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https://github.com/discourse/discourse-ai.git
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f5cf1019fb
* Use AR model for embeddings features * endpoints * Embeddings CRUD UI * Add presets. Hide a couple more settings * system specs * Seed embedding definition from old settings * Generate search bit index on the fly. cleanup orphaned data * support for seeded models * Fix run test for new embedding * fix selected model not set correctly
41 lines
1.2 KiB
Ruby
41 lines
1.2 KiB
Ruby
# frozen_string_literal: true
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Fabricator(:embedding_definition) do
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display_name "Multilingual E5 Large"
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provider "hugging_face"
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tokenizer_class "DiscourseAi::Tokenizer::MultilingualE5LargeTokenizer"
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api_key "123"
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url "https://test.com/embeddings"
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provider_params nil
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pg_function "<=>"
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max_sequence_length 512
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dimensions 1024
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end
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Fabricator(:cloudflare_embedding_def, from: :embedding_definition) do
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display_name "BGE Large EN"
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provider "cloudflare"
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pg_function "<#>"
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tokenizer_class "DiscourseAi::Tokenizer::BgeLargeEnTokenizer"
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provider_params nil
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end
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Fabricator(:open_ai_embedding_def, from: :embedding_definition) do
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display_name "ADA 002"
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provider "open_ai"
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url "https://api.openai.com/v1/embeddings"
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tokenizer_class "DiscourseAi::Tokenizer::OpenAiTokenizer"
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provider_params { { model_name: "text-embedding-ada-002" } }
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max_sequence_length 8191
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dimensions 1536
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end
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Fabricator(:gemini_embedding_def, from: :embedding_definition) do
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display_name "Gemini's embedding-001"
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provider "google"
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dimensions 768
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max_sequence_length 1536
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tokenizer_class "DiscourseAi::Tokenizer::OpenAiTokenizer"
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url "https://generativelanguage.googleapis.com/v1beta/models/embedding-001:embedContent"
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end
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