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Àkàndé

A self-hosted, provider-agnostic voice assistant that delivers structured executive briefings via voice or text from 11 LLM providers.

Build Registry Docs OpenSSF Scorecard License: Apache-2.0 OR MIT Python >= 3.10


Contents

Getting started

The Àkàndé ecosystem

Library reference

Operational


Install

As a Python library

[dependencies]
akande = "^0.0.7"
# Core install : provider SDKs and mic capture are optional extras
pip install akande

# Full kit : every provider + microphone + MCP
pip install "akande[all,mic,mcp]"

From source

git clone https://github.com/sebastienrousseau/akande
cd akande
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

Requirements

Requirement Supported Version Details
Python >= 3.10 (tested on 3.10, 3.11, 3.12, 3.13, 3.14) Core runtime environment
PortAudio >= 19 (optional) Required for microphone audio input (akande[mic])
FFmpeg Any modern release (optional) Required for MP3 / non-WAV audio transcoding
Platforms Linux (x86_64, aarch64), macOS (Intel, Apple Silicon), Windows Platform-agnostic Python package

Quick Start

import asyncio
import os

from akande.akande import Akande
from akande.providers.registry import get_provider

os.environ["LLM_PROVIDER"] = (
    "ollama"  # or openai, anthropic, google, claude_cli, etc.
)


async def main() -> None:
    provider = get_provider()
    assistant = Akande(openai_service=provider)
    response = await assistant.generate_response(
        "Provide a morning executive briefing on market trends."
    )
    print(response)


asyncio.run(main())

This runs the end-to-end Àkàndé pipeline: intent classification, safety wrapping, provider execution, and optional speech synthesis.


The Àkàndé ecosystem

Àkàndé provides a complete voice-first executive briefing stack across command-line, graphical terminal, REST, and protocol interfaces:

Component Purpose Use case
akande.pipeline Core orchestration pipeline Intent classification, safety envelopes, tool dispatch
akande.server REST and SSE streaming server Web-based clients and HTTP streaming integrations
akande.tui Bubble Tea interactive terminal UI Full-screen interactive terminal workflow
akande.mcp Model Context Protocol client and server Exposing Àkàndé tools to Claude Desktop, Cursor, Continue

Capabilities at a glance

Area Capability Status
Providers 11 LLM providers (OpenAI, Anthropic, Google, Claude CLI, Mistral, Cohere, etc.) Production
Speech-to-Text SpeechRecognition and Faster-Whisper backends Production
Text-to-Speech gTTS and local Kokoro-82M ONNX offline synthesis Production
Safety & Audit Input sanitization, safety envelopes, cryptographically verifiable PDF audits Production
Compliance EU AI Act Article 50 transparency and AudioSeal audio watermarking Production

Ecosystem comparison

Project Self-Hosted Multi-Provider Voice STT/TTS Article 50 Audit
Àkàndé Yes 11 providers Yes (Native) Yes (Cryptographic)
Open-WebUI Yes Yes Partial No
LocalAI Yes Local only Yes No

See docs/COMPARISON.md for the evidence and complete matrix.


Benchmarks

Scenario Result Environment
Pipeline dispatch overhead < 1.2 ms Apple Silicon M3 / Python 3.13
Watermark verification latency < 18 ms Apple Silicon M3 / 1s audio
Audio sanitization & safety wrapping < 0.3 ms Ubuntu 24.04 / Python 3.12

See docs/BENCHMARKS.md for methodology and full results.


Features

  • 11 LLM Providers : Switch between OpenAI, Anthropic, Google Gemini, Claude Code CLI, Mistral, Cohere, Groq, Ollama, LM Studio, Azure, and Codex CLI.
  • Safety Envelope : Strict transcript sanitization, control character stripping, length clamping, and <user_input> boundary envelopes.
  • SSRF Prevention : Built-in host validation restricting loopbacks, private RFC 1918 subnets, link-local addresses, and cloud metadata services.
  • Regulatory Transparency : Full EU AI Act Article 50 compliance with machine-readable audit manifests and AudioSeal watermarking.

Configuration

Set configuration through environment variables or .env files:

# Provider selection
export LLM_PROVIDER=openai  # anthropic, google, ollama, claude_cli, etc.

# Operational profile
export AKANDE_PROFILE=eu    # eu (strict compliance) or default

# Audio configuration
export AKANDE_TTS=kokoro    # gtts or kokoro
export AKANDE_STT=sr        # sr or faster_whisper

Examples

Runnable examples demonstrating features:


When not to use Àkàndé

  • Raw conversational chatbot : Àkàndé is optimized for structured, factual executive briefings and action synthesis rather than open-ended chit-chat.
  • Ultra-low-latency telephony : Real-time sub-100ms voice agents require specialized WebRTC infrastructure; Àkàndé targets structured turn-taking.

Development

uv venv
uv pip install -e ".[all,dev]" mcp
uv run --extra dev pytest
uv run --extra dev ruff check .

All contributions must pass the verification gates (pytest with >= 95% coverage, ruff, mypy, bandit, pip-audit).


Security

Àkàndé enforces security best practices across input validation, network tools, and credential handling:

  • Private IP and SSRF rejection on external fetch tools.
  • Strict input sanitization and delimiter escaping on speech transcripts.
  • Cryptographically signed audit manifests with SHA-256 sidecars.

Report vulnerabilities according to SECURITY.md.


Documentation


Stability guarantees

Àkàndé adheres to strict Semantic Versioning:

  • Patch releases (0.0.x -> 0.0.y) : Backwards-compatible bug fixes and security patches.
  • Breaking changes : Never introduced in patch releases. Deprecations documented at least one minor iteration in advance.

License

Dual-licensed under Apache-2.0 OR MIT at your option:

Metadata

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