.",
     "actual": "progress"
    },
    {
     "id": "example-1-2",
     "text": "progress sample document number 2 for this supplied dataset.",
     "actual": "progress"
    },
    {
     "id": "example-2-0",
     "text": "decision sample document number 0 for this supplied dataset.",
     "actual": "decision"
    },
    {
     "id": "example-2-1",
     "text": "decision sample document number 1 for this supplied dataset.",
     "actual": "decision"
    },
    {
     "id": "example-2-2",
     "text": "decision sample document number 2 for this supplied dataset.",
     "actual": "decision"
    },
    {
     "id": "example-3-0",
     "text": "review sample document number 0 for this supplied dataset.",
     "actual": "review"
    },
    {
     "id": "example-3-1",
     "text": "review sample document number 1 for this supplied dataset.",
     "actual": "review"
    },
    {
     "id": "example-3-2",
     "text": "review sample document number 2 for this supplied dataset.",
     "actual": "review"
    }
   ],
   "maxItems": 200,
   "minItems": 2
  },
  "query_texts": {
   "type": "array",
   "items": {
    "type": "string",
    "default": "",
    "maxLength": 1000
   },
   "default": [
    "planning sample"
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/meeting-topic-local-text-classifier-naive-bayes-09b6a4ff/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)