alphaear-search

name	alphaear-search
description	Perform web searches and local context searches. Use when the user needs general info from the web (Jina/DDG/Baidu) or needs to retrieve information from a local document store (RAG).

AlphaEar Search Skill

Overview

This skill provides unified search capabilities: web search (via DuckDuckGo, Jina, or Baidu) and local hybrid search (BM25 + Vector) for RAG applications.

Capabilities

1. Web Search

Use scripts/search_tools.py to perform web searches.

Key Methods:

• search(query, engine, max_results): Execute a search.
  • Engines: jina, ddg, baidu.
  • Returns: Dictionary with results (JSON string) and metadata.
• aggregate_search(query): Search across multiple engines and aggregate results.

Example Usage (Python):

from scripts.database_manager import DatabaseManager
from scripts.search_tools import SearchTools

db = DatabaseManager()
tools = SearchTools(db)

# Simple Search
results = tools.search("NVIDIA Earnings", engine="ddg")
print(results)

2. Local Hybrid Search (RAG)

Use scripts/hybrid_search.py for in-memory document retrieval.

Key Features:

• Add documents.
• Search with weighted keyword matching (simple algorithm).

Example Usage (Python):

from scripts.hybrid_search import InMemoryRAG

rag = InMemoryRAG()
rag.add({"id": "doc1", "content": "Apple released Vision Pro.", "title": "Tech News"})
rag.add({"id": "doc2", "content": "Tesla cybertruck delivery.", "title": "Auto News"})

# Search
hits = rag.search("Vision Pro")
print(hits)

Dependencies

• duckduckgo-search
• requests
• sqlite3 (built-in)

Ensure DatabaseManager is initialized correctly.