akande 0.0.5

A self-hosted, provider-agnostic voice assistant that delivers structured executive briefings via voice or text from 10 LLM providers.

Àkàndé

Àkàndé is a self-hosted, provider-agnostic voice assistant that delivers structured executive briefings from any of 10 supported LLM providers. Ask a question by voice or text; receive a concise Overview / Solution / Conclusion / Recommendations briefing with automatic PDF and CSV artefact generation. Run it against OpenAI, or keep your data entirely private with Ollama or LM Studio on your own hardware.

The name "Àkàndé" (Yoruba: "firstborn") signifies a pioneering approach to voice-driven intelligence briefings.

Why Àkàndé?

Ask a question. Get a structured briefing. Keep your data.

That is the entire workflow. Voice, text, or web -- Àkàndé listens, queries the LLM of your choice, and delivers a four-section executive briefing: Overview, Solution, Conclusion, Recommendations. PDF and CSV artefacts are generated automatically.

No framework to learn. No output parsing to build. No provider lock-in to accept.

Ten LLM providers -- including fully private local inference through Ollama and LM Studio -- all behind one environment variable. Your hardware. Your models. Your data.

Every other tool gives you the engine and expects you to build the car. Àkàndé hands you the keys. This is how AI assistants should have always worked.

Who is Àkàndé for?

Python developers who deploy it: clone, configure a provider, and run. Àkàndé is a standard Python package with a CLI entry point, a CherryPy web server mode, and 161 tests.

End users and executives who interact with it: speak or type a question and receive a structured briefing read aloud and saved as PDF/CSV. No technical knowledge required once deployed.

Quick Start

Prerequisites

• Python 3.9+
• PortAudio (for microphone input): Ubuntu/Debian sudo apt install portaudio19-dev, macOS brew install portaudio
• ffmpeg (for audio conversion): Ubuntu/Debian sudo apt install ffmpeg, macOS brew install ffmpeg

Installation

git clone https://github.com/sebastienrousseau/akande
cd akande
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt

cp .env.example .env
# Edit .env: set OPENAI_API_KEY=sk-your-key-here

python -m akande

Select option 2 ("Ask a question"), type your query, and receive a structured briefing.

Provider Configuration

Set LLM_PROVIDER in your .env file. Install extras for non-OpenAI providers.

Provider	LLM_PROVIDER	Required env vars	Install extras	Default model
OpenAI	openai	OPENAI_API_KEY	(included)	gpt-3.5-turbo
Anthropic	anthropic	ANTHROPIC_API_KEY	pip install akande[anthropic]	claude-3-haiku-20240307
Google Gemini	google	GOOGLE_API_KEY	pip install akande[google]	gemini-pro
Ollama	ollama	OLLAMA_HOST	(included)	llama3
Azure OpenAI	azure_openai	AZURE_OPENAI_API_KEY, AZURE_OPENAI_ENDPOINT	(included)	gpt-35-turbo
Mistral	mistral	MISTRAL_API_KEY	pip install akande[mistral]	mistral-small-latest
Cohere	cohere	COHERE_API_KEY	pip install akande[cohere]	command-r
Hugging Face	huggingface	HUGGINGFACE_API_KEY	pip install akande[huggingface]	mistralai/Mistral-7B-Instruct-v0.2
Groq	groq	GROQ_API_KEY	(included)	llama3-8b-8192
LM Studio	lmstudio	LMSTUDIO_HOST	(included)	local-model

To install all optional provider SDKs: pip install akande[all]

Interaction Modes

Àkàndé presents a CLI menu with four options:

1. Use voice -- speak your question via microphone; response is read aloud
2. Ask a question -- type your question; response is printed and read aloud
3. Start server -- launches a web UI at http://127.0.0.1:8080 with voice and text input
4. Stop -- exits the assistant

Example Interaction

Question: "What is quantitative easing?"

Overview Quantitative easing (QE) is a monetary policy tool used by central banks to stimulate economic activity when conventional interest rate cuts are insufficient.

Solution

• Central banks purchase government bonds and other securities to inject money into the economy
• This lowers long-term interest rates, encouraging borrowing and investment
• QE increases the money supply without printing physical currency

Conclusion QE can stabilise financial markets during crises but carries risks of asset bubbles and currency devaluation.

Recommendations

• Monitor inflation indicators alongside QE announcements
• Consider the impact on bond yields for portfolio decisions

Each response is automatically saved as a timestamped PDF and CSV in the output directory.

Troubleshooting

Problem	Cause	Fix
Could not find PyAudio	PortAudio missing	Ubuntu: sudo apt install portaudio19-dev. macOS: brew install portaudio. Then pip install pyaudio.
ffmpeg not found	ffmpeg not installed	Ubuntu: sudo apt install ffmpeg. macOS: brew install ffmpeg.
Microphone not detected	OS permissions	Grant microphone access in system settings.
ModuleNotFoundError: No module named 'anthropic'	Provider SDK not installed	pip install akande[anthropic]. See the provider table above.
Invalid or missing OPENAI_API_KEY	Key not set or malformed	Ensure .env contains a valid sk- prefixed key.

Roadmap

• Streaming responses for reduced time-to-first-token
• Conversation memory with multi-turn context
• Markdown and HTML briefing output formats
• Plugin system for domain-specific briefing templates
• Docker image for single-command deployment

Trust

• 161 tests covering providers, caching, services, server, and utilities
• Apache 2.0 licence -- permissive, enterprise-friendly
• Euxis-audited architecture and security posture

Contributing

Pull requests are welcome. See CONTRIBUTING.md for guidelines.

License

This project is licensed under the Apache Software License -- see the LICENSE file for details.