Groq Data Handling Skill

Groq Data Handling

Overview

Manage data flowing through Groq's inference API. Covers prompt sanitization before sending to Groq, response filtering after receiving, PII redaction, conversation audit logging, and token usage tracking. Key fact: Groq does not use API data for model training (Groq Privacy Policy).

Groq Data Policy

Groq does not train on API request/response data
Prompts and completions are processed and discarded
Groq may temporarily log requests for abuse prevention
For enterprise: contact Groq for DPA and SOC 2 compliance details

Instructions

Step 1: Prompt Sanitization Layer

import Groq from "groq-sdk";

const groq = new Groq();

interface RedactionRule {
  name: string;
  pattern: RegExp;
  replacement: string;
}

const PII_RULES: RedactionRule[] = [
  { name: "email", pattern: /\b[\w.+-]+@[\w-]+\.[\w.]+\b/g, replacement: "[EMAIL]" },
  { name: "phone", pattern: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g, replacement: "[PHONE]" },
  { name: "ssn", pattern: /\b\d{3}-\d{2}-\d{4}\b/g, replacement: "[SSN]" },
  { name: "credit_card", pattern: /\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b/g, replacement: "[CARD]" },
  { name: "ip_address", pattern: /\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b/g, replacement: "[IP]" },
];

function sanitizeText(text: string): { sanitized: string; redactedTypes: string[] } {
  let sanitized = text;
  const redactedTypes: string[] = [];

  for (const rule of PII_RULES) {
    if (rule.pattern.test(sanitized)) {
      redactedTypes.push(rule.name);
      sanitized = sanitized.replace(rule.pattern, rule.replacement);
    }
  }

  return { sanitized, redactedTypes };
}

function sanitizeMessages(messages: any[]): { messages: any[]; hadPII: boolean } {
  let hadPII = false;
  const sanitized = messages.map((m) => {
    if (typeof m.content !== "string") return m;
    const { sanitized: text, redactedTypes } = sanitizeText(m.content);
    if (redactedTypes.length > 0) hadPII = true;
    return { ...m, content: text };
  });

  return { messages: sanitized, hadPII };
}

Step 2: Safe Completion Wrapper

async function safeCompletion(
  messages: any[],
  model = "llama-3.3-70b-versatile",
  options?: { maxTokens?: number }
) {
  // Sanitize input
  const { messages: sanitized, hadPII } = sanitizeMessages(messages);
  if (hadPII) {
    console.warn("[groq-data] PII detected and redacted before sending to Groq API");
  }

  // Call Groq
  const completion = await groq.chat.completions.create({
    model,
    messages: sanitized,
    max_tokens: options?.maxTokens ?? 1024,
  });

  // Filter response
  const responseContent = completion.choices[0].message.content || "";
  const { sanitized: filteredContent, redactedTypes } = sanitizeText(responseContent);

  if (redactedTypes.length > 0) {
    console.warn(`[groq-data] Response contained PII: ${redactedTypes.join(", ")}`);
  }

  return {
    ...completion,
    choices: [{
      ...completion.choices[0],
      message: {
        ...completion.choices[0].message,
        content: filteredContent,
      },
    }],
  };
}

Step 3: Token Usage Tracking

interface UsageRecord {
  timestamp: string;
  model: string;
  promptTokens: number;
  completionTokens: number;
  totalTokens: number;
  estimatedCostUsd: number;
  sessionId?: string;
}

const COST_PER_1M: Record<string, { input: number; output: number }> = {
  "llama-3.1-8b-instant": { input: 0.05, output: 0.08 },
  "llama-3.3-70b-versatile": { input: 0.59, output: 0.79 },
  "llama-3.3-70b-specdec": { input: 0.59, output: 0.99 },
  "meta-llama/llama-4-scout-17b-16e-instruct": { input: 0.11, output: 0.34 },
};

function calculateCost(model: string, usage: any): number {
  const pricing = COST_PER_1M[model] || { input: 0.10, output: 0.10 };
  return (
    (usage.prompt_tokens / 1_000_000) * pricing.input +
    (usage.completion_tokens / 1_000_000) * pricing.output
  );
}

function trackUsage(model: string, usage: any, sessionId?: string): UsageRecord {
  const record: UsageRecord = {
    timestamp: new Date().toISOString(),
    model,
    promptTokens: usage.prompt_tokens,
    completionTokens: usage.completion_tokens,
    totalTokens: usage.total_tokens,
    estimatedCostUsd: calculateCost(model, usage),
    sessionId,
  };

  // Store in your preferred backend
  console.log(JSON.stringify({ type: "groq_usage", ...record }));
  return record;
}

Step 4: Audit-Logged Completion

interface AuditLog {
  timestamp: string;
  sessionId: string;
  model: string;
  promptHash: string;        // Hash of input (not the input itself)
  piiDetected: boolean;
  responseFiltered: boolean;
  usage: UsageRecord;
}

async function auditedCompletion(
  sessionId: string,
  messages: any[],
  model = "llama-3.3-70b-versatile"
): Promise<{ content: string; audit: AuditLog }> {
  const { messages: sanitized, hadPII } = sanitizeMessages(messages);

  const completion = await groq.chat.completions.create({
    model,
    messages: sanitized,
  });

  const responseContent = completion.choices[0].message.content || "";
  const { sanitized: filtered, redactedTypes } = sanitizeText(responseContent);
  const usage = trackUsage(model, completion.usage, sessionId);

  const audit: AuditLog = {
    timestamp: new Date().toISOString(),
    sessionId,
    model,
    promptHash: createHash("sha256")
      .update(sanitized.map((m: any) => m.content).join("|"))
      .digest("hex"),
    piiDetected: hadPII,
    responseFiltered: redactedTypes.length > 0,
    usage,
  };

  // Log audit entry (don't log prompt content, only hash)
  console.log(JSON.stringify({ type: "groq_audit", ...audit }));

  return { content: filtered, audit };
}

Step 5: Content Safety Check

// Use Groq's Llama Guard for content moderation
async function moderateContent(text: string): Promise<{
  safe: boolean;
  categories: string[];
}> {
  const completion = await groq.chat.completions.create({
    model: "meta-llama/llama-guard-4-12b",
    messages: [{ role: "user", content: text }],
    max_tokens: 100,
  });

  const response = completion.choices[0].message.content || "";
  const safe = response.trim().toLowerCase().startsWith("safe");

  return {
    safe,
    categories: safe ? [] : response.split("\n").slice(1).map((l) => l.trim()).filter(Boolean),
  };
}

Step 6: Daily Cost Report

function generateCostReport(records: UsageRecord[]) {
  const totalCost = records.reduce((sum, r) => sum + r.estimatedCostUsd, 0);
  const totalTokens = records.reduce((sum, r) => sum + r.totalTokens, 0);

  const byModel: Record<string, { cost: number; tokens: number; calls: number }> = {};
  for (const r of records) {
    if (!byModel[r.model]) byModel[r.model] = { cost: 0, tokens: 0, calls: 0 };
    byModel[r.model].cost += r.estimatedCostUsd;
    byModel[r.model].tokens += r.totalTokens;
    byModel[r.model].calls++;
  }

  return {
    totalCost: `$${totalCost.toFixed(4)}`,
    totalTokens,
    totalCalls: records.length,
    byModel: Object.fromEntries(
      Object.entries(byModel).map(([model, data]) => [
        model,
        { cost: `$${data.cost.toFixed(4)}`, tokens: data.tokens, calls: data.calls },
      ])
    ),
  };
}

Error Handling

| Issue | Cause | Solution | |-------|-------|----------| | PII leaks in response | Model echoes sensitive input | Apply response filtering on all completions | | Cost spike | 70B model for all requests | Route simple tasks to 8B | | Missing usage data | Streaming mode | Use non-streaming for tracked requests, or estimate | | Audit gaps | Not all code paths use wrapper | Lint rule: ban direct groq.chat.completions.create |

Resources

Next Steps

For enterprise access controls, see groq-enterprise-rbac.

Agent Skills: Groq Data Handling

Install this agent skill to your local

Skill Files