Process Multilingual Input
neuroverse_processProcess mixed-language inputs to detect language, extract intent, and perform safety checks. Supports Tamil, Hindi, Telugu, Kannada, and English code-switched text.
Instructions
Process mixed-language input through the full NeuroVerse pipeline.
Pipeline: Language Detect → Normalise → Intent Extract → Safety Check → (optional) Execute
Supported languages: Tamil, Hindi, Telugu, Kannada + English (code-switched).
Args:
text (string): Raw user input, possibly code-switched
user_id (string): User / agent identifier (default: "anonymous")
execute (boolean): Whether to also execute the intent (default: true)
Returns: JSON with keys: language, intent, safety, execution (if execute=true)
Examples:
"anna indha file ah csv convert pannu" → detects Tamil+English, extracts convert_format
"report banao sales ka" → detects Hindi+English, extracts generate_report
"drop database production" → BLOCKED by safety layer
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Raw user input (may be code-switched, e.g. Tamil+English) | |
| user_id | No | Identifier for the user / agent | anonymous |
| execute | No | If true, also execute the extracted intent after safety check |
Implementation Reference
- npm/src/index.ts:76-126 (handler)The handler implementation for the `neuroverse_process` tool, which orchestrates language detection, intent extraction, safety checks, and optional execution.
server.registerTool( "neuroverse_process", { title: "Process Multilingual Input", description: `Process mixed-language input through the full NeuroVerse pipeline. Pipeline: Language Detect → Normalise → Intent Extract → Safety Check → (optional) Execute Supported languages: Tamil, Hindi, Telugu, Kannada + English (code-switched). Args: - text (string): Raw user input, possibly code-switched - user_id (string): User / agent identifier (default: "anonymous") - execute (boolean): Whether to also execute the intent (default: true) Returns: JSON with keys: language, intent, safety, execution (if execute=true) Examples: - "anna indha file ah csv convert pannu" → detects Tamil+English, extracts convert_format - "report banao sales ka" → detects Hindi+English, extracts generate_report - "drop database production" → BLOCKED by safety layer`, inputSchema: ProcessInputSchema, annotations: { readOnlyHint: false, destructiveHint: false, idempotentHint: true, openWorldHint: true, }, }, async (params) => { const lang = detectLanguage(params.text); const intent = await extractIntent(lang.normalizedText); const safety = await checkSafety(intent, params.text); const result: Record<string, unknown> = { language: lang, intent, safety, }; if (params.execute) { const exec = await executeIntent(intent, safety); result["execution"] = exec; } return { content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }], }; } ); - npm/src/index.ts:58-74 (schema)Input validation schema (using Zod) for the `neuroverse_process` tool.
const ProcessInputSchema = z .object({ text: z .string() .min(1, "Text is required") .max(5000, "Text must not exceed 5000 characters") .describe("Raw user input (may be code-switched, e.g. Tamil+English)"), user_id: z .string() .default("anonymous") .describe("Identifier for the user / agent"), execute: z .boolean() .default(true) .describe("If true, also execute the extracted intent after safety check"), }) .strict();