Spaces:
Running
Running
File size: 13,628 Bytes
b49a7bf 51ee66c b49a7bf 51ee66c b49a7bf 51ee66c bd13718 b49a7bf 5a8d72d b49a7bf 51ee66c b49a7bf 51ee66c b49a7bf |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 |
"""
Shared utilities for HuggingFace Space Generator
Consolidated common functionality following Gradio best practices
"""
import os
import re
import json
import requests
import tempfile
from datetime import datetime
from typing import List, Dict, Tuple, Optional, Any
from urllib.parse import urlparse
from bs4 import BeautifulSoup
import gradio as gr
# Theme management following Gradio 5.x best practices
AVAILABLE_THEMES = {
"Default": gr.themes.Default(),
"Soft": gr.themes.Soft(),
"Glass": gr.themes.Glass(),
"Monochrome": gr.themes.Monochrome(),
"Base": gr.themes.Base(),
}
def get_theme(theme_name: str) -> gr.themes.Base:
"""Get a Gradio theme by name with safe fallback"""
return AVAILABLE_THEMES.get(theme_name, gr.themes.Default())
def validate_url_domain(url: str) -> bool:
"""Basic URL domain validation"""
try:
parsed = urlparse(url)
return bool(parsed.netloc and '.' in parsed.netloc)
except:
return False
def extract_urls_from_text(text: str) -> List[str]:
"""Extract and validate URLs from text"""
if not text:
return []
url_pattern = r'https?://[^\s<>"{}|\\^`\[\]"]+'
urls = re.findall(url_pattern, text)
# Validate and clean URLs
validated_urls = []
for url in urls:
# Remove trailing punctuation
url = url.rstrip('.,!?;:')
# Basic validation
if validate_url_domain(url) and len(url) > 10:
validated_urls.append(url)
return validated_urls
def fetch_url_content(url: str, timeout: int = 15, max_chars: int = 4000) -> str:
"""Enhanced URL content fetching with better error handling"""
if not validate_url_domain(url):
return f"Invalid URL format: {url}"
try:
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Language': 'en-US,en;q=0.5',
'Accept-Encoding': 'gzip, deflate',
'Connection': 'keep-alive'
}
response = requests.get(url, timeout=timeout, headers=headers)
response.raise_for_status()
# Parse content
soup = BeautifulSoup(response.content, 'html.parser')
# Remove non-content elements
for element in soup(["script", "style", "nav", "header", "footer", "aside", "form"]):
element.decompose()
# Extract main content
main_content = (
soup.find('main') or
soup.find('article') or
soup.find('div', class_=lambda x: bool(x and 'content' in x.lower())) or
soup
)
text = main_content.get_text()
# Clean text
lines = (line.strip() for line in text.splitlines())
chunks = (phrase.strip() for line in lines for phrase in line.split(" "))
text = ' '.join(chunk for chunk in chunks if chunk and len(chunk) > 2)
# Smart truncation
if len(text) > max_chars:
# Try to end at sentence boundary
truncated = text[:max_chars]
last_period = truncated.rfind('.')
if last_period > max_chars * 0.8:
text = truncated[:last_period + 1]
else:
text = truncated + "..."
return text if text.strip() else "No readable content found at this URL"
except requests.exceptions.Timeout:
return f"Timeout error fetching {url} ({timeout}s limit exceeded)"
except requests.exceptions.RequestException as e:
return f"Error fetching {url}: {str(e)}"
except Exception as e:
return f"Error processing content from {url}: {str(e)}"
def create_safe_filename(base_name: str, suffix: str = ".md", prefix: str = "",
include_timestamp: bool = True) -> str:
"""Create a safe filename with consistent sanitization"""
# Sanitize base name
safe_name = re.sub(r'[^\w\s-]', '', base_name.strip()) if base_name else "export"
safe_name = re.sub(r'[-\s]+', '_', safe_name)
# Add prefix if provided
if prefix:
safe_prefix = re.sub(r'[^\w\s-]', '', prefix.strip())
safe_prefix = re.sub(r'[-\s]+', '_', safe_prefix)
safe_name = f"{safe_prefix}_{safe_name}" if safe_name else safe_prefix
# Add timestamp if requested
if include_timestamp:
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
safe_name = f"{safe_name}_{timestamp}" if safe_name else f"export_{timestamp}"
# Ensure we have a valid name
if not safe_name:
safe_name = "export"
return f"{safe_name}{suffix}"
def export_conversation_to_markdown(history: List[Dict[str, str]],
config: Optional[Dict[str, Any]] = None) -> str:
"""Export conversation history to markdown format"""
if not history:
return "No conversation to export."
# Build header
markdown_content = f"""# Conversation Export
Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
"""
# Add configuration info if provided
if config:
markdown_content += f"""
Assistant: {config.get('name', 'AI Assistant')}
Model: {config.get('model', 'Unknown')}
"""
markdown_content += "\n---\n\n"
# Process messages
message_pair_count = 0
for message in history:
if isinstance(message, dict):
role = message.get('role', 'unknown')
content = message.get('content', '')
if role == 'user':
message_pair_count += 1
markdown_content += f"## User Message {message_pair_count}\n\n{content}\n\n"
elif role == 'assistant':
markdown_content += f"## Assistant Response {message_pair_count}\n\n{content}\n\n---\n\n"
return markdown_content
def process_file_upload(file_path: str, max_chars: int = 8000) -> str:
"""Process uploaded files using Gradio best practices"""
if not file_path or not os.path.exists(file_path):
return "β File not found"
try:
file_size = os.path.getsize(file_path)
file_name = os.path.basename(file_path)
_, ext = os.path.splitext(file_path.lower())
# Text file extensions
text_extensions = {
'.txt', '.md', '.markdown', '.rst',
'.py', '.js', '.jsx', '.ts', '.tsx', '.json', '.yaml', '.yml',
'.html', '.htm', '.xml', '.css', '.scss',
'.java', '.c', '.cpp', '.h', '.cs', '.go', '.rs',
'.sh', '.bash', '.log', '.csv', '.sql'
}
if ext in text_extensions:
with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
content = f.read(max_chars)
if len(content) == max_chars:
content += "\n... [truncated]"
return f"π **{file_name}** ({file_size:,} bytes)\n```{ext[1:]}\n{content}\n```"
# Special file types
elif ext == '.pdf':
return f"π **{file_name}** (PDF, {file_size:,} bytes)\nβ οΈ PDF support requires additional libraries"
elif ext in {'.jpg', '.jpeg', '.png', '.gif', '.webp'}:
return f"πΌοΈ **{file_name}** (Image, {file_size:,} bytes)"
elif ext in {'.xlsx', '.xls'}:
return f"π **{file_name}** (Spreadsheet, {file_size:,} bytes)"
elif ext in {'.zip', '.tar', '.gz', '.rar'}:
return f"ποΈ **{file_name}** (Archive, {file_size:,} bytes)"
else:
return f"π **{file_name}** ({ext or 'no extension'}, {file_size:,} bytes)"
except Exception as e:
return f"β Error processing file: {str(e)}"
class ConfigurationManager:
"""Manage configuration with validation and persistence"""
def __init__(self, default_config: Dict[str, Any]):
self.default_config = default_config
self.config_path = "config.json"
self.backup_dir = "config_backups"
def load_config(self) -> Dict[str, Any]:
"""Load configuration with fallback to defaults"""
try:
with open(self.config_path, 'r') as f:
config = json.load(f)
print("β
Loaded configuration from config.json")
return config
except FileNotFoundError:
print("βΉοΈ No config.json found, using defaults")
self.save_config(self.default_config)
return self.default_config.copy()
except Exception as e:
print(f"β οΈ Error loading config: {e}")
return self.default_config.copy()
def save_config(self, config: Dict[str, Any]) -> bool:
"""Save configuration with backup"""
try:
# Create backup
self._create_backup()
# Save new config
with open(self.config_path, 'w') as f:
json.dump(config, f, indent=2)
return True
except Exception as e:
print(f"β Error saving config: {e}")
return False
def _create_backup(self):
"""Create timestamped backup of current config"""
try:
if os.path.exists(self.config_path):
os.makedirs(self.backup_dir, exist_ok=True)
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
backup_path = os.path.join(self.backup_dir, f"config_{timestamp}.json")
with open(self.config_path, 'r') as source:
with open(backup_path, 'w') as dest:
dest.write(source.read())
# Keep only last 10 backups
self._cleanup_old_backups()
except Exception as e:
print(f"Warning: Could not create backup: {e}")
def _cleanup_old_backups(self):
"""Remove old backup files, keeping only the most recent 10"""
try:
backups = sorted([
f for f in os.listdir(self.backup_dir)
if f.endswith('.json')
])
if len(backups) > 10:
for old_backup in backups[:-10]:
os.remove(os.path.join(self.backup_dir, old_backup))
except Exception:
pass
def validate_config(self, config: Dict[str, Any]) -> Tuple[bool, str]:
"""Validate configuration structure and values"""
required_fields = ['name', 'description', 'system_prompt', 'model',
'temperature', 'max_tokens', 'api_key_var']
# Check required fields
for field in required_fields:
if field not in config:
return False, f"Missing required field: {field}"
# Validate temperature
if not (0 <= config.get('temperature', 0.7) <= 2):
return False, "Temperature must be between 0 and 2"
# Validate max_tokens
if not (50 <= config.get('max_tokens', 750) <= 4096):
return False, "Max tokens must be between 50 and 4096"
return True, "Configuration is valid"
# Model definitions with metadata
AVAILABLE_MODELS = [
# Google models
{
"id": "google/gemini-2.0-flash-001",
"name": "Gemini 2.0 Flash",
"description": "Fast, reliable for general tasks"
},
{
"id": "google/gemma-3-27b-it",
"name": "Gemma 3 27B",
"description": "High-performance open model"
},
# Anthropic models
{
"id": "anthropic/claude-3.5-sonnet",
"name": "Claude 3.5 Sonnet",
"description": "Superior reasoning and analysis"
},
{
"id": "anthropic/claude-3.5-haiku",
"name": "Claude 3.5 Haiku",
"description": "Fast, efficient Claude model"
},
# OpenAI models
{
"id": "openai/gpt-4o-mini",
"name": "GPT-4o Mini",
"description": "Fast, cost-effective GPT-4o variant"
},
{
"id": "openai/gpt-4o-mini-search-preview",
"name": "GPT-4o Mini Search",
"description": "GPT-4o with search capabilities"
},
{
"id": "openai/gpt-oss-120b",
"name": "GPT-OSS 120B",
"description": "Open source GPT model"
},
# MistralAI models
{
"id": "mistralai/mistral-medium-3",
"name": "Mistral Medium 3",
"description": "Balanced performance and efficiency"
},
# DeepSeek models
{
"id": "deepseek/deepseek-r1-distill-qwen-32b",
"name": "DeepSeek R1 Distill Qwen 32B",
"description": "Efficient distilled model"
},
# NVIDIA models
{
"id": "nvidia/llama-3.1-nemotron-70b-instruct",
"name": "Llama 3.1 Nemotron 70B",
"description": "NVIDIA-optimized Llama"
},
# Qwen models
{
"id": "qwen/qwen3-30b-a3b-instruct-2507",
"name": "Qwen3 30B",
"description": "Alibaba's multilingual model"
}
]
def get_model_choices() -> List[str]:
"""Get list of available model IDs"""
return [model["id"] for model in AVAILABLE_MODELS]
def get_model_info(model_id: str) -> Dict[str, str]:
"""Get information about a specific model"""
for model in AVAILABLE_MODELS:
if model["id"] == model_id:
return model
return {"id": model_id, "name": model_id, "description": "Custom model"} |