v0.8.0 — OpenAI-Compatible Provider + Agent Invoke

What's New

OpenAI-Compatible LLM Provider

One adapter that unlocks the entire LLM ecosystem beyond Ollama and Vertex AI:

• OpenAI (GPT-4o, GPT-4o-mini)
• DeepSeek (V3.2 — $0.28/M input, great for agents)
• Hugging Face Inference (free tier available)
• OpenRouter (access any model)
• Together AI, Fireworks AI
• LM Studio, vLLM (local servers)

Auto-detects provider from environment variables — just set your API key and go:

# fozikio.json
llm: openai
llm_options:
  openai_model: deepseek-chat
# Set DEEPSEEK_API_KEY env var — base URL auto-detected

agent_invoke Tool

New MCP tool that dispatches tasks to a cortex-backed agent using your configured LLM:

1. Queries cortex for existing knowledge about the topic
2. Builds context-aware prompt with what's already known
3. Runs the LLM (Ollama, Gemini Flash, DeepSeek — whatever you configured)
4. Stores findings back into cortex as observations
5. Returns results with full provenance

This replaces expensive host-agent subagents with cheap, knowledge-accumulating cortex agents. Findings compound across sessions — the second time you research a topic, the agent already knows what it found last time.

cortex.agent_invoke({
  task: "Research FSRS scheduling algorithms",
  store_results: true
})

Why This Matters

The LLM provider + agent_invoke combination means cortex can now think on its own using cheap models, while the host agent (Claude, Gemini, etc.) focuses on complex reasoning. Background tasks, research, analysis — all at pennies per call instead of subscription tokens.

Breaking Changes

None. Existing ollama and gemini configurations continue to work unchanged.

Full Changelog

• feat: v0.8.0 — OpenAI-compatible LLM provider
• feat: agent_invoke tool — cortex-backed agent dispatch
• fix: dream abstraction truncation — increase token limit, validate completeness
• fix: reframe init output to emphasize modular namespace architecture