galet

Provider-agnostic LLM, embedding, and image generation stack.

Lineage

This package is extracted from the Lucy monorepo (src/llm) as described in the Lucy design doc software/ai/lucy/design/llm-module-extraction.md.

It is a fresh repository with no shared git history. The extracted module's behaviour, public interface, optional-SDK import fallbacks, and no-fail-on-missing-credential semantics are preserved as-is; the only intentional change is the configuration boundary (see settings.py).

Features

• Chat / completions — provider-agnostic create_response with temperature, tool calling, and response metadata. Providers: OpenAI, DeepSeek, Gemini, Mistral, Ollama.
• Routing — explicit provider argument, or automatic model-name prefix routing with OpenAI fallback. Connectors self-register their name, model-name prefixes, and default model with ProviderRegistry.
• Tool calling — bounded tool loop; tools own name(), tool_def(), result_schema(), and execute().
• Image generation — OpenAI (dall-e-*, gpt-image-*) and Gemini (gemini-*, imagen-*) backends behind a common interface.
• Image description — vision-capable models describe images sent inline (base64, no upload).
• Embeddings — OpenAI and Mistral embedding adapters.
• Optional SDKs — imports degrade gracefully when a provider SDK is not installed; missing credentials never raise at import or call time.

Quick start

python -m venv .venv
.venv/bin/pip install -e .

Runnable examples live in samples/:

See samples/README.md for each script's full usage.

Configuration

galet needs two pieces of configuration, and both can be set with an environment variable or a command-line flag.

Credentials (API keys)

Only non-Ollama providers need an API key. galet resolves a key in this order:

1. The provider's own environment variable (OPENAI_API_KEY, DEEPSEEK_API_KEY, GEMINI_API_KEY, MISTRAL_API_KEY).
2. A credential file in the directory named by --credential-path, or the GALET_CREDENTIAL_PATH environment variable when no flag is given.

Credential file names:

Example credential file (oaicred.json):

{"openai_api_key": "sk-..."}

python samples/send_request.py --credential-path /path/to/credentials --provider openai "hi"
GALET_CREDENTIAL_PATH=/path/to/credentials python samples/send_request.py --provider openai "hi"

Ollama base URL

Ollama needs no API key, but galet must know where the Ollama server is. galet resolves the address in this order:

1. --ollama-base-url (command-line flag)
2. OLLAMA_BASE_URL (environment variable)
3. http://localhost:11434/v1 (default, Ollama's OpenAI-compatible endpoint)

# Default local Ollama
python samples/send_request.py --provider ollama "hi"

# Explicit URL
python samples/send_request.py --provider ollama --ollama-base-url http://localhost:11434/v1 "hi"

# Environment variable
OLLAMA_BASE_URL=http://192.168.87.40:11434/v1 python samples/send_request.py --provider ollama "hi"

Note the /v1 suffix: galet talks to Ollama's OpenAI-compatible endpoint, not the native Ollama API.