b9f44cd03a
Add RAG (Retrieval Augmented Generation) tools for storing documentation in Qdrant vector database and querying with semantic search. This replaces the Python tools/rag implementation with a native Go solution. New commands: - core rag ingest [directory] - Ingest markdown files into Qdrant - core rag query [question] - Query vector database with semantic search - core rag collections - List and manage Qdrant collections Features: - Markdown chunking by sections and paragraphs with overlap - UTF-8 safe text handling for international content - Automatic category detection from file paths - Multiple output formats: text, JSON, LLM context injection - Environment variable support for host configuration Dependencies: - github.com/qdrant/go-client (gRPC client) - github.com/ollama/ollama/api (embeddings API) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
25 lines
636 B
Go
25 lines
636 B
Go
// Package rag provides RAG (Retrieval Augmented Generation) commands.
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//
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// Commands:
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// - core rag ingest: Ingest markdown files into Qdrant
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// - core rag query: Query the vector database
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// - core rag collections: List and manage collections
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package rag
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import (
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"github.com/host-uk/core/pkg/cli"
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"github.com/spf13/cobra"
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)
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func init() {
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cli.RegisterCommands(AddRAGCommands)
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}
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// AddRAGCommands registers the 'rag' command and all subcommands.
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func AddRAGCommands(root *cobra.Command) {
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initFlags()
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ragCmd.AddCommand(ingestCmd)
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ragCmd.AddCommand(queryCmd)
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ragCmd.AddCommand(collectionsCmd)
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root.AddCommand(ragCmd)
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}
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