odidere/README.org

• odidere
  • Features
  • Limitations
  • Security
  • Requirements
  • Installation
  • Configuration
  • Deployment
  • API Endpoints
  • License

odidere

odidere is a voice assistant service that orchestrates speech-to-text (STT), large language model (LLM), and text-to-speech (TTS) services. It accepts audio or text input with attachments, transcribes speech via whisper-server, queries an OpenAI-compatible LLM (with optional tool calling), and returns synthesized audio via kokoro-fastapi.

This project is under active development and breaking changes are possible.

Features

• HTTP API and web UI for voice interaction
• Speech-to-text via whisper-server
• LLM queries via OpenAI-compatible API (hosted or local)
• Text-to-speech via kokoro-fastapi
• Configurable concurrency for serializing access to a GPU, or to allow parallel message processing
• Streaming responses via Server-Sent Events (SSE)
• Tools defined with YAML, parsed with Go templates, and executed as subprocesses

Limitations

• Tools do not support variadic arguments. The {{ json . }} template function may serve as a workaround when a tool accepts a JSON blob.
• Audio is base64 encoded in JSON requests and responses.

Security

odidere can expose its host to a variety of security risks:

• Denial-of-Service: local LLM inference consumes significant compute; hosted providers incur billing. Large audio files and frequent requests are another avenue of attack.
• Prompt injection (direct, indirect, and crescendo attacks)
• Unexpected costs (from tokens, tools, retries)
• Data exposure, if using a hosted LLM provider, or via manipulated tools.
• Arbitrary command execution and all its consequences, depending on the tools exposed.

Mitigations which a user can consider include:

• Constraining the runtime and sandboxing odidere
• Sandboxing tools (jails, containers)
• Opting for narrow tools over broad ones (e.g., scripts versus bash -c)
• Monitoring and constraining resource usage or LLM API costs
• Auditing logs
• Defensive system prompts that constrain model behavior
• Network isolation or authentication for the HTTP server

This software is provided as-is; refer to the license.

Requirements

• Go 1.25+
• An LLM server with OpenAI-compatible API (e.g., llama.cpp's llama-server)
• whisper-server for speech-to-text
• kokoro-fastapi for text-to-speech

Installation

From source:

git clone https://code.chimeric.al/odidere.git
cd odidere
make

The binary is written to bin/odidere.

To install to $GOBIN:

make install

Configuration

Environment variables can be referenced with ${VAR} syntax.

Reference config.example.yaml for all options.

Deployment

The path to the configuration file is required:

odidere -c ~/.config/odidere/config.yaml # or /etc/odidere/config.yaml

Example systemd service files for system or user-level services are in init/systemd/.

API Endpoints

• GET / — Web UI
• GET /status — Health check
• GET /static/* — Embedded static assets
• POST /v1/chat/voice — Voice API (JSON request/response with base64 audio)
• POST /v1/chat/voice/stream — Streaming voice API (SSE with incremental messages and audio)
• GET /v1/voices — List available TTS voices
• GET /v1/models — List available LLM models

License

MIT