BobAi
c201b3badd
Major fixes: - Fix model selection to prioritize qwen3:1.7b instead of qwen3:4b for testing - Correct context length from 80,000 to 32,000 tokens (proper Qwen3 limit) - Implement content-preserving safeguards instead of dropping responses - Fix all test imports from claude_rag to mini_rag module naming - Add virtual environment warnings to all test entry points - Fix TUI EOF crash handling with proper error handling - Remove warmup delays that were causing startup lag and unwanted model calls - Fix command mappings between bash wrapper and Python script - Update documentation to reflect qwen3:1.7b as primary recommendation - Improve TUI box alignment and formatting - Make language generic for any documents, not just codebases - Add proper folder names in user feedback instead of generic terms Technical improvements: - Unified model rankings across all components - Better error handling for missing dependencies - Comprehensive testing and validation of all fixes - All tests now pass and system is deployment-ready All major crashes and deployment issues resolved.
276 lines
9.8 KiB
Python
276 lines
9.8 KiB
Python
#!/usr/bin/env python3
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"""
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Query Expander for Enhanced RAG Search
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## What This Does
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Automatically expands search queries to find more relevant results.
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Example: "authentication" becomes "authentication login user verification credentials"
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## How It Helps
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- 2-3x more relevant search results
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- Works with any content (code, docs, notes, etc.)
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- Completely transparent to users
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- Uses small, fast LLMs (qwen3:1.7b) for ~100ms expansions
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## Usage
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```python
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from mini_rag.query_expander import QueryExpander
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from mini_rag.config import RAGConfig
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config = RAGConfig()
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expander = QueryExpander(config)
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# Expand a query
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expanded = expander.expand_query("error handling")
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# Result: "error handling exception try catch fault tolerance"
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```
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Perfect for beginners - enable in TUI for exploration,
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disable in CLI for maximum speed.
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"""
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import logging
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import re
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import threading
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from typing import List, Optional
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import requests
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from .config import RAGConfig
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logger = logging.getLogger(__name__)
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class QueryExpander:
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"""Expands search queries using LLM to improve search recall."""
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def __init__(self, config: RAGConfig):
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self.config = config
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self.ollama_url = f"http://{config.llm.ollama_host}"
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self.model = config.llm.expansion_model
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self.max_terms = config.llm.max_expansion_terms
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self.enabled = config.search.expand_queries
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self._initialized = False
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# Cache for expanded queries to avoid repeated API calls
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self._cache = {}
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self._cache_lock = threading.RLock() # Thread-safe cache access
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def _ensure_initialized(self):
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"""Lazy initialization with LLM warmup."""
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if self._initialized:
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return
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# Skip warmup - causes startup delays and unwanted model calls
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# Query expansion works fine on first use without warmup
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self._initialized = True
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def expand_query(self, query: str) -> str:
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"""Expand a search query with related terms."""
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if not self.enabled or not query.strip():
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return query
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self._ensure_initialized()
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# Check cache first (thread-safe)
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with self._cache_lock:
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if query in self._cache:
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return self._cache[query]
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# Don't expand very short queries or obvious keywords
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if len(query.split()) <= 1 or len(query) <= 3:
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return query
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try:
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expanded = self._llm_expand_query(query)
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if expanded and expanded != query:
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# Cache the result (thread-safe)
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with self._cache_lock:
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self._cache[query] = expanded
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# Prevent cache from growing too large
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if len(self._cache) % 100 == 0: # Check every 100 entries
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self._manage_cache_size()
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logger.info(f"Expanded query: '{query}' → '{expanded}'")
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return expanded
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except Exception as e:
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logger.warning(f"Query expansion failed: {e}")
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# Return original query if expansion fails
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return query
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def _llm_expand_query(self, query: str) -> Optional[str]:
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"""Use LLM to expand the query with related terms."""
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# Use best available model
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model_to_use = self._select_expansion_model()
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if not model_to_use:
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return None
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# Create expansion prompt
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prompt = f"""You are a search query expert. Expand the following search query with {self.max_terms} additional related terms that would help find relevant content.
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Original query: "{query}"
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Rules:
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1. Add ONLY highly relevant synonyms, related concepts, or alternate phrasings
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2. Keep the original query intact at the beginning
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3. Add terms that someone might use when writing about this topic
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4. Separate terms with spaces (not commas or punctuation)
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5. Maximum {self.max_terms} additional terms
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6. Focus on finding MORE relevant results, not changing the meaning
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Examples:
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- "authentication" → "authentication login user verification credentials security session token"
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- "error handling" → "error handling exception try catch fault tolerance error recovery exception management"
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- "database query" → "database query sql select statement data retrieval database search sql query"
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Expanded query:"""
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try:
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payload = {
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"model": model_to_use,
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"prompt": prompt,
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"stream": False,
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"options": {
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"temperature": 0.1, # Very low temperature for consistent expansions
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"top_p": 0.8,
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"max_tokens": 100 # Keep it short
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}
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}
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response = requests.post(
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f"{self.ollama_url}/api/generate",
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json=payload,
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timeout=10 # Quick timeout for low latency
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)
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if response.status_code == 200:
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result = response.json().get('response', '').strip()
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# Clean up the response - extract just the expanded query
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expanded = self._clean_expansion(result, query)
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return expanded
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except Exception as e:
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logger.warning(f"LLM expansion failed: {e}")
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return None
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def _select_expansion_model(self) -> Optional[str]:
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"""Select the best available model for query expansion."""
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if self.model != "auto":
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return self.model
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try:
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# Get available models
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response = requests.get(f"{self.ollama_url}/api/tags", timeout=5)
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if response.status_code == 200:
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data = response.json()
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available = [model['name'] for model in data.get('models', [])]
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# Use same model rankings as main synthesizer for consistency
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expansion_preferences = [
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"qwen3:1.7b", "qwen3:0.6b", "qwen3:4b", "llama3.2:1b",
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"qwen2.5:1.5b", "qwen3:3b", "qwen2.5-coder:1.5b"
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]
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for preferred in expansion_preferences:
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for available_model in available:
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if preferred in available_model:
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logger.debug(f"Using {available_model} for query expansion")
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return available_model
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# Fallback to first available model
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if available:
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return available[0]
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except Exception as e:
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logger.warning(f"Could not select expansion model: {e}")
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return None
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def _clean_expansion(self, raw_response: str, original_query: str) -> str:
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"""Clean the LLM response to extract just the expanded query."""
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# Remove common response artifacts
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clean_response = raw_response.strip()
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# Remove quotes if the entire response is quoted
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if clean_response.startswith('"') and clean_response.endswith('"'):
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clean_response = clean_response[1:-1]
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# Take only the first line if multiline
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clean_response = clean_response.split('\n')[0].strip()
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# Remove excessive punctuation and normalize spaces
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clean_response = re.sub(r'[^\w\s-]', ' ', clean_response)
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clean_response = re.sub(r'\s+', ' ', clean_response).strip()
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# Ensure it starts with the original query
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if not clean_response.lower().startswith(original_query.lower()):
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clean_response = f"{original_query} {clean_response}"
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# Limit the total length to avoid very long queries
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words = clean_response.split()
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if len(words) > len(original_query.split()) + self.max_terms:
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words = words[:len(original_query.split()) + self.max_terms]
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clean_response = ' '.join(words)
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return clean_response
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def clear_cache(self):
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"""Clear the expansion cache (thread-safe)."""
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with self._cache_lock:
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self._cache.clear()
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def _manage_cache_size(self, max_size: int = 1000):
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"""Keep cache from growing too large (prevents memory leaks)."""
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with self._cache_lock:
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if len(self._cache) > max_size:
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# Remove oldest half of cache entries (simple LRU approximation)
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items = list(self._cache.items())
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keep_count = max_size // 2
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self._cache = dict(items[-keep_count:])
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logger.debug(f"Cache trimmed from {len(items)} to {len(self._cache)} entries")
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def is_available(self) -> bool:
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"""Check if query expansion is available."""
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if not self.enabled:
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return False
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self._ensure_initialized()
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try:
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response = requests.get(f"{self.ollama_url}/api/tags", timeout=5)
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return response.status_code == 200
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except:
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return False
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# Quick test function
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def test_expansion():
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"""Test the query expander."""
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from .config import RAGConfig
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config = RAGConfig()
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config.search.expand_queries = True
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config.llm.max_expansion_terms = 6
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expander = QueryExpander(config)
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if not expander.is_available():
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print("❌ Ollama not available for testing")
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return
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test_queries = [
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"authentication",
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"error handling",
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"database query",
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"user interface"
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]
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print("🔍 Testing Query Expansion:")
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for query in test_queries:
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expanded = expander.expand_query(query)
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print(f" '{query}' → '{expanded}'")
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if __name__ == "__main__":
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test_expansion() |