crowe-logic 0.2.2

Crowe Logic. Universal AI Agent powered by CroweLM on Azure AI Foundry.

Crowe Logic

Universal AI agent powered by the CroweLM model stack on Azure AI Foundry. The default lineup now fronts gpt-5.4-pro as CroweLM Pro and claude-opus-4-6 as CroweLM Opus, alongside the existing CroweLM Core, Kernel, and GLM tiers.

Install

pip install crowe-logic

npm i @michaelcrowe11/crowe-logic

Setup

1. Deploy the CroweLM-backed Foundry models on Azure AI Foundry
2. Configure credentials:

cp .env.example .env
# Fill in the Azure endpoints and API keys for the CroweLM resources

3. Authenticate with Azure:

az login

4. Verify the model stack:

crowe-logic deploy

5. Start chatting:

crowe-logic

Usage

crowe-logic              # Interactive chat (default)
crowe-logic chat         # Interactive chat session
crowe-logic run "prompt" # Single prompt, get response
crowe-logic deploy       # Verify provider health across the CroweLM stack
crowe-logic models sync --account <account> --resource-group <resource-group>
crowe-logic status       # Show agent status
crowe-logic tools        # List available tools

CroweLM Pro is now wired to stream reasoning summaries through both the terminal UI and crowe-logic headless when the Azure Responses API emits them, so hosts that consume the JSON event stream can render reasoning deltas before answer tokens.

Extra Models

The base MODEL_CHAIN can now be extended without editing source. Crowe Logic will load extra model entries from:

• CROWE_LOGIC_EXTRA_MODELS_JSON
• CROWE_LOGIC_EXTRA_MODELS_PATH
• config/models.extra.json
• ~/.config/crowe-logic/models.extra.json
• ~/.crowe-logic/models.extra.json

Start from config/models.extra.example.json and save your generated file as config/models.extra.json, or point CROWE_LOGIC_EXTRA_MODELS_PATH at it.

If you already have Azure deployments and want to turn them into Foundry model entries, generate the file with:

crowe-logic models sync --account <account> --resource-group <resource-group>

By default that writes to ~/.config/crowe-logic/models.extra.json, which the runtime already loads. Use --output config/models.extra.json if you want a project-local registry instead.

You can also sync from a saved Azure CLI payload:

az cognitiveservices account deployment list --name <account> --resource-group <resource-group> --output json > deployments.json
crowe-logic models sync --input deployments.json --output config/models.extra.json

Tools (79)

Category	Tools	Description
Filesystem	4	Read, write, edit, list files and directories
Shell	1	Execute commands with timeout and working directory
Web & Search	3	Web search, grep/ripgrep, URL fetching
Git	5	Status, diff, log, commit, clone
Browser Automation	5	Playwright-based navigation, screenshots, interaction
macOS / AppleScript	3	System automation, app control, notifications
iTerm2	18	Windows, tabs, panes, broadcast, badges, colors, variables
Quantum Computing	4	QubitFlow circuits, Synapse evaluation, Trinity pipeline
Music Composition	11	Talon engine -- chords, drums, melody, emotion, quantum composition
Vision & Image	2	Multi-backend photo analysis (OpenRouter, Crowe Vision)
Video Generation	1	CroweLM Motion text/image-to-video on Azure AI Foundry
CroweLM Training	10	Dataset management, curation, fine-tuning pipeline
CroweLM Pipeline	4	Staging, promotion, agent runner, audit logs
Crowe Logic Platform	4	Chat, vision, grow logs, SOP generation
MCP Client	4	Search registry, list tools, call tools, stop servers

MCP Server

The Crowe Logic platform is also available as a standalone MCP server for any MCP client:

uvx crowe-logic-mcp

See crowe-logic-mcp for configuration details.

Specialized Agents

Agent	Focus
cultivation	Mushroom cultivation with Crowe Logic platform integration
quantum	Quantum computing with QubitFlow + Synapse + Trinity bridge
music	Music composition with Talon engine
code	General software development
research	Web research and analysis

Environment Variables

Variable	Description
PROJECT_ENDPOINT	Legacy Azure AI Foundry project endpoint
MODEL_DEPLOYMENT_NAME	Legacy Azure Agents deployment name
AZURE_CORE_ENDPOINT	Core CroweLM Azure OpenAI endpoint (gpt-5.4-pro, gpt-5.4-nano, Kimi-K2.5)
AZURE_CORE_API_KEY	API key for the core CroweLM Azure OpenAI endpoint
AZURE_ANTHROPIC_ENDPOINT	Azure Anthropic endpoint for claude-opus-4-6
AZURE_ANTHROPIC_API_KEY	API key for the Azure Anthropic endpoint
AZURE_GLM_ENDPOINT	Optional GLM endpoint (FW-GLM-5)
AZURE_GLM_API_KEY	API key for the GLM endpoint
AZURE_SORA_ENDPOINT	Optional dedicated CroweLM Motion endpoint; falls back to AZURE_CORE_ENDPOINT
AZURE_SORA_API_KEY	Optional dedicated CroweLM Motion API key; falls back to AZURE_CORE_API_KEY
AZURE_SORA_DEPLOYMENT_NAME	CroweLM Motion deployment name, usually sora-2
OPENROUTER_API_KEY	OpenRouter API key (vision fallback)
CROWE_LOGIC_URL	Crowe Logic platform URL
CROWE_LOGIC_KEY	Crowe Logic API key

Docker

docker pull michaelcrowe1111/crowe-logic:latest
docker run -it --env-file .env michaelcrowe1111/crowe-logic

GPU variant for fine-tuning:

docker build --target gpu -t crowe-logic:gpu .

Requirements

• Python 3.10+
• Azure AI Foundry account with gpt-5.4-pro and claude-opus-4-6 deployments
• Azure CLI (az login) for authentication

Author

Michael Crowe -- Crowe Logic, Inc.

License

MIT