Text Generation
Transformers
Safetensors
qwen2
coder
code
agent
conversational
text-generation-inference
Instructions to use AdminReal/NexusCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdminReal/NexusCoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AdminReal/NexusCoder") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AdminReal/NexusCoder") model = AutoModelForCausalLM.from_pretrained("AdminReal/NexusCoder", device_map="auto") 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 AdminReal/NexusCoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AdminReal/NexusCoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AdminReal/NexusCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AdminReal/NexusCoder
- SGLang
How to use AdminReal/NexusCoder 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 "AdminReal/NexusCoder" \ --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": "AdminReal/NexusCoder", "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 "AdminReal/NexusCoder" \ --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": "AdminReal/NexusCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AdminReal/NexusCoder with Docker Model Runner:
docker model run hf.co/AdminReal/NexusCoder
File size: 7,608 Bytes
eca5751 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 | """
Code Coverage Tool - Run tests với coverage bằng coverage.py.
Author: Hieu Louis (2026)
Lazy import `coverage` package. Trả về coverage %, uncovered lines per file.
Hỗ trợ 2 report formats: text (default, parseable) và json (structured).
DANGEROUS (executes tests), requires_confirmation.
"""
from __future__ import annotations
import io
import json
import os
import shutil
import subprocess
from typing import Any, Dict, List, Optional
from .base import Tool, ToolResult, ToolContext, ToolCategory, ToolSafety
class CodeCoverageTool(Tool):
"""Run tests với coverage.py. Trả về coverage % và uncovered lines."""
category = ToolCategory.EXEC
safety = ToolSafety.DANGEROUS # executes tests
requires_confirmation = True
@property
def name(self) -> str:
return "code_coverage"
@property
def description(self) -> str:
return (
"Run tests với coverage.py. Trả về coverage %, uncovered lines per file. "
"Yêu cầu `coverage` package và pytest. Hỗ trợ text/json report."
)
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string", "description": "Thư mục source để đo coverage"},
"module": {
"type": "string",
"description": "Test module/path (vd 'tests/' hoặc 'test_x.py'). Mặc định 'tests/'.",
},
"source": {
"type": "string",
"description": "Package để đo coverage (mặc định = path)",
},
"report_format": {
"type": "string",
"enum": ["text", "json"],
"default": "text",
"description": "Report format",
},
},
"required": ["path"],
}
def validate_args(self, args: Dict[str, Any]) -> Optional[str]:
if not args.get("path"):
return "Missing required arg: path"
fmt = args.get("report_format", "text")
if fmt not in {"text", "json"}:
return f"Unsupported report_format: {fmt}. Chọn: ['text', 'json']"
return None
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
path: str = args["path"]
module: str = args.get("module", "tests/")
source: str = args.get("source", path)
report_format: str = args.get("report_format", "text")
if not os.path.exists(path):
return ToolResult(success=False, error=f"Path không tồn tại: {path}", return_code=1)
# Lazy import coverage
try:
import coverage # type: ignore
except ImportError as e:
return ToolResult(
success=False,
error=f"coverage not installed: {e}. Cài: pip install coverage",
return_code=127,
)
if context.dry_run:
return ToolResult(
success=True,
output=(
f"[dry-run] Sẽ chạy: coverage run --source={source} -m pytest {module}, "
f"sau đó report (format={report_format})"
),
metadata={"dry_run": True, "source": source, "module": module, "format": report_format},
)
# Locate pytest executable
pytest_cmd = shutil.which("pytest")
if not pytest_cmd:
pytest_cmd = shutil.which("python3")
if not pytest_cmd:
return ToolResult(
success=False,
error="pytest không tìm thấy trong PATH. Cài: pip install pytest",
return_code=127,
)
# Build pytest command
full_cmd: List[str] = [pytest_cmd]
if pytest_cmd.endswith("python3"):
full_cmd += ["-m", "pytest"]
full_cmd += ["-q", module]
# Run tests under coverage
cov = coverage.Coverage(source=[source])
cov.start()
try:
try:
cp = subprocess.run(
full_cmd,
capture_output=True,
text=True,
timeout=context.timeout,
cwd=context.working_dir or path,
env={**os.environ, **context.env},
)
except subprocess.TimeoutExpired:
# finally block below sẽ chạy cov.stop()/cov.save()
return ToolResult(
success=False,
error=f"Test timeout ({context.timeout}s)",
return_code=124,
metadata={"command": " ".join(full_cmd)},
)
finally:
cov.stop()
cov.save()
# Build report
try:
if report_format == "json":
buf = io.StringIO()
# cov.json_report writes to a file or stdout-like stream
cov.json_report(outfile=buf) # type: ignore[arg-type]
report_str = buf.getvalue()
try:
report_data = json.loads(report_str)
except json.JSONDecodeError:
return ToolResult(
success=False,
error="Không parse được JSON coverage report",
return_code=1,
)
totals = report_data.get("totals", {})
pct = float(totals.get("percent_covered", 0.0))
files_info: List[Dict[str, Any]] = []
for fname, finfo in report_data.get("files", {}).items():
summary = finfo.get("summary", {})
files_info.append({
"file": fname,
"covered": summary.get("covered_lines", 0),
"missing": summary.get("missing_lines", 0),
"percent": round(summary.get("percent_covered", 0.0), 2),
"missing_lines": finfo.get("missing_lines", []),
})
output = json.dumps(
{"totals": totals, "files": files_info},
indent=2, ensure_ascii=False,
)
else:
buf = io.StringIO()
cov.report(file=buf)
output = buf.getvalue()
# Parse TOTAL line for summary %
pct = 0.0
for line in output.splitlines():
if line.strip().startswith("TOTAL"):
parts = line.split()
if parts:
try:
pct = float(parts[-1].rstrip("%"))
except ValueError:
pass
except Exception as e:
return ToolResult(success=False, error=f"Report lỗi: {e}", return_code=1)
return ToolResult(
success=(cp.returncode == 0),
output=output,
error=cp.stderr if cp.stderr else None,
return_code=cp.returncode,
metadata={
"command": " ".join(full_cmd),
"source": source,
"module": module,
"coverage_pct": round(pct, 2),
"report_format": report_format,
"test_returncode": cp.returncode,
},
)
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