Synthadoc v0.2.0 introduces a range of advanced features aimed at enhancing the efficiency and effectiveness of domain-specific knowledge management systems. Here's a summary of key enhancements:
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Query Decomposition: Complex queries are broken down into simpler sub-queries that can be processed in parallel, improving response time and accuracy.
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Vector Re-ranking (Optional): Synthadoc now supports semantic re-ranking using BAAI/bge-small-en-v1.5 via
fastembed. This feature enhances the relevance of search results by considering the context and meaning beyond keyword matching. -
Knowledge Gap Detection: The system can identify gaps in knowledge based on three signals (BM25 pool size, vector top candidates, and purpose.md scope) and automatically generate targeted ingest suggestions to fill these gaps.
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Web Search Decomposition: Broad search topics are split into focused queries using Tavily, with URL deduplication and a cap to manage the volume of ingested data efficiently.
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Per-Model Cost Tracking: Detailed cost tracking per token and operation is provided, allowing users to monitor and control their spending on LLM services like OpenAI or Anthropic.
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**Query Audit Trail
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