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)# pip install -U transformers accelerate # 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=256) 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: 8,872 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 | """
PDF Generator Tool - Sinh PDF từ text/HTML/markdown.
===========================================
Tool sinh PDF từ nội dung text thuần, HTML hoặc Markdown.
Backend: `reportlab` (text/markdown trực tiếp) hoặc `weasyprint` (HTML→PDF).
Author: Hieu Louis (2026)
"""
from __future__ import annotations
import os
import subprocess
from typing import Any, Dict, Optional
from .base import Tool, ToolResult, ToolContext, ToolCategory, ToolSafety
PAGE_SIZES = {"A4", "A3", "LETTER", "LEGAL"}
class PDFGeneratorTool(Tool):
"""Sinh PDF từ text/HTML/markdown content."""
category = ToolCategory.CONVERT
safety = ToolSafety.MODERATE
requires_confirmation = True
@property
def name(self) -> str:
return "pdf_generator"
@property
def description(self) -> str:
return "Sinh PDF từ text/HTML/markdown. Backend: reportlab (text/md) hoặc weasyprint (HTML)."
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"content": {"type": "string", "description": "Nội dung cần convert"},
"output_path": {"type": "string", "description": "Đường dẫn file PDF output"},
"format": {
"type": "string",
"enum": ["text", "html", "markdown"],
"default": "text",
},
"page_size": {
"type": "string",
"enum": sorted(PAGE_SIZES),
"default": "A4",
},
"title": {"type": "string", "description": "Metadata title của PDF"},
"author": {"type": "string", "description": "Metadata author của PDF"},
},
"required": ["content", "output_path"],
}
def validate_args(self, args: Dict[str, Any]) -> Optional[str]:
if not args.get("content"):
return "Missing required arg: content"
if not args.get("output_path"):
return "Missing required arg: output_path"
page = args.get("page_size", "A4")
if page not in PAGE_SIZES:
return f"Invalid page_size='{page}'. Supported: {sorted(PAGE_SIZES)}"
return None
# ---- Backends -------------------------------------------------------
def _gen_reportlab(
self,
content: str,
output_path: str,
fmt: str,
page_size: str,
title: Optional[str],
author: Optional[str],
) -> ToolResult:
"""Sinh PDF bằng reportlab (plaintext hoặc markdown đơn giản)."""
try:
from reportlab.lib.pagesizes import A4, A3, letter, legal # type: ignore
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer # type: ignore
from reportlab.lib.styles import getSampleStyleSheet # type: ignore
from reportlab.lib.units import inch # type: ignore # noqa: F401
from reportlab.lib import colors # type: ignore # noqa: F401
except ImportError:
return ToolResult(
success=False,
error="reportlab chưa cài. Cài đặt: pip install reportlab",
return_code=127,
)
size_map = {"A4": A4, "A3": A3, "LETTER": letter, "LEGAL": legal}
try:
doc = SimpleDocTemplate(
output_path,
pagesize=size_map[page_size],
title=title or "Nexus PDF",
author=author or "Nexus Coder",
)
styles = getSampleStyleSheet()
story = []
if fmt == "markdown":
# Parse markdown rất cơ bản: ## → Heading2, # → Heading1, else Paragraph
for line in content.split("\n"):
stripped = line.strip()
if not stripped:
story.append(Spacer(1, 6))
elif stripped.startswith("# "):
story.append(Paragraph(stripped[2:], styles["Heading1"]))
elif stripped.startswith("## "):
story.append(Paragraph(stripped[3:], styles["Heading2"]))
elif stripped.startswith("### "):
story.append(Paragraph(stripped[4:], styles["Heading3"]))
else:
# Escape XML chars / escape XML special chars
safe = stripped.replace("&", "&").replace("<", "<").replace(">", ">")
story.append(Paragraph(safe, styles["Normal"]))
else:
for line in content.split("\n"):
safe = line.replace("&", "&").replace("<", "<").replace(">", ">") or " "
story.append(Paragraph(safe, styles["Normal"]))
doc.build(story)
return ToolResult(
success=True,
output=f"PDF generated → {output_path}",
artifacts=[output_path],
metadata={"backend": "reportlab", "page_size": page_size, "format": fmt},
)
except Exception as e:
return ToolResult(success=False, error=f"reportlab build failed: {e}", return_code=1)
def _gen_weasyprint(self, html_content: str, output_path: str, page_size: str, title: Optional[str], author: Optional[str]) -> ToolResult:
"""Sinh PDF từ HTML bằng weasyprint."""
try:
from weasyprint import HTML # type: ignore
except ImportError:
return ToolResult(
success=False,
error="weasyprint chưa cài. Cài đặt: pip install weasyprint",
return_code=127,
)
try:
html_obj = HTML(string=html_content)
html_obj.write_pdf(output_path)
return ToolResult(
success=True,
output=f"PDF generated → {output_path}",
artifacts=[output_path],
metadata={"backend": "weasyprint", "page_size": page_size, "format": "html"},
)
except Exception as e:
return ToolResult(success=False, error=f"weasyprint build failed: {e}", return_code=1)
# ---- Execute --------------------------------------------------------
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
content = args["content"]
output_path = args["output_path"]
fmt = args.get("format", "text")
page_size = args.get("page_size", "A4")
title = args.get("title")
author = args.get("author")
if context.dry_run:
return ToolResult(
success=True,
output=f"[dry-run] Sẽ sinh PDF ({fmt}, {page_size}) → {output_path} ({len(content)} chars)",
metadata={"output_path": output_path, "format": fmt, "page_size": page_size, "dry_run": True},
)
# Đảm bảo thư mục cha tồn tại / ensure parent dir exists
parent = os.path.dirname(os.path.abspath(output_path))
os.makedirs(parent, exist_ok=True)
if fmt == "html":
return self._gen_weasyprint(content, output_path, page_size, title, author)
if fmt == "markdown":
# Thử pandoc trước (chất lượng cao) / try pandoc first
import shutil
if shutil.which("pandoc"):
tmp_md = os.path.join(parent, f".nexus_pdf_{os.getpid()}.md")
try:
with open(tmp_md, "w", encoding="utf-8") as f:
f.write(content)
cmd = ["pandoc", tmp_md, "-f", "markdown", "-t", "pdf", "-o", output_path, "-V", f"geometry:{page_size}paper"]
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=context.timeout, check=False)
if proc.returncode == 0:
return ToolResult(
success=True,
output=f"PDF generated (pandoc) → {output_path}",
artifacts=[output_path],
metadata={"backend": "pandoc", "format": "markdown"},
)
# pandoc fail → fallback reportlab
except subprocess.TimeoutExpired:
return ToolResult(success=False, error="pandoc timeout", return_code=124)
finally:
if os.path.exists(tmp_md):
os.remove(tmp_md)
return self._gen_reportlab(content, output_path, fmt, page_size, title, author)
# format == "text"
return self._gen_reportlab(content, output_path, fmt, page_size, title, author)
|