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refactor: Update workflow plan system and template organization

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- Remove --analyze|--deep parameters from plan.md, use default analysis
- Change .analysis to .process directory structure for better organization
- Create ANALYSIS_RESULTS.md template focused on verified results
- Add .process folder to workflow-architecture.md file structure
- Template emphasizes verification of files, methods, and commands
- Prevent execution errors from non-existent references

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
catlog22
2025-09-18 16:26:50 +08:00
parent 9167e4e39e
commit fc6e851230
49 changed files with 5865 additions and 174 deletions
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51
.claude/commands/workflow/plan.md
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@@ -13,7 +13,7 @@ examples:
## Usage
```bash
/workflow:plan [--AM gemini|codex] [--analyze|--deep] <input>
/workflow:plan <input>
```
## Input Detection
@@ -21,20 +21,37 @@ examples:
- **Issues**: `ISS-*`, `ISSUE-*`, `*-request-*` → Loads issue data and acceptance criteria
- **Text**: Everything else → Parses natural language requirements
## Analysis Levels
- **Quick** (default): Structure only (5s)
- **--analyze**: Structure + context analysis (30s)
- **--deep**: Structure + comprehensive parallel analysis (1-2m)
## Default Analysis Workflow
### Automatic Intelligence Selection
The command automatically performs comprehensive analysis by:
1. **Context Gathering**: Reading relevant CLAUDE.md documentation based on task requirements
2. **Task Assignment**: Automatically assigning Task agents based on complexity:
- **Simple tasks** (≤3 modules): Direct CLI tools (`~/.claude/scripts/gemini-wrapper` or `codex --full-auto exec`)
- **Complex tasks** (>3 modules): Task agents with integrated CLI tool access
3. **Process Documentation**: Generates analysis artifacts in `.workflow/WFS-[session]/.process/ANALYSIS_RESULTS.md`
4. **Flow Control Integration**: Automatic tool selection managed by flow_control system
### Analysis Artifacts Generated
- **ANALYSIS_RESULTS.md**: Documents context analysis, codebase structure, pattern identification, and task decomposition results
- **Context mapping**: Project structure, dependencies, and cohesion groups
- **Implementation strategy**: Tool selection and execution approach
## Core Rules
### Dependency Context Resolution (CRITICAL)
⚠️ **For tasks with dependencies or documentation associations**: MUST include bash content retrieval as first step in flow_control.pre_analysis
### Agent Execution Context (CRITICAL)
⚠️ **For agent execution phase**: Agents will automatically load context from plan-generated documents
**Required Pattern**:
**Agent Context Loading Pattern**:
```json
"flow_control": {
"pre_analysis": [
{
"step": "load_planning_context",
"action": "Load plan-generated analysis and context",
"command": "bash(cat .workflow/WFS-[session]/.process/ANALYSIS_RESULTS.md 2>/dev/null || echo 'planning analysis not found')",
"output_to": "planning_context"
}, // 可选：Task任务较为复杂时
{
"step": "load_dependencies",
"action": "Retrieve dependency task summaries",
@@ -43,7 +60,7 @@ examples:
},
{
"step": "load_documentation",
"action": "Retrieve project documentation",
"action": "Retrieve project documentation based on task requirements",
"command": "bash(cat CLAUDE.md README.md 2>/dev/null || echo 'documentation not found')",
"output_to": "doc_context"
}
@@ -59,13 +76,15 @@ examples:
**Content Sources**:
- Task summaries: `.workflow/WFS-[session]/.summaries/IMPL-[task-id]-summary.md` (主任务) / `IMPL-[task-id].[subtask-id]-summary.md` (子任务)
- Documentation: `CLAUDE.md`, `README.md`, config files
- Documentation: `CLAUDE.md`, `README.md`, config files (loaded based on task context requirements)
- Schema definitions: `.json`, `.yaml`, `.sql` files
- Dependency contexts: `.workflow/WFS-[session]/.task/IMPL-*.json`
- Analysis artifacts: `.workflow/WFS-[session]/.process/ANALYSIS_RESULTS.md`
### File Structure Reference
**Architecture**: @~/.claude/workflows/workflow-architecture.md
### Task Limits & Decomposition
- **Maximum 10 tasks**: Hard enforced limit - projects exceeding must be re-scoped
- **Function-based decomposition**: By complete functional units, not files/steps
@@ -100,10 +119,11 @@ examples:
### Project Structure Analysis & Engineering Enhancement
**⚠️ CRITICAL PRE-PLANNING STEP**: Must complete comprehensive project analysis before any task planning begins
**Analysis Process**: Context Gathering → Codebase Exploration → Pattern Recognition → Implementation Strategy
**Tool Selection Protocol**:
- **Simple patterns** (≤3 modules): Use `~/.claude/scripts/gemini-wrapper` or `codex --full-auto exec`
- **Complex analysis** (>3 modules): Launch Task agents with integrated CLI tool access
**Tool Selection Protocol** (Managed by flow_control):
- **Simple patterns** (≤3 modules): Direct CLI tools (`~/.claude/scripts/gemini-wrapper` or `codex --full-auto exec`)
- **Complex analysis** (>3 modules): Task agents with integrated CLI tool access and built-in tool capabilities
**Tool Priority**: Task(complex) > Direct CLI(simple) > Hybrid(mixed complexity)
**Automatic Selection**: flow_control system determines optimal tool based on task complexity and context requirements
**Core Principles**:
- **Complexity-Driven Selection**: Simple patterns use direct CLI, complex analysis uses Task agents with CLI integration
@@ -140,14 +160,17 @@ examples:
### Auto-Created (complexity > simple)
- **TODO_LIST.md**: Hierarchical progress tracking
- **.task/*.json**: Individual task definitions with flow_control
- **.process/ANALYSIS_RESULTS.md**: Analysis results and planning artifacts.Template:@~/.claude/workflows/ANALYSIS_RESULTS.md
### Document Structure
```
.workflow/WFS-[topic]/
├── IMPL_PLAN.md # Main planning document
├── TODO_LIST.md # Progress tracking (if complex)
├── .process/
│ └── ANALYSIS_RESULTS.md # Analysis results and planning artifacts
└── .task/
├── IMPL-001.json # Task definitions
├── IMPL-001.json # Task definitions with flow_control
└── IMPL-002.json
```

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.claude/python_script/__init__.py Normal file
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@@ -0,0 +1,35 @@
"""
Refactored Python Script Analyzer
Modular, reusable architecture for intelligent file analysis and workflow automation.
"""
__version__ = "2.0.0"
__author__ = "Claude Development Team"
__email__ = "dev@example.com"
from .analyzer import Analyzer
from .indexer import ProjectIndexer
from .cli import AnalysisCLI
from .core import (
Config, FileIndexer, FileInfo, IndexStats,
ContextAnalyzer, AnalysisResult,
PathMatcher, MatchResult, PathMatchingResult,
EmbeddingManager, GitignoreParser
)
from .tools import ModuleAnalyzer, ModuleInfo, TechStackLoader
from .utils import Colors, CacheManager, IOHelpers
__all__ = [
'Analyzer', 'ProjectIndexer', 'AnalysisCLI',
# Core modules
'Config',
'FileIndexer', 'FileInfo', 'IndexStats',
'ContextAnalyzer', 'AnalysisResult',
'PathMatcher', 'MatchResult', 'PathMatchingResult',
'EmbeddingManager', 'GitignoreParser',
# Tools
'ModuleAnalyzer', 'ModuleInfo',
'TechStackLoader',
# Utils
'Colors', 'CacheManager', 'IOHelpers'
]

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#!/usr/bin/env python3
"""
Unified Path-Aware Analyzer
Main entry point for the refactored analyzer system.
Provides a clean, simple API for intelligent file analysis.
"""
import os
import sys
import argparse
import logging
import json
import time
from pathlib import Path
from typing import Dict, List, Optional, Any
# Add current directory to path for imports
sys.path.insert(0, str(Path(__file__).parent))
from core.config import get_config
from core.file_indexer import FileIndexer, IndexStats
from core.context_analyzer import ContextAnalyzer, AnalysisResult
from core.path_matcher import PathMatcher, PathMatchingResult
from core.embedding_manager import EmbeddingManager
from utils.colors import Colors
class Analyzer:
"""Main analyzer class with simplified API."""
def __init__(self, config_path: Optional[str] = None, root_path: str = "."):
self.root_path = Path(root_path).resolve()
self.config = get_config(config_path)
# Setup logging
logging.basicConfig(
level=getattr(logging, self.config.get('logging.level', 'INFO')),
format=self.config.get('logging.format', '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
)
self.logger = logging.getLogger(__name__)
# Initialize core components
self.indexer = FileIndexer(self.config, str(self.root_path))
self.context_analyzer = ContextAnalyzer(self.config)
self.path_matcher = PathMatcher(self.config)
# Initialize embedding manager if enabled
self.embedding_manager = None
if self.config.is_embedding_enabled():
try:
self.embedding_manager = EmbeddingManager(self.config)
except ImportError:
self.logger.warning("Embedding dependencies not available. Install sentence-transformers for enhanced functionality.")
def build_index(self) -> IndexStats:
"""Build or update the file index."""
print(Colors.yellow("Building file index..."))
start_time = time.time()
self.indexer.build_index()
stats = self.indexer.get_stats()
elapsed = time.time() - start_time
if stats:
print(Colors.green(f"Index built: {stats.total_files} files, ~{stats.total_tokens:,} tokens ({elapsed:.2f}s)"))
else:
print(Colors.green(f"Index built successfully ({elapsed:.2f}s)"))
return stats
def analyze(self, prompt: str, mode: str = "auto", patterns: Optional[List[str]] = None,
token_limit: Optional[int] = None, use_embeddings: Optional[bool] = None) -> Dict[str, Any]:
"""Analyze and return relevant file paths for a given prompt."""
print(Colors.yellow("Analyzing project and prompt..."))
start_time = time.time()
# Load or build index
index = self.indexer.load_index()
if not index:
self.build_index()
index = self.indexer.load_index()
stats = self.indexer.get_stats()
print(Colors.cyan(f"Project stats: ~{stats.total_tokens:,} tokens across {stats.total_files} files"))
print(Colors.cyan(f"Categories: {', '.join(f'{k}: {v}' for k, v in stats.categories.items())}"))
# Determine project size
project_size = self._classify_project_size(stats.total_tokens)
print(Colors.cyan(f"Project size: {project_size}"))
# Analyze prompt context
print(Colors.yellow("Analyzing prompt context..."))
context_result = self.context_analyzer.analyze(prompt)
print(Colors.cyan(f"Identified: {len(context_result.domains)} domains, {len(context_result.languages)} languages"))
if context_result.domains:
print(Colors.cyan(f"Top domains: {', '.join(context_result.domains[:3])}"))
# Determine if we should use embeddings
should_use_embeddings = use_embeddings
if should_use_embeddings is None:
should_use_embeddings = (
self.embedding_manager is not None and
self.config.is_embedding_enabled() and
len(context_result.keywords) < 5 # Use embeddings for vague queries
)
similar_files = []
if should_use_embeddings and self.embedding_manager:
print(Colors.yellow("Using semantic similarity search..."))
# Update embeddings if needed
if not self.embedding_manager.embeddings_exist():
print(Colors.yellow("Building embeddings (first run)..."))
self.embedding_manager.update_embeddings(index)
similar_files = self.embedding_manager.find_similar_files(prompt, index)
print(Colors.cyan(f"Found {len(similar_files)} semantically similar files"))
# Match files to context
print(Colors.yellow("Matching files to context..."))
matching_result = self.path_matcher.match_files(
index,
context_result,
token_limit=token_limit,
explicit_patterns=patterns
)
elapsed = time.time() - start_time
print(Colors.green(f"Analysis complete: {len(matching_result.matched_files)} files, ~{matching_result.total_tokens:,} tokens"))
print(Colors.cyan(f"Confidence: {matching_result.confidence_score:.2f}"))
print(Colors.cyan(f"Execution time: {elapsed:.2f}s"))
return {
'files': [match.file_info.relative_path for match in matching_result.matched_files],
'total_tokens': matching_result.total_tokens,
'confidence': matching_result.confidence_score,
'context': {
'domains': context_result.domains,
'languages': context_result.languages,
'keywords': context_result.keywords
},
'stats': {
'project_size': project_size,
'total_files': stats.total_files,
'analysis_time': elapsed,
'embeddings_used': should_use_embeddings
}
}
def generate_command(self, prompt: str, tool: str = "gemini", **kwargs) -> str:
"""Generate a command for external tools (gemini/codex)."""
analysis_result = self.analyze(prompt, **kwargs)
# Format file patterns
file_patterns = " ".join(f"@{{{file}}}" for file in analysis_result['files'])
if tool == "gemini":
if len(analysis_result['files']) > 50: # Too many files for individual patterns
return f'gemini --all-files -p "{prompt}"'
else:
return f'gemini -p "{file_patterns} {prompt}"'
elif tool == "codex":
workspace_flag = "-s workspace-write" if analysis_result['total_tokens'] > 100000 else "-s danger-full-access"
return f'codex {workspace_flag} --full-auto exec "{file_patterns} {prompt}"'
else:
raise ValueError(f"Unsupported tool: {tool}")
def _classify_project_size(self, tokens: int) -> str:
"""Classify project size based on token count."""
small_limit = self.config.get('token_limits.small_project', 500000)
medium_limit = self.config.get('token_limits.medium_project', 2000000)
if tokens < small_limit:
return "small"
elif tokens < medium_limit:
return "medium"
else:
return "large"
def get_project_stats(self) -> Dict[str, Any]:
"""Get comprehensive project statistics."""
stats = self.indexer.get_stats()
embedding_stats = {}
if self.embedding_manager:
embedding_stats = {
'embeddings_exist': self.embedding_manager.embeddings_exist(),
'embedding_count': len(self.embedding_manager.load_embeddings()) if self.embedding_manager.embeddings_exist() else 0
}
return {
'files': stats.total_files,
'tokens': stats.total_tokens,
'size_bytes': stats.total_size,
'categories': stats.categories,
'project_size': self._classify_project_size(stats.total_tokens),
'last_updated': stats.last_updated,
'embeddings': embedding_stats,
'config': {
'cache_dir': self.config.get_cache_dir(),
'embedding_enabled': self.config.is_embedding_enabled(),
'exclude_patterns_count': len(self.config.get_exclude_patterns())
}
}
def main():
"""CLI entry point."""
parser = argparse.ArgumentParser(
description="Path-Aware Analyzer - Intelligent file pattern detection",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
python analyzer.py "analyze authentication flow"
python analyzer.py "fix database connection" --patterns "src/**/*.py"
python analyzer.py "review API endpoints" --tool gemini
python analyzer.py --stats
"""
)
parser.add_argument('prompt', nargs='?', help='Analysis prompt or task description')
parser.add_argument('--patterns', nargs='*', help='Explicit file patterns to include')
parser.add_argument('--tool', choices=['gemini', 'codex'], help='Generate command for specific tool')
parser.add_argument('--output', choices=['patterns', 'json'], default='patterns', help='Output format')
parser.add_argument('--verbose', '-v', action='store_true', help='Verbose output')
parser.add_argument('--stats', action='store_true', help='Show project statistics and exit')
parser.add_argument('--build-index', action='store_true', help='Build file index and exit')
args = parser.parse_args()
# Create analyzer with default values
analyzer = Analyzer(config_path=None, root_path=".")
# Handle special commands
if args.build_index:
analyzer.build_index()
return
if args.stats:
stats = analyzer.get_project_stats()
if args.output == 'json':
print(json.dumps(stats, indent=2, default=str))
else:
print(f"Total files: {stats['files']}")
print(f"Total tokens: {stats['tokens']:,}")
print(f"Categories: {stats['categories']}")
if 'embeddings' in stats:
print(f"Embeddings: {stats['embeddings']['embedding_count']}")
return
# Require prompt for analysis
if not args.prompt:
parser.error("Analysis prompt is required unless using --build-index or --stats")
# Perform analysis
try:
result = analyzer.analyze(
args.prompt,
patterns=args.patterns,
use_embeddings=False # Disable embeddings by default for simplicity
)
# Generate output
if args.tool:
# Generate command using already computed result
file_patterns = " ".join(f"@{{{file}}}" for file in result['files'])
if args.tool == "gemini":
if len(result['files']) > 50:
command = f'gemini --all-files -p "{args.prompt}"'
else:
command = f'gemini -p "{file_patterns} {args.prompt}"'
elif args.tool == "codex":
workspace_flag = "-s workspace-write" if result['total_tokens'] > 100000 else "-s danger-full-access"
command = f'codex {workspace_flag} --full-auto exec "{file_patterns} {args.prompt}"'
print(command)
elif args.output == 'json':
print(json.dumps(result, indent=2, default=str))
else: # patterns output (default)
for file_path in result['files']:
print(f"@{{{file_path}}}")
# Show verbose details
if args.verbose:
print(f"\n# Analysis Details:")
print(f"# Matched files: {len(result['files'])}")
print(f"# Total tokens: {result['total_tokens']:,}")
print(f"# Confidence: {result['confidence']:.2f}")
except KeyboardInterrupt:
print(Colors.warning("\nAnalysis interrupted by user"))
sys.exit(1)
except Exception as e:
print(Colors.error(f"Analysis failed: {e}"))
if args.verbose:
import traceback
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()

156
.claude/python_script/cache/embedding_index.json vendored Normal file
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@@ -0,0 +1,156 @@
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"vector_size": 384
},
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"file_path": "config.yaml",
"content_hash": "fc0526eea28cf37d15425035d2dd17d9",
"embedding_hash": "4866d8bd2b14c16c448c34c0251d199e",
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"vector_size": 384
},
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"content_hash": "6649df913eadef34fa2f253aed541dfd",
"embedding_hash": "54af072da7c1139108c79b64bd1ee291",
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},
"requirements.txt": {
"file_path": "requirements.txt",
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.claude/python_script/cli.py Normal file
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#!/usr/bin/env python3
"""
CLI Interface for Path-Aware Analysis
Provides command-line interface for intelligent file analysis and pattern matching.
"""
import sys
import argparse
import logging
import json
import time
from pathlib import Path
from typing import Dict, List, Optional, Any
# Add current directory to path for imports
sys.path.insert(0, str(Path(__file__).parent))
from core.config import get_config
from core.file_indexer import FileIndexer
from core.context_analyzer import ContextAnalyzer
from core.path_matcher import PathMatcher
from utils.colors import Colors
class AnalysisCLI:
"""Command-line interface for file analysis and pattern matching."""
def __init__(self, config_path: Optional[str] = None, root_path: str = "."):
self.root_path = Path(root_path).resolve()
self.config = get_config(config_path)
# Setup logging
logging.basicConfig(
level=getattr(logging, self.config.get('logging.level', 'INFO')),
format=self.config.get('logging.format', '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
)
self.logger = logging.getLogger(__name__)
# Initialize core components
self.indexer = FileIndexer(self.config, str(self.root_path))
self.context_analyzer = ContextAnalyzer(self.config)
self.path_matcher = PathMatcher(self.config)
def analyze(self, prompt: str, patterns: Optional[List[str]] = None) -> Dict[str, Any]:
"""Analyze and return relevant file paths for a given prompt."""
print(Colors.yellow("Analyzing project and prompt..."))
start_time = time.time()
# Load index (build if not exists)
index = self.indexer.load_index()
if not index:
print(Colors.warning("No file index found. Run 'python indexer.py --build' first or use --auto-build"))
return {}
stats = self.indexer.get_stats()
print(Colors.cyan(f"Project stats: ~{stats.total_tokens:,} tokens across {stats.total_files} files"))
print(Colors.cyan(f"Categories: {', '.join(f'{k}: {v}' for k, v in stats.categories.items())}"))
# Determine project size
project_size = self._classify_project_size(stats.total_tokens)
print(Colors.cyan(f"Project size: {project_size}"))
# Analyze prompt context
print(Colors.yellow("Analyzing prompt context..."))
context_result = self.context_analyzer.analyze(prompt)
print(Colors.cyan(f"Identified: {len(context_result.domains)} domains, {len(context_result.languages)} languages"))
if context_result.domains:
print(Colors.cyan(f"Top domains: {', '.join(context_result.domains[:3])}"))
# Match files to context
print(Colors.yellow("Matching files to context..."))
matching_result = self.path_matcher.match_files(
index,
context_result,
explicit_patterns=patterns
)
elapsed = time.time() - start_time
print(Colors.green(f"Analysis complete: {len(matching_result.matched_files)} files, ~{matching_result.total_tokens:,} tokens"))
print(Colors.cyan(f"Confidence: {matching_result.confidence_score:.2f}"))
print(Colors.cyan(f"Execution time: {elapsed:.2f}s"))
return {
'files': [match.file_info.relative_path for match in matching_result.matched_files],
'total_tokens': matching_result.total_tokens,
'confidence': matching_result.confidence_score,
'context': {
'domains': context_result.domains,
'languages': context_result.languages,
'keywords': context_result.keywords
},
'stats': {
'project_size': project_size,
'total_files': stats.total_files,
'analysis_time': elapsed
}
}
def generate_command(self, prompt: str, tool: str, files: List[str]) -> str:
"""Generate a command for external tools (gemini/codex)."""
file_patterns = " ".join(f"@{{{file}}}" for file in files)
if tool == "gemini":
if len(files) > 50:
return f'gemini --all-files -p "{prompt}"'
else:
return f'gemini -p "{file_patterns} {prompt}"'
elif tool == "codex":
# Estimate tokens for workspace selection
total_tokens = sum(len(file) * 50 for file in files) # Rough estimate
workspace_flag = "-s workspace-write" if total_tokens > 100000 else "-s danger-full-access"
return f'codex {workspace_flag} --full-auto exec "{file_patterns} {prompt}"'
else:
raise ValueError(f"Unsupported tool: {tool}")
def _classify_project_size(self, tokens: int) -> str:
"""Classify project size based on token count."""
small_limit = self.config.get('token_limits.small_project', 500000)
medium_limit = self.config.get('token_limits.medium_project', 2000000)
if tokens < small_limit:
return "small"
elif tokens < medium_limit:
return "medium"
else:
return "large"
def auto_build_index(self):
"""Auto-build index if it doesn't exist."""
from indexer import ProjectIndexer
indexer = ProjectIndexer(root_path=str(self.root_path))
indexer.build_index()
def main():
"""CLI entry point for analysis."""
parser = argparse.ArgumentParser(
description="Path-Aware Analysis CLI - Intelligent file pattern detection",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
python cli.py "analyze authentication flow"
python cli.py "fix database connection" --patterns "src/**/*.py"
python cli.py "review API endpoints" --tool gemini
"""
)
parser.add_argument('prompt', help='Analysis prompt or task description')
parser.add_argument('--patterns', nargs='*', help='Explicit file patterns to include')
parser.add_argument('--tool', choices=['gemini', 'codex'], help='Generate command for specific tool')
parser.add_argument('--output', choices=['patterns', 'json'], default='patterns', help='Output format')
parser.add_argument('--verbose', '-v', action='store_true', help='Verbose output')
parser.add_argument('--auto-build', action='store_true', help='Auto-build index if missing')
parser.add_argument('--config', help='Configuration file path')
parser.add_argument('--root', default='.', help='Root directory to analyze')
args = parser.parse_args()
# Create CLI interface
cli = AnalysisCLI(args.config, args.root)
try:
# Auto-build index if requested and missing
if args.auto_build:
index = cli.indexer.load_index()
if not index:
print(Colors.yellow("Auto-building missing index..."))
cli.auto_build_index()
# Perform analysis
result = cli.analyze(args.prompt, patterns=args.patterns)
if not result:
sys.exit(1)
# Generate output
if args.tool:
command = cli.generate_command(args.prompt, args.tool, result['files'])
print(command)
elif args.output == 'json':
print(json.dumps(result, indent=2, default=str))
else: # patterns output (default)
for file_path in result['files']:
print(f"@{{{file_path}}}")
# Show verbose details
if args.verbose:
print(f"\n# Analysis Details:")
print(f"# Matched files: {len(result['files'])}")
print(f"# Total tokens: {result['total_tokens']:,}")
print(f"# Confidence: {result['confidence']:.2f}")
except KeyboardInterrupt:
print(Colors.warning("\nAnalysis interrupted by user"))
sys.exit(1)
except Exception as e:
print(Colors.error(f"Analysis failed: {e}"))
if args.verbose:
import traceback
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()

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# Configuration for UltraThink Path-Aware Analyzer
# Based on gemini-wrapper patterns with intelligent enhancements
# Token limits for project size classification
token_limits:
small_project: 500000 # <500K tokens - include most files
medium_project: 2000000 # 500K-2M tokens - smart selection
large_project: 10000000 # >2M tokens - precise targeting
max_files: 1000 # Maximum files to process
# File patterns to exclude (performance and relevance)
exclude_patterns:
- "*/node_modules/*"
- "*/.git/*"
- "*/build/*"
- "*/dist/*"
- "*/.next/*"
- "*/.nuxt/*"
- "*/target/*"
- "*/vendor/*"
- "*/__pycache__/*"
- "*.pyc"
- "*.pyo"
- "*.log"
- "*.tmp"
- "*.temp"
- "*.history"
# File extensions grouped by category
file_extensions:
code:
- ".py"
- ".js"
- ".ts"
- ".tsx"
- ".jsx"
- ".java"
- ".cpp"
- ".c"
- ".h"
- ".rs"
- ".go"
- ".php"
- ".rb"
- ".sh"
- ".bash"
docs:
- ".md"
- ".txt"
- ".rst"
- ".adoc"
config:
- ".json"
- ".yaml"
- ".yml"
- ".toml"
- ".ini"
- ".env"
web:
- ".html"
- ".css"
- ".scss"
- ".sass"
- ".xml"
# Embedding/RAG configuration
embedding:
enabled: true # Set to true to enable RAG features
model: "all-MiniLM-L6-v2" # Lightweight sentence transformer
cache_dir: "cache"
similarity_threshold: 0.3
max_context_length: 512
batch_size: 32
# Context analysis settings
context_analysis:
# Keywords that indicate specific domains/modules
domain_keywords:
auth: ["auth", "login", "user", "password", "jwt", "token", "session"]
database: ["db", "database", "sql", "query", "model", "schema", "migration"]
api: ["api", "endpoint", "route", "controller", "service", "handler"]
frontend: ["ui", "component", "view", "template", "style", "css"]
backend: ["server", "service", "logic", "business", "core"]
test: ["test", "spec", "unit", "integration", "mock"]
config: ["config", "setting", "environment", "env"]
util: ["util", "helper", "common", "shared", "lib"]
# Programming language indicators
language_indicators:
python: [".py", "python", "pip", "requirements.txt", "setup.py"]
javascript: [".js", ".ts", "npm", "package.json", "node"]
java: [".java", "maven", "gradle", "pom.xml"]
go: [".go", "go.mod", "go.sum"]
rust: [".rs", "cargo", "Cargo.toml"]
# Path matching and ranking
path_matching:
# Scoring weights for relevance calculation
weights:
keyword_match: 0.4 # Direct keyword match in filename/path
extension_match: 0.2 # File extension relevance
directory_context: 0.2 # Directory name relevance
file_size_penalty: 0.1 # Penalty for very large files
recency_bonus: 0.1 # Bonus for recently modified files
# Maximum files to return per category
max_files_per_category: 20
# Minimum relevance score to include file
min_relevance_score: 0.1
# Output formatting
output:
# How to format path patterns
pattern_format: "@{{{path}}}" # Results in @{path/to/file}
# Include project documentation by default
always_include:
- "CLAUDE.md"
- "**/CLAUDE.md"
- "README.md"
- "docs/**/*.md"
# Maximum total files in output
max_total_files: 50
# Analysis modes
modes:
auto:
description: "Fully automatic path detection"
enabled: true
guided:
description: "Suggest paths for user confirmation"
enabled: true
pattern:
description: "Use explicit patterns from user"
enabled: true
hybrid:
description: "Combine auto-detection with user patterns"
enabled: true
# Performance settings
performance:
# Cache settings
cache_enabled: true
cache_ttl: 3600 # Cache TTL in seconds (1 hour)
# File size limits
max_file_size: 10485760 # 10MB max file size to analyze
# Parallel processing
max_workers: 4 # Number of parallel workers for file processing
# Logging configuration
logging:
level: "INFO" # DEBUG, INFO, WARNING, ERROR
file: ".claude/scripts/ultrathink/ultrathink.log"
format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"

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.claude/python_script/core/__init__.py Normal file
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"""
Core modules for the Python script analyzer.
Provides unified interfaces for file indexing, context analysis, and path matching.
"""
from .config import Config
from .file_indexer import FileIndexer, FileInfo, IndexStats
from .context_analyzer import ContextAnalyzer, AnalysisResult
from .path_matcher import PathMatcher, MatchResult, PathMatchingResult
from .embedding_manager import EmbeddingManager
from .gitignore_parser import GitignoreParser
__all__ = [
'Config',
'FileIndexer',
'FileInfo',
'IndexStats',
'ContextAnalyzer',
'AnalysisResult',
'PathMatcher',
'MatchResult',
'PathMatchingResult',
'EmbeddingManager',
'GitignoreParser'
]

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#!/usr/bin/env python3
"""
Configuration Management Module
Provides unified configuration management with gitignore integration.
"""
import os
import yaml
import logging
from pathlib import Path
from typing import Dict, Any, Optional, List
from .gitignore_parser import get_all_gitignore_patterns
class Config:
"""Singleton configuration manager with hierarchical loading."""
_instance = None
_initialized = False
def __new__(cls, config_path: Optional[str] = None):
if cls._instance is None:
cls._instance = super(Config, cls).__new__(cls)
return cls._instance
def __init__(self, config_path: Optional[str] = None):
if self._initialized:
return
self.config_path = config_path
self.config = {}
self.logger = logging.getLogger(__name__)
self._load_config()
self._add_gitignore_patterns()
self._apply_env_overrides()
self._validate_config()
self._initialized = True
def _load_config(self):
"""Load configuration from file with fallback hierarchy."""
config_paths = self._get_config_paths()
for config_file in config_paths:
if config_file.exists():
try:
with open(config_file, 'r', encoding='utf-8') as f:
loaded_config = yaml.safe_load(f)
if loaded_config:
self.config = self._merge_configs(self.config, loaded_config)
self.logger.info(f"Loaded config from {config_file}")
except Exception as e:
self.logger.warning(f"Failed to load config from {config_file}: {e}")
# Apply default config if no config loaded
if not self.config:
self.config = self._get_default_config()
self.logger.info("Using default configuration")
def _get_config_paths(self) -> List[Path]:
"""Get ordered list of config file paths to check."""
paths = []
# 1. Explicitly provided config path
if self.config_path:
paths.append(Path(self.config_path))
# 2. Current directory config.yaml
paths.append(Path('config.yaml'))
# 3. Script directory config.yaml
script_dir = Path(__file__).parent.parent
paths.append(script_dir / 'config.yaml')
# 4. Default config in script directory
paths.append(script_dir / 'default_config.yaml')
return paths
def _get_default_config(self) -> Dict[str, Any]:
"""Get default configuration."""
return {
'token_limits': {
'small_project': 500000,
'medium_project': 2000000,
'large_project': 10000000,
'max_files': 1000
},
'exclude_patterns': [
"*/node_modules/*",
"*/.git/*",
"*/build/*",
"*/dist/*",
"*/.next/*",
"*/.nuxt/*",
"*/target/*",
"*/vendor/*",
"*/__pycache__/*",
"*.pyc",
"*.pyo",
"*.log",
"*.tmp",
"*.temp",
"*.history"
],
'file_extensions': {
'code': ['.py', '.js', '.ts', '.tsx', '.jsx', '.java', '.cpp', '.c', '.h', '.rs', '.go', '.php', '.rb', '.sh', '.bash'],
'docs': ['.md', '.txt', '.rst', '.adoc'],
'config': ['.json', '.yaml', '.yml', '.toml', '.ini', '.env'],
'web': ['.html', '.css', '.scss', '.sass', '.xml']
},
'embedding': {
'enabled': True,
'model': 'all-MiniLM-L6-v2',
'cache_dir': 'cache',
'similarity_threshold': 0.3,
'max_context_length': 512,
'batch_size': 32
},
'context_analysis': {
'domain_keywords': {
'auth': ['auth', 'login', 'user', 'password', 'jwt', 'token', 'session'],
'database': ['db', 'database', 'sql', 'query', 'model', 'schema', 'migration'],
'api': ['api', 'endpoint', 'route', 'controller', 'service', 'handler'],
'frontend': ['ui', 'component', 'view', 'template', 'style', 'css'],
'backend': ['server', 'service', 'logic', 'business', 'core'],
'test': ['test', 'spec', 'unit', 'integration', 'mock'],
'config': ['config', 'setting', 'environment', 'env'],
'util': ['util', 'helper', 'common', 'shared', 'lib']
},
'language_indicators': {
'python': ['.py', 'python', 'pip', 'requirements.txt', 'setup.py'],
'javascript': ['.js', '.ts', 'npm', 'package.json', 'node'],
'java': ['.java', 'maven', 'gradle', 'pom.xml'],
'go': ['.go', 'go.mod', 'go.sum'],
'rust': ['.rs', 'cargo', 'Cargo.toml']
}
},
'path_matching': {
'weights': {
'keyword_match': 0.4,
'extension_match': 0.2,
'directory_context': 0.2,
'file_size_penalty': 0.1,
'recency_bonus': 0.1
},
'max_files_per_category': 20,
'min_relevance_score': 0.1
},
'output': {
'pattern_format': '@{{{path}}}',
'always_include': [
'CLAUDE.md',
'**/CLAUDE.md',
'README.md',
'docs/**/*.md'
],
'max_total_files': 50
},
'performance': {
'cache_enabled': True,
'cache_ttl': 3600,
'max_file_size': 10485760,
'max_workers': 4
},
'logging': {
'level': 'INFO',
'format': '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
}
}
def _merge_configs(self, base: Dict, override: Dict) -> Dict:
"""Recursively merge configuration dictionaries."""
result = base.copy()
for key, value in override.items():
if key in result and isinstance(result[key], dict) and isinstance(value, dict):
result[key] = self._merge_configs(result[key], value)
else:
result[key] = value
return result
def _add_gitignore_patterns(self):
"""Add patterns from .gitignore files to exclude_patterns."""
try:
# Find root directory (current working directory or script parent)
root_dir = Path.cwd()
gitignore_patterns = get_all_gitignore_patterns(str(root_dir))
if gitignore_patterns:
# Ensure exclude_patterns exists
if 'exclude_patterns' not in self.config:
self.config['exclude_patterns'] = []
# Add gitignore patterns, avoiding duplicates
existing_patterns = set(self.config['exclude_patterns'])
new_patterns = [p for p in gitignore_patterns if p not in existing_patterns]
self.config['exclude_patterns'].extend(new_patterns)
self.logger.info(f"Added {len(new_patterns)} patterns from .gitignore files")
except Exception as e:
self.logger.warning(f"Failed to load .gitignore patterns: {e}")
def _apply_env_overrides(self):
"""Apply environment variable overrides."""
env_mappings = {
'ANALYZER_CACHE_DIR': ('embedding', 'cache_dir'),
'ANALYZER_LOG_LEVEL': ('logging', 'level'),
'ANALYZER_MAX_FILES': ('token_limits', 'max_files'),
'ANALYZER_EMBEDDING_MODEL': ('embedding', 'model')
}
for env_var, config_path in env_mappings.items():
env_value = os.getenv(env_var)
if env_value:
self._set_nested_value(config_path, env_value)
self.logger.info(f"Applied environment override: {env_var} = {env_value}")
def _set_nested_value(self, path: tuple, value: str):
"""Set a nested configuration value."""
current = self.config
for key in path[:-1]:
if key not in current:
current[key] = {}
current = current[key]
# Try to convert value to appropriate type
if isinstance(current.get(path[-1]), int):
try:
value = int(value)
except ValueError:
pass
elif isinstance(current.get(path[-1]), bool):
value = value.lower() in ('true', '1', 'yes', 'on')
current[path[-1]] = value
def _validate_config(self):
"""Validate configuration values."""
required_sections = ['exclude_patterns', 'file_extensions', 'token_limits']
for section in required_sections:
if section not in self.config:
self.logger.warning(f"Missing required config section: {section}")
# Validate token limits
if 'token_limits' in self.config:
limits = self.config['token_limits']
if limits.get('small_project', 0) >= limits.get('medium_project', 0):
self.logger.warning("Token limit configuration may be incorrect")
def get(self, path: str, default: Any = None) -> Any:
"""Get configuration value using dot notation."""
keys = path.split('.')
current = self.config
try:
for key in keys:
current = current[key]
return current
except (KeyError, TypeError):
return default
def set(self, path: str, value: Any):
"""Set configuration value using dot notation."""
keys = path.split('.')
current = self.config
for key in keys[:-1]:
if key not in current:
current[key] = {}
current = current[key]
current[keys[-1]] = value
def get_exclude_patterns(self) -> List[str]:
"""Get all exclude patterns including gitignore patterns."""
return self.config.get('exclude_patterns', [])
def get_file_extensions(self) -> Dict[str, List[str]]:
"""Get file extension mappings."""
return self.config.get('file_extensions', {})
def is_embedding_enabled(self) -> bool:
"""Check if embedding functionality is enabled."""
return self.config.get('embedding', {}).get('enabled', False)
def get_cache_dir(self) -> str:
"""Get cache directory path."""
return self.config.get('embedding', {}).get('cache_dir', 'cache')
def to_dict(self) -> Dict[str, Any]:
"""Return configuration as dictionary."""
return self.config.copy()
def reload(self, config_path: Optional[str] = None):
"""Reload configuration from file."""
self._initialized = False
if config_path:
self.config_path = config_path
self.__init__(self.config_path)
# Global configuration instance
_global_config = None
def get_config(config_path: Optional[str] = None) -> Config:
"""Get global configuration instance."""
global _global_config
if _global_config is None:
_global_config = Config(config_path)
return _global_config
if __name__ == "__main__":
# Test configuration loading
config = Config()
print("Configuration loaded successfully!")
print(f"Cache dir: {config.get_cache_dir()}")
print(f"Exclude patterns: {len(config.get_exclude_patterns())}")
print(f"Embedding enabled: {config.is_embedding_enabled()}")

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#!/usr/bin/env python3
"""
Context Analyzer Module for UltraThink Path-Aware Analyzer
Analyzes user prompts to extract relevant context and keywords.
"""
import re
import logging
from typing import Dict, List, Set, Tuple, Optional
from dataclasses import dataclass
from collections import Counter
import string
@dataclass
class AnalysisResult:
"""Results of context analysis."""
keywords: List[str]
domains: List[str]
languages: List[str]
file_patterns: List[str]
confidence_scores: Dict[str, float]
extracted_entities: Dict[str, List[str]]
class ContextAnalyzer:
"""Analyzes user prompts to understand context and intent."""
def __init__(self, config: Dict):
self.config = config
self.logger = logging.getLogger(__name__)
# Load domain and language mappings from config
self.domain_keywords = config.get('context_analysis', {}).get('domain_keywords', {})
self.language_indicators = config.get('context_analysis', {}).get('language_indicators', {})
# Common programming terms and patterns
self.technical_terms = self._build_technical_terms()
self.file_pattern_indicators = self._build_pattern_indicators()
# Stop words to filter out
self.stop_words = {
'the', 'a', 'an', 'and', 'or', 'but', 'in', 'on', 'at', 'to', 'for', 'of', 'with',
'by', 'from', 'up', 'about', 'into', 'through', 'during', 'before', 'after',
'above', 'below', 'between', 'among', 'as', 'is', 'are', 'was', 'were', 'be',
'been', 'being', 'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would',
'could', 'should', 'may', 'might', 'must', 'can', 'this', 'that', 'these',
'those', 'i', 'you', 'he', 'she', 'it', 'we', 'they', 'me', 'him', 'her',
'us', 'them', 'my', 'your', 'his', 'its', 'our', 'their'
}
def _build_technical_terms(self) -> Dict[str, List[str]]:
"""Build comprehensive list of technical terms grouped by category."""
return {
'authentication': [
'auth', 'authentication', 'login', 'logout', 'signin', 'signout',
'user', 'password', 'token', 'jwt', 'oauth', 'session', 'cookie',
'credential', 'authorize', 'permission', 'role', 'access'
],
'database': [
'database', 'db', 'sql', 'query', 'table', 'schema', 'migration',
'model', 'orm', 'entity', 'relation', 'index', 'transaction',
'crud', 'select', 'insert', 'update', 'delete', 'join'
],
'api': [
'api', 'rest', 'graphql', 'endpoint', 'route', 'controller',
'handler', 'middleware', 'service', 'request', 'response',
'http', 'get', 'post', 'put', 'delete', 'patch'
],
'frontend': [
'ui', 'component', 'view', 'template', 'page', 'layout',
'style', 'css', 'html', 'javascript', 'react', 'vue',
'angular', 'dom', 'event', 'state', 'props'
],
'backend': [
'server', 'service', 'business', 'logic', 'core', 'engine',
'worker', 'job', 'queue', 'cache', 'redis', 'memcache'
],
'testing': [
'test', 'testing', 'spec', 'unit', 'integration', 'e2e',
'mock', 'stub', 'fixture', 'assert', 'expect', 'should'
],
'configuration': [
'config', 'configuration', 'setting', 'environment', 'env',
'variable', 'constant', 'parameter', 'option'
],
'utility': [
'util', 'utility', 'helper', 'common', 'shared', 'lib',
'library', 'tool', 'function', 'method'
]
}
def _build_pattern_indicators(self) -> Dict[str, List[str]]:
"""Build indicators that suggest specific file patterns."""
return {
'source_code': ['implement', 'code', 'function', 'class', 'method'],
'tests': ['test', 'testing', 'spec', 'unittest', 'pytest'],
'documentation': ['doc', 'readme', 'guide', 'documentation', 'manual'],
'configuration': ['config', 'setting', 'env', 'environment'],
'build': ['build', 'compile', 'package', 'deploy', 'release'],
'scripts': ['script', 'automation', 'tool', 'utility']
}
def extract_keywords(self, text: str) -> List[str]:
"""Extract meaningful keywords from text."""
# Clean and normalize text
text = text.lower()
text = re.sub(r'[^\w\s-]', ' ', text) # Remove punctuation except hyphens
words = text.split()
# Filter stop words and short words
keywords = []
for word in words:
word = word.strip('-') # Remove leading/trailing hyphens
if (len(word) >= 2 and
word not in self.stop_words and
not word.isdigit()):
keywords.append(word)
# Count frequency and return top keywords
word_counts = Counter(keywords)
return [word for word, count in word_counts.most_common(20)]
def identify_domains(self, keywords: List[str]) -> List[Tuple[str, float]]:
"""Identify relevant domains based on keywords."""
domain_scores = {}
for domain, domain_keywords in self.domain_keywords.items():
score = 0.0
matched_keywords = []
for keyword in keywords:
for domain_keyword in domain_keywords:
if keyword in domain_keyword or domain_keyword in keyword:
score += 1.0
matched_keywords.append(keyword)
break
if score > 0:
# Normalize score by number of domain keywords
normalized_score = score / len(domain_keywords)
domain_scores[domain] = normalized_score
# Also check technical terms
for category, terms in self.technical_terms.items():
score = 0.0
for keyword in keywords:
for term in terms:
if keyword in term or term in keyword:
score += 1.0
break
if score > 0:
normalized_score = score / len(terms)
if category not in domain_scores:
domain_scores[category] = normalized_score
else:
domain_scores[category] = max(domain_scores[category], normalized_score)
# Sort by score and return top domains
sorted_domains = sorted(domain_scores.items(), key=lambda x: x[1], reverse=True)
return sorted_domains[:5]
def identify_languages(self, keywords: List[str]) -> List[Tuple[str, float]]:
"""Identify programming languages based on keywords."""
language_scores = {}
for language, indicators in self.language_indicators.items():
score = 0.0
for keyword in keywords:
for indicator in indicators:
if keyword in indicator or indicator in keyword:
score += 1.0
break
if score > 0:
normalized_score = score / len(indicators)
language_scores[language] = normalized_score
sorted_languages = sorted(language_scores.items(), key=lambda x: x[1], reverse=True)
return sorted_languages[:3]
def extract_file_patterns(self, text: str) -> List[str]:
"""Extract explicit file patterns from text."""
patterns = []
# Look for @{pattern} syntax
at_patterns = re.findall(r'@\{([^}]+)\}', text)
patterns.extend(at_patterns)
# Look for file extensions
extensions = re.findall(r'\*\.(\w+)', text)
for ext in extensions:
patterns.append(f"*.{ext}")
# Look for directory patterns
dir_patterns = re.findall(r'(\w+)/\*\*?', text)
for dir_pattern in dir_patterns:
patterns.append(f"{dir_pattern}/**/*")
# Look for specific file names
file_patterns = re.findall(r'\b(\w+\.\w+)\b', text)
for file_pattern in file_patterns:
if '.' in file_pattern:
patterns.append(file_pattern)
return list(set(patterns)) # Remove duplicates
def suggest_patterns_from_domains(self, domains: List[str]) -> List[str]:
"""Suggest file patterns based on identified domains."""
patterns = []
domain_to_patterns = {
'auth': ['**/auth/**/*', '**/login/**/*', '**/user/**/*'],
'authentication': ['**/auth/**/*', '**/login/**/*', '**/user/**/*'],
'database': ['**/db/**/*', '**/model/**/*', '**/migration/**/*', '**/*model*'],
'api': ['**/api/**/*', '**/route/**/*', '**/controller/**/*', '**/handler/**/*'],
'frontend': ['**/ui/**/*', '**/component/**/*', '**/view/**/*', '**/template/**/*'],
'backend': ['**/service/**/*', '**/core/**/*', '**/server/**/*'],
'test': ['**/test/**/*', '**/spec/**/*', '**/*test*', '**/*spec*'],
'testing': ['**/test/**/*', '**/spec/**/*', '**/*test*', '**/*spec*'],
'config': ['**/config/**/*', '**/*.config.*', '**/env/**/*'],
'configuration': ['**/config/**/*', '**/*.config.*', '**/env/**/*'],
'util': ['**/util/**/*', '**/helper/**/*', '**/common/**/*'],
'utility': ['**/util/**/*', '**/helper/**/*', '**/common/**/*']
}
for domain in domains:
if domain in domain_to_patterns:
patterns.extend(domain_to_patterns[domain])
return list(set(patterns)) # Remove duplicates
def extract_entities(self, text: str) -> Dict[str, List[str]]:
"""Extract named entities from text."""
entities = {
'files': [],
'functions': [],
'classes': [],
'variables': [],
'technologies': []
}
# File patterns
file_patterns = re.findall(r'\b(\w+\.\w+)\b', text)
entities['files'] = list(set(file_patterns))
# Function patterns (camelCase or snake_case followed by parentheses)
function_patterns = re.findall(r'\b([a-z][a-zA-Z0-9_]*)\s*\(', text)
entities['functions'] = list(set(function_patterns))
# Class patterns (PascalCase)
class_patterns = re.findall(r'\b([A-Z][a-zA-Z0-9]*)\b', text)
entities['classes'] = list(set(class_patterns))
# Technology mentions
tech_keywords = [
'react', 'vue', 'angular', 'node', 'express', 'django', 'flask',
'spring', 'rails', 'laravel', 'docker', 'kubernetes', 'aws',
'azure', 'gcp', 'postgresql', 'mysql', 'mongodb', 'redis'
]
text_lower = text.lower()
for tech in tech_keywords:
if tech in text_lower:
entities['technologies'].append(tech)
return entities
def analyze(self, prompt: str) -> AnalysisResult:
"""Perform comprehensive analysis of the user prompt."""
self.logger.debug(f"Analyzing prompt: {prompt[:100]}...")
# Extract keywords
keywords = self.extract_keywords(prompt)
# Identify domains and languages
domains_with_scores = self.identify_domains(keywords)
languages_with_scores = self.identify_languages(keywords)
# Extract patterns and entities
explicit_patterns = self.extract_file_patterns(prompt)
entities = self.extract_entities(prompt)
# Get top domains and languages
domains = [domain for domain, score in domains_with_scores]
languages = [lang for lang, score in languages_with_scores]
# Suggest additional patterns based on domains
suggested_patterns = self.suggest_patterns_from_domains(domains)
# Combine explicit and suggested patterns
all_patterns = list(set(explicit_patterns + suggested_patterns))
# Build confidence scores
confidence_scores = {
'keywords': len(keywords) / 20, # Normalize to 0-1
'domain_match': max([score for _, score in domains_with_scores[:1]], default=0),
'language_match': max([score for _, score in languages_with_scores[:1]], default=0),
'pattern_extraction': len(explicit_patterns) / 5, # Normalize to 0-1
}
result = AnalysisResult(
keywords=keywords,
domains=domains,
languages=languages,
file_patterns=all_patterns,
confidence_scores=confidence_scores,
extracted_entities=entities
)
self.logger.info(f"Analysis complete: {len(domains)} domains, {len(languages)} languages, {len(all_patterns)} patterns")
return result
def main():
"""Command-line interface for context analyzer."""
import yaml
import argparse
import json
parser = argparse.ArgumentParser(description="Context Analyzer for UltraThink")
parser.add_argument("prompt", help="Prompt to analyze")
parser.add_argument("--config", default="config.yaml", help="Configuration file path")
parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
args = parser.parse_args()
# Setup logging
level = logging.DEBUG if args.verbose else logging.INFO
logging.basicConfig(level=level, format='%(levelname)s: %(message)s')
# Load configuration
from pathlib import Path
config_path = Path(__file__).parent / args.config
with open(config_path, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
# Create analyzer
analyzer = ContextAnalyzer(config)
# Analyze prompt
result = analyzer.analyze(args.prompt)
# Output results
print(f"Keywords: {', '.join(result.keywords[:10])}")
print(f"Domains: {', '.join(result.domains[:5])}")
print(f"Languages: {', '.join(result.languages[:3])}")
print(f"Patterns: {', '.join(result.file_patterns[:10])}")
if args.verbose:
print("\nDetailed Results:")
print(json.dumps({
'keywords': result.keywords,
'domains': result.domains,
'languages': result.languages,
'file_patterns': result.file_patterns,
'confidence_scores': result.confidence_scores,
'extracted_entities': result.extracted_entities
}, indent=2))
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Embedding Manager Module for UltraThink Path-Aware Analyzer
Manages embeddings for semantic similarity search (RAG functionality).
"""
import os
import json
import hashlib
import logging
import pickle
from pathlib import Path
from typing import Dict, List, Tuple, Optional, Any
from dataclasses import dataclass
import time
# Optional imports for embedding functionality
try:
import numpy as np
NUMPY_AVAILABLE = True
except ImportError:
NUMPY_AVAILABLE = False
try:
from sentence_transformers import SentenceTransformer
SENTENCE_TRANSFORMERS_AVAILABLE = True
except ImportError:
SENTENCE_TRANSFORMERS_AVAILABLE = False
from .file_indexer import FileInfo
@dataclass
class EmbeddingInfo:
"""Information about a file's embedding."""
file_path: str
content_hash: str
embedding_hash: str
created_time: float
vector_size: int
@dataclass
class SimilarityResult:
"""Result of similarity search."""
file_info: FileInfo
similarity_score: float
matching_content: str
class EmbeddingManager:
"""Manages embeddings for semantic file matching."""
def __init__(self, config: Dict):
self.config = config
self.logger = logging.getLogger(__name__)
# Check if embeddings are enabled
self.enabled = config.get('embedding', {}).get('enabled', False)
if not self.enabled:
self.logger.info("Embeddings disabled in configuration")
return
# Check dependencies
if not NUMPY_AVAILABLE:
self.logger.warning("NumPy not available, disabling embeddings")
self.enabled = False
return
if not SENTENCE_TRANSFORMERS_AVAILABLE:
self.logger.warning("sentence-transformers not available, disabling embeddings")
self.enabled = False
return
# Load configuration
self.model_name = config.get('embedding', {}).get('model', 'all-MiniLM-L6-v2')
self.cache_dir = Path(config.get('embedding', {}).get('cache_dir', '.claude/cache/embeddings'))
self.similarity_threshold = config.get('embedding', {}).get('similarity_threshold', 0.6)
self.max_context_length = config.get('embedding', {}).get('max_context_length', 512)
self.batch_size = config.get('embedding', {}).get('batch_size', 32)
# Setup cache directories
self.cache_dir.mkdir(parents=True, exist_ok=True)
self.embeddings_file = self.cache_dir / "embeddings.pkl"
self.index_file = self.cache_dir / "embedding_index.json"
# Initialize model lazily
self._model = None
self._embeddings_cache = None
self._embedding_index = None
@property
def model(self):
"""Lazy load the embedding model."""
if not self.enabled:
return None
if self._model is None:
try:
self.logger.info(f"Loading embedding model: {self.model_name}")
self._model = SentenceTransformer(self.model_name)
self.logger.info(f"Model loaded successfully")
except Exception as e:
self.logger.error(f"Failed to load embedding model: {e}")
self.enabled = False
return None
return self._model
def embeddings_exist(self) -> bool:
"""Check if embeddings cache exists."""
return self.embeddings_file.exists() and self.index_file.exists()
def _load_embedding_cache(self) -> Dict[str, np.ndarray]:
"""Load embeddings from cache."""
if self._embeddings_cache is not None:
return self._embeddings_cache
if not self.embeddings_file.exists():
self._embeddings_cache = {}
return self._embeddings_cache
try:
with open(self.embeddings_file, 'rb') as f:
self._embeddings_cache = pickle.load(f)
self.logger.debug(f"Loaded {len(self._embeddings_cache)} embeddings from cache")
except Exception as e:
self.logger.warning(f"Failed to load embeddings cache: {e}")
self._embeddings_cache = {}
return self._embeddings_cache
def _save_embedding_cache(self):
"""Save embeddings to cache."""
if self._embeddings_cache is None:
return
try:
with open(self.embeddings_file, 'wb') as f:
pickle.dump(self._embeddings_cache, f)
self.logger.debug(f"Saved {len(self._embeddings_cache)} embeddings to cache")
except Exception as e:
self.logger.error(f"Failed to save embeddings cache: {e}")
def _load_embedding_index(self) -> Dict[str, EmbeddingInfo]:
"""Load embedding index."""
if self._embedding_index is not None:
return self._embedding_index
if not self.index_file.exists():
self._embedding_index = {}
return self._embedding_index
try:
with open(self.index_file, 'r', encoding='utf-8') as f:
data = json.load(f)
self._embedding_index = {}
for path, info_dict in data.items():
self._embedding_index[path] = EmbeddingInfo(**info_dict)
self.logger.debug(f"Loaded embedding index with {len(self._embedding_index)} entries")
except Exception as e:
self.logger.warning(f"Failed to load embedding index: {e}")
self._embedding_index = {}
return self._embedding_index
def _save_embedding_index(self):
"""Save embedding index."""
if self._embedding_index is None:
return
try:
data = {}
for path, info in self._embedding_index.items():
data[path] = {
'file_path': info.file_path,
'content_hash': info.content_hash,
'embedding_hash': info.embedding_hash,
'created_time': info.created_time,
'vector_size': info.vector_size
}
with open(self.index_file, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=2)
self.logger.debug(f"Saved embedding index with {len(self._embedding_index)} entries")
except Exception as e:
self.logger.error(f"Failed to save embedding index: {e}")
def _extract_text_content(self, file_info: FileInfo) -> Optional[str]:
"""Extract text content from a file for embedding."""
try:
file_path = Path(file_info.path)
# Skip binary files and very large files
if file_info.size > self.config.get('performance', {}).get('max_file_size', 10485760):
return None
# Only process text-based files
text_extensions = {'.py', '.js', '.ts', '.tsx', '.jsx', '.java', '.cpp', '.c', '.h',
'.rs', '.go', '.php', '.rb', '.sh', '.bash', '.md', '.txt', '.json',
'.yaml', '.yml', '.xml', '.html', '.css', '.scss', '.sass'}
if file_info.extension.lower() not in text_extensions:
return None
with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
content = f.read()
# Truncate content if too long
if len(content) > self.max_context_length * 4: # Approximate token limit
content = content[:self.max_context_length * 4]
return content
except Exception as e:
self.logger.debug(f"Could not extract content from {file_info.path}: {e}")
return None
def _create_embedding(self, text: str) -> Optional[np.ndarray]:
"""Create embedding for text content."""
if not self.enabled or self.model is None:
return None
try:
# Truncate text if needed
if len(text) > self.max_context_length * 4:
text = text[:self.max_context_length * 4]
embedding = self.model.encode([text])[0]
return embedding
except Exception as e:
self.logger.warning(f"Failed to create embedding: {e}")
return None
def _get_content_hash(self, content: str) -> str:
"""Get hash of content for caching."""
return hashlib.md5(content.encode('utf-8')).hexdigest()
def _get_embedding_hash(self, embedding: np.ndarray) -> str:
"""Get hash of embedding for verification."""
return hashlib.md5(embedding.tobytes()).hexdigest()
def update_embeddings(self, file_index: Dict[str, FileInfo], force_rebuild: bool = False) -> int:
"""Update embeddings for files in the index."""
if not self.enabled:
self.logger.info("Embeddings disabled, skipping update")
return 0
self.logger.info("Updating embeddings...")
# Load caches
embeddings_cache = self._load_embedding_cache()
embedding_index = self._load_embedding_index()
new_embeddings = 0
batch_texts = []
batch_paths = []
for file_path, file_info in file_index.items():
# Check if embedding exists and is current
if not force_rebuild and file_path in embedding_index:
cached_info = embedding_index[file_path]
if cached_info.content_hash == file_info.content_hash:
continue # Embedding is current
# Extract content
content = self._extract_text_content(file_info)
if content is None:
continue
# Prepare for batch processing
batch_texts.append(content)
batch_paths.append(file_path)
# Process batch when full
if len(batch_texts) >= self.batch_size:
self._process_batch(batch_texts, batch_paths, file_index, embeddings_cache, embedding_index)
new_embeddings += len(batch_texts)
batch_texts = []
batch_paths = []
# Process remaining batch
if batch_texts:
self._process_batch(batch_texts, batch_paths, file_index, embeddings_cache, embedding_index)
new_embeddings += len(batch_texts)
# Save caches
self._save_embedding_cache()
self._save_embedding_index()
self.logger.info(f"Updated {new_embeddings} embeddings")
return new_embeddings
def _process_batch(self, texts: List[str], paths: List[str], file_index: Dict[str, FileInfo],
embeddings_cache: Dict[str, np.ndarray], embedding_index: Dict[str, EmbeddingInfo]):
"""Process a batch of texts for embedding."""
try:
# Create embeddings for batch
embeddings = self.model.encode(texts)
for i, (text, path) in enumerate(zip(texts, paths)):
embedding = embeddings[i]
file_info = file_index[path]
# Store embedding
content_hash = self._get_content_hash(text)
embedding_hash = self._get_embedding_hash(embedding)
embeddings_cache[path] = embedding
embedding_index[path] = EmbeddingInfo(
file_path=path,
content_hash=content_hash,
embedding_hash=embedding_hash,
created_time=time.time(),
vector_size=len(embedding)
)
except Exception as e:
self.logger.error(f"Failed to process embedding batch: {e}")
def find_similar_files(self, query: str, file_index: Dict[str, FileInfo],
top_k: int = 20) -> List[SimilarityResult]:
"""Find files similar to the query using embeddings."""
if not self.enabled:
return []
# Create query embedding
query_embedding = self._create_embedding(query)
if query_embedding is None:
return []
# Load embeddings
embeddings_cache = self._load_embedding_cache()
if not embeddings_cache:
self.logger.warning("No embeddings available for similarity search")
return []
# Calculate similarities
similarities = []
for file_path, file_embedding in embeddings_cache.items():
if file_path not in file_index:
continue
try:
# Calculate cosine similarity
similarity = np.dot(query_embedding, file_embedding) / (
np.linalg.norm(query_embedding) * np.linalg.norm(file_embedding)
)
if similarity >= self.similarity_threshold:
similarities.append((file_path, similarity))
except Exception as e:
self.logger.debug(f"Failed to calculate similarity for {file_path}: {e}")
continue
# Sort by similarity
similarities.sort(key=lambda x: x[1], reverse=True)
# Create results
results = []
for file_path, similarity in similarities[:top_k]:
file_info = file_index[file_path]
# Extract a snippet of matching content
content = self._extract_text_content(file_info)
snippet = content[:200] + "..." if content and len(content) > 200 else content or ""
result = SimilarityResult(
file_info=file_info,
similarity_score=similarity,
matching_content=snippet
)
results.append(result)
self.logger.info(f"Found {len(results)} similar files for query")
return results
def get_stats(self) -> Dict[str, Any]:
"""Get statistics about the embedding cache."""
if not self.enabled:
return {'enabled': False}
embedding_index = self._load_embedding_index()
embeddings_cache = self._load_embedding_cache()
return {
'enabled': True,
'model_name': self.model_name,
'total_embeddings': len(embedding_index),
'cache_size_mb': os.path.getsize(self.embeddings_file) / 1024 / 1024 if self.embeddings_file.exists() else 0,
'similarity_threshold': self.similarity_threshold,
'vector_size': list(embedding_index.values())[0].vector_size if embedding_index else 0
}
def main():
"""Command-line interface for embedding manager."""
import yaml
import argparse
from .file_indexer import FileIndexer
parser = argparse.ArgumentParser(description="Embedding Manager for UltraThink")
parser.add_argument("--config", default="config.yaml", help="Configuration file path")
parser.add_argument("--update", action="store_true", help="Update embeddings")
parser.add_argument("--rebuild", action="store_true", help="Force rebuild all embeddings")
parser.add_argument("--query", help="Search for similar files")
parser.add_argument("--stats", action="store_true", help="Show embedding statistics")
parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
args = parser.parse_args()
# Setup logging
level = logging.DEBUG if args.verbose else logging.INFO
logging.basicConfig(level=level, format='%(levelname)s: %(message)s')
# Load configuration
config_path = Path(__file__).parent / args.config
with open(config_path, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
# Create components
indexer = FileIndexer(config)
embedding_manager = EmbeddingManager(config)
if not embedding_manager.enabled:
print("Embeddings are disabled. Enable in config.yaml or install required dependencies.")
return
# Load file index
file_index = indexer.load_index()
if not file_index:
print("Building file index...")
file_index = indexer.build_index()
if args.stats:
stats = embedding_manager.get_stats()
print("Embedding Statistics:")
for key, value in stats.items():
print(f" {key}: {value}")
return
if args.update or args.rebuild:
count = embedding_manager.update_embeddings(file_index, force_rebuild=args.rebuild)
print(f"Updated {count} embeddings")
if args.query:
results = embedding_manager.find_similar_files(args.query, file_index)
print(f"Found {len(results)} similar files:")
for result in results:
print(f" {result.file_info.relative_path} (similarity: {result.similarity_score:.3f})")
if args.verbose and result.matching_content:
print(f" Content: {result.matching_content[:100]}...")
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
File Indexer Module for UltraThink Path-Aware Analyzer
Builds and maintains an index of repository files with metadata.
Enhanced with gitignore support and unified configuration.
"""
import os
import hashlib
import json
import time
import logging
from pathlib import Path
from typing import Dict, List, Optional, Set, Tuple, Union
from dataclasses import dataclass, asdict
from datetime import datetime
import fnmatch
from .gitignore_parser import GitignoreParser
@dataclass
class FileInfo:
"""Information about a single file in the repository."""
path: str
relative_path: str
size: int
modified_time: float
extension: str
category: str # code, docs, config, web
estimated_tokens: int
content_hash: str
def to_dict(self) -> Dict:
return asdict(self)
@classmethod
def from_dict(cls, data: Dict) -> 'FileInfo':
return cls(**data)
@dataclass
class IndexStats:
"""Statistics about the file index."""
total_files: int
total_tokens: int
total_size: int
categories: Dict[str, int]
last_updated: float
def to_dict(self) -> Dict:
return asdict(self)
class FileIndexer:
"""Builds and maintains an efficient index of repository files."""
def __init__(self, config: Union['Config', Dict], root_path: str = "."):
# Support both Config object and Dict for backward compatibility
if hasattr(config, 'to_dict'):
self.config_obj = config
self.config = config.to_dict()
else:
self.config_obj = None
self.config = config
self.root_path = Path(root_path).resolve()
self.cache_dir = Path(self.config.get('embedding', {}).get('cache_dir', '.claude/cache'))
self.cache_dir.mkdir(parents=True, exist_ok=True)
self.index_file = self.cache_dir / "file_index.json"
# Setup logging
self.logger = logging.getLogger(__name__)
# File extension mappings
self.extension_categories = self._build_extension_map()
# Exclude patterns from config
self.exclude_patterns = list(self.config.get('exclude_patterns', []))
# Initialize gitignore parser and add patterns
self.gitignore_parser = GitignoreParser(str(self.root_path))
self._load_gitignore_patterns()
# Performance settings
self.max_file_size = self.config.get('performance', {}).get('max_file_size', 10485760)
def _build_extension_map(self) -> Dict[str, str]:
"""Build mapping from file extensions to categories."""
ext_map = {}
for category, extensions in self.config.get('file_extensions', {}).items():
for ext in extensions:
ext_map[ext.lower()] = category
return ext_map
def _load_gitignore_patterns(self):
"""Load patterns from .gitignore files and add to exclude_patterns."""
try:
gitignore_patterns = self.gitignore_parser.parse_all_gitignores()
if gitignore_patterns:
# Avoid duplicates
existing_patterns = set(self.exclude_patterns)
new_patterns = [p for p in gitignore_patterns if p not in existing_patterns]
self.exclude_patterns.extend(new_patterns)
self.logger.info(f"Added {len(new_patterns)} patterns from .gitignore files")
except Exception as e:
self.logger.warning(f"Failed to load .gitignore patterns: {e}")
def _should_exclude_file(self, file_path: Path) -> bool:
"""Check if file should be excluded based on patterns and gitignore rules."""
relative_path = str(file_path.relative_to(self.root_path))
# Check against exclude patterns from config
for pattern in self.exclude_patterns:
# Convert pattern to work with fnmatch
if fnmatch.fnmatch(relative_path, pattern) or fnmatch.fnmatch(str(file_path), pattern):
return True
# Check if any parent directory matches
parts = relative_path.split(os.sep)
for i in range(len(parts)):
partial_path = "/".join(parts[:i+1])
if fnmatch.fnmatch(partial_path, pattern):
return True
# Also check gitignore rules using dedicated parser
# Note: gitignore patterns are already included in self.exclude_patterns
# but we can add additional gitignore-specific checking here if needed
try:
# The gitignore patterns are already loaded into exclude_patterns,
# but we can do additional gitignore-specific checks if needed
pass
except Exception as e:
self.logger.debug(f"Error in gitignore checking for {file_path}: {e}")
return False
def _estimate_tokens(self, file_path: Path) -> int:
"""Estimate token count for a file (chars/4 approximation)."""
try:
if file_path.stat().st_size > self.max_file_size:
return file_path.stat().st_size // 8 # Penalty for large files
with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
content = f.read()
return len(content) // 4 # Rough approximation
except (UnicodeDecodeError, OSError):
# Binary files or unreadable files
return file_path.stat().st_size // 8
def _get_file_hash(self, file_path: Path) -> str:
"""Get a hash of file metadata for change detection."""
stat = file_path.stat()
return hashlib.md5(f"{file_path}:{stat.st_size}:{stat.st_mtime}".encode()).hexdigest()
def _categorize_file(self, file_path: Path) -> str:
"""Categorize file based on extension."""
extension = file_path.suffix.lower()
return self.extension_categories.get(extension, 'other')
def _scan_file(self, file_path: Path) -> Optional[FileInfo]:
"""Scan a single file and create FileInfo."""
try:
if not file_path.is_file() or self._should_exclude_file(file_path):
return None
stat = file_path.stat()
relative_path = str(file_path.relative_to(self.root_path))
file_info = FileInfo(
path=str(file_path),
relative_path=relative_path,
size=stat.st_size,
modified_time=stat.st_mtime,
extension=file_path.suffix.lower(),
category=self._categorize_file(file_path),
estimated_tokens=self._estimate_tokens(file_path),
content_hash=self._get_file_hash(file_path)
)
return file_info
except (OSError, PermissionError) as e:
self.logger.warning(f"Could not scan file {file_path}: {e}")
return None
def build_index(self, force_rebuild: bool = False) -> Dict[str, FileInfo]:
"""Build or update the file index."""
self.logger.info(f"Building file index for {self.root_path}")
# Load existing index if available
existing_index = {}
if not force_rebuild and self.index_file.exists():
existing_index = self.load_index()
new_index = {}
changed_files = 0
# Walk through all files
for file_path in self.root_path.rglob('*'):
if not file_path.is_file():
continue
file_info = self._scan_file(file_path)
if file_info is None:
continue
# Check if file has changed
relative_path = file_info.relative_path
if relative_path in existing_index:
old_info = existing_index[relative_path]
if old_info.content_hash == file_info.content_hash:
# File unchanged, keep old info
new_index[relative_path] = old_info
continue
# File is new or changed
new_index[relative_path] = file_info
changed_files += 1
self.logger.info(f"Indexed {len(new_index)} files ({changed_files} new/changed)")
# Save index
self.save_index(new_index)
return new_index
def load_index(self) -> Dict[str, FileInfo]:
"""Load file index from cache."""
if not self.index_file.exists():
return {}
try:
with open(self.index_file, 'r', encoding='utf-8') as f:
data = json.load(f)
index = {}
for path, info_dict in data.get('files', {}).items():
index[path] = FileInfo.from_dict(info_dict)
return index
except (json.JSONDecodeError, KeyError) as e:
self.logger.warning(f"Could not load index: {e}")
return {}
def save_index(self, index: Dict[str, FileInfo]) -> None:
"""Save file index to cache."""
try:
# Calculate stats
stats = self._calculate_stats(index)
data = {
'stats': stats.to_dict(),
'files': {path: info.to_dict() for path, info in index.items()}
}
with open(self.index_file, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=2)
except OSError as e:
self.logger.error(f"Could not save index: {e}")
def _calculate_stats(self, index: Dict[str, FileInfo]) -> IndexStats:
"""Calculate statistics for the index."""
total_files = len(index)
total_tokens = sum(info.estimated_tokens for info in index.values())
total_size = sum(info.size for info in index.values())
categories = {}
for info in index.values():
categories[info.category] = categories.get(info.category, 0) + 1
return IndexStats(
total_files=total_files,
total_tokens=total_tokens,
total_size=total_size,
categories=categories,
last_updated=time.time()
)
def get_stats(self) -> Optional[IndexStats]:
"""Get statistics about the current index."""
if not self.index_file.exists():
return None
try:
with open(self.index_file, 'r', encoding='utf-8') as f:
data = json.load(f)
return IndexStats(**data.get('stats', {}))
except (json.JSONDecodeError, KeyError):
return None
def find_files_by_pattern(self, pattern: str, index: Optional[Dict[str, FileInfo]] = None) -> List[FileInfo]:
"""Find files matching a glob pattern."""
if index is None:
index = self.load_index()
matching_files = []
for path, info in index.items():
if fnmatch.fnmatch(path, pattern) or fnmatch.fnmatch(info.path, pattern):
matching_files.append(info)
return matching_files
def find_files_by_category(self, category: str, index: Optional[Dict[str, FileInfo]] = None) -> List[FileInfo]:
"""Find files by category (code, docs, config, etc.)."""
if index is None:
index = self.load_index()
return [info for info in index.values() if info.category == category]
def find_files_by_keywords(self, keywords: List[str], index: Optional[Dict[str, FileInfo]] = None) -> List[FileInfo]:
"""Find files whose paths contain any of the specified keywords."""
if index is None:
index = self.load_index()
matching_files = []
keywords_lower = [kw.lower() for kw in keywords]
for info in index.values():
path_lower = info.relative_path.lower()
if any(keyword in path_lower for keyword in keywords_lower):
matching_files.append(info)
return matching_files
def get_recent_files(self, limit: int = 20, index: Optional[Dict[str, FileInfo]] = None) -> List[FileInfo]:
"""Get most recently modified files."""
if index is None:
index = self.load_index()
files = list(index.values())
files.sort(key=lambda f: f.modified_time, reverse=True)
return files[:limit]
def main():
"""Command-line interface for file indexer."""
import yaml
import argparse
parser = argparse.ArgumentParser(description="File Indexer for UltraThink")
parser.add_argument("--config", default="config.yaml", help="Configuration file path")
parser.add_argument("--rebuild", action="store_true", help="Force rebuild index")
parser.add_argument("--stats", action="store_true", help="Show index statistics")
parser.add_argument("--pattern", help="Find files matching pattern")
args = parser.parse_args()
# Load configuration
config_path = Path(__file__).parent / args.config
with open(config_path, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
# Setup logging
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
# Create indexer
indexer = FileIndexer(config)
if args.stats:
stats = indexer.get_stats()
if stats:
print(f"Total files: {stats.total_files}")
print(f"Total tokens: {stats.total_tokens:,}")
print(f"Total size: {stats.total_size:,} bytes")
print(f"Categories: {stats.categories}")
print(f"Last updated: {datetime.fromtimestamp(stats.last_updated)}")
else:
print("No index found. Run without --stats to build index.")
return
# Build index
index = indexer.build_index(force_rebuild=args.rebuild)
if args.pattern:
files = indexer.find_files_by_pattern(args.pattern, index)
print(f"Found {len(files)} files matching pattern '{args.pattern}':")
for file_info in files[:20]: # Limit output
print(f" {file_info.relative_path}")
else:
stats = indexer._calculate_stats(index)
print(f"Index built: {stats.total_files} files, ~{stats.total_tokens:,} tokens")
if __name__ == "__main__":
main()

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.claude/python_script/core/gitignore_parser.py Normal file
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#!/usr/bin/env python3
"""
GitIgnore Parser Module
Parses .gitignore files and converts rules to fnmatch patterns for file exclusion.
"""
import os
import fnmatch
from pathlib import Path
from typing import List, Set, Optional
class GitignoreParser:
"""Parser for .gitignore files that converts rules to fnmatch patterns."""
def __init__(self, root_path: str = "."):
self.root_path = Path(root_path).resolve()
self.patterns: List[str] = []
self.negation_patterns: List[str] = []
def parse_file(self, gitignore_path: str) -> List[str]:
"""Parse a .gitignore file and return exclude patterns."""
gitignore_file = Path(gitignore_path)
if not gitignore_file.exists():
return []
patterns = []
try:
with open(gitignore_file, 'r', encoding='utf-8') as f:
for line_num, line in enumerate(f, 1):
pattern = self._parse_line(line.strip())
if pattern:
patterns.append(pattern)
except (UnicodeDecodeError, IOError):
# Fallback to system encoding if UTF-8 fails
try:
with open(gitignore_file, 'r') as f:
for line_num, line in enumerate(f, 1):
pattern = self._parse_line(line.strip())
if pattern:
patterns.append(pattern)
except IOError:
# If file can't be read, return empty list
return []
return patterns
def _parse_line(self, line: str) -> Optional[str]:
"""Parse a single line from .gitignore file."""
# Skip empty lines and comments
if not line or line.startswith('#'):
return None
# Handle negation patterns (starting with !)
if line.startswith('!'):
# For now, we'll skip negation patterns as they require
# more complex logic to implement correctly
return None
# Convert gitignore pattern to fnmatch pattern
return self._convert_to_fnmatch(line)
def _convert_to_fnmatch(self, pattern: str) -> str:
"""Convert gitignore pattern to fnmatch pattern."""
# Remove trailing slash (directory indicator)
if pattern.endswith('/'):
pattern = pattern[:-1]
# Handle absolute paths (starting with /)
if pattern.startswith('/'):
pattern = pattern[1:]
# Make it match from root
return pattern
# Handle patterns that should match anywhere in the tree
# If pattern doesn't contain '/', it matches files/dirs at any level
if '/' not in pattern:
return f"*/{pattern}"
# Pattern contains '/', so it's relative to the gitignore location
return pattern
def parse_all_gitignores(self, root_path: Optional[str] = None) -> List[str]:
"""Parse all .gitignore files in the repository hierarchy."""
if root_path:
self.root_path = Path(root_path).resolve()
all_patterns = []
# Find all .gitignore files in the repository
gitignore_files = self._find_gitignore_files()
for gitignore_file in gitignore_files:
patterns = self.parse_file(gitignore_file)
all_patterns.extend(patterns)
return all_patterns
def _find_gitignore_files(self) -> List[Path]:
"""Find all .gitignore files in the repository."""
gitignore_files = []
# Start with root .gitignore
root_gitignore = self.root_path / '.gitignore'
if root_gitignore.exists():
gitignore_files.append(root_gitignore)
# Find .gitignore files in subdirectories
try:
for gitignore_file in self.root_path.rglob('.gitignore'):
if gitignore_file != root_gitignore:
gitignore_files.append(gitignore_file)
except (PermissionError, OSError):
# Skip directories we can't access
pass
return gitignore_files
def should_exclude(self, file_path: str, gitignore_patterns: List[str]) -> bool:
"""Check if a file should be excluded based on gitignore patterns."""
# Convert to relative path from root
try:
rel_path = str(Path(file_path).relative_to(self.root_path))
except ValueError:
# File is not under root path
return False
# Normalize path separators for consistent matching
rel_path = rel_path.replace(os.sep, '/')
for pattern in gitignore_patterns:
if self._matches_pattern(rel_path, pattern):
return True
return False
def _matches_pattern(self, file_path: str, pattern: str) -> bool:
"""Check if a file path matches a gitignore pattern."""
# Normalize pattern separators
pattern = pattern.replace(os.sep, '/')
# Handle different pattern types
if pattern.startswith('*/'):
# Pattern like */pattern - matches at any level
sub_pattern = pattern[2:]
return fnmatch.fnmatch(file_path, f"*/{sub_pattern}") or fnmatch.fnmatch(file_path, sub_pattern)
elif '/' in pattern:
# Pattern contains slash - match exact path
return fnmatch.fnmatch(file_path, pattern)
else:
# Simple pattern - match filename or directory at any level
parts = file_path.split('/')
return any(fnmatch.fnmatch(part, pattern) for part in parts)
def parse_gitignore(gitignore_path: str) -> List[str]:
"""Convenience function to parse a single .gitignore file."""
parser = GitignoreParser()
return parser.parse_file(gitignore_path)
def get_all_gitignore_patterns(root_path: str = ".") -> List[str]:
"""Convenience function to get all gitignore patterns in a repository."""
parser = GitignoreParser(root_path)
return parser.parse_all_gitignores()
if __name__ == "__main__":
import sys
if len(sys.argv) > 1:
gitignore_path = sys.argv[1]
patterns = parse_gitignore(gitignore_path)
print(f"Parsed {len(patterns)} patterns from {gitignore_path}:")
for pattern in patterns:
print(f" {pattern}")
else:
# Parse all .gitignore files in current directory
patterns = get_all_gitignore_patterns()
print(f"Found {len(patterns)} gitignore patterns:")
for pattern in patterns:
print(f" {pattern}")

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#!/usr/bin/env python3
"""
Path Matcher Module for UltraThink Path-Aware Analyzer
Matches files to analysis context and ranks them by relevance.
"""
import re
import logging
import fnmatch
from typing import Dict, List, Tuple, Optional, Set
from dataclasses import dataclass
from pathlib import Path
import math
from .file_indexer import FileInfo
from .context_analyzer import AnalysisResult
@dataclass
class MatchResult:
"""Result of path matching with relevance score."""
file_info: FileInfo
relevance_score: float
match_reasons: List[str]
category_bonus: float
@dataclass
class PathMatchingResult:
"""Complete result of path matching operation."""
matched_files: List[MatchResult]
total_tokens: int
categories: Dict[str, int]
patterns_used: List[str]
confidence_score: float
class PathMatcher:
"""Matches files to analysis context using various algorithms."""
def __init__(self, config: Dict):
self.config = config
self.logger = logging.getLogger(__name__)
# Load scoring weights
self.weights = config.get('path_matching', {}).get('weights', {
'keyword_match': 0.4,
'extension_match': 0.2,
'directory_context': 0.2,
'file_size_penalty': 0.1,
'recency_bonus': 0.1
})
# Load limits
self.max_files_per_category = config.get('path_matching', {}).get('max_files_per_category', 20)
self.min_relevance_score = config.get('path_matching', {}).get('min_relevance_score', 0.1)
self.max_total_files = config.get('output', {}).get('max_total_files', 50)
# Load always include patterns
self.always_include = config.get('output', {}).get('always_include', [])
# Category priorities
self.category_priorities = {
'code': 1.0,
'config': 0.8,
'docs': 0.6,
'web': 0.4,
'other': 0.2
}
def _calculate_keyword_score(self, file_info: FileInfo, keywords: List[str]) -> Tuple[float, List[str]]:
"""Calculate score based on keyword matches in file path."""
if not keywords:
return 0.0, []
path_lower = file_info.relative_path.lower()
filename_lower = Path(file_info.relative_path).name.lower()
matches = []
score = 0.0
for keyword in keywords:
keyword_lower = keyword.lower()
# Exact filename match (highest weight)
if keyword_lower in filename_lower:
score += 2.0
matches.append(f"filename:{keyword}")
continue
# Directory name match
if keyword_lower in path_lower:
score += 1.0
matches.append(f"path:{keyword}")
continue
# Partial match in path components
path_parts = path_lower.split('/')
for part in path_parts:
if keyword_lower in part:
score += 0.5
matches.append(f"partial:{keyword}")
break
# Normalize by number of keywords
normalized_score = score / len(keywords) if keywords else 0.0
return min(normalized_score, 1.0), matches
def _calculate_extension_score(self, file_info: FileInfo, languages: List[str]) -> float:
"""Calculate score based on file extension relevance."""
if not languages:
return 0.5 # Neutral score
extension = file_info.extension.lower()
# Language-specific extension mapping
lang_extensions = {
'python': ['.py', '.pyx', '.pyi'],
'javascript': ['.js', '.jsx', '.mjs'],
'typescript': ['.ts', '.tsx'],
'java': ['.java'],
'go': ['.go'],
'rust': ['.rs'],
'cpp': ['.cpp', '.cc', '.cxx', '.c', '.h', '.hpp'],
'csharp': ['.cs'],
'php': ['.php'],
'ruby': ['.rb'],
'shell': ['.sh', '.bash', '.zsh']
}
score = 0.0
for language in languages:
if language in lang_extensions:
if extension in lang_extensions[language]:
score = 1.0
break
# Fallback to category-based scoring
if score == 0.0:
category_scores = {
'code': 1.0,
'config': 0.8,
'docs': 0.6,
'web': 0.4,
'other': 0.2
}
score = category_scores.get(file_info.category, 0.2)
return score
def _calculate_directory_score(self, file_info: FileInfo, domains: List[str]) -> Tuple[float, List[str]]:
"""Calculate score based on directory context."""
if not domains:
return 0.0, []
path_parts = file_info.relative_path.lower().split('/')
matches = []
score = 0.0
# Domain-specific directory patterns
domain_patterns = {
'auth': ['auth', 'authentication', 'login', 'user', 'account'],
'authentication': ['auth', 'authentication', 'login', 'user', 'account'],
'database': ['db', 'database', 'model', 'entity', 'migration', 'schema'],
'api': ['api', 'rest', 'graphql', 'route', 'controller', 'handler'],
'frontend': ['ui', 'component', 'view', 'template', 'client', 'web'],
'backend': ['service', 'server', 'core', 'business', 'logic'],
'test': ['test', 'spec', 'tests', '__tests__', 'testing'],
'testing': ['test', 'spec', 'tests', '__tests__', 'testing'],
'config': ['config', 'configuration', 'env', 'settings'],
'configuration': ['config', 'configuration', 'env', 'settings'],
'util': ['util', 'utils', 'helper', 'common', 'shared', 'lib'],
'utility': ['util', 'utils', 'helper', 'common', 'shared', 'lib']
}
for domain in domains:
if domain in domain_patterns:
patterns = domain_patterns[domain]
for pattern in patterns:
for part in path_parts:
if pattern in part:
score += 1.0
matches.append(f"dir:{domain}->{pattern}")
break
# Normalize by number of domains
normalized_score = score / len(domains) if domains else 0.0
return min(normalized_score, 1.0), matches
def _calculate_size_penalty(self, file_info: FileInfo) -> float:
"""Calculate penalty for very large files."""
max_size = self.config.get('performance', {}).get('max_file_size', 10485760) # 10MB
if file_info.size > max_size:
# Heavy penalty for oversized files
return -0.5
elif file_info.size > max_size * 0.5:
# Light penalty for large files
return -0.2
else:
return 0.0
def _calculate_recency_bonus(self, file_info: FileInfo) -> float:
"""Calculate bonus for recently modified files."""
import time
current_time = time.time()
file_age = current_time - file_info.modified_time
# Files modified in last day get bonus
if file_age < 86400: # 1 day
return 0.3
elif file_age < 604800: # 1 week
return 0.1
else:
return 0.0
def calculate_relevance_score(self, file_info: FileInfo, analysis: AnalysisResult) -> MatchResult:
"""Calculate overall relevance score for a file."""
# Calculate individual scores
keyword_score, keyword_matches = self._calculate_keyword_score(file_info, analysis.keywords)
extension_score = self._calculate_extension_score(file_info, analysis.languages)
directory_score, dir_matches = self._calculate_directory_score(file_info, analysis.domains)
size_penalty = self._calculate_size_penalty(file_info)
recency_bonus = self._calculate_recency_bonus(file_info)
# Apply weights
weighted_score = (
keyword_score * self.weights.get('keyword_match', 0.4) +
extension_score * self.weights.get('extension_match', 0.2) +
directory_score * self.weights.get('directory_context', 0.2) +
size_penalty * self.weights.get('file_size_penalty', 0.1) +
recency_bonus * self.weights.get('recency_bonus', 0.1)
)
# Category bonus
category_bonus = self.category_priorities.get(file_info.category, 0.2)
# Final score with category bonus
final_score = weighted_score + (category_bonus * 0.1)
# Collect match reasons
match_reasons = keyword_matches + dir_matches
if extension_score > 0.5:
match_reasons.append(f"extension:{file_info.extension}")
if recency_bonus > 0:
match_reasons.append("recent")
return MatchResult(
file_info=file_info,
relevance_score=max(0.0, final_score),
match_reasons=match_reasons,
category_bonus=category_bonus
)
def match_by_patterns(self, file_index: Dict[str, FileInfo], patterns: List[str]) -> List[FileInfo]:
"""Match files using explicit glob patterns."""
matched_files = []
for pattern in patterns:
for path, file_info in file_index.items():
# Try matching both relative path and full path
if (fnmatch.fnmatch(path, pattern) or
fnmatch.fnmatch(file_info.path, pattern) or
fnmatch.fnmatch(Path(path).name, pattern)):
matched_files.append(file_info)
# Remove duplicates based on path
seen_paths = set()
unique_files = []
for file_info in matched_files:
if file_info.relative_path not in seen_paths:
seen_paths.add(file_info.relative_path)
unique_files.append(file_info)
return unique_files
def match_always_include(self, file_index: Dict[str, FileInfo]) -> List[FileInfo]:
"""Match files that should always be included."""
return self.match_by_patterns(file_index, self.always_include)
def rank_files(self, files: List[FileInfo], analysis: AnalysisResult) -> List[MatchResult]:
"""Rank files by relevance score."""
match_results = []
for file_info in files:
match_result = self.calculate_relevance_score(file_info, analysis)
if match_result.relevance_score >= self.min_relevance_score:
match_results.append(match_result)
# Sort by relevance score (descending)
match_results.sort(key=lambda x: x.relevance_score, reverse=True)
return match_results
def select_best_files(self, ranked_files: List[MatchResult], token_limit: Optional[int] = None) -> List[MatchResult]:
"""Select the best files within token limits and category constraints."""
if not ranked_files:
return []
selected_files = []
total_tokens = 0
category_counts = {}
for match_result in ranked_files:
file_info = match_result.file_info
category = file_info.category
# Check category limit
if category_counts.get(category, 0) >= self.max_files_per_category:
continue
# Check token limit
if token_limit and total_tokens + file_info.estimated_tokens > token_limit:
continue
# Check total file limit
if len(selected_files) >= self.max_total_files:
break
# Add file
selected_files.append(match_result)
total_tokens += file_info.estimated_tokens
category_counts[category] = category_counts.get(category, 0) + 1
return selected_files
def match_files(self, file_index: Dict[str, FileInfo], analysis: AnalysisResult,
token_limit: Optional[int] = None, explicit_patterns: Optional[List[str]] = None) -> PathMatchingResult:
"""Main file matching function."""
self.logger.info(f"Matching files for analysis with {len(analysis.keywords)} keywords and {len(analysis.domains)} domains")
# Start with always-include files
always_include_files = self.match_always_include(file_index)
self.logger.debug(f"Always include: {len(always_include_files)} files")
# Add explicit pattern matches
pattern_files = []
patterns_used = []
if explicit_patterns:
pattern_files = self.match_by_patterns(file_index, explicit_patterns)
patterns_used.extend(explicit_patterns)
self.logger.debug(f"Explicit patterns: {len(pattern_files)} files")
# Add suggested pattern matches
if analysis.file_patterns:
suggested_files = self.match_by_patterns(file_index, analysis.file_patterns)
pattern_files.extend(suggested_files)
patterns_used.extend(analysis.file_patterns)
self.logger.debug(f"Suggested patterns: {len(suggested_files)} files")
# Combine all candidate files and remove duplicates
all_files = always_include_files + pattern_files + list(file_index.values())
seen_paths = set()
all_candidates = []
for file_info in all_files:
if file_info.relative_path not in seen_paths:
seen_paths.add(file_info.relative_path)
all_candidates.append(file_info)
self.logger.debug(f"Total candidates: {len(all_candidates)} files")
# Rank all candidates
ranked_files = self.rank_files(all_candidates, analysis)
self.logger.debug(f"Files above threshold: {len(ranked_files)}")
# Select best files within limits
selected_files = self.select_best_files(ranked_files, token_limit)
self.logger.info(f"Selected {len(selected_files)} files")
# Calculate statistics
total_tokens = sum(match.file_info.estimated_tokens for match in selected_files)
categories = {}
for match in selected_files:
category = match.file_info.category
categories[category] = categories.get(category, 0) + 1
# Calculate confidence score
confidence_score = self._calculate_confidence(selected_files, analysis)
return PathMatchingResult(
matched_files=selected_files,
total_tokens=total_tokens,
categories=categories,
patterns_used=patterns_used,
confidence_score=confidence_score
)
def _calculate_confidence(self, selected_files: List[MatchResult], analysis: AnalysisResult) -> float:
"""Calculate confidence score for the matching result."""
if not selected_files:
return 0.0
# Average relevance score
avg_relevance = sum(match.relevance_score for match in selected_files) / len(selected_files)
# Keyword coverage (how many keywords are represented)
keyword_coverage = 0.0
if analysis.keywords:
covered_keywords = set()
for match in selected_files:
for reason in match.match_reasons:
if reason.startswith('filename:') or reason.startswith('path:'):
keyword = reason.split(':', 1)[1]
covered_keywords.add(keyword)
keyword_coverage = len(covered_keywords) / len(analysis.keywords)
# Domain coverage
domain_coverage = 0.0
if analysis.domains:
covered_domains = set()
for match in selected_files:
for reason in match.match_reasons:
if reason.startswith('dir:'):
domain = reason.split('->', 1)[0].split(':', 1)[1]
covered_domains.add(domain)
domain_coverage = len(covered_domains) / len(analysis.domains)
# Weighted confidence score
confidence = (
avg_relevance * 0.5 +
keyword_coverage * 0.3 +
domain_coverage * 0.2
)
return min(confidence, 1.0)
def format_patterns(self, selected_files: List[MatchResult]) -> List[str]:
"""Format selected files as @{pattern} strings."""
pattern_format = self.config.get('output', {}).get('pattern_format', '@{{{path}}}')
patterns = []
for match in selected_files:
pattern = pattern_format.format(path=match.file_info.relative_path)
patterns.append(pattern)
return patterns
def main():
"""Command-line interface for path matcher."""
import yaml
import argparse
import json
from .file_indexer import FileIndexer
from .context_analyzer import ContextAnalyzer
parser = argparse.ArgumentParser(description="Path Matcher for UltraThink")
parser.add_argument("prompt", help="Prompt to analyze and match")
parser.add_argument("--config", default="config.yaml", help="Configuration file path")
parser.add_argument("--token-limit", type=int, help="Token limit for selection")
parser.add_argument("--patterns", nargs="*", help="Explicit patterns to include")
parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
args = parser.parse_args()
# Setup logging
level = logging.DEBUG if args.verbose else logging.INFO
logging.basicConfig(level=level, format='%(levelname)s: %(message)s')
# Load configuration
config_path = Path(__file__).parent / args.config
with open(config_path, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
# Create components
indexer = FileIndexer(config)
analyzer = ContextAnalyzer(config)
matcher = PathMatcher(config)
# Build file index
file_index = indexer.load_index()
if not file_index:
print("Building file index...")
file_index = indexer.build_index()
# Analyze prompt
analysis = analyzer.analyze(args.prompt)
# Match files
result = matcher.match_files(
file_index=file_index,
analysis=analysis,
token_limit=args.token_limit,
explicit_patterns=args.patterns
)
# Output results
print(f"Matched {len(result.matched_files)} files (~{result.total_tokens:,} tokens)")
print(f"Categories: {result.categories}")
print(f"Confidence: {result.confidence_score:.2f}")
print()
patterns = matcher.format_patterns(result.matched_files)
print("Patterns:")
for pattern in patterns[:20]: # Limit output
print(f" {pattern}")
if args.verbose:
print("\nDetailed matches:")
for match in result.matched_files[:10]:
print(f" {match.file_info.relative_path} (score: {match.relevance_score:.3f})")
print(f" Reasons: {', '.join(match.match_reasons)}")
if __name__ == "__main__":
main()

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.claude/python_script/indexer.py Normal file
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#!/usr/bin/env python3
"""
File Structure Indexer
Builds and maintains file indices for intelligent analysis.
"""
import sys
import argparse
import logging
import json
import time
from pathlib import Path
from typing import Dict, List, Optional, Any
# Add current directory to path for imports
sys.path.insert(0, str(Path(__file__).parent))
from core.config import get_config
from core.file_indexer import FileIndexer, IndexStats
from core.embedding_manager import EmbeddingManager
from utils.colors import Colors
class ProjectIndexer:
"""Manages file indexing and project statistics."""
def __init__(self, config_path: Optional[str] = None, root_path: str = "."):
self.root_path = Path(root_path).resolve()
self.config = get_config(config_path)
# Setup logging
logging.basicConfig(
level=getattr(logging, self.config.get('logging.level', 'INFO')),
format=self.config.get('logging.format', '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
)
self.logger = logging.getLogger(__name__)
# Initialize core components
self.indexer = FileIndexer(self.config, str(self.root_path))
# Initialize embedding manager if enabled
self.embedding_manager = None
if self.config.is_embedding_enabled():
try:
self.embedding_manager = EmbeddingManager(self.config)
except ImportError:
self.logger.warning("Embedding dependencies not available. Install sentence-transformers for enhanced functionality.")
def build_index(self) -> IndexStats:
"""Build or update the file index."""
print(Colors.yellow("Building file index..."))
start_time = time.time()
self.indexer.build_index()
stats = self.indexer.get_stats()
elapsed = time.time() - start_time
if stats:
print(Colors.green(f"Index built: {stats.total_files} files, ~{stats.total_tokens:,} tokens ({elapsed:.2f}s)"))
else:
print(Colors.green(f"Index built successfully ({elapsed:.2f}s)"))
return stats
def update_embeddings(self) -> bool:
"""Update embeddings for semantic similarity."""
if not self.embedding_manager:
print(Colors.error("Embedding functionality not available"))
return False
print(Colors.yellow("Updating embeddings..."))
start_time = time.time()
# Load file index
index = self.indexer.load_index()
if not index:
print(Colors.warning("No file index found. Building index first..."))
self.build_index()
index = self.indexer.load_index()
try:
count = self.embedding_manager.update_embeddings(index)
elapsed = time.time() - start_time
print(Colors.green(f"Updated {count} embeddings ({elapsed:.2f}s)"))
return True
except Exception as e:
print(Colors.error(f"Failed to update embeddings: {e}"))
return False
def get_project_stats(self) -> Dict[str, Any]:
"""Get comprehensive project statistics."""
stats = self.indexer.get_stats()
embedding_stats = {}
if self.embedding_manager:
embedding_stats = {
'embeddings_exist': self.embedding_manager.embeddings_exist(),
'embedding_count': len(self.embedding_manager._load_embedding_cache()) if self.embedding_manager.embeddings_exist() else 0
}
project_size = self._classify_project_size(stats.total_tokens if stats else 0)
return {
'files': stats.total_files if stats else 0,
'tokens': stats.total_tokens if stats else 0,
'size_bytes': stats.total_size if stats else 0,
'categories': stats.categories if stats else {},
'project_size': project_size,
'last_updated': stats.last_updated if stats else 0,
'embeddings': embedding_stats,
'config': {
'cache_dir': self.config.get_cache_dir(),
'embedding_enabled': self.config.is_embedding_enabled(),
'exclude_patterns_count': len(self.config.get_exclude_patterns())
}
}
def _classify_project_size(self, tokens: int) -> str:
"""Classify project size based on token count."""
small_limit = self.config.get('token_limits.small_project', 500000)
medium_limit = self.config.get('token_limits.medium_project', 2000000)
if tokens < small_limit:
return "small"
elif tokens < medium_limit:
return "medium"
else:
return "large"
def cleanup_cache(self):
"""Clean up old cache files."""
cache_dir = Path(self.config.get_cache_dir())
if cache_dir.exists():
print(Colors.yellow("Cleaning up cache..."))
for file in cache_dir.glob("*"):
if file.is_file():
file.unlink()
print(f"Removed: {file}")
print(Colors.green("Cache cleaned"))
def main():
"""CLI entry point for indexer."""
parser = argparse.ArgumentParser(
description="Project File Indexer - Build and manage file indices",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
python indexer.py --build # Build file index
python indexer.py --stats # Show project statistics
python indexer.py --embeddings # Update embeddings
python indexer.py --cleanup # Clean cache
"""
)
parser.add_argument('--build', action='store_true', help='Build file index')
parser.add_argument('--stats', action='store_true', help='Show project statistics')
parser.add_argument('--embeddings', action='store_true', help='Update embeddings')
parser.add_argument('--cleanup', action='store_true', help='Clean up cache files')
parser.add_argument('--output', choices=['json', 'text'], default='text', help='Output format')
parser.add_argument('--config', help='Configuration file path')
parser.add_argument('--root', default='.', help='Root directory to analyze')
args = parser.parse_args()
# Require at least one action
if not any([args.build, args.stats, args.embeddings, args.cleanup]):
parser.error("At least one action is required: --build, --stats, --embeddings, or --cleanup")
# Create indexer
indexer = ProjectIndexer(args.config, args.root)
try:
if args.cleanup:
indexer.cleanup_cache()
if args.build:
indexer.build_index()
if args.embeddings:
indexer.update_embeddings()
if args.stats:
stats = indexer.get_project_stats()
if args.output == 'json':
print(json.dumps(stats, indent=2, default=str))
else:
print(f"Total files: {stats['files']}")
print(f"Total tokens: {stats['tokens']:,}")
print(f"Project size: {stats['project_size']}")
print(f"Categories: {stats['categories']}")
if 'embeddings' in stats:
print(f"Embeddings: {stats['embeddings']['embedding_count']}")
except KeyboardInterrupt:
print(Colors.warning("\nOperation interrupted by user"))
sys.exit(1)
except Exception as e:
print(Colors.error(f"Operation failed: {e}"))
sys.exit(1)
if __name__ == "__main__":
main()

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#!/bin/bash
# Installation script for UltraThink Path-Aware Analyzer
set -e
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
# Functions
print_status() {
echo -e "${BLUE}[INFO]${NC} $1"
}
print_success() {
echo -e "${GREEN}[SUCCESS]${NC} $1"
}
print_warning() {
echo -e "${YELLOW}[WARNING]${NC} $1"
}
print_error() {
echo -e "${RED}[ERROR]${NC} $1"
}
# Check Python version
check_python() {
if command -v python3 &> /dev/null; then
PYTHON_VERSION=$(python3 -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')")
PYTHON_CMD="python3"
elif command -v python &> /dev/null; then
PYTHON_VERSION=$(python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')")
PYTHON_CMD="python"
else
print_error "Python not found. Please install Python 3.8 or later."
exit 1
fi
# Check version
if [[ $(echo "$PYTHON_VERSION >= 3.8" | bc -l) -eq 1 ]]; then
print_success "Python $PYTHON_VERSION found"
else
print_error "Python 3.8 or later required. Found Python $PYTHON_VERSION"
exit 1
fi
}
# Install dependencies
install_dependencies() {
print_status "Installing core dependencies..."
# Install core requirements
$PYTHON_CMD -m pip install --user -r requirements.txt
if [ $? -eq 0 ]; then
print_success "Core dependencies installed"
else
print_error "Failed to install core dependencies"
exit 1
fi
}
# Install optional dependencies
install_optional() {
read -p "Install RAG/embedding features? (requires ~200MB download) [y/N]: " install_rag
if [[ $install_rag =~ ^[Yy]$ ]]; then
print_status "Installing RAG dependencies..."
$PYTHON_CMD -m pip install --user sentence-transformers numpy
if [ $? -eq 0 ]; then
print_success "RAG dependencies installed"
else
print_warning "Failed to install RAG dependencies (optional)"
fi
fi
read -p "Install development tools? [y/N]: " install_dev
if [[ $install_dev =~ ^[Yy]$ ]]; then
print_status "Installing development dependencies..."
$PYTHON_CMD -m pip install --user pytest pytest-cov black flake8
if [ $? -eq 0 ]; then
print_success "Development dependencies installed"
else
print_warning "Failed to install development dependencies (optional)"
fi
fi
}
# Create wrapper script
create_wrapper() {
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" &> /dev/null && pwd)"
WRAPPER_PATH="$HOME/.local/bin/ultrathink"
# Create .local/bin if it doesn't exist
mkdir -p "$HOME/.local/bin"
# Create wrapper script
cat > "$WRAPPER_PATH" << EOF
#!/bin/bash
# UltraThink Path-Aware Analyzer Wrapper
# Auto-generated by install.sh
SCRIPT_DIR="$SCRIPT_DIR"
export PYTHONPATH="\$SCRIPT_DIR:\$PYTHONPATH"
exec $PYTHON_CMD "\$SCRIPT_DIR/path_aware_analyzer.py" "\$@"
EOF
chmod +x "$WRAPPER_PATH"
if [ -f "$WRAPPER_PATH" ]; then
print_success "Wrapper script created at $WRAPPER_PATH"
else
print_error "Failed to create wrapper script"
exit 1
fi
}
# Update configuration
setup_config() {
print_status "Setting up configuration..."
# Create cache directory
mkdir -p .claude/cache/embeddings
# Check if config needs updating
if [ ! -f config.yaml ]; then
print_error "Configuration file config.yaml not found"
exit 1
fi
print_success "Configuration ready"
}
# Test installation
test_installation() {
print_status "Testing installation..."
# Test basic functionality
if $PYTHON_CMD path_aware_analyzer.py --stats &> /dev/null; then
print_success "Installation test passed"
else
print_warning "Installation test failed - but this might be normal for first run"
fi
}
# Add to PATH instructions
show_path_instructions() {
if [[ ":$PATH:" != *":$HOME/.local/bin:"* ]]; then
print_warning "Add $HOME/.local/bin to your PATH to use 'ultrathink' command globally"
echo ""
echo "Add this line to your ~/.bashrc or ~/.zshrc:"
echo "export PATH=\"\$HOME/.local/bin:\$PATH\""
echo ""
echo "Or run: echo 'export PATH=\"\$HOME/.local/bin:\$PATH\"' >> ~/.bashrc"
echo "Then: source ~/.bashrc"
fi
}
# Main installation
main() {
print_status "Installing UltraThink Path-Aware Analyzer..."
echo ""
check_python
install_dependencies
install_optional
create_wrapper
setup_config
test_installation
echo ""
print_success "Installation complete!"
echo ""
print_status "Usage examples:"
echo " ./path_aware_analyzer.py \"analyze authentication flow\""
echo " ultrathink \"implement user login feature\""
echo " ultrathink --tool gemini \"review API endpoints\""
echo ""
show_path_instructions
}
# Run main function
main "$@"

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# Core dependencies for embedding tests
numpy>=1.21.0
scikit-learn>=1.0.0
# Sentence Transformers for advanced embeddings
sentence-transformers>=2.2.0
# Optional: For better performance and additional models
torch>=1.9.0
# Development and testing
pytest>=6.0.0
# Data handling
pandas>=1.3.0

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#!/usr/bin/env python3
"""
Setup script for UltraThink Path-Aware Analyzer
"""
from setuptools import setup, find_packages
from pathlib import Path
# Read README
readme_path = Path(__file__).parent / "README.md"
long_description = readme_path.read_text(encoding='utf-8') if readme_path.exists() else ""
# Read requirements
requirements_path = Path(__file__).parent / "requirements.txt"
requirements = []
if requirements_path.exists():
with open(requirements_path, 'r', encoding='utf-8') as f:
for line in f:
line = line.strip()
if line and not line.startswith('#'):
requirements.append(line)
setup(
name="ultrathink-path-analyzer",
version="1.0.0",
description="Lightweight path-aware program for intelligent file pattern detection and analysis",
long_description=long_description,
long_description_content_type="text/markdown",
author="UltraThink Development Team",
author_email="dev@ultrathink.ai",
url="https://github.com/ultrathink/path-analyzer",
packages=find_packages(),
py_modules=[
'analyzer', # Main entry point
],
install_requires=requirements,
extras_require={
'rag': [
'sentence-transformers>=2.2.0',
'numpy>=1.21.0'
],
'nlp': [
'nltk>=3.8',
'spacy>=3.4.0'
],
'performance': [
'numba>=0.56.0'
],
'dev': [
'pytest>=7.0.0',
'pytest-cov>=4.0.0',
'black>=22.0.0',
'flake8>=5.0.0'
]
},
entry_points={
'console_scripts': [
'path-analyzer=cli:main',
'path-indexer=indexer:main',
'analyzer=analyzer:main', # Legacy compatibility
'module-analyzer=tools.module_analyzer:main',
'tech-stack=tools.tech_stack:main',
],
},
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Topic :: Software Development :: Tools",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Operating System :: OS Independent",
],
python_requires=">=3.8",
keywords="ai, analysis, path-detection, code-analysis, file-matching, rag, nlp",
project_urls={
"Bug Reports": "https://github.com/ultrathink/path-analyzer/issues",
"Source": "https://github.com/ultrathink/path-analyzer",
"Documentation": "https://github.com/ultrathink/path-analyzer/docs",
},
)

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"""
Independent tool scripts for specialized analysis tasks.
Provides module analysis, tech stack detection, and workflow management tools.
"""
from .module_analyzer import ModuleAnalyzer, ModuleInfo
from .tech_stack import TechStackLoader
__all__ = [
'ModuleAnalyzer',
'ModuleInfo',
'TechStackLoader'
]

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#!/usr/bin/env python3
"""
Unified Module Analyzer
Combines functionality from detect_changed_modules.py and get_modules_by_depth.py
into a single, comprehensive module analysis tool.
"""
import os
import sys
import subprocess
import time
import json
from pathlib import Path
from typing import List, Dict, Optional, Set, Tuple
from dataclasses import dataclass, asdict
# Add parent directory for imports
sys.path.insert(0, str(Path(__file__).parent.parent))
from core.config import get_config
from core.gitignore_parser import GitignoreParser
@dataclass
class ModuleInfo:
"""Information about a module/directory."""
depth: int
path: str
files: int
types: List[str]
has_claude: bool
status: str = "normal" # changed, normal, new, deleted
last_modified: Optional[float] = None
def to_dict(self) -> Dict:
return asdict(self)
class ModuleAnalyzer:
"""Unified module analysis tool with change detection and depth analysis."""
def __init__(self, root_path: str = ".", config_path: Optional[str] = None):
self.root_path = Path(root_path).resolve()
self.config = get_config(config_path)
# Source file extensions for analysis
self.source_extensions = {
'.md', '.js', '.ts', '.jsx', '.tsx', '.py', '.go', '.rs',
'.java', '.cpp', '.c', '.h', '.sh', '.ps1', '.json', '.yaml', '.yml',
'.php', '.rb', '.swift', '.kt', '.scala', '.dart'
}
# Initialize gitignore parser for exclusions
self.gitignore_parser = GitignoreParser(str(self.root_path))
self.exclude_patterns = self._build_exclusion_patterns()
def _build_exclusion_patterns(self) -> Set[str]:
"""Build exclusion patterns from config and gitignore."""
exclusions = {
'.git', '.history', '.vscode', '__pycache__', '.pytest_cache',
'node_modules', 'dist', 'build', '.egg-info', '.env',
'.cache', '.tmp', '.temp', '.DS_Store', 'Thumbs.db'
}
# Add patterns from config
config_patterns = self.config.get('exclude_patterns', [])
for pattern in config_patterns:
# Extract directory names from patterns
if '/' in pattern:
parts = pattern.replace('*/', '').replace('/*', '').split('/')
exclusions.update(part for part in parts if part and not part.startswith('*'))
return exclusions
def _should_exclude_directory(self, dir_path: Path) -> bool:
"""Check if directory should be excluded from analysis."""
dir_name = dir_path.name
# Check against exclusion patterns
if dir_name in self.exclude_patterns:
return True
# Check if directory starts with . (hidden directories)
if dir_name.startswith('.') and dir_name not in {'.github', '.vscode'}:
return True
return False
def get_git_changed_files(self, since: str = "HEAD") -> Set[str]:
"""Get files changed in git."""
changed_files = set()
try:
# Check if we're in a git repository
subprocess.run(['git', 'rev-parse', '--git-dir'],
check=True, capture_output=True, cwd=self.root_path)
# Get changes since specified reference
commands = [
['git', 'diff', '--name-only', since], # Changes since reference
['git', 'diff', '--name-only', '--staged'], # Staged changes
['git', 'ls-files', '--others', '--exclude-standard'] # Untracked files
]
for cmd in commands:
try:
result = subprocess.run(cmd, capture_output=True, text=True,
cwd=self.root_path, check=True)
if result.stdout.strip():
files = result.stdout.strip().split('\n')
changed_files.update(f for f in files if f)
except subprocess.CalledProcessError:
continue
except subprocess.CalledProcessError:
# Not a git repository or git not available
pass
return changed_files
def get_recently_modified_files(self, hours: int = 24) -> Set[str]:
"""Get files modified within the specified hours."""
cutoff_time = time.time() - (hours * 3600)
recent_files = set()
try:
for file_path in self.root_path.rglob('*'):
if file_path.is_file():
try:
if file_path.stat().st_mtime > cutoff_time:
rel_path = file_path.relative_to(self.root_path)
recent_files.add(str(rel_path))
except (OSError, ValueError):
continue
except Exception:
pass
return recent_files
def analyze_directory(self, dir_path: Path) -> Optional[ModuleInfo]:
"""Analyze a single directory and return module information."""
if self._should_exclude_directory(dir_path):
return None
try:
# Count files by type
file_types = set()
file_count = 0
has_claude = False
last_modified = 0
for item in dir_path.iterdir():
if item.is_file():
file_count += 1
# Track file types
if item.suffix.lower() in self.source_extensions:
file_types.add(item.suffix.lower())
# Check for CLAUDE.md
if item.name.upper() == 'CLAUDE.MD':
has_claude = True
# Track latest modification
try:
mtime = item.stat().st_mtime
last_modified = max(last_modified, mtime)
except OSError:
continue
# Calculate depth relative to root
try:
relative_path = dir_path.relative_to(self.root_path)
depth = len(relative_path.parts)
except ValueError:
depth = 0
return ModuleInfo(
depth=depth,
path=str(relative_path) if depth > 0 else ".",
files=file_count,
types=sorted(list(file_types)),
has_claude=has_claude,
last_modified=last_modified if last_modified > 0 else None
)
except (PermissionError, OSError):
return None
def detect_changed_modules(self, since: str = "HEAD") -> List[ModuleInfo]:
"""Detect modules affected by changes."""
changed_files = self.get_git_changed_files(since)
# If no git changes, fall back to recently modified files
if not changed_files:
changed_files = self.get_recently_modified_files(24)
# Get affected directories
affected_dirs = set()
for file_path in changed_files:
full_path = self.root_path / file_path
if full_path.exists():
# Add the file's directory and parent directories
current_dir = full_path.parent
while current_dir != self.root_path and current_dir.parent != current_dir:
affected_dirs.add(current_dir)
current_dir = current_dir.parent
# Analyze affected directories
modules = []
for dir_path in affected_dirs:
module_info = self.analyze_directory(dir_path)
if module_info:
module_info.status = "changed"
modules.append(module_info)
return sorted(modules, key=lambda m: (m.depth, m.path))
def analyze_by_depth(self, max_depth: Optional[int] = None) -> List[ModuleInfo]:
"""Analyze all modules organized by depth (deepest first)."""
modules = []
def scan_directory(dir_path: Path, current_depth: int = 0):
"""Recursively scan directories."""
if max_depth and current_depth > max_depth:
return
module_info = self.analyze_directory(dir_path)
if module_info and module_info.files > 0:
modules.append(module_info)
# Recurse into subdirectories
try:
for item in dir_path.iterdir():
if item.is_dir() and not self._should_exclude_directory(item):
scan_directory(item, current_depth + 1)
except (PermissionError, OSError):
pass
scan_directory(self.root_path)
# Sort by depth (deepest first), then by path
return sorted(modules, key=lambda m: (-m.depth, m.path))
def get_dependencies(self, module_path: str) -> List[str]:
"""Get module dependencies (basic implementation)."""
dependencies = []
module_dir = self.root_path / module_path
if not module_dir.exists() or not module_dir.is_dir():
return dependencies
# Look for common dependency files
dependency_files = [
'package.json', # Node.js
'requirements.txt', # Python
'Cargo.toml', # Rust
'go.mod', # Go
'pom.xml', # Java Maven
'build.gradle', # Java Gradle
]
for dep_file in dependency_files:
dep_path = module_dir / dep_file
if dep_path.exists():
dependencies.append(str(dep_path.relative_to(self.root_path)))
return dependencies
def find_modules_with_pattern(self, pattern: str) -> List[ModuleInfo]:
"""Find modules matching a specific pattern in their path or files."""
modules = self.analyze_by_depth()
matching_modules = []
for module in modules:
# Check if pattern matches path
if pattern.lower() in module.path.lower():
matching_modules.append(module)
continue
# Check if pattern matches file types
if any(pattern.lower() in ext.lower() for ext in module.types):
matching_modules.append(module)
return matching_modules
def export_analysis(self, modules: List[ModuleInfo], format: str = "json") -> str:
"""Export module analysis in specified format."""
if format == "json":
return json.dumps([module.to_dict() for module in modules], indent=2)
elif format == "list":
lines = []
for module in modules:
status = f"[{module.status}]" if module.status != "normal" else ""
claude_marker = "[CLAUDE]" if module.has_claude else ""
lines.append(f"{module.path} (depth:{module.depth}, files:{module.files}) {status} {claude_marker}")
return "\n".join(lines)
elif format == "grouped":
grouped = {}
for module in modules:
depth = module.depth
if depth not in grouped:
grouped[depth] = []
grouped[depth].append(module)
lines = []
for depth in sorted(grouped.keys()):
lines.append(f"\n=== Depth {depth} ===")
for module in grouped[depth]:
status = f"[{module.status}]" if module.status != "normal" else ""
claude_marker = "[CLAUDE]" if module.has_claude else ""
lines.append(f" {module.path} (files:{module.files}) {status} {claude_marker}")
return "\n".join(lines)
elif format == "paths":
return "\n".join(module.path for module in modules)
else:
raise ValueError(f"Unsupported format: {format}")
def main():
"""Main CLI entry point."""
import argparse
parser = argparse.ArgumentParser(description="Module Analysis Tool")
parser.add_argument("command", choices=["changed", "depth", "dependencies", "find"],
help="Analysis command to run")
parser.add_argument("--format", choices=["json", "list", "grouped", "paths"],
default="list", help="Output format")
parser.add_argument("--since", default="HEAD~1",
help="Git reference for change detection (default: HEAD~1)")
parser.add_argument("--max-depth", type=int,
help="Maximum directory depth to analyze")
parser.add_argument("--pattern", help="Pattern to search for (for find command)")
parser.add_argument("--module", help="Module path for dependency analysis")
parser.add_argument("--config", help="Configuration file path")
args = parser.parse_args()
analyzer = ModuleAnalyzer(config_path=args.config)
if args.command == "changed":
modules = analyzer.detect_changed_modules(args.since)
print(analyzer.export_analysis(modules, args.format))
elif args.command == "depth":
modules = analyzer.analyze_by_depth(args.max_depth)
print(analyzer.export_analysis(modules, args.format))
elif args.command == "dependencies":
if not args.module:
print("Error: --module required for dependencies command", file=sys.stderr)
sys.exit(1)
deps = analyzer.get_dependencies(args.module)
if args.format == "json":
print(json.dumps(deps, indent=2))
else:
print("\n".join(deps))
elif args.command == "find":
if not args.pattern:
print("Error: --pattern required for find command", file=sys.stderr)
sys.exit(1)
modules = analyzer.find_modules_with_pattern(args.pattern)
print(analyzer.export_analysis(modules, args.format))
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Python equivalent of tech-stack-loader.sh
DMSFlow Tech Stack Guidelines Loader
Returns tech stack specific coding guidelines and best practices for Claude processing
Usage: python tech_stack_loader.py [command] [tech_stack]
"""
import sys
import argparse
import re
from pathlib import Path
from typing import Dict, List, Optional, Tuple
class TechStackLoader:
"""Load tech stack specific development guidelines."""
def __init__(self, script_dir: Optional[str] = None):
if script_dir:
self.script_dir = Path(script_dir)
else:
self.script_dir = Path(__file__).parent
# Look for template directory in multiple locations
possible_template_dirs = [
self.script_dir / "../tech-stack-templates",
self.script_dir / "../workflows/cli-templates/tech-stacks",
self.script_dir / "tech-stack-templates",
self.script_dir / "templates",
]
self.template_dir = None
for template_dir in possible_template_dirs:
if template_dir.exists():
self.template_dir = template_dir.resolve()
break
if not self.template_dir:
# Create a default template directory
self.template_dir = self.script_dir / "tech-stack-templates"
self.template_dir.mkdir(exist_ok=True)
def parse_yaml_frontmatter(self, content: str) -> Tuple[Dict[str, str], str]:
"""Parse YAML frontmatter from markdown content."""
frontmatter = {}
content_start = 0
lines = content.split('\n')
if lines and lines[0].strip() == '---':
# Find the closing ---
for i, line in enumerate(lines[1:], 1):
if line.strip() == '---':
content_start = i + 1
break
elif ':' in line:
key, value = line.split(':', 1)
frontmatter[key.strip()] = value.strip()
# Return frontmatter and content without YAML
remaining_content = '\n'.join(lines[content_start:])
return frontmatter, remaining_content
def list_available_guidelines(self) -> str:
"""List all available development guidelines."""
output = ["Available Development Guidelines:", "=" * 33]
if not self.template_dir.exists():
output.append("No template directory found.")
return '\n'.join(output)
for file_path in self.template_dir.glob("*.md"):
try:
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
frontmatter, _ = self.parse_yaml_frontmatter(content)
name = frontmatter.get('name', file_path.stem)
description = frontmatter.get('description', 'No description available')
output.append(f"{name:<20} - {description}")
except Exception as e:
output.append(f"{file_path.stem:<20} - Error reading file: {e}")
return '\n'.join(output)
def load_guidelines(self, tech_stack: str) -> str:
"""Load specific development guidelines."""
template_path = self.template_dir / f"{tech_stack}.md"
if not template_path.exists():
# Try with different naming conventions
alternatives = [
f"{tech_stack}-dev.md",
f"{tech_stack}_dev.md",
f"{tech_stack.replace('-', '_')}.md",
f"{tech_stack.replace('_', '-')}.md"
]
for alt in alternatives:
alt_path = self.template_dir / alt
if alt_path.exists():
template_path = alt_path
break
else:
raise FileNotFoundError(
f"Error: Development guidelines '{tech_stack}' not found\n"
f"Use --list to see available guidelines"
)
try:
with open(template_path, 'r', encoding='utf-8') as f:
content = f.read()
# Parse and return content without YAML frontmatter
_, content_without_yaml = self.parse_yaml_frontmatter(content)
return content_without_yaml.strip()
except Exception as e:
raise RuntimeError(f"Error reading guidelines file: {e}")
def get_version(self) -> str:
"""Get version information."""
return "DMSFlow tech-stack-loader v2.0 (Python)\nSemantic-based development guidelines system"
def get_help(self) -> str:
"""Get help message."""
return """Usage:
tech_stack_loader.py --list List all available guidelines with descriptions
tech_stack_loader.py --load <name> Load specific development guidelines
tech_stack_loader.py <name> Load specific guidelines (legacy format)
tech_stack_loader.py --help Show this help message
tech_stack_loader.py --version Show version information
Examples:
tech_stack_loader.py --list
tech_stack_loader.py --load javascript-dev
tech_stack_loader.py python-dev"""
def main():
"""Command-line interface."""
parser = argparse.ArgumentParser(
description="DMSFlow Tech Stack Guidelines Loader",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""Examples:
python tech_stack_loader.py --list
python tech_stack_loader.py --load javascript-dev
python tech_stack_loader.py python-dev"""
)
parser.add_argument("command", nargs="?", help="Command or tech stack name")
parser.add_argument("tech_stack", nargs="?", help="Tech stack name (when using --load)")
parser.add_argument("--list", action="store_true", help="List all available guidelines")
parser.add_argument("--load", metavar="TECH_STACK", help="Load specific development guidelines")
parser.add_argument("--version", "-v", action="store_true", help="Show version information")
parser.add_argument("--template-dir", help="Override template directory path")
args = parser.parse_args()
try:
loader = TechStackLoader(args.template_dir)
# Handle version check
if args.version or args.command == "--version":
print(loader.get_version())
return
# Handle list command
if args.list or args.command == "--list":
print(loader.list_available_guidelines())
return
# Handle load command
if args.load:
result = loader.load_guidelines(args.load)
print(result)
return
if args.command == "--load" and args.tech_stack:
result = loader.load_guidelines(args.tech_stack)
print(result)
return
# Handle legacy usage (direct tech stack name)
if args.command and args.command not in ["--help", "--list", "--load"]:
result = loader.load_guidelines(args.command)
print(result)
return
# Show help
print(loader.get_help())
except (FileNotFoundError, RuntimeError) as e:
print(str(e), file=sys.stderr)
sys.exit(1)
except Exception as e:
print(f"Unexpected error: {e}", file=sys.stderr)
sys.exit(1)
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Python equivalent of update_module_claude.sh
Update CLAUDE.md for a specific module with automatic layer detection
Usage: python update_module_claude.py <module_path> [update_type]
module_path: Path to the module directory
update_type: full|related (default: full)
Script automatically detects layer depth and selects appropriate template
"""
import os
import sys
import subprocess
import time
import argparse
from pathlib import Path
from typing import Optional, Tuple, Dict
from dataclasses import dataclass
@dataclass
class LayerInfo:
"""Information about a documentation layer."""
name: str
template_path: str
analysis_strategy: str
class ModuleClaudeUpdater:
"""Update CLAUDE.md documentation for modules with layer detection."""
def __init__(self, home_dir: Optional[str] = None):
self.home_dir = Path(home_dir) if home_dir else Path.home()
self.template_base = self.home_dir / ".claude/workflows/cli-templates/prompts/dms"
def detect_layer(self, module_path: str) -> LayerInfo:
"""Determine documentation layer based on path patterns."""
clean_path = module_path.replace('./', '') if module_path.startswith('./') else module_path
if module_path == ".":
# Root directory
return LayerInfo(
name="Layer 1 (Root)",
template_path=str(self.template_base / "claude-layer1-root.txt"),
analysis_strategy="--all-files"
)
elif '/' not in clean_path:
# Top-level directories (e.g., .claude, src, tests)
return LayerInfo(
name="Layer 2 (Domain)",
template_path=str(self.template_base / "claude-layer2-domain.txt"),
analysis_strategy="@{*/CLAUDE.md}"
)
elif clean_path.count('/') == 1:
# Second-level directories (e.g., .claude/scripts, src/components)
return LayerInfo(
name="Layer 3 (Module)",
template_path=str(self.template_base / "claude-layer3-module.txt"),
analysis_strategy="@{*/CLAUDE.md}"
)
else:
# Deeper directories (e.g., .claude/workflows/cli-templates/prompts)
return LayerInfo(
name="Layer 4 (Sub-Module)",
template_path=str(self.template_base / "claude-layer4-submodule.txt"),
analysis_strategy="--all-files"
)
def load_template(self, template_path: str) -> str:
"""Load template content from file."""
try:
with open(template_path, 'r', encoding='utf-8') as f:
return f.read()
except FileNotFoundError:
print(f" [WARN] Template not found: {template_path}, using fallback")
return "Update CLAUDE.md documentation for this module following hierarchy standards."
except Exception as e:
print(f" [WARN] Error reading template: {e}, using fallback")
return "Update CLAUDE.md documentation for this module following hierarchy standards."
def build_prompt(self, layer_info: LayerInfo, module_path: str, update_type: str) -> str:
"""Build the prompt for gemini."""
template_content = self.load_template(layer_info.template_path)
module_name = os.path.basename(module_path)
if update_type == "full":
update_context = """
Update Mode: Complete refresh
- Perform comprehensive analysis of all content
- Document patterns, architecture, and purpose
- Consider existing documentation hierarchy
- Follow template guidelines strictly"""
else:
update_context = """
Update Mode: Context-aware update
- Focus on recent changes and affected areas
- Maintain consistency with existing documentation
- Update only relevant sections
- Follow template guidelines for updated content"""
base_prompt = f"""
[CRITICAL] RULES - MUST FOLLOW:
1. ONLY modify CLAUDE.md files at any hierarchy level
2. NEVER modify source code files
3. Focus exclusively on updating documentation
4. Follow the template guidelines exactly
{template_content}
{update_context}
Module Information:
- Name: {module_name}
- Path: {module_path}
- Layer: {layer_info.name}
- Analysis Strategy: {layer_info.analysis_strategy}"""
return base_prompt
def execute_gemini_command(self, prompt: str, analysis_strategy: str, module_path: str) -> bool:
"""Execute gemini command with the appropriate strategy."""
original_dir = os.getcwd()
try:
os.chdir(module_path)
if analysis_strategy == "--all-files":
cmd = ["gemini", "--all-files", "--yolo", "-p", prompt]
else:
cmd = ["gemini", "--yolo", "-p", f"{analysis_strategy} {prompt}"]
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode == 0:
return True
else:
print(f" [ERROR] Gemini command failed: {result.stderr}")
return False
except subprocess.CalledProcessError as e:
print(f" [ERROR] Error executing gemini: {e}")
return False
except FileNotFoundError:
print(f" [ERROR] Gemini command not found. Make sure gemini is installed and in PATH.")
return False
finally:
os.chdir(original_dir)
def update_module_claude(self, module_path: str, update_type: str = "full") -> bool:
"""Main function to update CLAUDE.md for a module."""
# Validate parameters
if not module_path:
print("[ERROR] Module path is required")
print("Usage: update_module_claude.py <module_path> [update_type]")
return False
path_obj = Path(module_path)
if not path_obj.exists() or not path_obj.is_dir():
print(f"[ERROR] Directory '{module_path}' does not exist")
return False
# Check if directory has files
files = list(path_obj.glob('*'))
file_count = len([f for f in files if f.is_file()])
if file_count == 0:
print(f"[SKIP] Skipping '{module_path}' - no files found")
return True
# Detect layer and get configuration
layer_info = self.detect_layer(module_path)
print(f"[UPDATE] Updating: {module_path}")
print(f" Layer: {layer_info.name} | Type: {update_type} | Files: {file_count}")
print(f" Template: {os.path.basename(layer_info.template_path)} | Strategy: {layer_info.analysis_strategy}")
# Build prompt
prompt = self.build_prompt(layer_info, module_path, update_type)
# Execute update
start_time = time.time()
print(" [PROGRESS] Starting update...")
success = self.execute_gemini_command(prompt, layer_info.analysis_strategy, module_path)
if success:
duration = int(time.time() - start_time)
print(f" [OK] Completed in {duration}s")
return True
else:
print(f" [ERROR] Update failed for {module_path}")
return False
def main():
"""Command-line interface."""
parser = argparse.ArgumentParser(
description="Update CLAUDE.md for a specific module with automatic layer detection",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""Examples:
python update_module_claude.py .
python update_module_claude.py src/components full
python update_module_claude.py .claude/scripts related"""
)
parser.add_argument("module_path", help="Path to the module directory")
parser.add_argument("update_type", nargs="?", choices=["full", "related"],
default="full", help="Update type (default: full)")
parser.add_argument("--home", help="Override home directory path")
parser.add_argument("--dry-run", action="store_true",
help="Show what would be done without executing")
args = parser.parse_args()
try:
updater = ModuleClaudeUpdater(args.home)
if args.dry_run:
layer_info = updater.detect_layer(args.module_path)
prompt = updater.build_prompt(layer_info, args.module_path, args.update_type)
print("[DRY-RUN] Dry run mode - showing configuration:")
print(f"Module Path: {args.module_path}")
print(f"Update Type: {args.update_type}")
print(f"Layer: {layer_info.name}")
print(f"Template: {layer_info.template_path}")
print(f"Strategy: {layer_info.analysis_strategy}")
print("\nPrompt preview:")
print("-" * 50)
print(prompt[:500] + "..." if len(prompt) > 500 else prompt)
return
success = updater.update_module_claude(args.module_path, args.update_type)
sys.exit(0 if success else 1)
except KeyboardInterrupt:
print("\n[ERROR] Operation cancelled by user")
sys.exit(1)
except Exception as e:
print(f"[ERROR] Unexpected error: {e}")
sys.exit(1)
if __name__ == "__main__":
main()

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"""
Shared utility functions and helpers.
Provides common functionality for colors, caching, and I/O operations.
"""
from .colors import Colors
from .cache import CacheManager
from .io_helpers import IOHelpers, ensure_directory, safe_read_file
__all__ = [
'Colors',
'CacheManager',
'IOHelpers',
'ensure_directory',
'safe_read_file'
]

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#!/usr/bin/env python3
"""
Cache Management Utility
Provides unified caching functionality for the analyzer system.
"""
import os
import json
import time
import hashlib
import pickle
import logging
from pathlib import Path
from typing import Any, Optional, Dict, Union
from dataclasses import dataclass, asdict
@dataclass
class CacheEntry:
"""Cache entry with metadata."""
value: Any
timestamp: float
ttl: Optional[float] = None
key_hash: Optional[str] = None
def is_expired(self) -> bool:
"""Check if cache entry is expired."""
if self.ttl is None:
return False
return time.time() - self.timestamp > self.ttl
def to_dict(self) -> Dict:
"""Convert to dictionary for JSON serialization."""
return {
'value': self.value,
'timestamp': self.timestamp,
'ttl': self.ttl,
'key_hash': self.key_hash
}
@classmethod
def from_dict(cls, data: Dict) -> 'CacheEntry':
"""Create from dictionary."""
return cls(**data)
class CacheManager:
"""Unified cache manager with multiple storage backends."""
def __init__(self, cache_dir: str = "cache", default_ttl: int = 3600):
self.cache_dir = Path(cache_dir)
self.cache_dir.mkdir(parents=True, exist_ok=True)
self.default_ttl = default_ttl
self.logger = logging.getLogger(__name__)
# In-memory cache for fast access
self._memory_cache: Dict[str, CacheEntry] = {}
# Cache subdirectories
self.json_cache_dir = self.cache_dir / "json"
self.pickle_cache_dir = self.cache_dir / "pickle"
self.temp_cache_dir = self.cache_dir / "temp"
for cache_subdir in [self.json_cache_dir, self.pickle_cache_dir, self.temp_cache_dir]:
cache_subdir.mkdir(exist_ok=True)
def _generate_key_hash(self, key: str) -> str:
"""Generate a hash for the cache key."""
return hashlib.md5(key.encode('utf-8')).hexdigest()
def _get_cache_path(self, key: str, cache_type: str = "json") -> Path:
"""Get cache file path for a key."""
key_hash = self._generate_key_hash(key)
if cache_type == "json":
return self.json_cache_dir / f"{key_hash}.json"
elif cache_type == "pickle":
return self.pickle_cache_dir / f"{key_hash}.pkl"
elif cache_type == "temp":
return self.temp_cache_dir / f"{key_hash}.tmp"
else:
raise ValueError(f"Unsupported cache type: {cache_type}")
def set(self, key: str, value: Any, ttl: Optional[int] = None,
storage: str = "memory") -> bool:
"""Set a cache value."""
if ttl is None:
ttl = self.default_ttl
entry = CacheEntry(
value=value,
timestamp=time.time(),
ttl=ttl,
key_hash=self._generate_key_hash(key)
)
try:
if storage == "memory":
self._memory_cache[key] = entry
return True
elif storage == "json":
cache_path = self._get_cache_path(key, "json")
with open(cache_path, 'w', encoding='utf-8') as f:
json.dump(entry.to_dict(), f, indent=2, default=str)
return True
elif storage == "pickle":
cache_path = self._get_cache_path(key, "pickle")
with open(cache_path, 'wb') as f:
pickle.dump(entry, f)
return True
else:
self.logger.warning(f"Unsupported storage type: {storage}")
return False
except Exception as e:
self.logger.error(f"Failed to set cache for key '{key}': {e}")
return False
def get(self, key: str, storage: str = "memory",
default: Any = None) -> Any:
"""Get a cache value."""
try:
entry = None
if storage == "memory":
entry = self._memory_cache.get(key)
elif storage == "json":
cache_path = self._get_cache_path(key, "json")
if cache_path.exists():
with open(cache_path, 'r', encoding='utf-8') as f:
data = json.load(f)
entry = CacheEntry.from_dict(data)
elif storage == "pickle":
cache_path = self._get_cache_path(key, "pickle")
if cache_path.exists():
with open(cache_path, 'rb') as f:
entry = pickle.load(f)
else:
self.logger.warning(f"Unsupported storage type: {storage}")
return default
if entry is None:
return default
# Check if entry is expired
if entry.is_expired():
self.delete(key, storage)
return default
return entry.value
except Exception as e:
self.logger.error(f"Failed to get cache for key '{key}': {e}")
return default
def delete(self, key: str, storage: str = "memory") -> bool:
"""Delete a cache entry."""
try:
if storage == "memory":
if key in self._memory_cache:
del self._memory_cache[key]
return True
elif storage in ["json", "pickle", "temp"]:
cache_path = self._get_cache_path(key, storage)
if cache_path.exists():
cache_path.unlink()
return True
else:
self.logger.warning(f"Unsupported storage type: {storage}")
return False
except Exception as e:
self.logger.error(f"Failed to delete cache for key '{key}': {e}")
return False
def exists(self, key: str, storage: str = "memory") -> bool:
"""Check if a cache entry exists and is not expired."""
return self.get(key, storage) is not None
def clear(self, storage: Optional[str] = None) -> bool:
"""Clear cache entries."""
try:
if storage is None or storage == "memory":
self._memory_cache.clear()
if storage is None or storage == "json":
for cache_file in self.json_cache_dir.glob("*.json"):
cache_file.unlink()
if storage is None or storage == "pickle":
for cache_file in self.pickle_cache_dir.glob("*.pkl"):
cache_file.unlink()
if storage is None or storage == "temp":
for cache_file in self.temp_cache_dir.glob("*.tmp"):
cache_file.unlink()
return True
except Exception as e:
self.logger.error(f"Failed to clear cache: {e}")
return False
def cleanup_expired(self) -> int:
"""Clean up expired cache entries."""
cleaned_count = 0
try:
# Clean memory cache
expired_keys = []
for key, entry in self._memory_cache.items():
if entry.is_expired():
expired_keys.append(key)
for key in expired_keys:
del self._memory_cache[key]
cleaned_count += 1
# Clean file caches
for cache_type in ["json", "pickle"]:
cache_dir = self.json_cache_dir if cache_type == "json" else self.pickle_cache_dir
extension = f".{cache_type}" if cache_type == "json" else ".pkl"
for cache_file in cache_dir.glob(f"*{extension}"):
try:
if cache_type == "json":
with open(cache_file, 'r', encoding='utf-8') as f:
data = json.load(f)
entry = CacheEntry.from_dict(data)
else:
with open(cache_file, 'rb') as f:
entry = pickle.load(f)
if entry.is_expired():
cache_file.unlink()
cleaned_count += 1
except Exception:
# If we can't read the cache file, delete it
cache_file.unlink()
cleaned_count += 1
self.logger.info(f"Cleaned up {cleaned_count} expired cache entries")
return cleaned_count
except Exception as e:
self.logger.error(f"Failed to cleanup expired cache entries: {e}")
return 0
def get_stats(self) -> Dict[str, Any]:
"""Get cache statistics."""
stats = {
'memory_entries': len(self._memory_cache),
'json_files': len(list(self.json_cache_dir.glob("*.json"))),
'pickle_files': len(list(self.pickle_cache_dir.glob("*.pkl"))),
'temp_files': len(list(self.temp_cache_dir.glob("*.tmp"))),
'cache_dir_size': 0
}
# Calculate total cache directory size
try:
for cache_file in self.cache_dir.rglob("*"):
if cache_file.is_file():
stats['cache_dir_size'] += cache_file.stat().st_size
except Exception:
pass
return stats
def set_file_cache(self, key: str, file_path: Union[str, Path],
ttl: Optional[int] = None) -> bool:
"""Cache a file by copying it to the cache directory."""
try:
source_path = Path(file_path)
if not source_path.exists():
return False
cache_path = self.temp_cache_dir / f"{self._generate_key_hash(key)}.cached"
# Copy file to cache
import shutil
shutil.copy2(source_path, cache_path)
# Store metadata
metadata = {
'original_path': str(source_path),
'cached_path': str(cache_path),
'size': source_path.stat().st_size,
'timestamp': time.time(),
'ttl': ttl or self.default_ttl
}
return self.set(f"{key}_metadata", metadata, ttl, "json")
except Exception as e:
self.logger.error(f"Failed to cache file '{file_path}': {e}")
return False
def get_file_cache(self, key: str) -> Optional[Path]:
"""Get cached file path."""
metadata = self.get(f"{key}_metadata", "json")
if metadata is None:
return None
cached_path = Path(metadata['cached_path'])
if not cached_path.exists():
# Cache file missing, clean up metadata
self.delete(f"{key}_metadata", "json")
return None
return cached_path
# Global cache manager instance
_global_cache = None
def get_cache_manager(cache_dir: str = "cache", default_ttl: int = 3600) -> CacheManager:
"""Get global cache manager instance."""
global _global_cache
if _global_cache is None:
_global_cache = CacheManager(cache_dir, default_ttl)
return _global_cache
if __name__ == "__main__":
# Test cache functionality
cache = CacheManager("test_cache")
# Test memory cache
cache.set("test_key", {"data": "test_value"}, ttl=60)
print(f"Memory cache: {cache.get('test_key')}")
# Test JSON cache
cache.set("json_key", {"complex": {"data": [1, 2, 3]}}, ttl=60, storage="json")
print(f"JSON cache: {cache.get('json_key', storage='json')}")
# Test stats
print(f"Cache stats: {cache.get_stats()}")
# Clean up
cache.clear()

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#!/usr/bin/env python3
"""
Terminal Colors Utility
Provides ANSI color codes for terminal output formatting.
"""
import os
import sys
from typing import Optional
class Colors:
"""ANSI color codes for terminal output."""
# Basic colors
RED = '\033[0;31m'
GREEN = '\033[0;32m'
YELLOW = '\033[1;33m'
BLUE = '\033[0;34m'
PURPLE = '\033[0;35m'
CYAN = '\033[0;36m'
WHITE = '\033[0;37m'
BLACK = '\033[0;30m'
# Bright colors
BRIGHT_RED = '\033[1;31m'
BRIGHT_GREEN = '\033[1;32m'
BRIGHT_YELLOW = '\033[1;33m'
BRIGHT_BLUE = '\033[1;34m'
BRIGHT_PURPLE = '\033[1;35m'
BRIGHT_CYAN = '\033[1;36m'
BRIGHT_WHITE = '\033[1;37m'
# Background colors
BG_RED = '\033[41m'
BG_GREEN = '\033[42m'
BG_YELLOW = '\033[43m'
BG_BLUE = '\033[44m'
BG_PURPLE = '\033[45m'
BG_CYAN = '\033[46m'
BG_WHITE = '\033[47m'
# Text formatting
BOLD = '\033[1m'
DIM = '\033[2m'
UNDERLINE = '\033[4m'
BLINK = '\033[5m'
REVERSE = '\033[7m'
STRIKETHROUGH = '\033[9m'
# Reset
NC = '\033[0m' # No Color / Reset
RESET = '\033[0m'
@classmethod
def is_tty(cls) -> bool:
"""Check if output is a TTY (supports colors)."""
return hasattr(sys.stdout, 'isatty') and sys.stdout.isatty()
@classmethod
def supports_color(cls) -> bool:
"""Check if the terminal supports color output."""
# Check environment variables
if os.getenv('NO_COLOR'):
return False
if os.getenv('FORCE_COLOR'):
return True
# Check if output is a TTY
if not cls.is_tty():
return False
# Check TERM environment variable
term = os.getenv('TERM', '').lower()
if 'color' in term or term in ('xterm', 'xterm-256color', 'screen', 'tmux'):
return True
# Windows Terminal detection
if os.name == 'nt':
# Windows 10 version 1511 and later support ANSI colors
try:
import subprocess
result = subprocess.run(['ver'], capture_output=True, text=True, shell=True)
if result.returncode == 0:
version_info = result.stdout
# Extract Windows version (simplified check)
if 'Windows' in version_info:
return True
except Exception:
pass
return False
@classmethod
def colorize(cls, text: str, color: str, bold: bool = False) -> str:
"""Apply color to text if colors are supported."""
if not cls.supports_color():
return text
prefix = color
if bold:
prefix = cls.BOLD + prefix
return f"{prefix}{text}{cls.RESET}"
@classmethod
def red(cls, text: str, bold: bool = False) -> str:
"""Color text red."""
return cls.colorize(text, cls.RED, bold)
@classmethod
def green(cls, text: str, bold: bool = False) -> str:
"""Color text green."""
return cls.colorize(text, cls.GREEN, bold)
@classmethod
def yellow(cls, text: str, bold: bool = False) -> str:
"""Color text yellow."""
return cls.colorize(text, cls.YELLOW, bold)
@classmethod
def blue(cls, text: str, bold: bool = False) -> str:
"""Color text blue."""
return cls.colorize(text, cls.BLUE, bold)
@classmethod
def purple(cls, text: str, bold: bool = False) -> str:
"""Color text purple."""
return cls.colorize(text, cls.PURPLE, bold)
@classmethod
def cyan(cls, text: str, bold: bool = False) -> str:
"""Color text cyan."""
return cls.colorize(text, cls.CYAN, bold)
@classmethod
def bold(cls, text: str) -> str:
"""Make text bold."""
return cls.colorize(text, '', True)
@classmethod
def dim(cls, text: str) -> str:
"""Make text dim."""
return cls.colorize(text, cls.DIM)
@classmethod
def underline(cls, text: str) -> str:
"""Underline text."""
return cls.colorize(text, cls.UNDERLINE)
@classmethod
def success(cls, text: str) -> str:
"""Format success message (green)."""
return cls.green(f"[SUCCESS] {text}", bold=True)
@classmethod
def error(cls, text: str) -> str:
"""Format error message (red)."""
return cls.red(f"[ERROR] {text}", bold=True)
@classmethod
def warning(cls, text: str) -> str:
"""Format warning message (yellow)."""
return cls.yellow(f"[WARNING] {text}", bold=True)
@classmethod
def info(cls, text: str) -> str:
"""Format info message (blue)."""
return cls.blue(f"[INFO] {text}")
@classmethod
def highlight(cls, text: str) -> str:
"""Highlight text (cyan background)."""
if not cls.supports_color():
return f"[{text}]"
return f"{cls.BG_CYAN}{cls.BLACK}{text}{cls.RESET}"
@classmethod
def strip_colors(cls, text: str) -> str:
"""Remove ANSI color codes from text."""
import re
ansi_escape = re.compile(r'\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])')
return ansi_escape.sub('', text)
# Convenience functions for common usage
def colorize(text: str, color: str) -> str:
"""Convenience function to colorize text."""
return Colors.colorize(text, color)
def red(text: str) -> str:
"""Red text."""
return Colors.red(text)
def green(text: str) -> str:
"""Green text."""
return Colors.green(text)
def yellow(text: str) -> str:
"""Yellow text."""
return Colors.yellow(text)
def blue(text: str) -> str:
"""Blue text."""
return Colors.blue(text)
def success(text: str) -> str:
"""Success message."""
return Colors.success(text)
def error(text: str) -> str:
"""Error message."""
return Colors.error(text)
def warning(text: str) -> str:
"""Warning message."""
return Colors.warning(text)
def info(text: str) -> str:
"""Info message."""
return Colors.info(text)
if __name__ == "__main__":
# Test color output
print(Colors.red("Red text"))
print(Colors.green("Green text"))
print(Colors.yellow("Yellow text"))
print(Colors.blue("Blue text"))
print(Colors.purple("Purple text"))
print(Colors.cyan("Cyan text"))
print(Colors.bold("Bold text"))
print(Colors.success("Success message"))
print(Colors.error("Error message"))
print(Colors.warning("Warning message"))
print(Colors.info("Info message"))
print(Colors.highlight("Highlighted text"))
print(f"Color support: {Colors.supports_color()}")
print(f"TTY: {Colors.is_tty()}")

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#!/usr/bin/env python3
"""
I/O Helper Functions
Provides common file and directory operations with error handling.
"""
import os
import json
import yaml
import logging
from pathlib import Path
from typing import Any, Optional, Union, List, Dict
import shutil
import tempfile
class IOHelpers:
"""Collection of I/O helper methods."""
@staticmethod
def ensure_directory(path: Union[str, Path], mode: int = 0o755) -> bool:
"""Ensure directory exists, create if necessary."""
try:
dir_path = Path(path)
dir_path.mkdir(parents=True, exist_ok=True, mode=mode)
return True
except (PermissionError, OSError) as e:
logging.error(f"Failed to create directory '{path}': {e}")
return False
@staticmethod
def safe_read_file(file_path: Union[str, Path], encoding: str = 'utf-8',
fallback_encoding: str = 'latin-1') -> Optional[str]:
"""Safely read file content with encoding fallback."""
path = Path(file_path)
if not path.exists():
return None
encodings = [encoding, fallback_encoding] if encoding != fallback_encoding else [encoding]
for enc in encodings:
try:
with open(path, 'r', encoding=enc) as f:
return f.read()
except UnicodeDecodeError:
continue
except (IOError, OSError) as e:
logging.error(f"Failed to read file '{file_path}': {e}")
return None
logging.warning(f"Failed to decode file '{file_path}' with any encoding")
return None
@staticmethod
def safe_write_file(file_path: Union[str, Path], content: str,
encoding: str = 'utf-8', backup: bool = False) -> bool:
"""Safely write content to file with optional backup."""
path = Path(file_path)
try:
# Create backup if requested and file exists
if backup and path.exists():
backup_path = path.with_suffix(path.suffix + '.bak')
shutil.copy2(path, backup_path)
# Ensure parent directory exists
if not IOHelpers.ensure_directory(path.parent):
return False
# Write to temporary file first, then move to final location
with tempfile.NamedTemporaryFile(mode='w', encoding=encoding,
dir=path.parent, delete=False) as tmp_file:
tmp_file.write(content)
tmp_path = Path(tmp_file.name)
# Atomic move
shutil.move(str(tmp_path), str(path))
return True
except (IOError, OSError) as e:
logging.error(f"Failed to write file '{file_path}': {e}")
return False
@staticmethod
def read_json(file_path: Union[str, Path], default: Any = None) -> Any:
"""Read JSON file with error handling."""
content = IOHelpers.safe_read_file(file_path)
if content is None:
return default
try:
return json.loads(content)
except json.JSONDecodeError as e:
logging.error(f"Failed to parse JSON from '{file_path}': {e}")
return default
@staticmethod
def write_json(file_path: Union[str, Path], data: Any,
indent: int = 2, backup: bool = False) -> bool:
"""Write data to JSON file."""
try:
content = json.dumps(data, indent=indent, ensure_ascii=False, default=str)
return IOHelpers.safe_write_file(file_path, content, backup=backup)
except (TypeError, ValueError) as e:
logging.error(f"Failed to serialize data to JSON for '{file_path}': {e}")
return False
@staticmethod
def read_yaml(file_path: Union[str, Path], default: Any = None) -> Any:
"""Read YAML file with error handling."""
content = IOHelpers.safe_read_file(file_path)
if content is None:
return default
try:
return yaml.safe_load(content)
except yaml.YAMLError as e:
logging.error(f"Failed to parse YAML from '{file_path}': {e}")
return default
@staticmethod
def write_yaml(file_path: Union[str, Path], data: Any, backup: bool = False) -> bool:
"""Write data to YAML file."""
try:
content = yaml.dump(data, default_flow_style=False, allow_unicode=True)
return IOHelpers.safe_write_file(file_path, content, backup=backup)
except yaml.YAMLError as e:
logging.error(f"Failed to serialize data to YAML for '{file_path}': {e}")
return False
@staticmethod
def find_files(directory: Union[str, Path], pattern: str = "*",
recursive: bool = True, max_depth: Optional[int] = None) -> List[Path]:
"""Find files matching pattern in directory."""
dir_path = Path(directory)
if not dir_path.exists() or not dir_path.is_dir():
return []
files = []
try:
if recursive:
if max_depth is not None:
# Implement depth-limited search
def search_with_depth(path: Path, current_depth: int = 0):
if current_depth > max_depth:
return
for item in path.iterdir():
if item.is_file() and item.match(pattern):
files.append(item)
elif item.is_dir() and current_depth < max_depth:
search_with_depth(item, current_depth + 1)
search_with_depth(dir_path)
else:
files = list(dir_path.rglob(pattern))
else:
files = list(dir_path.glob(pattern))
return sorted(files)
except (PermissionError, OSError) as e:
logging.error(f"Failed to search files in '{directory}': {e}")
return []
@staticmethod
def get_file_stats(file_path: Union[str, Path]) -> Optional[Dict[str, Any]]:
"""Get file statistics."""
path = Path(file_path)
if not path.exists():
return None
try:
stat = path.stat()
return {
'size': stat.st_size,
'modified_time': stat.st_mtime,
'created_time': stat.st_ctime,
'is_file': path.is_file(),
'is_dir': path.is_dir(),
'permissions': oct(stat.st_mode)[-3:],
'extension': path.suffix.lower(),
'name': path.name,
'parent': str(path.parent)
}
except (OSError, PermissionError) as e:
logging.error(f"Failed to get stats for '{file_path}': {e}")
return None
@staticmethod
def copy_with_backup(source: Union[str, Path], dest: Union[str, Path]) -> bool:
"""Copy file with automatic backup if destination exists."""
source_path = Path(source)
dest_path = Path(dest)
if not source_path.exists():
logging.error(f"Source file '{source}' does not exist")
return False
try:
# Create backup if destination exists
if dest_path.exists():
backup_path = dest_path.with_suffix(dest_path.suffix + '.bak')
shutil.copy2(dest_path, backup_path)
logging.info(f"Created backup: {backup_path}")
# Ensure destination directory exists
if not IOHelpers.ensure_directory(dest_path.parent):
return False
# Copy file
shutil.copy2(source_path, dest_path)
return True
except (IOError, OSError) as e:
logging.error(f"Failed to copy '{source}' to '{dest}': {e}")
return False
@staticmethod
def move_with_backup(source: Union[str, Path], dest: Union[str, Path]) -> bool:
"""Move file with automatic backup if destination exists."""
source_path = Path(source)
dest_path = Path(dest)
if not source_path.exists():
logging.error(f"Source file '{source}' does not exist")
return False
try:
# Create backup if destination exists
if dest_path.exists():
backup_path = dest_path.with_suffix(dest_path.suffix + '.bak')
shutil.move(str(dest_path), str(backup_path))
logging.info(f"Created backup: {backup_path}")
# Ensure destination directory exists
if not IOHelpers.ensure_directory(dest_path.parent):
return False
# Move file
shutil.move(str(source_path), str(dest_path))
return True
except (IOError, OSError) as e:
logging.error(f"Failed to move '{source}' to '{dest}': {e}")
return False
@staticmethod
def clean_temp_files(directory: Union[str, Path], extensions: List[str] = None,
max_age_hours: int = 24) -> int:
"""Clean temporary files older than specified age."""
if extensions is None:
extensions = ['.tmp', '.temp', '.bak', '.swp', '.~']
dir_path = Path(directory)
if not dir_path.exists():
return 0
import time
cutoff_time = time.time() - (max_age_hours * 3600)
cleaned_count = 0
try:
for file_path in dir_path.rglob('*'):
if file_path.is_file():
# Check extension
if file_path.suffix.lower() in extensions:
# Check age
if file_path.stat().st_mtime < cutoff_time:
try:
file_path.unlink()
cleaned_count += 1
except OSError:
continue
logging.info(f"Cleaned {cleaned_count} temporary files from '{directory}'")
return cleaned_count
except (PermissionError, OSError) as e:
logging.error(f"Failed to clean temp files in '{directory}': {e}")
return 0
@staticmethod
def get_directory_size(directory: Union[str, Path]) -> int:
"""Get total size of directory in bytes."""
dir_path = Path(directory)
if not dir_path.exists() or not dir_path.is_dir():
return 0
total_size = 0
try:
for file_path in dir_path.rglob('*'):
if file_path.is_file():
total_size += file_path.stat().st_size
except (PermissionError, OSError):
pass
return total_size
@staticmethod
def make_executable(file_path: Union[str, Path]) -> bool:
"""Make file executable (Unix/Linux/Mac)."""
if os.name == 'nt': # Windows
return True # Windows doesn't use Unix permissions
try:
path = Path(file_path)
current_mode = path.stat().st_mode
path.chmod(current_mode | 0o111) # Add execute permission
return True
except (OSError, PermissionError) as e:
logging.error(f"Failed to make '{file_path}' executable: {e}")
return False
# Convenience functions
def ensure_directory(path: Union[str, Path]) -> bool:
"""Ensure directory exists."""
return IOHelpers.ensure_directory(path)
def safe_read_file(file_path: Union[str, Path]) -> Optional[str]:
"""Safely read file content."""
return IOHelpers.safe_read_file(file_path)
def safe_write_file(file_path: Union[str, Path], content: str) -> bool:
"""Safely write content to file."""
return IOHelpers.safe_write_file(file_path, content)
def read_json(file_path: Union[str, Path], default: Any = None) -> Any:
"""Read JSON file."""
return IOHelpers.read_json(file_path, default)
def write_json(file_path: Union[str, Path], data: Any) -> bool:
"""Write data to JSON file."""
return IOHelpers.write_json(file_path, data)
def read_yaml(file_path: Union[str, Path], default: Any = None) -> Any:
"""Read YAML file."""
return IOHelpers.read_yaml(file_path, default)
def write_yaml(file_path: Union[str, Path], data: Any) -> bool:
"""Write data to YAML file."""
return IOHelpers.write_yaml(file_path, data)
if __name__ == "__main__":
# Test I/O operations
test_dir = Path("test_io")
# Test directory creation
print(f"Create directory: {ensure_directory(test_dir)}")
# Test file operations
test_file = test_dir / "test.txt"
content = "Hello, World!\nThis is a test file."
print(f"Write file: {safe_write_file(test_file, content)}")
print(f"Read file: {safe_read_file(test_file)}")
# Test JSON operations
json_file = test_dir / "test.json"
json_data = {"name": "test", "numbers": [1, 2, 3], "nested": {"key": "value"}}
print(f"Write JSON: {write_json(json_file, json_data)}")
print(f"Read JSON: {read_json(json_file)}")
# Test file stats
stats = IOHelpers.get_file_stats(test_file)
print(f"File stats: {stats}")
# Cleanup
shutil.rmtree(test_dir, ignore_errors=True)

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# Analysis Results Documentation
## Metadata
- **Generated by**: `/workflow:plan` command
- **Session**: `WFS-[session-id]`
- **Task Context**: `[task-description]`
- **Analysis Date**: `[timestamp]`
## 1. Verified Project Assets
### Confirmed Documentation Files
```bash
# Verified file existence with full paths:
✓ [/absolute/path/to/CLAUDE.md] - [file size] - Contains: [key sections found]
✓ [/absolute/path/to/README.md] - [file size] - Contains: [technical info]
✓ [/absolute/path/to/package.json] - [file size] - Dependencies: [list]
```
### Confirmed Technical Stack
- **Package Manager**: [npm/yarn/pnpm] (confirmed via `[specific file path]`)
- **Framework**: [React/Vue/Angular/etc] (version: [x.x.x])
- **Build Tool**: [webpack/vite/etc] (config: `[config file path]`)
- **Test Framework**: [jest/vitest/etc] (config: `[config file path]`)
## 2. Verified Code Structure
### Confirmed Directory Structure
```
[project-root]/
├── [actual-folder-name]/ # [purpose - verified]
│ ├── [actual-file.ext] # [size] [last-modified]
│ └── [actual-file.ext] # [size] [last-modified]
└── [actual-folder-name]/ # [purpose - verified]
├── [actual-file.ext] # [size] [last-modified]
└── [actual-file.ext] # [size] [last-modified]
```
### Confirmed Key Modules
- **Module 1**: `[/absolute/path/to/module]`
- **Entry Point**: `[actual-file.js]` (exports: [verified-exports])
- **Key Methods**: `[method1()]`, `[method2()]` (line numbers: [X-Y])
- **Dependencies**: `[import statements verified]`
- **Module 2**: `[/absolute/path/to/module]`
- **Entry Point**: `[actual-file.js]` (exports: [verified-exports])
- **Key Methods**: `[method1()]`, `[method2()]` (line numbers: [X-Y])
- **Dependencies**: `[import statements verified]`
## 3. Confirmed Implementation Standards
### Verified Coding Patterns
- **Naming Convention**: [verified pattern from actual files]
- Files: `[example1.js]`, `[example2.js]` (pattern: [pattern])
- Functions: `[actualFunction()]` from `[file:line]`
- Classes: `[ActualClass]` from `[file:line]`
### Confirmed Build Commands
```bash
# Verified commands (tested successfully):
✓ [npm run build] - Output: [build result]
✓ [npm run test] - Framework: [test framework found]
✓ [npm run lint] - Tool: [linter found]
```
## 4. Task Decomposition Results
### Task Count Determination
- **Identified Tasks**: [exact number] (based on functional boundaries)
- **Structure**: [Flat ≤5 | Hierarchical 6-10 | Re-scope >10]
- **Merge Rationale**: [specific reasons for combining related files]
### Confirmed Task Breakdown
- **IMPL-001**: `[Specific functional description]`
- **Target Files**: `[/absolute/path/file1.js]`, `[/absolute/path/file2.js]` (verified)
- **Key Methods to Implement**: `[method1()]`, `[method2()]` (signatures defined)
- **Size**: [X files, ~Y lines] (measured from similar existing code)
- **Dependencies**: Uses `[existingModule.method()]` from `[verified-path]`
- **IMPL-002**: `[Specific functional description]`
- **Target Files**: `[/absolute/path/file3.js]`, `[/absolute/path/file4.js]` (verified)
- **Key Methods to Implement**: `[method3()]`, `[method4()]` (signatures defined)
- **Size**: [X files, ~Y lines] (measured from similar existing code)
- **Dependencies**: Uses `[existingModule.method()]` from `[verified-path]`
### Verified Dependency Chain
```bash
# Confirmed execution order (based on actual imports):
IMPL-001 → Uses: [existing-file:method]
IMPL-002 → Depends: IMPL-001.[method] → Uses: [existing-file:method]
```
## 5. Implementation Execution Plan
### Confirmed Integration Points
- **Existing Entry Points**:
- `[actual-file.js:line]` exports `[verified-method]`
- `[actual-config.json]` contains `[verified-setting]`
- **Integration Methods**:
- Hook into `[existing-method()]` at `[file:line]`
- Extend `[ExistingClass]` from `[file:line]`
### Validated Commands
```bash
# Commands verified to work in current environment:
✓ [exact build command] - Tested: [timestamp]
✓ [exact test command] - Tested: [timestamp]
✓ [exact lint command] - Tested: [timestamp]
```
## 6. Success Validation Criteria
### Testable Outcomes
- **IMPL-001 Success**:
- `[specific test command]` passes
- `[integration point]` correctly calls `[new method]`
- No regression in `[existing test suite]`
- **IMPL-002 Success**:
- `[specific test command]` passes
- Feature accessible via `[verified UI path]`
- Performance: `[measurable criteria]`
### Quality Gates
- **Code Standards**: Must pass `[verified lint command]`
- **Test Coverage**: Maintain `[current coverage %]` (measured by `[tool]`)
- **Build**: Must complete `[verified build command]` without errors
---
## Template Instructions
**CRITICAL**: Every bracketed item MUST be filled with verified, existing information:
- File paths must be confirmed with `ls` or `find`
- Method names must be found in actual source code
- Commands must be tested and work
- Line numbers should reference actual code locations
- Dependencies must trace to real imports/requires
**Verification Required Before Use**:
1. All file paths exist and are readable
2. All referenced methods/classes exist in specified locations
3. All commands execute successfully
4. All integration points are actual, not assumed

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# Agent Orchestration Patterns
## Core Agent Coordination Features
- **Gemini Context Analysis**: MANDATORY context gathering before any agent execution
- **Context-Driven Coordination**: Agents work with comprehensive codebase understanding
- **Dynamic Agent Selection**: Choose agents based on discovered context and patterns
- **Continuous Context Updates**: Refine understanding throughout agent execution
- **Cross-Agent Context Sharing**: Maintain shared context state across all agents
- **Pattern-Aware Execution**: Leverage discovered patterns for optimal implementation
- **Quality Gates**: Each Agent validates input and ensures output standards
- **Error Recovery**: Graceful handling of Agent coordination failures
## Workflow Implementation Patterns
### Simple Workflow Pattern
```pseudocode
Flow: Gemini Context Analysis → TodoWrite Creation → Context-Aware Implementation → Review
1. MANDATORY Gemini Context Analysis:
- Analyze target files and immediate dependencies
- Discover existing patterns and conventions
- Identify utilities and libraries to use
- Generate context package for agents
2. TodoWrite Creation (Context-informed):
- "Execute Gemini context analysis"
- "Implement solution following discovered patterns"
- "Review against codebase standards"
- "Complete task with context validation"
3. Context-Aware Implementation:
Task(code-developer): Implementation with Gemini context package
Input: CONTEXT_PACKAGE, PATTERNS_DISCOVERED, CONVENTIONS_IDENTIFIED
Output: SUMMARY, FILES_MODIFIED, TESTS, VERIFICATION
4. Context-Aware Review:
Task(code-review-agent): Review with codebase standards context
Input: CONTEXT_PACKAGE, IMPLEMENTATION_RESULTS
Output: STATUS, SCORE, ISSUES, RECOMMENDATIONS
Resume Support: Load todos + full context state from checkpoint
```
### Medium Workflow Pattern
```pseudocode
Flow: Comprehensive Gemini Analysis → TodoWrite → Multi-Context Implementation → Review
1. MANDATORY Comprehensive Gemini Context Analysis:
- Analyze feature area and related components
- Discover cross-file patterns and architectural decisions
- Identify integration points and dependencies
- Generate comprehensive context packages for multiple agents
2. TodoWrite Creation (Context-driven, 5-7 todos):
- "Execute comprehensive Gemini context analysis"
- "Coordinate multi-agent implementation with shared context"
- "Implement following discovered architectural patterns"
- "Validate against existing system patterns", "Review", "Complete"
3. Multi-Context Implementation:
Task(code-developer): Implementation with comprehensive context
Input: CONTEXT_PACKAGES, ARCHITECTURAL_PATTERNS, INTEGRATION_POINTS
Update context as new patterns discovered
4. Context-Aware Review:
Task(code-review-agent): Comprehensive review with system context
Input: FULL_CONTEXT_STATE, IMPLEMENTATION_RESULTS, PATTERN_COMPLIANCE
Verify against discovered architectural patterns
Resume Support: Full context state + pattern discovery restoration
```
### Complex Workflow Pattern
```pseudocode
Flow: Deep Gemini Analysis → TodoWrite → Orchestrated Multi-Agent → Review → Iterate (max 2)
1. MANDATORY Deep Gemini Context Analysis:
- System-wide architectural understanding
- Deep pattern analysis across entire codebase
- Integration complexity assessment
- Multi-agent coordination requirements discovery
- Risk pattern identification
2. TodoWrite Creation (Context-orchestrated, 7-10 todos):
- "Execute deep system-wide Gemini analysis"
- "Orchestrate multi-agent coordination with shared context"
- "Implement with continuous context refinement"
- "Validate against system architectural patterns", "Review", "Iterate", "Complete"
3. Orchestrated Multi-Agent Implementation:
Multiple specialized agents with shared deep context
Input: SYSTEM_CONTEXT, ARCHITECTURAL_PATTERNS, RISK_ASSESSMENT
Continuous Gemini context updates throughout execution
Cross-agent context synchronization
4. Deep Context Review & Iteration Loop (max 2 iterations):
Task(code-review-agent): Production-ready review with full system context
If CRITICAL_ISSUES found: Re-analyze context and coordinate fixes
Continue until no critical issues or max iterations reached
Context Validation: Verify deep context analysis maintained throughout
Resume Support: Full context state + iteration tracking + cross-agent coordination
```
## Workflow Characteristics by Pattern
| Pattern | Context Analysis | Agent Coordination | Iteration Strategy |
|---------|------------------|--------------------|--------------------|
| **Complex** | Deep system-wide Gemini analysis | Multi-agent orchestration with shared context | Multiple rounds with context refinement |
| **Medium** | Comprehensive multi-file analysis | Context-driven coordination | Single thorough pass with pattern validation |
| **Simple** | Focused file-level analysis | Direct context-aware execution | Quick context validation |
## Context-Driven Task Invocation Examples
```bash
# Gemini Context Analysis (Always First)
gemini "Analyze authentication patterns in codebase - identify existing implementations,
conventions, utilities, and integration patterns"
# Context-Aware Research Task
Task(subagent_type="general-purpose",
prompt="Research authentication patterns in codebase",
context="[GEMINI_CONTEXT_PACKAGE]")
# Context-Informed Implementation Task
Task(subagent_type="code-developer",
prompt="Implement email validation function following discovered patterns",
context="PATTERNS: [pattern_list], UTILITIES: [util_list], CONVENTIONS: [conv_list]")
# Context-Driven Review Task
Task(subagent_type="code-review-agent",
prompt="Review authentication service against codebase standards and patterns",
context="STANDARDS: [discovered_standards], PATTERNS: [existing_patterns]")
# Cross-Agent Context Sharing
Task(subagent_type="code-developer",
prompt="Coordinate with previous agent results using shared context",
context="PREVIOUS_CONTEXT: [agent_context], SHARED_STATE: [context_state]")
```
## Gemini Context Integration Points
### Pre-Agent Context Gathering
```bash
# Always execute before agent coordination
gemini "Comprehensive analysis for [task] - discover patterns, conventions, and optimal approach"
```
### During-Agent Context Updates
```bash
# Continuous context refinement
gemini "Update context understanding based on agent discoveries in [area]"
```
### Cross-Agent Context Synchronization
```bash
# Ensure context consistency across agents
gemini "Synchronize context between [agent1] and [agent2] work on [feature]"
```

2
.claude/workflows/workflow-architecture.md
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@@ -245,6 +245,8 @@ All workflows use the same file structure definition regardless of complexity. *
├── [.chat/] # CLI interaction sessions (created when analysis is run)
│ ├── chat-*.md # Saved chat sessions
│ └── analysis-*.md # Analysis results
├── [.process/] # Planning analysis results (created by /workflow:plan)
│ └── ANALYSIS_RESULTS.md # Analysis results and planning artifacts
├── IMPL_PLAN.md # Planning document (REQUIRED)
├── TODO_LIST.md # Progress tracking (REQUIRED)
├── [.summaries/] # Task completion summaries (created when tasks complete)