Instructions to use my-ai-stack/Stack-2-9-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use my-ai-stack/Stack-2-9-finetuned with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="my-ai-stack/Stack-2-9-finetuned")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-2-9-finetuned")
model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-2-9-finetuned")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use my-ai-stack/Stack-2-9-finetuned with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "my-ai-stack/Stack-2-9-finetuned"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/my-ai-stack/Stack-2-9-finetuned

SGLang

How to use my-ai-stack/Stack-2-9-finetuned with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "my-ai-stack/Stack-2-9-finetuned" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "my-ai-stack/Stack-2-9-finetuned" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "my-ai-stack/Stack-2-9-finetuned",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use my-ai-stack/Stack-2-9-finetuned with Docker Model Runner:
```
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
```

Stack-2-9-finetuned / stack /docs /archive /STACK_CLI_README.md

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Stack 2.9 CLI & Agent Interface

A powerful command-line interface and agent that showcases Stack 2.9 capabilities. Features interactive chat, command execution, voice input, and comprehensive tool support.

Features

Interactive Chat Mode: Conversational interface with the agent
Command Execution: Run single commands and get results
Voice Input Support (requires setup): Speech-to-text interaction
37 Built-in Tools: File ops, git, code execution, web search, memory, planning
Context Awareness: Project scanning and memory integration
Self-Reflection: Agent evaluates and improves its own responses
Multi-mode Operation: Chat, command-line, or voice interfaces

Quick Start

Installation

cd /Users/walidsobhi/.openclaw/workspace/stack-2.9
pip install -e .

Basic Usage

Interactive Chat:

stack

Single Command:

stack -c "read README.md"

Execute Specific Tools:

stack -t git_status project_scan

Voice Mode (requires setup):

stack -v

Modes

1. Interactive Chat Mode

Start a conversation with the agent:

stack

Commands in chat mode:

/tools - List tools used in current session
/schema - Show tool schemas
/context - Show current workspace context
/history - Show conversation history
/clear - Clear history
/voice - Toggle voice input
/exit - Exit

2. Command Mode

Execute a single query:

stack -c "list my tasks"
stack -c "search for *.py files"
stack -c "git status"

3. Tool Mode

Execute specific tools directly:

stack -t read project_scan memory_list

4. Voice Mode

Use voice input/output (requires SpeechRecognition and pyttsx3):

pip install SpeechRecognition pyttsx3 pyaudio
stack -v

Tool Categories

File Operations

read - Read file contents
write - Write to file
edit - Edit file with text replacement
search - Search for files
grep - Search patterns in files
copy - Copy files/directories
move - Move/rename files
delete - Delete files

Git Operations

git_status - Get git status
git_commit - Create commit
git_push - Push to remote
git_pull - Pull from remote
git_branch - Manage branches
git_log - View commit history
git_diff - Show changes

Code Execution

run - Run shell commands
test - Run tests (pytest)
lint - Lint code (ruff/pylint/mypy)
format - Format code (ruff/black)
typecheck - Type checking (mypy)
server - Start development server
install - Install dependencies

Web Tools

web_search - Search the web
fetch - Fetch URL content
download - Download files
check_url - Check URL accessibility
screenshot - Take webpage screenshot

Memory & Context

memory_recall - Search memory
memory_save - Save to memory
memory_list - List memory entries
context_load - Load project context
project_scan - Scan project structure

Task Planning

create_task - Create a task
list_tasks - List tasks
update_task - Update task status
delete_task - Delete task
create_plan - Create execution plan
execute_plan - Execute plan

Query Examples

File operations:

"read main.py"
"show me the contents of README.md"
"create a file called notes.txt with 'Hello World'"

Git operations:

"git status"
"commit with message 'update'"
"push to origin main"

Code execution:

"run pytest"
"lint the code"
"format all files"

Web search:

"search the web for Python async best practices"
"look up how to use FastAPI"
"fetch https://example.com"

Memory:

"remember that the API key is in .env"
"what do you remember about this project?"
"list all memories"

Tasks:

"create task: implement login"
"list my tasks"
"complete task abc123"

Architecture

stack-2.9/
├── stack_cli/
│   ├── __init__.py      # Package init
│   ├── cli.py           # CLI entry point
│   ├── agent.py         # Core agent logic
│   ├── tools.py         # 37 built-in tools
│   └── context.py       # Context management
├── stack.py             # Main entry script
├── pyproject.toml       # Package config
└── requirements.txt     # Dependencies

Setup

Install dependencies:

pip install -e .

(Optional) Install voice dependencies:

pip install SpeechRecognition pyttsx3 pyaudio

Run the CLI:

stack

Customization

Configure workspace context in AGENTS.md, SOUL.md, TOOLS.md
Long-term memory stored in MEMORY.md and memory/ folder
Session files in .tasks.json and .plans.json

License

MIT