Text Generation
Transformers
English
qwen2
code-generation
python
fine-tuning
Qwen
tools
agent-framework
multi-agent
conversational
Eval Results (legacy)
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
- Transformers
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
- 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
File size: 16,175 Bytes
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"""Comprehensive audit script for Stack 2.9 tools and skills.
This script:
1. Imports all tools and skills
2. Tests each tool with appropriate test input
3. Measures execution time
4. Reports pass/fail status
"""
import asyncio
import json
import sys
import time
import traceback
from datetime import datetime
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional
# Ensure proper imports
sys.path.insert(0, '/Users/walidsobhi/stack-2.9/src')
# Import tools module (triggers registration)
import tools
from tools.base import BaseTool, ToolResult
from tools.registry import get_registry
# Test input definitions for each tool
TOOL_TEST_INPUTS: Dict[str, Dict[str, Any]] = {
# File tools
"file_read": {"path": "/Users/walidsobhi/stack-2.9/audit_tools.py"},
"file_exists": {"path": "/Users/walidsobhi/stack-2.9/audit_tools.py"},
"file_write": {"path": "/tmp/audit_test.txt", "content": "Test content from audit"},
"file_edit": {
"file_path": "/tmp/audit_test_edit.txt",
"old_string": "old content",
"new_string": "new content",
"replace_all": False
},
"glob": {"pattern": "**/*.py", "path": "/Users/walidsobhi/stack-2.9/src"},
"grep": {"pattern": "def ", "path": "/Users/walidsobhi/stack-2.9/src/tools"},
# Web tools
"WebSearch": {"query": "Python testing"},
"WebFetch": {"url": "https://example.com", "prompt": "Extract the main heading"},
# Task tools
"task_create": {"subject": "Test task", "description": "Test description", "activeForm": "Testing"},
"task_list": {},
"task_update": {"taskId": "nonexistent", "status": "completed"},
"task_get": {"taskId": "test"},
# Todo tools
"todo_list": {},
"todo_add": {"content": "Test todo item"},
"todo_complete": {"item_id": "test"},
"todo_delete": {"item_id": "test"},
# Config tools
"config_get": {"key": "test.key"},
"config_set": {"key": "test.key", "value": "test_value"},
# Team tools
"team_list": {},
"team_create": {"team_name": "test_team", "members": ["user1"]},
"team_delete": {"team_name": "test_team"},
# Skill tools
"skill_list": {},
"skill_search": {"query": "test"},
"skill_info": {"skill_name": "nonexistent"},
"skill_execute": {"skill_name": "nonexistent"},
"skill_chain": {"skills": []},
# Scheduling
"schedule_list": {},
"schedule_add": {"title": "Test event", "time": "2025-01-01T10:00:00"},
"schedule_delete": {"event_id": "test"},
# Messaging
"message_send": {"recipient": "test_user", "message": "Test message"},
"message_list": {},
# Brief tool
"brief_generate": {"content": "This is test content for the brief tool."},
# Ask question
"ask_question": {"question": "What is 2+2?"},
# Sleep tool
"sleep": {"seconds": 0.1},
# Plan mode
"plan_create": {"prompt": "Create a test plan"},
"plan_execute": {"plan_id": "test"},
# MCP tool
"mcp_list": {},
"mcp_invoke": {"server": "test", "method": "test"},
# Worktree tool
"worktree_list": {},
"worktree_create": {"name": "test-branch", "base": "main"},
"worktree_remove": {"name": "test-branch"},
# Remote trigger
"remote_trigger_execute": {"target": "test-target", "action": "ping"},
"remote_trigger_status": {"job_id": "test"},
# Agent tool
"agent_execute": {"task": "Test task", "context": {}},
"agent_status": {"job_id": "test"},
# Synthetic output
"synthetic_generate": {"prompt": "Generate test data", "format": "json"},
# Tool discovery
"tool_discover": {"query": "file"},
"tool_search": {"pattern": "file"},
# Config
"config_list": {},
"config_delete": {"key": "test.key"},
}
def get_test_input(tool_name: str) -> Optional[Dict[str, Any]]:
"""Get test input for a specific tool."""
return TOOL_TEST_INPUTS.get(tool_name)
class AuditResult:
"""Result of auditing a single tool."""
def __init__(
self,
tool_name: str,
load_success: bool = False,
execution_success: bool = False,
response_time: float = 0.0,
error: str = "",
data: Any = None,
):
self.tool_name = tool_name
self.load_success = load_success
self.execution_success = execution_success
self.response_time = response_time
self.error = error
self.data = data
self.timestamp = datetime.now().isoformat()
def to_dict(self) -> Dict[str, Any]:
return {
"tool_name": self.tool_name,
"load_success": self.load_success,
"execution_success": self.execution_success,
"response_time": self.response_time,
"error": self.error,
"data": self.data,
"timestamp": self.timestamp,
}
async def test_tool_async(tool: BaseTool, test_input: Dict[str, Any]) -> AuditResult:
"""Test a tool with async execution."""
result = AuditResult(tool_name=tool.name, load_success=True)
try:
start_time = time.perf_counter()
# Check if tool has async execute method
if asyncio.iscoroutinefunction(tool.execute):
result_data = await tool.execute(**test_input)
else:
result_data = tool.execute(**test_input)
result.response_time = time.perf_counter() - start_time
# Check if result is a ToolResult
if isinstance(result_data, ToolResult):
result.execution_success = result_data.success
result.error = result_data.error or ""
result.data = result_data.data
else:
# Handle non-ToolResult returns
result.execution_success = True
result.data = result_data
except Exception as e:
result.response_time = time.perf_counter() - start_time
result.execution_success = False
result.error = f"{type(e).__name__}: {str(e)}"
result.data = traceback.format_exc()
return result
def test_tool_sync(tool: BaseTool, test_input: Dict[str, Any]) -> AuditResult:
"""Test a tool with sync execution."""
result = AuditResult(tool_name=tool.name, load_success=True)
try:
start_time = time.perf_counter()
result_data = tool.execute(**test_input)
result.response_time = time.perf_counter() - start_time
# Check if result is a ToolResult
if isinstance(result_data, ToolResult):
result.execution_success = result_data.success
result.error = result_data.error or ""
result.data = result_data.data
else:
result.execution_success = True
result.data = result_data
except Exception as e:
result.response_time = time.perf_counter() - start_time
result.execution_success = False
result.error = f"{type(e).__name__}: {str(e)}"
result.data = traceback.format_exc()
return result
def test_tool_call_method(tool: BaseTool, test_input: Dict[str, Any]) -> AuditResult:
"""Test a tool using the call method."""
result = AuditResult(tool_name=tool.name, load_success=True)
try:
start_time = time.perf_counter()
result_data = tool.call(test_input)
result.response_time = time.perf_counter() - start_time
if isinstance(result_data, ToolResult):
result.execution_success = result_data.success
result.error = result_data.error or ""
result.data = result_data.data
else:
result.execution_success = True
result.data = result_data
except Exception as e:
result.response_time = time.perf_counter() - start_time
result.execution_success = False
result.error = f"{type(e).__name__}: {str(e)}"
result.data = traceback.format_exc()
return result
async def audit_tool(tool: BaseTool) -> AuditResult:
"""Audit a single tool."""
tool_name = tool.name
# Get test input for this tool
test_input = get_test_input(tool_name)
if not test_input:
# Use empty dict as default
test_input = {}
# Try different execution methods
try:
# First try the call method which handles timing and validation
return test_tool_call_method(tool, test_input)
except Exception as e:
# If call method fails, try async execute
if asyncio.iscoroutinefunction(tool.execute):
try:
return await test_tool_async(tool, test_input)
except Exception as e2:
return AuditResult(
tool_name=tool_name,
load_success=True,
execution_success=False,
error=f"Async execute failed: {type(e2).__name__}: {str(e2)}"
)
else:
# Try sync execute
try:
return test_tool_sync(tool, test_input)
except Exception as e2:
return AuditResult(
tool_name=tool_name,
load_success=True,
execution_success=False,
error=f"Sync execute failed: {type(e2).__name__}: {str(e2)}"
)
async def audit_tools() -> List[AuditResult]:
"""Audit all registered tools."""
registry = get_registry()
tool_names = registry.list()
print(f"\n{'='*60}")
print(f"STACK 2.9 TOOLS AUDIT")
print(f"{'='*60}")
print(f"Found {len(tool_names)} registered tools:")
for name in sorted(tool_names):
print(f" - {name}")
results = []
for tool_name in tool_names:
tool = registry.get(tool_name)
if tool is None:
print(f"\n[ERROR] Tool '{tool_name}' not found in registry")
continue
print(f"\n[TESTING] {tool_name}...", end=" ", flush=True)
result = await audit_tool(tool)
results.append(result)
if result.execution_success:
print(f"PASS ({result.response_time:.4f}s)")
else:
print(f"FAIL ({result.response_time:.4f}s)")
if result.error:
error_preview = result.error[:100] if len(result.error) > 100 else result.error
print(f" Error: {error_preview}")
return results
def check_skills() -> Dict[str, Any]:
"""Check for available skills."""
from tools.skill_tool import _discover_skills, SKILLS_FILE, SKILL_DIRS
print(f"\n{'='*60}")
print(f"SKILLS CHECK")
print(f"{'='*60}")
skills_info = {
"skills_file": str(SKILLS_FILE),
"skills_file_exists": SKILLS_FILE.exists(),
"skill_dirs": [str(d) for d in SKILL_DIRS],
"skill_dirs_exist": [d.exists() for d in SKILL_DIRS],
"discovered_skills": [],
}
try:
discovered = _discover_skills()
skills_info["discovered_skills"] = discovered
print(f"Discovered {len(discovered)} skills from directories")
for skill in discovered:
print(f" - {skill['name']}: {skill.get('description', 'No description')[:50]}")
except Exception as e:
print(f"Error discovering skills: {e}")
skills_info["error"] = str(e)
return skills_info
def generate_report(results: List[AuditResult], skills_info: Dict[str, Any]) -> str:
"""Generate a comprehensive audit report."""
# Calculate statistics
total_tools = len(results)
passed = sum(1 for r in results if r.execution_success)
failed = total_tools - passed
response_times = [r.response_time for r in results if r.response_time > 0]
avg_response_time = sum(response_times) / len(response_times) if response_times else 0
min_response_time = min(response_times) if response_times else 0
max_response_time = max(response_times) if response_times else 0
report = f"""
================================================================================
STACK 2.9 COMPREHENSIVE AUDIT REPORT
================================================================================
Generated: {datetime.now().isoformat()}
--------------------------------------------------------------------------------
TOOLS SUMMARY
--------------------------------------------------------------------------------
Total Tools Tested: {total_tools}
Passed: {passed}
Failed: {failed}
Pass Rate: {passed/total_tools*100:.1f}%
--------------------------------------------------------------------------------
RESPONSE TIME STATISTICS
--------------------------------------------------------------------------------
Average Response Time: {avg_response_time:.4f}s
Minimum Response Time: {min_response_time:.4f}s
Maximum Response Time: {max_response_time:.4f}s
--------------------------------------------------------------------------------
DETAILED RESULTS
--------------------------------------------------------------------------------
"""
# Sort results by tool name
sorted_results = sorted(results, key=lambda x: x.tool_name)
for result in sorted_results:
status = "PASS" if result.execution_success else "FAIL"
report += f"""
Tool: {result.tool_name}
Status: {status}
Load Success: {result.load_success}
Response Time: {result.response_time:.4f}s
"""
if result.error:
error_lines = result.error.split('\n')
report += f" Error: {error_lines[0]}\n"
# Skills section
report += f"""
--------------------------------------------------------------------------------
SKILLS SUMMARY
--------------------------------------------------------------------------------
Skills File: {skills_info.get('skills_file', 'N/A')}
Skills File Exists: {skills_info.get('skills_file_exists', False)}
Skill Directories:
"""
for i, (dir_exists, dir_path) in enumerate(zip(skills_info.get('skill_dirs_exist', []), skills_info.get('skill_dirs', []))):
status = "EXISTS" if dir_exists else "MISSING"
report += f" [{status}] {dir_path}\n"
discovered = skills_info.get('discovered_skills', [])
report += f"""
Discovered Skills: {len(discovered)}
"""
for skill in discovered:
report += f" - {skill['name']}: {skill.get('description', 'N/A')[:50]}\n"
if skills_info.get('error'):
report += f"""
Skills Error: {skills_info['error']}
"""
# Final summary
report += f"""
================================================================================
END OF AUDIT REPORT
================================================================================
"""
return report
async def main():
"""Main audit function."""
print("\nStarting Stack 2.9 Comprehensive Audit...")
print(f"Working directory: /Users/walidsobhi/stack-2.9")
# Audit all tools
results = await audit_tools()
# Check skills
skills_info = check_skills()
# Generate and print report
report = generate_report(results, skills_info)
print(report)
# Save report to file
report_path = "/Users/walidsobhi/stack-2.9/audit_report.txt"
with open(report_path, 'w') as f:
f.write(report)
print(f"\nReport saved to: {report_path}")
# Save JSON results
json_results = {
"timestamp": datetime.now().isoformat(),
"total_tools": len(results),
"passed": sum(1 for r in results if r.execution_success),
"failed": sum(1 for r in results if not r.execution_success),
"tools": [r.to_dict() for r in results],
"skills": skills_info,
}
json_path = "/Users/walidsobhi/stack-2.9/audit_results.json"
with open(json_path, 'w') as f:
json.dump(json_results, f, indent=2)
print(f"JSON results saved to: {json_path}")
# Return exit code based on failures
failed_count = sum(1 for r in results if not r.execution_success)
return failed_count
if __name__ == "__main__":
failed = asyncio.run(main())
sys.exit(0 if failed == 0 else 1) |