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5e80f93e4c
This PR introduces several enhancements and refactorings to the AI Persona and RAG (Retrieval-Augmented Generation) functionalities within the discourse-ai plugin. Here's a breakdown of the changes: **1. LLM Model Association for RAG and Personas:** - **New Database Columns:** Adds `rag_llm_model_id` to both `ai_personas` and `ai_tools` tables. This allows specifying a dedicated LLM for RAG indexing, separate from the persona's primary LLM. Adds `default_llm_id` and `question_consolidator_llm_id` to `ai_personas`. - **Migration:** Includes a migration (`20250210032345_migrate_persona_to_llm_model_id.rb`) to populate the new `default_llm_id` and `question_consolidator_llm_id` columns in `ai_personas` based on the existing `default_llm` and `question_consolidator_llm` string columns, and a post migration to remove the latter. - **Model Changes:** The `AiPersona` and `AiTool` models now `belong_to` an `LlmModel` via `rag_llm_model_id`. The `LlmModel.proxy` method now accepts an `LlmModel` instance instead of just an identifier. `AiPersona` now has `default_llm_id` and `question_consolidator_llm_id` attributes. - **UI Updates:** The AI Persona and AI Tool editors in the admin panel now allow selecting an LLM for RAG indexing (if PDF/image support is enabled). The RAG options component displays an LLM selector. - **Serialization:** The serializers (`AiCustomToolSerializer`, `AiCustomToolListSerializer`, `LocalizedAiPersonaSerializer`) have been updated to include the new `rag_llm_model_id`, `default_llm_id` and `question_consolidator_llm_id` attributes. **2. PDF and Image Support for RAG:** - **Site Setting:** Introduces a new hidden site setting, `ai_rag_pdf_images_enabled`, to control whether PDF and image files can be indexed for RAG. This defaults to `false`. - **File Upload Validation:** The `RagDocumentFragmentsController` now checks the `ai_rag_pdf_images_enabled` setting and allows PDF, PNG, JPG, and JPEG files if enabled. Error handling is included for cases where PDF/image indexing is attempted with the setting disabled. - **PDF Processing:** Adds a new utility class, `DiscourseAi::Utils::PdfToImages`, which uses ImageMagick (`magick`) to convert PDF pages into individual PNG images. A maximum PDF size and conversion timeout are enforced. - **Image Processing:** A new utility class, `DiscourseAi::Utils::ImageToText`, is included to handle OCR for the images and PDFs. - **RAG Digestion Job:** The `DigestRagUpload` job now handles PDF and image uploads. It uses `PdfToImages` and `ImageToText` to extract text and create document fragments. - **UI Updates:** The RAG uploader component now accepts PDF and image file types if `ai_rag_pdf_images_enabled` is true. The UI text is adjusted to indicate supported file types. **3. Refactoring and Improvements:** - **LLM Enumeration:** The `DiscourseAi::Configuration::LlmEnumerator` now provides a `values_for_serialization` method, which returns a simplified array of LLM data (id, name, vision_enabled) suitable for use in serializers. This avoids exposing unnecessary details to the frontend. - **AI Helper:** The `AiHelper::Assistant` now takes optional `helper_llm` and `image_caption_llm` parameters in its constructor, allowing for greater flexibility. - **Bot and Persona Updates:** Several updates were made across the codebase, changing the string based association to a LLM to the new model based. - **Audit Logs:** The `DiscourseAi::Completions::Endpoints::Base` now formats raw request payloads as pretty JSON for easier auditing. - **Eval Script:** An evaluation script is included. **4. Testing:** - The PR introduces a new eval system for LLMs, this allows us to test how functionality works across various LLM providers. This lives in `/evals`
77 lines
2.3 KiB
Ruby
77 lines
2.3 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Admin
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class RagDocumentFragmentsController < ::Admin::AdminController
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requires_plugin ::DiscourseAi::PLUGIN_NAME
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def indexing_status_check
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if params[:target_type] == "AiPersona"
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@target = AiPersona.find(params[:target_id])
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elsif params[:target_type] == "AiTool"
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@target = AiTool.find(params[:target_id])
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else
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raise Discourse::InvalidParameters.new("Invalid target type")
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end
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render json: RagDocumentFragment.indexing_status(@target, @target.uploads)
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end
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def upload_file
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file = params[:file] || params[:files].first
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if !DiscourseAi::Embeddings.enabled?
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raise Discourse::InvalidAccess.new("Embeddings not enabled")
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end
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validate_extension!(file.original_filename)
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validate_file_size!(file.tempfile.size)
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hijack do
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upload =
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UploadCreator.new(
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file.tempfile,
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file.original_filename,
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type: "discourse_ai_rag_upload",
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skip_validations: true,
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).create_for(current_user.id)
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if upload.persisted?
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render json: UploadSerializer.new(upload)
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else
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render json: failed_json.merge(errors: upload.errors.full_messages), status: 422
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end
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end
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end
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private
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def validate_extension!(filename)
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extension = File.extname(filename)[1..-1] || ""
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authorized_extensions = %w[txt md]
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authorized_extensions.concat(%w[pdf png jpg jpeg]) if SiteSetting.ai_rag_pdf_images_enabled
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if !authorized_extensions.include?(extension)
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raise Discourse::InvalidParameters.new(
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I18n.t(
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"upload.unauthorized",
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authorized_extensions: authorized_extensions.join(" "),
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),
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)
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end
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end
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def validate_file_size!(filesize)
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max_size_bytes = 20.megabytes
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if filesize > max_size_bytes
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raise Discourse::InvalidParameters.new(
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I18n.t(
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"upload.attachments.too_large_humanized",
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max_size: ActiveSupport::NumberHelper.number_to_human_size(max_size_bytes),
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),
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)
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end
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end
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end
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end
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end
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