Quickstart: MultiMind in 5 Minutes

Install, make your first model call, guard it against PII leaks, track what it costs, and scan text for sensitive data from the command line. Every snippet below is copy-paste runnable.

Not a developer? Read the plain-language getting started guide instead.

1. Install (30 seconds)

pip install multimind-sdk

That is the whole core install: multi-provider models, the PII guard, cost tracking, hallucination checks, and the CLI. Extras like [rag] or [gateway] are only needed for those features — see the installation guide.

2. Pick a model path

Path A — cloud provider (needs one API key). Set the key for whichever provider you have:

export OPENAI_API_KEY=sk-...      # or GROQ_API_KEY, ANTHROPIC_API_KEY,
                                  # GEMINI_API_KEY, MISTRAL_API_KEY, DEEPSEEK_API_KEY

Path B — fully local, no API key. Install Ollama, then:

ollama pull mistral

MultiMind talks to Ollama over HTTP; no extra Python packages needed.

To see which providers are configured at any time (works offline):

multimind models list

3. First generation

Path A (cloud):

import asyncio
from multimind import OpenAIModel

async def main():
    model = OpenAIModel(model_name="gpt-4o-mini")
    print(await model.generate("Explain quantum computing in one paragraph"))

asyncio.run(main())

Path B (local, no key):

import asyncio
from multimind import OllamaModel

async def main():
    model = OllamaModel(model_name="mistral")
    print(await model.generate("Explain quantum computing in one paragraph"))

asyncio.run(main())

The interface is identical for every provider — ClaudeModel, GeminiModel, GroqModel, MistralAIModel, DeepSeekModel all work the same way. Prefer plain functions over asyncio? Use model.generate_sync(...) — see the cookbook.

4. Guard it against PII leaks

Wrap any model so emails, SSNs, credit cards, API keys, and other PII are redacted before they ever reach the provider — with an audit trail:

import asyncio
from multimind import OpenAIModel
from multimind.compliance import guard

async def main():
    model = guard(
        OpenAIModel(model_name="gpt-4o-mini"),   # or OllamaModel(model_name="mistral")
        strategy="mask",                          # emails become [EMAIL], SSNs [SSN], ...
        block_on=("credit_card", "ssn"),          # refuse these outright
        audit_log="compliance_audit.jsonl",       # types & counts only — never raw PII
    )
    print(await model.generate("Email [e-mail] about the invoice"))
    # The provider only ever saw: "Email [EMAIL] about the invoice"

asyncio.run(main())

Then look at compliance_audit.jsonl — one JSON line per event, recording what was detected and redacted (types, counts, and hashes only; never the raw values).

5. Track what it costs

import asyncio
from multimind import OpenAIModel
from multimind.observability import CostTracker, track_costs

async def main():
    tracker = CostTracker()   # add jsonl_path="costs.jsonl" to persist records
    model = track_costs(OpenAIModel(model_name="gpt-4o-mini"), tracker=tracker)

    await model.generate("Say hello in five languages")
    print(tracker.report())   # tokens and dollars, per model and total

asyncio.run(main())

Want a hard spending ceiling instead of just a report? Add budget=Budget(max_cost=1.00) — calls past the ceiling are blocked before dispatch. Recipe: budget-capped calls.

6. Scan for PII from the command line

No Python needed — one command, works completely offline:

multimind compliance scan-text "My email is [e-mail] and my card is 4111 1111 1111 1111"

Output is a table of findings (type, position, matched text) and the command exits with code 1 if any PII was found, so it drops straight into CI pipelines. Scan a file instead, and print a redacted version:

multimind compliance scan-text --file customer_notes.txt --redact mask

Where to next

• Cookbook — short task-oriented recipes: switch providers, structured output with Pydantic, hallucination detection, the gateway API, and more
• Compliance guide — the full GDPR/HIPAA compliance module
• Deployment guide — docker pull ghcr.io/multimindlab/multimind-sdk:latest, docker compose, and a fully local stack
• Docs index — everything else