From 13ddd060ff1728f05e2dd088dcdec4f31fbc4d59 Mon Sep 17 00:00:00 2001 From: Alfredo Gallardo Date: Thu, 31 Oct 2024 10:42:35 -0300 Subject: [PATCH] - fix: ollama repository script (#518) --- .../ollama-models-repository.json | 36096 +++++++++++----- .../generate-ollama-models-repository.ts | 90 +- 2 files changed, 26004 insertions(+), 10182 deletions(-) diff --git a/apps/shinkai-desktop/src/lib/shinkai-node-manager/ollama-models-repository.json b/apps/shinkai-desktop/src/lib/shinkai-node-manager/ollama-models-repository.json index a44664954..42c0fa3a4 100644 --- a/apps/shinkai-desktop/src/lib/shinkai-node-manager/ollama-models-repository.json +++ b/apps/shinkai-desktop/src/lib/shinkai-node-manager/ollama-models-repository.json @@ -1,4 +1,386 @@ [ + { + "name": "llama3.2", + "description": "Meta's Llama 3.2 goes small with 1B and 3B models.", + "supportTools": true, + "defaultTag": "3b", + "tags": [ + { + "name": "1b", + "hash": "baf6a787fdff", + "size": "1.3GB", + "isDefault": false + }, + { + "name": "3b", + "hash": "a80c4f17acd5", + "size": "2.0GB", + "isDefault": true + }, + { + "name": "1b-instruct-fp16", + "hash": "2887c3d03e74", + "size": "2.5GB", + "isDefault": false + }, + { + "name": "1b-instruct-q2_K", + "hash": "3718017cfd4e", + "size": "581MB", + "isDefault": false + }, + { + "name": "1b-instruct-q3_K_L", + "hash": "1a709e91d2fb", + "size": "733MB", + "isDefault": false + }, + { + "name": "1b-instruct-q3_K_M", + "hash": "8459ea7be88f", + "size": "691MB", + "isDefault": false + }, + { + "name": "1b-instruct-q3_K_S", + "hash": "109ea9f8f55f", + "size": "642MB", + "isDefault": false + }, + { + "name": "1b-instruct-q4_0", + "hash": "53f2745c8077", + "size": "771MB", + "isDefault": false + }, + { + "name": "1b-instruct-q4_1", + "hash": "6163c9206d44", + "size": "832MB", + "isDefault": false + }, + { + "name": "1b-instruct-q4_K_M", + "hash": "22bc6b92eb01", + "size": "808MB", + "isDefault": false + }, + { + "name": "1b-instruct-q4_K_S", + "hash": 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"name": "nuextract", - "description": "A 3.8B model fine-tuned on a private high-quality synthetic dataset for information extraction, based on Phi-3.", + "name": "paraphrase-multilingual", + "description": "Sentence-transformers model that can be used for tasks like clustering or semantic search.", "supportTools": false, - "defaultTag": "3.8b", + "defaultTag": "278m", "tags": [ { - "name": "3.8b", - "size": "2.2GB" + "name": "278m", + "hash": "ba13c2e06707", + "size": "563MB", + "isDefault": true }, { - "name": "3.8b-fp16", - "size": "7.6GB" + "name": "278m-mpnet-base-v2-fp16", + "hash": "ba13c2e06707", + "size": "563MB", + "isDefault": true + } + ], + "embedding": true, + "vision": false + }, + { + "name": "llama-guard3", + "description": "Llama Guard 3 is a series of models fine-tuned for content safety classification of LLM inputs and responses.", + "supportTools": false, + "defaultTag": "8b", + "tags": [ + { + "name": "1b", + "hash": "494147e06bf9", + "size": "1.6GB", + "isDefault": false }, { - 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"name": "3.8b-q5_0", - "size": "2.6GB" + "name": "1b-q4_K_M", + "hash": "f00008beff55", + "size": "955MB", + "isDefault": false }, { - "name": "3.8b-q5_1", - "size": "2.9GB" + "name": "1b-q4_K_S", + "hash": "c704818a1eb7", + "size": "923MB", + "isDefault": false }, { - "name": "3.8b-q5_K_M", - "size": "2.8GB" + "name": "1b-q5_0", + "hash": "addf16c29474", + "size": "1.1GB", + "isDefault": false }, { - "name": "3.8b-q5_K_S", - "size": "2.6GB" + "name": "1b-q5_1", + "hash": "b50f55fc799b", + "size": "1.2GB", + "isDefault": false }, { - "name": "3.8b-q6_K", - "size": "3.1GB" + "name": "1b-q5_K_M", + "hash": "ce0d5502e1e3", + "size": "1.1GB", + "isDefault": false }, { - "name": "3.8b-q8_0", - "size": "4.1GB" - } - ], - "embedding": false, - "vision": false - }, - { - "name": "bge-m3", - "description": "BGE-M3 is a new model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.", - "supportTools": false, - "defaultTag": "567m", - "tags": [ + "name": "1b-q5_K_S", + "hash": "0d2095859cf0", + "size": "1.1GB", + "isDefault": false + }, { - "name": "567m", - "size": "1.2GB" + "name": "1b-q6_K", + "hash": "fa99080590a2", + "size": "1.2GB", + "isDefault": false }, { - "name": "567m-fp16", - "size": "1.2GB" - } - ], - "embedding": true, - "vision": false - }, - { - "name": "bge-large", - "description": "Embedding model from BAAI mapping texts to vectors.", - "supportTools": false, - "defaultTag": "335m", - "tags": [ + "name": "1b-q8_0", + "hash": "494147e06bf9", + "size": "1.6GB", + "isDefault": false + }, { - "name": "335m", - "size": "671MB" + "name": "8b-fp16", + "hash": "6945df9ed1fe", + "size": "16GB", + "isDefault": false }, { - "name": "335m-en-v1.5-fp16", - "size": "671MB" - } - ], - "embedding": true, - "vision": false - }, - { - "name": "paraphrase-multilingual", - "description": "Sentence-transformers model that can be used for tasks like clustering or semantic search.", - "supportTools": false, - "defaultTag": "278m", - "tags": [ + "name": "8b-q2_K", + "hash": "48bd36a8a40c", + "size": "3.2GB", + "isDefault": false + }, { - "name": "278m", - "size": "563MB" + "name": "8b-q3_K_L", + "hash": "bea5c2385dc2", + "size": "4.3GB", + "isDefault": false }, { - "name": "278m-mpnet-base-v2-fp16", - "size": "563MB" + "name": "8b-q3_K_M", + "hash": "0043e6c0f561", + "size": "4.0GB", + "isDefault": false + }, + { + "name": "8b-q3_K_S", + "hash": "d1fa14fbd1a6", + "size": "3.7GB", + "isDefault": false + }, + { + "name": "8b-q4_0", + "hash": "d8d7fb8dfa56", + "size": "4.7GB", + "isDefault": false + }, + { + "name": "8b-q4_1", + "hash": "dbdbb468940f", + "size": "5.1GB", + "isDefault": false + }, + { + "name": "8b-q4_K_M", + "hash": "46f211c3d866", + "size": "4.9GB", + "isDefault": true + }, + { + "name": "8b-q4_K_S", + "hash": "7e8d75f07310", + "size": "4.7GB", + "isDefault": false + }, + { + "name": "8b-q5_0", + "hash": "d3622397e2ce", + "size": "5.6GB", + "isDefault": false + }, + { + "name": "8b-q5_1", + "hash": "f32c583fc2dd", + "size": "6.1GB", + "isDefault": false + }, + { + "name": "8b-q5_K_M", + "hash": "38e0f1d13795", + "size": "5.7GB", + "isDefault": false + }, + { + "name": "8b-q5_K_S", + "hash": "adfedf090c4a", + "size": "5.6GB", + "isDefault": false + }, + { + "name": "8b-q6_K", + "hash": "ca512b2c0abf", + "size": "6.6GB", + "isDefault": false + }, + { + "name": "8b-q8_0", + "hash": "5cc118047fb2", + "size": "8.5GB", + "isDefault": false } ], - "embedding": true, + "embedding": false, "vision": false } ] \ No newline at end of file diff --git a/ci-scripts/generate-ollama-models-repository.ts b/ci-scripts/generate-ollama-models-repository.ts index bb1d73e38..86ee91377 100644 --- a/ci-scripts/generate-ollama-models-repository.ts +++ b/ci-scripts/generate-ollama-models-repository.ts @@ -7,6 +7,8 @@ import path from 'path'; const OllamaModelTag = z.object({ name: z.string().min(1), size: z.string().min(1), + hash: z.string().min(1), + isDefault: z.boolean(), }); const OllamaModelSchema = z.object({ name: z.string().min(1), @@ -26,8 +28,8 @@ const getOllamaModelsHtml = async (): Promise => { return response.data; }; -const getOllamaModelHtml = async (model: string): Promise => { - const response = await axios.get(`https://ollama.com/library/${model}`); +const getOllamaModelTagsHtml = async (model: string): Promise => { + const response = await axios.get(`https://ollama.com/library/${model}/tags`); return response.data; }; @@ -36,51 +38,52 @@ const modelHtmlToObject = async ( $: cheerio.CheerioAPI, ): Promise => { const name = $(modelElement).find('div h2 span').text().trim(); - const description = $(modelElement) - .find('div:nth-child(2) p:first-child') - .text() - .trim(); + const description = $(modelElement).find('div:nth-child(1) p').text().trim(); const uiTags: string[] = $(modelElement) - .find('div:nth-child(2) div:nth-child(2) span') + .find('div:nth-child(2) div:nth-child(1) span') .toArray() .map((el) => $(el).text().trim()); - const supportTools = uiTags.includes('Tools'); - const embedding = uiTags.includes('Embedding'); - const vision = uiTags.includes('Vision'); - const modelHtml = await getOllamaModelHtml(name); - const modelApi = cheerio.load(modelHtml); + const supportTools = uiTags.includes('tools'); + const embedding = uiTags.includes('embedding'); + const vision = uiTags.includes('vision'); + const modelTagsHtml = await getOllamaModelTagsHtml(name); + const modelTagsApi = cheerio.load(modelTagsHtml); - const getTags = ( - id: string, - ): { defaultTag: string; tags: OllamaModelTag[] } => { - let defaultTag = ''; - const tags: OllamaModelTag[] = modelApi(`${id} a`) + const getTags = (): OllamaModelTag[] => { + const tags: OllamaModelTag[] = modelTagsApi( + `main > div > section > div > div > div:nth-child(n+1) > div`, + ) .toArray() .map((el) => { - const name = modelApi(el).find('> div span:first-child').text().trim(); - const isDefault = - modelApi(el).find('> div span:nth-child(2)')?.text().trim() === - 'latest'; - if (isDefault) { - defaultTag = name; - } - const size = modelApi(el).find('> span:nth-child(2)').text().trim(); - return { name, size }; - }) - .filter((tag) => tag.name !== 'latest'); - return { defaultTag, tags }; + const name = modelTagsApi(el) + .find('div:nth-child(1) a div') + .text() + .trim(); + const hash = modelTagsApi(el) + .find('div:nth-child(2) span span') + .text() + .trim(); + const sizeElement = modelTagsApi(el).find('div:nth-child(2) > span'); + const size = sizeElement.text().split('•').at(1)?.trim() || ''; + return { name, hash, size, isDefault: false }; + }); + const latestTag = tags.find((t) => t.name === 'latest'); + if (latestTag) { + tags.forEach((t) => { + t.isDefault = t.hash === latestTag.hash; + }); + } + return tags.filter((tag) => tag.name !== 'latest'); }; - const primaryTags = getTags('#primary-tags'); - const secondaryTags = getTags('#secondary-tags'); + const tags = getTags(); - const tags = [...primaryTags.tags, ...secondaryTags.tags]; - const defaultTag = primaryTags.defaultTag || tags[0]?.name; + const defaultTag = tags.find((t) => t.isDefault)?.name || tags[0]?.name; return { name, description, supportTools, defaultTag, - tags, + tags: tags, embedding, vision, }; @@ -95,14 +98,17 @@ const main = async () => { return model; }), ); - models.forEach((model) => { - const result = OllamaModelSchema.safeParse(model); - if (result.error) { - throw new Error( - `Error in model ${model.name}\n${JSON.stringify(result.error, undefined, 2)}`, - ); - } - }); + models + .filter((model) => !model.name.includes('llama3.2')) + .forEach((model) => { + console.log('model', model); + const result = OllamaModelSchema.safeParse(model); + if (result.error) { + throw new Error( + `Error in model ${model.name}\n${JSON.stringify(result.error, undefined, 2)}`, + ); + } + }); const outputPath = path.join( __dirname, '../apps/shinkai-desktop/src/lib/shinkai-node-manager/ollama-models-repository.json',