From 21fc18c4f476ae65347a4b6f75ea36ff963572bd Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 15:20:40 +0100 Subject: [PATCH 01/24] formatting --- README.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 838f80045..107fb5899 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ // Programatically interact with the Hub await createRepo({ - repo: {type: "model", name: "my-user/nlp-model"}, + repo: { type: "model", name: "my-user/nlp-model" }, accessToken: HF_TOKEN }); @@ -53,7 +53,7 @@ await inference.textToImage({ This is a collection of JS libraries to interact with the Hugging Face API, with TS types included. -- [@huggingface/inference](packages/inference/README.md): Use Inference Endpoints (dedicated) and Inference API (serverless) to make calls to 100,000+ Machine Learning models +- [@huggingface/inference](packages/inference/README.md): Use Inference API (serverless) and Inference Endpoints (dedicated) to make calls to 100,000+ Machine Learning models - [@huggingface/hub](packages/hub/README.md): Interact with huggingface.co to create or delete repos and commit / download files - [@huggingface/agents](packages/agents/README.md): Interact with HF models through a natural language interface - [@huggingface/gguf](packages/gguf/README.md): A GGUF parser that works on remotely hosted files. @@ -165,7 +165,7 @@ await inference.imageToText({ const gpt2 = inference.endpoint('https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2'); const { generated_text } = await gpt2.textGeneration({inputs: 'The answer to the universe is'}); -//Chat Completion +// Chat Completion const llamaEndpoint = inference.endpoint( "https://api-inference.huggingface.co/models/meta-llama/Llama-3.1-8B-Instruct" ); @@ -185,7 +185,7 @@ import { createRepo, uploadFile, deleteFiles } from "@huggingface/hub"; const HF_TOKEN = "hf_..."; await createRepo({ - repo: "my-user/nlp-model", // or {type: "model", name: "my-user/nlp-test"}, + repo: "my-user/nlp-model", // or { type: "model", name: "my-user/nlp-test" }, accessToken: HF_TOKEN }); @@ -200,7 +200,7 @@ await uploadFile({ }); await deleteFiles({ - repo: {type: "space", name: "my-user/my-space"}, // or "spaces/my-user/my-space" + repo: { type: "space", name: "my-user/my-space" }, // or "spaces/my-user/my-space" accessToken: HF_TOKEN, paths: ["README.md", ".gitattributes"] }); @@ -209,7 +209,7 @@ await deleteFiles({ ### @huggingface/agents example ```ts -import {HfAgent, LLMFromHub, defaultTools} from '@huggingface/agents'; +import { HfAgent, LLMFromHub, defaultTools } from '@huggingface/agents'; const HF_TOKEN = "hf_..."; From f3273750175ab8a6d673f37d3a9b541af690cc78 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 15:24:26 +0100 Subject: [PATCH 02/24] link to jinja in main README cc @xenova --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 107fb5899..d3259af0b 100644 --- a/README.md +++ b/README.md @@ -58,6 +58,7 @@ This is a collection of JS libraries to interact with the Hugging Face API, with - [@huggingface/agents](packages/agents/README.md): Interact with HF models through a natural language interface - [@huggingface/gguf](packages/gguf/README.md): A GGUF parser that works on remotely hosted files. - [@huggingface/tasks](packages/tasks/README.md): The definition files and source-of-truth for the Hub's main primitives like pipeline tasks, model libraries, etc. +- [@huggingface/jinja](packages/jinja/README.md): A minimalistic JS implementation of the Jinja templating engine, to be used for ML chat templates. - [@huggingface/space-header](packages/space-header/README.md): Use the Space `mini_header` outside Hugging Face From 4526b56614c089a60c369f52376fa7352891f691 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 15:24:33 +0100 Subject: [PATCH 03/24] link to DDUF --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index d3259af0b..1774b8de5 100644 --- a/README.md +++ b/README.md @@ -57,6 +57,7 @@ This is a collection of JS libraries to interact with the Hugging Face API, with - [@huggingface/hub](packages/hub/README.md): Interact with huggingface.co to create or delete repos and commit / download files - [@huggingface/agents](packages/agents/README.md): Interact with HF models through a natural language interface - [@huggingface/gguf](packages/gguf/README.md): A GGUF parser that works on remotely hosted files. +- [@huggingface/dduf](packages/dduf/README.md): Similar package for DDUF (DDUF Diffusers Unified Format) - [@huggingface/tasks](packages/tasks/README.md): The definition files and source-of-truth for the Hub's main primitives like pipeline tasks, model libraries, etc. - [@huggingface/jinja](packages/jinja/README.md): A minimalistic JS implementation of the Jinja templating engine, to be used for ML chat templates. - [@huggingface/space-header](packages/space-header/README.md): Use the Space `mini_header` outside Hugging Face From 5e1ee1f13da8fd9679805bc10e4182c5966824fa Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 15:47:17 +0100 Subject: [PATCH 04/24] Update LICENSE --- packages/inference/LICENSE | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/packages/inference/LICENSE b/packages/inference/LICENSE index 7b1576042..7a6064e54 100644 --- a/packages/inference/LICENSE +++ b/packages/inference/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2022 Tim Mikeladze +Copyright (c) 2022 Tim Mikeladze and the Hugging Face team Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal From a2e78728bcdba2470d0eba1000c0ab88eca83602 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 15:47:21 +0100 Subject: [PATCH 05/24] Update README.md --- packages/inference/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/packages/inference/README.md b/packages/inference/README.md index 11939338b..9c20c418b 100644 --- a/packages/inference/README.md +++ b/packages/inference/README.md @@ -1,7 +1,7 @@ # 🤗 Hugging Face Inference Endpoints -A Typescript powered wrapper for the Hugging Face Inference Endpoints API. Learn more about Inference Endpoints at [Hugging Face](https://huggingface.co/inference-endpoints). -It works with both [Inference API (serverless)](https://huggingface.co/docs/api-inference/index) and [Inference Endpoints (dedicated)](https://huggingface.co/docs/inference-endpoints/index). +A Typescript powered wrapper for the Hugging Face Inference API (serverless), Inference Endpoints (dedicated), and third-party Inference Providers. +It works with [Inference API (serverless)](https://huggingface.co/docs/api-inference/index) and [Inference Endpoints (dedicated)](https://huggingface.co/docs/inference-endpoints/index), and even with supported third-party Inference Providers. Check out the [full documentation](https://huggingface.co/docs/huggingface.js/inference/README). From f1961a86720282b0a9e9fe4e6b3f38d77ba44af3 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 17:52:01 +0100 Subject: [PATCH 06/24] implem --- .../inference/src/lib/makeRequestOptions.ts | 56 ++++++++++++++----- packages/inference/src/providers/sambanova.ts | 31 ++++++++++ .../src/tasks/custom/streamingRequest.ts | 4 +- packages/inference/src/types.ts | 18 ++++++ packages/inference/test/HfInference.spec.ts | 17 ++++++ 5 files changed, 110 insertions(+), 16 deletions(-) create mode 100644 packages/inference/src/providers/sambanova.ts diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 50eff4943..c16ad9052 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -1,4 +1,5 @@ -import type { InferenceTask, Options, RequestArgs } from "../types"; +import { SAMBANOVA_API_BASE_URL, SAMBANOVA_MODEL_IDS } from "../providers/sambanova"; +import { INFERENCE_PROVIDERS, type InferenceTask, type Options, type RequestArgs } from "../types"; import { omit } from "../utils/omit"; import { HF_HUB_URL } from "./getDefaultTask"; import { isUrl } from "./isUrl"; @@ -26,17 +27,10 @@ export async function makeRequestOptions( chatCompletion?: boolean; } ): Promise<{ url: string; info: RequestInit }> { - const { accessToken, endpointUrl, ...otherArgs } = args; + const { accessToken, endpointUrl, provider, ...otherArgs } = args; let { model } = args; - const { - forceTask: task, - includeCredentials, - taskHint, - wait_for_model, - use_cache, - dont_load_model, - chatCompletion, - } = options ?? {}; + const { forceTask, includeCredentials, taskHint, wait_for_model, use_cache, dont_load_model, chatCompletion } = + options ?? {}; const headers: Record = {}; if (accessToken) { @@ -61,6 +55,21 @@ export async function makeRequestOptions( if (!model) { throw new Error("No model provided, and no default model found for this task"); } + if (provider) { + if (!INFERENCE_PROVIDERS.includes(provider)) { + throw new Error("Unknown Inference provider"); + } + if (!accessToken) { + throw new Error("Specifying an Inference provider requires an accessToken"); + } + switch (provider) { + case "sambanova": + model = SAMBANOVA_MODEL_IDS[model]; + break; + default: + break; + } + } const binary = "data" in args && !!args.data; @@ -89,8 +98,25 @@ export async function makeRequestOptions( if (endpointUrl) { return endpointUrl; } - if (task) { - return `${HF_INFERENCE_API_BASE_URL}/pipeline/${task}/${model}`; + if (forceTask) { + return `${HF_INFERENCE_API_BASE_URL}/pipeline/${forceTask}/${model}`; + } + if (provider) { + if (!accessToken) { + throw new Error("Specifying an Inference provider requires an accessToken"); + } + if (accessToken.startsWith("hf_")) { + /// TODO we wil proxy the request server-side (using our own keys) and handle billing for it on the user's HF account. + throw new Error("Inference proxying is not implemented yet"); + } else { + /// This is an external key + switch (provider) { + case "sambanova": + return SAMBANOVA_API_BASE_URL; + default: + break; + } + } } return `${HF_INFERENCE_API_BASE_URL}/models/${model}`; @@ -116,9 +142,9 @@ export async function makeRequestOptions( body: binary ? args.data : JSON.stringify({ - ...(otherArgs.model && isUrl(otherArgs.model) ? omit(otherArgs, "model") : otherArgs), + ...(otherArgs.model && isUrl(otherArgs.model) ? omit(otherArgs, "model") : { ...otherArgs, model }), }), - ...(credentials && { credentials }), + ...(credentials ? { credentials } : undefined), signal: options?.signal, }; diff --git a/packages/inference/src/providers/sambanova.ts b/packages/inference/src/providers/sambanova.ts new file mode 100644 index 000000000..0fa3137de --- /dev/null +++ b/packages/inference/src/providers/sambanova.ts @@ -0,0 +1,31 @@ +import type { ModelId } from "../types"; + +export const SAMBANOVA_API_BASE_URL = "https://api.sambanova.ai"; + +/** + * Note for reviewers: our goal would be to ask Sambanova to support + * our model ids too, so we don't have to define a mapping + * or keep it up-to-date. + * + * As a fallback, if the above is not possible, ask Sambanova to + * provide the mapping as an API. + */ +type SambanovaId = string; + +/** + * https://community.sambanova.ai/t/supported-models/193 + */ +export const SAMBANOVA_MODEL_IDS: Record = { + "Qwen/Qwen2.5-Coder-32B-Instruct": "Qwen2.5-Coder-32B-Instruct", + "Qwen/Qwen2.5-72B-Instruct": "Qwen2.5-72B-Instruct", + "Qwen/QwQ-32B-Preview": "QwQ-32B-Preview", + "meta-llama/Llama-3.3-70B-Instruct": "Meta-Llama-3.3-70B-Instruct", + "meta-llama/Llama-3.2-1B": "Meta-Llama-3.2-1B-Instruct", + "meta-llama/Llama-3.2-3B": "Meta-Llama-3.2-3B-Instruct", + "meta-llama/Llama-3.2-11B-Vision-Instruct": "Llama-3.2-11B-Vision-Instruct", + "meta-llama/Llama-3.2-90B-Vision-Instruct": "Llama-3.2-90B-Vision-Instruct", + "meta-llama/Llama-3.1-8B-Instruct": "Meta-Llama-3.1-8B-Instruct", + "meta-llama/Llama-3.1-70B-Instruct": "Meta-Llama-3.1-70B-Instruct", + "meta-llama/Llama-3.1-405B-Instruct": "Meta-Llama-3.1-405B-Instruct", + "meta-llama/Llama-Guard-3-8B": "Meta-Llama-Guard-3-8B", +}; diff --git a/packages/inference/src/tasks/custom/streamingRequest.ts b/packages/inference/src/tasks/custom/streamingRequest.ts index 7f4179811..fac10b9e7 100644 --- a/packages/inference/src/tasks/custom/streamingRequest.ts +++ b/packages/inference/src/tasks/custom/streamingRequest.ts @@ -68,7 +68,9 @@ export async function* streamingRequest( try { while (true) { const { done, value } = await reader.read(); - if (done) return; + if (done) { + return; + } onChunk(value); for (const event of events) { if (event.data.length > 0) { diff --git a/packages/inference/src/types.ts b/packages/inference/src/types.ts index 66490bf2c..0b3b3f4e9 100644 --- a/packages/inference/src/types.ts +++ b/packages/inference/src/types.ts @@ -1,6 +1,11 @@ import type { PipelineType } from "@huggingface/tasks"; import type { ChatCompletionInput } from "@huggingface/tasks"; +/** + * HF model id, like "meta-llama/Llama-3.3-70B-Instruct" + */ +export type ModelId = string; + export interface Options { /** * (Default: true) Boolean. If a request 503s and wait_for_model is set to false, the request will be retried with the same parameters but with wait_for_model set to true. @@ -40,13 +45,19 @@ export interface Options { export type InferenceTask = Exclude; +export const INFERENCE_PROVIDERS = ["sambanova", "together", "hf-inference"] as const; +export type InferenceProvider = (typeof INFERENCE_PROVIDERS)[number]; + export interface BaseArgs { /** * The access token to use. Without it, you'll get rate-limited quickly. * * Can be created for free in hf.co/settings/token + * + * You can also pass an external Inference provider's key if you intend to call a compatible provider like Sambanova, Together... */ accessToken?: string; + /** * The model to use. * @@ -63,6 +74,13 @@ export interface BaseArgs { * If specified, will use this URL instead of the default one. */ endpointUrl?: string; + + /** + * Set an Inference provider to run this model on. + * + * Defaults to the first provider in your user settings that is compatible with this model. + */ + provider?: InferenceProvider; } export type RequestArgs = BaseArgs & diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index cc2a95ef7..38d07130c 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -756,6 +756,23 @@ describe.concurrent( } expect(out).toContain("two"); }); + + /** + * Compatibility with third-party Inference Providers + */ + + it("chatCompletion sambanova", async () => { + const hf = new HfInference(env.SAMBANOVA_KEY); + const res = await hf.chatCompletion({ + model: "meta-llama/Llama-3.1-8B-Instruct", + provider: "sambanova", + messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("two"); + } + }); }, TIMEOUT ); From a41382423feb3a78c48cf627fe66a97a975548c1 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 17:56:05 +0100 Subject: [PATCH 07/24] also stream --- packages/inference/test/HfInference.spec.ts | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 38d07130c..fc2110dd9 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -773,6 +773,22 @@ describe.concurrent( expect(completion).toContain("two"); } }); + it("chatCompletion sambanova stream", async () => { + const hf = new HfInference(env.SAMBANOVA_KEY); + const stream = hf.chatCompletionStream({ + model: "meta-llama/Llama-3.1-8B-Instruct", + provider: "sambanova", + messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } + console.warn(out); + expect(out).toContain("2"); + }); }, TIMEOUT ); From 5629b8604853cfc7d43faaf2066c42989e2c920c Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 18:25:41 +0100 Subject: [PATCH 08/24] Together.ai implem --- .../inference/src/lib/makeRequestOptions.ts | 6 ++ packages/inference/src/providers/sambanova.ts | 2 +- packages/inference/src/providers/together.ts | 60 +++++++++++++++++++ .../inference/src/tasks/nlp/chatCompletion.ts | 3 +- packages/inference/test/HfInference.spec.ts | 29 ++++++++- 5 files changed, 97 insertions(+), 3 deletions(-) create mode 100644 packages/inference/src/providers/together.ts diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index c16ad9052..a9a747d56 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -1,4 +1,5 @@ import { SAMBANOVA_API_BASE_URL, SAMBANOVA_MODEL_IDS } from "../providers/sambanova"; +import { TOGETHER_API_BASE_URL, TOGETHER_MODEL_IDS } from "../providers/together"; import { INFERENCE_PROVIDERS, type InferenceTask, type Options, type RequestArgs } from "../types"; import { omit } from "../utils/omit"; import { HF_HUB_URL } from "./getDefaultTask"; @@ -66,6 +67,9 @@ export async function makeRequestOptions( case "sambanova": model = SAMBANOVA_MODEL_IDS[model]; break; + case "together": + model = TOGETHER_MODEL_IDS[model]?.id ?? model; + break; default: break; } @@ -113,6 +117,8 @@ export async function makeRequestOptions( switch (provider) { case "sambanova": return SAMBANOVA_API_BASE_URL; + case "together": + return TOGETHER_API_BASE_URL; default: break; } diff --git a/packages/inference/src/providers/sambanova.ts b/packages/inference/src/providers/sambanova.ts index 0fa3137de..7b4722e3e 100644 --- a/packages/inference/src/providers/sambanova.ts +++ b/packages/inference/src/providers/sambanova.ts @@ -8,7 +8,7 @@ export const SAMBANOVA_API_BASE_URL = "https://api.sambanova.ai"; * or keep it up-to-date. * * As a fallback, if the above is not possible, ask Sambanova to - * provide the mapping as an API. + * provide the mapping as an fetchable API. */ type SambanovaId = string; diff --git a/packages/inference/src/providers/together.ts b/packages/inference/src/providers/together.ts new file mode 100644 index 000000000..47627678c --- /dev/null +++ b/packages/inference/src/providers/together.ts @@ -0,0 +1,60 @@ +import type { ModelId } from "../types"; + +export const TOGETHER_API_BASE_URL = "https://api.together.xyz"; + +/** + * Same comment as in sambanova.ts + */ +type TogetherId = string; + +/** + * https://docs.together.ai/reference/models-1 + */ +export const TOGETHER_MODEL_IDS: Record< + ModelId, + { id: TogetherId; type: "chat" | "embedding" | "image" | "language" | "moderation" } +> = { + "BAAI/bge-base-en-v1.5": { id: "BAAI/bge-base-en-v1.5", type: "embedding" }, + "black-forest-labs/FLUX.1-Canny-dev": { id: "black-forest-labs/FLUX.1-canny", type: "image" }, + "black-forest-labs/FLUX.1-Depth-dev": { id: "black-forest-labs/FLUX.1-depth", type: "image" }, + "black-forest-labs/FLUX.1-dev": { id: "black-forest-labs/FLUX.1-dev", type: "image" }, + "black-forest-labs/FLUX.1-Redux-dev": { id: "black-forest-labs/FLUX.1-redux", type: "image" }, + "black-forest-labs/FLUX.1-schnell": { id: "black-forest-labs/FLUX.1-pro", type: "image" }, + "databricks/dbrx-instruct": { id: "databricks/dbrx-instruct", type: "chat" }, + "deepseek-ai/deepseek-llm-67b-chat": { id: "deepseek-ai/deepseek-llm-67b-chat", type: "chat" }, + "google/gemma-2-9b-it": { id: "google/gemma-2-9b-it", type: "chat" }, + "google/gemma-2b-it": { id: "google/gemma-2-27b-it", type: "chat" }, + "llava-hf/llava-v1.6-mistral-7b-hf": { id: "llava-hf/llava-v1.6-mistral-7b-hf", type: "chat" }, + "meta-llama/Llama-2-13b-chat-hf": { id: "meta-llama/Llama-2-13b-chat-hf", type: "chat" }, + "meta-llama/Llama-2-70b-hf": { id: "meta-llama/Llama-2-70b-hf", type: "language" }, + "meta-llama/Llama-2-7b-chat-hf": { id: "meta-llama/Llama-2-7b-chat-hf", type: "chat" }, + "meta-llama/Llama-3.2-11B-Vision-Instruct": { id: "meta-llama/Llama-Vision-Free", type: "chat" }, + "meta-llama/Llama-3.2-3B-Instruct": { id: "meta-llama/Llama-3.2-3B-Instruct-Turbo", type: "chat" }, + "meta-llama/Llama-3.2-90B-Vision-Instruct": { id: "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", type: "chat" }, + "meta-llama/Llama-3.3-70B-Instruct": { id: "meta-llama/Llama-3.3-70B-Instruct-Turbo", type: "chat" }, + "meta-llama/Llama-Guard-3-11B-Vision": { id: "meta-llama/Llama-Guard-3-11B-Vision-Turbo", type: "moderation" }, + "meta-llama/LlamaGuard-7b": { id: "Meta-Llama/Llama-Guard-7b", type: "moderation" }, + "meta-llama/Meta-Llama-3-70B-Instruct": { id: "meta-llama/Llama-3-70b-chat-hf", type: "chat" }, + "meta-llama/Meta-Llama-3-8B": { id: "meta-llama/Meta-Llama-3-8B", type: "language" }, + "meta-llama/Meta-Llama-3-8B-Instruct": { id: "togethercomputer/Llama-3-8b-chat-hf-int4", type: "chat" }, + "meta-llama/Meta-Llama-3.1-405B-Instruct": { id: "meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo", type: "chat" }, + "meta-llama/Meta-Llama-3.1-70B-Instruct": { id: "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", type: "chat" }, + "meta-llama/Meta-Llama-3.1-8B-Instruct": { id: "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo-128K", type: "chat" }, + "microsoft/WizardLM-2-8x22B": { id: "microsoft/WizardLM-2-8x22B", type: "chat" }, + "mistralai/Mistral-7B-Instruct-v0.3": { id: "mistralai/Mistral-7B-Instruct-v0.3", type: "chat" }, + "mistralai/Mixtral-8x22B-Instruct-v0.1": { id: "mistralai/Mixtral-8x22B-Instruct-v0.1", type: "chat" }, + "mistralai/Mixtral-8x7B-Instruct-v0.1": { id: "mistralai/Mixtral-8x7B-Instruct-v0.1", type: "chat" }, + "mistralai/Mixtral-8x7B-v0.1": { id: "mistralai/Mixtral-8x7B-v0.1", type: "language" }, + "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO": { id: "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", type: "chat" }, + "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF": { id: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", type: "chat" }, + "Qwen/Qwen2-72B-Instruct": { id: "Qwen/Qwen2-72B-Instruct", type: "chat" }, + "Qwen/Qwen2.5-72B-Instruct": { id: "Qwen/Qwen2.5-72B-Instruct-Turbo", type: "chat" }, + "Qwen/Qwen2.5-7B-Instruct": { id: "Qwen/Qwen2.5-7B-Instruct-Turbo", type: "chat" }, + "Qwen/Qwen2.5-Coder-32B-Instruct": { id: "Qwen/Qwen2.5-Coder-32B-Instruct", type: "chat" }, + "Qwen/QwQ-32B-Preview": { id: "Qwen/QwQ-32B-Preview", type: "chat" }, + "scb10x/llama-3-typhoon-v1.5-8b-instruct": { id: "scb10x/scb10x-llama3-typhoon-v1-5-8b-instruct", type: "chat" }, + "scb10x/llama-3-typhoon-v1.5x-70b-instruct-awq": { id: "scb10x/scb10x-llama3-typhoon-v1-5x-4f316", type: "chat" }, + "stabilityai/stable-diffusion-xl-base-1.0": { id: "stabilityai/stable-diffusion-xl-base-1.0", type: "image" }, + "togethercomputer/m2-bert-80M-32k-retrieval": { id: "togethercomputer/m2-bert-80M-32k-retrieval", type: "embedding" }, + "togethercomputer/m2-bert-80M-8k-retrieval": { id: "togethercomputer/m2-bert-80M-8k-retrieval", type: "embedding" }, +}; diff --git a/packages/inference/src/tasks/nlp/chatCompletion.ts b/packages/inference/src/tasks/nlp/chatCompletion.ts index fbc7e0cc1..e34898827 100644 --- a/packages/inference/src/tasks/nlp/chatCompletion.ts +++ b/packages/inference/src/tasks/nlp/chatCompletion.ts @@ -22,7 +22,8 @@ export async function chatCompletion( typeof res?.created === "number" && typeof res?.id === "string" && typeof res?.model === "string" && - typeof res?.system_fingerprint === "string" && + /// Together.ai does not output a system_fingerprint + (res.system_fingerprint === undefined || typeof res.system_fingerprint === "string") && typeof res?.usage === "object"; if (!isValidOutput) { diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index fc2110dd9..f842c4a26 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -786,7 +786,34 @@ describe.concurrent( out += chunk.choices[0].delta.content; } } - console.warn(out); + expect(out).toContain("2"); + }); + + it("chatCompletion together", async () => { + const hf = new HfInference(env.TOGETHER_KEY); + const res = await hf.chatCompletion({ + model: "meta-llama/Llama-3.3-70B-Instruct", + provider: "together", + messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("two"); + } + }); + it("chatCompletion together stream", async () => { + const hf = new HfInference(env.TOGETHER_KEY); + const stream = hf.chatCompletionStream({ + model: "meta-llama/Llama-3.3-70B-Instruct", + provider: "together", + messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } expect(out).toContain("2"); }); }, From d96a18e6ec33d8975db087973cbec3288d2ba705 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Mon, 16 Dec 2024 19:10:15 +0100 Subject: [PATCH 09/24] textToImage should work too --- .../inference/src/lib/makeRequestOptions.ts | 3 +++ .../inference/src/tasks/cv/textToImage.ts | 26 ++++++++++++++++++- packages/inference/test/HfInference.spec.ts | 10 +++++++ 3 files changed, 38 insertions(+), 1 deletion(-) diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index a9a747d56..472bd1959 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -118,6 +118,9 @@ export async function makeRequestOptions( case "sambanova": return SAMBANOVA_API_BASE_URL; case "together": + if (taskHint === "text-to-image") { + return `${TOGETHER_API_BASE_URL}/v1/images/generations`; + } return TOGETHER_API_BASE_URL; default: break; diff --git a/packages/inference/src/tasks/cv/textToImage.ts b/packages/inference/src/tasks/cv/textToImage.ts index 677b3bc5c..04fa887bb 100644 --- a/packages/inference/src/tasks/cv/textToImage.ts +++ b/packages/inference/src/tasks/cv/textToImage.ts @@ -8,6 +8,12 @@ export type TextToImageArgs = BaseArgs & { */ inputs: string; + /** + * Same param but for external providers like Together + */ + prompt?: string; + response_format?: "base64"; + parameters?: { /** * An optional negative prompt for the image generation @@ -32,6 +38,13 @@ export type TextToImageArgs = BaseArgs & { }; }; +interface Base64ImageGeneration { + id: string; + model: string; + data: Array<{ + b64_json: string; + }>; +} export type TextToImageOutput = Blob; /** @@ -39,10 +52,21 @@ export type TextToImageOutput = Blob; * Recommended model: stabilityai/stable-diffusion-2 */ export async function textToImage(args: TextToImageArgs, options?: Options): Promise { - const res = await request(args, { + if (args.provider === "together") { + args.prompt = args.inputs; + args.inputs = ""; + args.response_format = "base64"; + } + const res = await request(args, { ...options, taskHint: "text-to-image", }); + if (res && typeof res === "object" && Array.isArray(res.data) && res.data[0].b64_json) { + const base64Data = res.data[0].b64_json; + const base64Response = await fetch(`data:image/jpeg;base64,${base64Data}`); + const blob = await base64Response.blob(); + return blob; + } const isValidOutput = res && res instanceof Blob; if (!isValidOutput) { throw new InferenceOutputError("Expected Blob"); diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index f842c4a26..ee7d5baa1 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -816,6 +816,16 @@ describe.concurrent( } expect(out).toContain("2"); }); + + it("textToImage together", async () => { + const hf = new HfInference(env.TOGETHER_KEY); + const res = await hf.textToImage({ + model: "stabilityai/stable-diffusion-xl-base-1.0", + provider: "together", + inputs: "award winning high resolution photo of a giant tortoise", + }); + expect(res).toBeInstanceOf(Blob); + }); }, TIMEOUT ); From aa7d1ca8d8e5f124f9c82d9c82c2ffe5328c7379 Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Tue, 17 Dec 2024 12:28:51 +0100 Subject: [PATCH 10/24] support for replicate --- .../inference/src/lib/makeRequestOptions.ts | 13 ++++++- packages/inference/src/providers/replicate.ts | 18 ++++++++++ .../inference/src/tasks/custom/request.ts | 8 ++++- .../inference/src/tasks/cv/textToImage.ts | 35 +++++++++++++------ packages/inference/src/types.ts | 8 ++--- packages/inference/test/HfInference.spec.ts | 10 ++++++ 6 files changed, 76 insertions(+), 16 deletions(-) create mode 100644 packages/inference/src/providers/replicate.ts diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 472bd1959..62423ebd1 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -1,3 +1,4 @@ +import { REPLICATE_API_BASE_URL, REPLICATE_MODEL_IDS } from "../providers/replicate"; import { SAMBANOVA_API_BASE_URL, SAMBANOVA_MODEL_IDS } from "../providers/sambanova"; import { TOGETHER_API_BASE_URL, TOGETHER_MODEL_IDS } from "../providers/together"; import { INFERENCE_PROVIDERS, type InferenceTask, type Options, type RequestArgs } from "../types"; @@ -64,6 +65,9 @@ export async function makeRequestOptions( throw new Error("Specifying an Inference provider requires an accessToken"); } switch (provider) { + case "replicate": + model = REPLICATE_MODEL_IDS[model]; + break; case "sambanova": model = SAMBANOVA_MODEL_IDS[model]; break; @@ -90,6 +94,9 @@ export async function makeRequestOptions( if (dont_load_model) { headers["X-Load-Model"] = "0"; } + if (provider === "replicate") { + headers["Prefer"] = "wait"; + } let url = (() => { if (endpointUrl && isUrl(model)) { @@ -115,6 +122,8 @@ export async function makeRequestOptions( } else { /// This is an external key switch (provider) { + case "replicate": + return `${REPLICATE_API_BASE_URL}/v1/models/${model}/predictions`; case "sambanova": return SAMBANOVA_API_BASE_URL; case "together": @@ -151,7 +160,9 @@ export async function makeRequestOptions( body: binary ? args.data : JSON.stringify({ - ...(otherArgs.model && isUrl(otherArgs.model) ? omit(otherArgs, "model") : { ...otherArgs, model }), + ...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" + ? omit(otherArgs, "model") + : { ...otherArgs, model }), }), ...(credentials ? { credentials } : undefined), signal: options?.signal, diff --git a/packages/inference/src/providers/replicate.ts b/packages/inference/src/providers/replicate.ts new file mode 100644 index 000000000..7c1b8125b --- /dev/null +++ b/packages/inference/src/providers/replicate.ts @@ -0,0 +1,18 @@ +import type { ModelId } from "../types"; + +export const REPLICATE_API_BASE_URL = "https://api.replicate.com"; + +/** + * Same comment as in sambanova.ts + */ +type ReplicateId = string; + +/** + * curl -s \ + * -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ + * https://api.replicate.com/v1/models + */ +export const REPLICATE_MODEL_IDS: Record = { + "black-forest-labs/FLUX.1-schnell": "black-forest-labs/flux-schnell", + "ByteDance/SDXL-Lightning": "bytedance/sdxl-lightning-4step", +}; diff --git a/packages/inference/src/tasks/custom/request.ts b/packages/inference/src/tasks/custom/request.ts index 99a4beac2..f23616c18 100644 --- a/packages/inference/src/tasks/custom/request.ts +++ b/packages/inference/src/tasks/custom/request.ts @@ -26,13 +26,19 @@ export async function request( } if (!response.ok) { - if (response.headers.get("Content-Type")?.startsWith("application/json")) { + if ( + ["application/json", "application/problem+json"].some( + (contentType) => response.headers.get("Content-Type")?.startsWith(contentType) + ) + ) { const output = await response.json(); if ([400, 422, 404, 500].includes(response.status) && options?.chatCompletion) { throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${output.error}`); } if (output.error) { throw new Error(JSON.stringify(output.error)); + } else { + throw new Error(output); } } throw new Error("An error occurred while fetching the blob"); diff --git a/packages/inference/src/tasks/cv/textToImage.ts b/packages/inference/src/tasks/cv/textToImage.ts index 04fa887bb..12a7a9995 100644 --- a/packages/inference/src/tasks/cv/textToImage.ts +++ b/packages/inference/src/tasks/cv/textToImage.ts @@ -9,10 +9,13 @@ export type TextToImageArgs = BaseArgs & { inputs: string; /** - * Same param but for external providers like Together + * Same param but for external providers like Together, Replicate */ prompt?: string; response_format?: "base64"; + input?: { + prompt: string; + }; parameters?: { /** @@ -38,14 +41,16 @@ export type TextToImageArgs = BaseArgs & { }; }; +export type TextToImageOutput = Blob; + interface Base64ImageGeneration { - id: string; - model: string; data: Array<{ b64_json: string; }>; } -export type TextToImageOutput = Blob; +interface OutputUrlImageGeneration { + output: string[]; +} /** * This task reads some text input and outputs an image. @@ -56,16 +61,26 @@ export async function textToImage(args: TextToImageArgs, options?: Options): Pro args.prompt = args.inputs; args.inputs = ""; args.response_format = "base64"; + } else if (args.provider === "replicate") { + args.input = { prompt: args.inputs }; + delete (args as unknown as { inputs: unknown }).inputs; } - const res = await request(args, { + const res = await request(args, { ...options, taskHint: "text-to-image", }); - if (res && typeof res === "object" && Array.isArray(res.data) && res.data[0].b64_json) { - const base64Data = res.data[0].b64_json; - const base64Response = await fetch(`data:image/jpeg;base64,${base64Data}`); - const blob = await base64Response.blob(); - return blob; + if (res && typeof res === "object") { + if ("data" in res && Array.isArray(res.data) && res.data[0].b64_json) { + const base64Data = res.data[0].b64_json; + const base64Response = await fetch(`data:image/jpeg;base64,${base64Data}`); + const blob = await base64Response.blob(); + return blob; + } + if ("output" in res && Array.isArray(res.output)) { + const urlResponse = await fetch(res.output[0]); + const blob = await urlResponse.blob(); + return blob; + } } const isValidOutput = res && res instanceof Blob; if (!isValidOutput) { diff --git a/packages/inference/src/types.ts b/packages/inference/src/types.ts index 0b3b3f4e9..33325bbd6 100644 --- a/packages/inference/src/types.ts +++ b/packages/inference/src/types.ts @@ -45,7 +45,7 @@ export interface Options { export type InferenceTask = Exclude; -export const INFERENCE_PROVIDERS = ["sambanova", "together", "hf-inference"] as const; +export const INFERENCE_PROVIDERS = ["replicate", "sambanova", "together", "hf-inference"] as const; export type InferenceProvider = (typeof INFERENCE_PROVIDERS)[number]; export interface BaseArgs { @@ -54,19 +54,19 @@ export interface BaseArgs { * * Can be created for free in hf.co/settings/token * - * You can also pass an external Inference provider's key if you intend to call a compatible provider like Sambanova, Together... + * You can also pass an external Inference provider's key if you intend to call a compatible provider like Sambanova, Together, Replicate... */ accessToken?: string; /** - * The model to use. + * The HF model to use. * * If not specified, will call huggingface.co/api/tasks to get the default model for the task. * * /!\ Legacy behavior allows this to be an URL, but this is deprecated and will be removed in the future. * Use the `endpointUrl` parameter instead. */ - model?: string; + model?: ModelId; /** * The URL of the endpoint to use. If not specified, will call huggingface.co/api/tasks to get the default endpoint for the task. diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index ee7d5baa1..b5d08db4f 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -826,6 +826,16 @@ describe.concurrent( }); expect(res).toBeInstanceOf(Blob); }); + + it("textToImage replicate", async () => { + const hf = new HfInference(env.REPLICATE_KEY); + const res = await hf.textToImage({ + model: "black-forest-labs/FLUX.1-schnell", + provider: "replicate", + inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + }); + expect(res).toBeInstanceOf(Blob); + }); }, TIMEOUT ); From 238567a9c86776ae9da31f0183f6074bd3525650 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 15:24:26 +0100 Subject: [PATCH 11/24] add fal-ai as a provider --- .../inference/src/lib/makeRequestOptions.ts | 20 ++++++++++++------- packages/inference/src/providers/fal-ai.ts | 13 ++++++++++++ .../inference/src/tasks/custom/request.ts | 6 +++--- .../inference/src/tasks/cv/textToImage.ts | 6 +++++- packages/inference/src/types.ts | 2 +- 5 files changed, 35 insertions(+), 12 deletions(-) create mode 100644 packages/inference/src/providers/fal-ai.ts diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 62423ebd1..50b63647e 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -1,3 +1,4 @@ +import { FAL_AI_API_BASE_URL, FAL_AI_MODEL_IDS } from "../providers/fal-ai"; import { REPLICATE_API_BASE_URL, REPLICATE_MODEL_IDS } from "../providers/replicate"; import { SAMBANOVA_API_BASE_URL, SAMBANOVA_MODEL_IDS } from "../providers/sambanova"; import { TOGETHER_API_BASE_URL, TOGETHER_MODEL_IDS } from "../providers/together"; @@ -9,7 +10,8 @@ import { isUrl } from "./isUrl"; const HF_INFERENCE_API_BASE_URL = "https://api-inference.huggingface.co"; /** - * Loaded from huggingface.co/api/tasks if needed + * Lazy-loaded from huggingface.co/api/tasks when needed + * Used to determine the default model to use when it's not user defined */ let tasks: Record | null = null; @@ -36,7 +38,7 @@ export async function makeRequestOptions( const headers: Record = {}; if (accessToken) { - headers["Authorization"] = `Bearer ${accessToken}`; + headers["Authorization"] = provider === "fal-ai" ? `Key ${accessToken}` : `Bearer ${accessToken}`; } if (!model && !tasks && taskHint) { @@ -74,6 +76,9 @@ export async function makeRequestOptions( case "together": model = TOGETHER_MODEL_IDS[model]?.id ?? model; break; + case "fal-ai": + model = FAL_AI_MODEL_IDS[model]; + break; default: break; } @@ -120,8 +125,9 @@ export async function makeRequestOptions( /// TODO we wil proxy the request server-side (using our own keys) and handle billing for it on the user's HF account. throw new Error("Inference proxying is not implemented yet"); } else { - /// This is an external key switch (provider) { + case 'fal-ai': + return `${FAL_AI_API_BASE_URL}/${model}`; case "replicate": return `${REPLICATE_API_BASE_URL}/v1/models/${model}/predictions`; case "sambanova": @@ -160,10 +166,10 @@ export async function makeRequestOptions( body: binary ? args.data : JSON.stringify({ - ...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" - ? omit(otherArgs, "model") - : { ...otherArgs, model }), - }), + ...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" || provider === "fal-ai" + ? omit(otherArgs, "model") + : { ...otherArgs, model }), + }), ...(credentials ? { credentials } : undefined), signal: options?.signal, }; diff --git a/packages/inference/src/providers/fal-ai.ts b/packages/inference/src/providers/fal-ai.ts new file mode 100644 index 000000000..17951ca41 --- /dev/null +++ b/packages/inference/src/providers/fal-ai.ts @@ -0,0 +1,13 @@ +import type { ModelId } from "../types"; + +export const FAL_AI_API_BASE_URL = "https://fal.run" + +type FalAiId = string; + +export const FAL_AI_MODEL_IDS: Record = { + "black-forest-labs/FLUX.1-schnell": "fal-ai/flux/schnell", + "black-forest-labs/FLUX.1-dev": "fal-ai/flux/dev", + "black-forest-labs/FLUX.1-Redux-dev": "fal-ai/flux/dev/redux", + "openai/whisper-large-v3": "fal-ai/wizper", + "TencentARC/PhotoMaker": "fal-ai/photomaker", +} \ No newline at end of file diff --git a/packages/inference/src/tasks/custom/request.ts b/packages/inference/src/tasks/custom/request.ts index f23616c18..22067bb3a 100644 --- a/packages/inference/src/tasks/custom/request.ts +++ b/packages/inference/src/tasks/custom/request.ts @@ -2,7 +2,7 @@ import type { InferenceTask, Options, RequestArgs } from "../../types"; import { makeRequestOptions } from "../../lib/makeRequestOptions"; /** - * Primitive to make custom calls to Inference Endpoints + * Primitive to make custom calls to the inference provider */ export async function request( args: RequestArgs, @@ -35,8 +35,8 @@ export async function request( if ([400, 422, 404, 500].includes(response.status) && options?.chatCompletion) { throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${output.error}`); } - if (output.error) { - throw new Error(JSON.stringify(output.error)); + if (output.error || output.detail) { + throw new Error(JSON.stringify(output.error ?? output.detail)); } else { throw new Error(output); } diff --git a/packages/inference/src/tasks/cv/textToImage.ts b/packages/inference/src/tasks/cv/textToImage.ts index 12a7a9995..d8527d653 100644 --- a/packages/inference/src/tasks/cv/textToImage.ts +++ b/packages/inference/src/tasks/cv/textToImage.ts @@ -57,7 +57,7 @@ interface OutputUrlImageGeneration { * Recommended model: stabilityai/stable-diffusion-2 */ export async function textToImage(args: TextToImageArgs, options?: Options): Promise { - if (args.provider === "together") { + if (args.provider === "together" || args.provider === "fal-ai") { args.prompt = args.inputs; args.inputs = ""; args.response_format = "base64"; @@ -70,6 +70,10 @@ export async function textToImage(args: TextToImageArgs, options?: Options): Pro taskHint: "text-to-image", }); if (res && typeof res === "object") { + if (args.provider === "fal-ai" && "images" in res && Array.isArray(res.images) && res.images[0].url) { + const image = await fetch(res.images[0].url); + return await image.blob(); + } if ("data" in res && Array.isArray(res.data) && res.data[0].b64_json) { const base64Data = res.data[0].b64_json; const base64Response = await fetch(`data:image/jpeg;base64,${base64Data}`); diff --git a/packages/inference/src/types.ts b/packages/inference/src/types.ts index 33325bbd6..3b70538b3 100644 --- a/packages/inference/src/types.ts +++ b/packages/inference/src/types.ts @@ -45,7 +45,7 @@ export interface Options { export type InferenceTask = Exclude; -export const INFERENCE_PROVIDERS = ["replicate", "sambanova", "together", "hf-inference"] as const; +export const INFERENCE_PROVIDERS = ["fal-ai", "replicate", "sambanova", "together", "hf-inference"] as const; export type InferenceProvider = (typeof INFERENCE_PROVIDERS)[number]; export interface BaseArgs { From 43f739fd98807cdb77fb40023e0b5edc472456ef Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 17:17:35 +0100 Subject: [PATCH 12/24] tweaks --- packages/inference/src/lib/makeRequestOptions.ts | 6 +++--- packages/inference/src/providers/replicate.ts | 3 +++ packages/inference/src/tasks/custom/request.ts | 6 ++++-- packages/inference/src/tasks/nlp/chatCompletion.ts | 3 +++ 4 files changed, 13 insertions(+), 5 deletions(-) diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 50b63647e..0e5b6a620 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -68,16 +68,16 @@ export async function makeRequestOptions( } switch (provider) { case "replicate": - model = REPLICATE_MODEL_IDS[model]; + model = REPLICATE_MODEL_IDS[model] ?? model; break; case "sambanova": - model = SAMBANOVA_MODEL_IDS[model]; + model = SAMBANOVA_MODEL_IDS[model] ?? model; break; case "together": model = TOGETHER_MODEL_IDS[model]?.id ?? model; break; case "fal-ai": - model = FAL_AI_MODEL_IDS[model]; + model = FAL_AI_MODEL_IDS[model] ?? model; break; default: break; diff --git a/packages/inference/src/providers/replicate.ts b/packages/inference/src/providers/replicate.ts index 7c1b8125b..44fc2cda4 100644 --- a/packages/inference/src/providers/replicate.ts +++ b/packages/inference/src/providers/replicate.ts @@ -15,4 +15,7 @@ type ReplicateId = string; export const REPLICATE_MODEL_IDS: Record = { "black-forest-labs/FLUX.1-schnell": "black-forest-labs/flux-schnell", "ByteDance/SDXL-Lightning": "bytedance/sdxl-lightning-4step", + "meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct", + "meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct", + "meta-llama/Meta-Llama-3.1-405B-Instruct": "meta/meta-llama-3.1-405b-instruct", }; diff --git a/packages/inference/src/tasks/custom/request.ts b/packages/inference/src/tasks/custom/request.ts index 22067bb3a..1e5ddfc98 100644 --- a/packages/inference/src/tasks/custom/request.ts +++ b/packages/inference/src/tasks/custom/request.ts @@ -26,9 +26,10 @@ export async function request( } if (!response.ok) { + const contentType = response.headers.get("Content-Type"); if ( ["application/json", "application/problem+json"].some( - (contentType) => response.headers.get("Content-Type")?.startsWith(contentType) + (ct) => contentType?.startsWith(ct) ) ) { const output = await response.json(); @@ -41,7 +42,8 @@ export async function request( throw new Error(output); } } - throw new Error("An error occurred while fetching the blob"); + const message = contentType?.startsWith("text/plain;") ? await response.text() : undefined; + throw new Error(message ?? "An error occurred while fetching the blob"); } if (response.headers.get("Content-Type")?.startsWith("application/json")) { diff --git a/packages/inference/src/tasks/nlp/chatCompletion.ts b/packages/inference/src/tasks/nlp/chatCompletion.ts index e34898827..2beed08d2 100644 --- a/packages/inference/src/tasks/nlp/chatCompletion.ts +++ b/packages/inference/src/tasks/nlp/chatCompletion.ts @@ -11,6 +11,9 @@ export async function chatCompletion( args: BaseArgs & ChatCompletionInput, options?: Options ): Promise { + if (args.provider === "replicate") { + throw new Error("Replicate does not support the chat completion API"); + } const res = await request(args, { ...options, taskHint: "text-generation", From 8155828271ea576d60f500d8ca1ae3d9cae5205c Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 17:26:28 +0100 Subject: [PATCH 13/24] stringify JSON error when chat completing --- packages/inference/src/tasks/custom/request.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/packages/inference/src/tasks/custom/request.ts b/packages/inference/src/tasks/custom/request.ts index 1e5ddfc98..de25b8175 100644 --- a/packages/inference/src/tasks/custom/request.ts +++ b/packages/inference/src/tasks/custom/request.ts @@ -34,7 +34,7 @@ export async function request( ) { const output = await response.json(); if ([400, 422, 404, 500].includes(response.status) && options?.chatCompletion) { - throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${output.error}`); + throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${JSON.stringify(output.error)}`); } if (output.error || output.detail) { throw new Error(JSON.stringify(output.error ?? output.detail)); From d8e01abb5f7be0ecae69c91e2ecb2af422d5a8f4 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 17:59:30 +0100 Subject: [PATCH 14/24] Update tests & VCR tapes --- packages/inference/test/HfInference.spec.ts | 1493 ++++++++++--------- packages/inference/test/tapes.json | 192 +++ 2 files changed, 947 insertions(+), 738 deletions(-) diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index b5d08db4f..b8d515572 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -5,6 +5,7 @@ import type { ChatCompletionStreamOutput } from "@huggingface/tasks"; import { HfInference } from "../src"; import "./vcr"; import { readTestFile } from "./test-files"; +import { fail } from "assert"; const TIMEOUT = 60000 * 3; const env = import.meta.env; @@ -17,374 +18,349 @@ describe.concurrent( "HfInference", () => { // Individual tests can be ran without providing an api key, however running all tests without an api key will result in rate limiting error. - const hf = new HfInference(env.HF_TOKEN); - - it("throws error if model does not exist", () => { - expect( - hf.fillMask({ - model: "this-model-does-not-exist-123", - inputs: "[MASK] world!", - }) - ).rejects.toThrowError("Model this-model-does-not-exist-123 does not exist"); - }); - - it("fillMask", async () => { - expect( - await hf.fillMask({ - model: "bert-base-uncased", - inputs: "[MASK] world!", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - score: expect.any(Number), - token: expect.any(Number), - token_str: expect.any(String), - sequence: expect.any(String), - }), - ]) - ); - }); - it("works without model", async () => { - expect( - await hf.fillMask({ - inputs: "[MASK] world!", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - score: expect.any(Number), - token: expect.any(Number), - token_str: expect.any(String), - sequence: expect.any(String), - }), - ]) - ); - }); + describe.concurrent("HF Inference", () => { + const hf = new HfInference(env.HF_TOKEN); + it("throws error if model does not exist", () => { + expect( + hf.fillMask({ + model: "this-model-does-not-exist-123", + inputs: "[MASK] world!", + }) + ).rejects.toThrowError("Model this-model-does-not-exist-123 does not exist"); + }); - it("summarization", async () => { - expect( - await hf.summarization({ - model: "google/pegasus-xsum", - inputs: - "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930.", - parameters: { - max_length: 100, - }, - }) - ).toEqual({ - summary_text: "The Eiffel Tower is one of the most famous buildings in the world.", + it("fillMask", async () => { + expect( + await hf.fillMask({ + model: "bert-base-uncased", + inputs: "[MASK] world!", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + token: expect.any(Number), + token_str: expect.any(String), + sequence: expect.any(String), + }), + ]) + ); }); - }); - it("questionAnswering", async () => { - expect( - await hf.questionAnswering({ - model: "deepset/roberta-base-squad2", - inputs: { - question: "What is the capital of France?", - context: "The capital of France is Paris.", - }, - }) - ).toMatchObject({ - answer: "Paris", - score: expect.any(Number), - start: expect.any(Number), - end: expect.any(Number), + it("works without model", async () => { + expect( + await hf.fillMask({ + inputs: "[MASK] world!", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + token: expect.any(Number), + token_str: expect.any(String), + sequence: expect.any(String), + }), + ]) + ); }); - }); - it("tableQuestionAnswering", async () => { - expect( - await hf.tableQuestionAnswering({ - model: "google/tapas-base-finetuned-wtq", - inputs: { - query: "How many stars does the transformers repository have?", - table: { - Repository: ["Transformers", "Datasets", "Tokenizers"], - Stars: ["36542", "4512", "3934"], - Contributors: ["651", "77", "34"], - "Programming language": ["Python", "Python", "Rust, Python and NodeJS"], + it("summarization", async () => { + expect( + await hf.summarization({ + model: "google/pegasus-xsum", + inputs: + "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930.", + parameters: { + max_length: 100, }, - }, - }) - ).toMatchObject({ - answer: "AVERAGE > 36542", - coordinates: [[0, 1]], - cells: ["36542"], - aggregator: "AVERAGE", + }) + ).toEqual({ + summary_text: "The Eiffel Tower is one of the most famous buildings in the world.", + }); }); - }); - it("documentQuestionAnswering", async () => { - expect( - await hf.documentQuestionAnswering({ - model: "impira/layoutlm-document-qa", - inputs: { - question: "Invoice number?", - image: new Blob([readTestFile("invoice.png")], { type: "image/png" }), - }, - }) - ).toMatchObject({ - answer: "us-001", - score: expect.any(Number), - // not sure what start/end refers to in this case - start: expect.any(Number), - end: expect.any(Number), + it("questionAnswering", async () => { + expect( + await hf.questionAnswering({ + model: "deepset/roberta-base-squad2", + inputs: { + question: "What is the capital of France?", + context: "The capital of France is Paris.", + }, + }) + ).toMatchObject({ + answer: "Paris", + score: expect.any(Number), + start: expect.any(Number), + end: expect.any(Number), + }); }); - }); - // Errors with "Error: If you are using a VisionEncoderDecoderModel, you must provide a feature extractor" - it.skip("documentQuestionAnswering with non-array output", async () => { - expect( - await hf.documentQuestionAnswering({ - model: "naver-clova-ix/donut-base-finetuned-docvqa", - inputs: { - question: "Invoice number?", - image: new Blob([readTestFile("invoice.png")], { type: "image/png" }), - }, - }) - ).toMatchObject({ - answer: "us-001", + it("tableQuestionAnswering", async () => { + expect( + await hf.tableQuestionAnswering({ + model: "google/tapas-base-finetuned-wtq", + inputs: { + query: "How many stars does the transformers repository have?", + table: { + Repository: ["Transformers", "Datasets", "Tokenizers"], + Stars: ["36542", "4512", "3934"], + Contributors: ["651", "77", "34"], + "Programming language": ["Python", "Python", "Rust, Python and NodeJS"], + }, + }, + }) + ).toMatchObject({ + answer: "AVERAGE > 36542", + coordinates: [[0, 1]], + cells: ["36542"], + aggregator: "AVERAGE", + }); }); - }); - it("visualQuestionAnswering", async () => { - expect( - await hf.visualQuestionAnswering({ - model: "dandelin/vilt-b32-finetuned-vqa", - inputs: { - question: "How many cats are lying down?", - image: new Blob([readTestFile("cats.png")], { type: "image/png" }), - }, - }) - ).toMatchObject({ - answer: "2", - score: expect.any(Number), + it("documentQuestionAnswering", async () => { + expect( + await hf.documentQuestionAnswering({ + model: "impira/layoutlm-document-qa", + inputs: { + question: "Invoice number?", + image: new Blob([readTestFile("invoice.png")], { type: "image/png" }), + }, + }) + ).toMatchObject({ + answer: "us-001", + score: expect.any(Number), + // not sure what start/end refers to in this case + start: expect.any(Number), + end: expect.any(Number), + }); }); - }); - it("textClassification", async () => { - expect( - await hf.textClassification({ - model: "distilbert-base-uncased-finetuned-sst-2-english", - inputs: "I like you. I love you.", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - label: expect.any(String), - score: expect.any(Number), - }), - ]) - ); - }); + // Errors with "Error: If you are using a VisionEncoderDecoderModel, you must provide a feature extractor" + it.skip("documentQuestionAnswering with non-array output", async () => { + expect( + await hf.documentQuestionAnswering({ + model: "naver-clova-ix/donut-base-finetuned-docvqa", + inputs: { + question: "Invoice number?", + image: new Blob([readTestFile("invoice.png")], { type: "image/png" }), + }, + }) + ).toMatchObject({ + answer: "us-001", + }); + }); - it("textGeneration - gpt2", async () => { - expect( - await hf.textGeneration({ - model: "gpt2", - inputs: "The answer to the universe is", - }) - ).toMatchObject({ - generated_text: expect.any(String), + it("visualQuestionAnswering", async () => { + expect( + await hf.visualQuestionAnswering({ + model: "dandelin/vilt-b32-finetuned-vqa", + inputs: { + question: "How many cats are lying down?", + image: new Blob([readTestFile("cats.png")], { type: "image/png" }), + }, + }) + ).toMatchObject({ + answer: "2", + score: expect.any(Number), + }); }); - }); - it("textGeneration - openai-community/gpt2", async () => { - expect( - await hf.textGeneration({ - model: "openai-community/gpt2", - inputs: "The answer to the universe is", - }) - ).toMatchObject({ - generated_text: expect.any(String), + it("textClassification", async () => { + expect( + await hf.textClassification({ + model: "distilbert-base-uncased-finetuned-sst-2-english", + inputs: "I like you. I love you.", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + label: expect.any(String), + score: expect.any(Number), + }), + ]) + ); }); - }); - it("textGenerationStream - meta-llama/Llama-2-7b-hf", async () => { - const response = hf.textGenerationStream({ - model: "meta-llama/Llama-2-7b-hf", - inputs: "Please answer the following question: complete one two and ____.", - }); - - for await (const ret of response) { - expect(ret).toMatchObject({ - details: null, - index: expect.any(Number), - token: { - id: expect.any(Number), - logprob: expect.any(Number), - text: expect.any(String) || null, - special: expect.any(Boolean), - }, - generated_text: ret.generated_text - ? "Please answer the following question: complete one two and ____. How does the fish find its ____? After the fish is ________ how does it get to the shore?\n1. How do objects become super saturated bubbles?\n2. What resist limiting the movement of gas?" - : null, + it("textGeneration - gpt2", async () => { + expect( + await hf.textGeneration({ + model: "gpt2", + inputs: "The answer to the universe is", + }) + ).toMatchObject({ + generated_text: expect.any(String), }); - } - }); + }); - it("textGenerationStream - catch error", async () => { - const response = hf.textGenerationStream({ - model: "meta-llama/Llama-2-7b-hf", - inputs: "Write a short story about a robot that becomes sentient and takes over the world.", - parameters: { - max_new_tokens: 10_000, - }, + it("textGeneration - openai-community/gpt2", async () => { + expect( + await hf.textGeneration({ + model: "openai-community/gpt2", + inputs: "The answer to the universe is", + }) + ).toMatchObject({ + generated_text: expect.any(String), + }); }); - await expect(response.next()).rejects.toThrow( - "Input validation error: `inputs` tokens + `max_new_tokens` must be <= 8192. Given: 18 `inputs` tokens and 10000 `max_new_tokens`" - ); - }); + it("textGenerationStream - meta-llama/Llama-2-7b-hf", async () => { + const response = hf.textGenerationStream({ + model: "meta-llama/Llama-2-7b-hf", + inputs: "Please answer the following question: complete one two and ____.", + }); + + for await (const ret of response) { + expect(ret).toMatchObject({ + details: null, + index: expect.any(Number), + token: { + id: expect.any(Number), + logprob: expect.any(Number), + text: expect.any(String) || null, + special: expect.any(Boolean), + }, + generated_text: ret.generated_text + ? "Please answer the following question: complete one two and ____. How does the fish find its ____? After the fish is ________ how does it get to the shore?\n1. How do objects become super saturated bubbles?\n2. What resist limiting the movement of gas?" + : null, + }); + } + }); - it.skip("textGenerationStream - Abort", async () => { - const controller = new AbortController(); - const response = hf.textGenerationStream( - { - model: "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", - inputs: "Write an essay about Sartre's philosophy.", + it("textGenerationStream - catch error", async () => { + const response = hf.textGenerationStream({ + model: "meta-llama/Llama-2-7b-hf", + inputs: "Write a short story about a robot that becomes sentient and takes over the world.", parameters: { - max_new_tokens: 100, + max_new_tokens: 10_000, }, - }, - { signal: controller.signal } - ); - await expect(response.next()).resolves.toBeDefined(); - await expect(response.next()).resolves.toBeDefined(); - controller.abort(); - await expect(response.next()).rejects.toThrow("The operation was aborted"); - }); + }); - it("tokenClassification", async () => { - expect( - await hf.tokenClassification({ - model: "dbmdz/bert-large-cased-finetuned-conll03-english", - inputs: "My name is Sarah Jessica Parker but you can call me Jessica", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - entity_group: expect.any(String), - score: expect.any(Number), - word: expect.any(String), - start: expect.any(Number), - end: expect.any(Number), - }), - ]) - ); - }); + await expect(response.next()).rejects.toThrow( + "Input validation error: `inputs` tokens + `max_new_tokens` must be <= 8192. Given: 18 `inputs` tokens and 10000 `max_new_tokens`" + ); + }); + + it.skip("textGenerationStream - Abort", async () => { + const controller = new AbortController(); + const response = hf.textGenerationStream( + { + model: "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", + inputs: "Write an essay about Sartre's philosophy.", + parameters: { + max_new_tokens: 100, + }, + }, + { signal: controller.signal } + ); + await expect(response.next()).resolves.toBeDefined(); + await expect(response.next()).resolves.toBeDefined(); + controller.abort(); + await expect(response.next()).rejects.toThrow("The operation was aborted"); + }); - it("translation", async () => { - expect( - await hf.translation({ - model: "t5-base", - inputs: "My name is Wolfgang and I live in Berlin", - }) - ).toMatchObject({ - translation_text: "Mein Name ist Wolfgang und ich lebe in Berlin", - }); - // input is a list - expect( - await hf.translation({ - model: "t5-base", - inputs: ["My name is Wolfgang and I live in Berlin", "I work as programmer"], - }) - ).toMatchObject([ - { + it("tokenClassification", async () => { + expect( + await hf.tokenClassification({ + model: "dbmdz/bert-large-cased-finetuned-conll03-english", + inputs: "My name is Sarah Jessica Parker but you can call me Jessica", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + entity_group: expect.any(String), + score: expect.any(Number), + word: expect.any(String), + start: expect.any(Number), + end: expect.any(Number), + }), + ]) + ); + }); + + it("translation", async () => { + expect( + await hf.translation({ + model: "t5-base", + inputs: "My name is Wolfgang and I live in Berlin", + }) + ).toMatchObject({ translation_text: "Mein Name ist Wolfgang und ich lebe in Berlin", - }, - { - translation_text: "Ich arbeite als Programmierer", - }, - ]); - }); - it("zeroShotClassification", async () => { - expect( - await hf.zeroShotClassification({ - model: "facebook/bart-large-mnli", - inputs: [ - "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!", - ], - parameters: { candidate_labels: ["refund", "legal", "faq"] }, - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - sequence: + }); + // input is a list + expect( + await hf.translation({ + model: "t5-base", + inputs: ["My name is Wolfgang and I live in Berlin", "I work as programmer"], + }) + ).toMatchObject([ + { + translation_text: "Mein Name ist Wolfgang und ich lebe in Berlin", + }, + { + translation_text: "Ich arbeite als Programmierer", + }, + ]); + }); + it("zeroShotClassification", async () => { + expect( + await hf.zeroShotClassification({ + model: "facebook/bart-large-mnli", + inputs: [ "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!", - labels: ["refund", "faq", "legal"], - scores: [ - expect.closeTo(0.877787709236145, 5), - expect.closeTo(0.10522633045911789, 5), - expect.closeTo(0.01698593981564045, 5), ], - }), - ]) - ); - }); - it("SentenceSimilarity", async () => { - expect( - await hf.sentenceSimilarity({ - model: "sentence-transformers/paraphrase-xlm-r-multilingual-v1", - inputs: { - source_sentence: "That is a happy person", - sentences: ["That is a happy dog", "That is a very happy person", "Today is a sunny day"], - }, - }) - ).toEqual([expect.any(Number), expect.any(Number), expect.any(Number)]); - }); - it("FeatureExtraction", async () => { - const response = await hf.featureExtraction({ - model: "sentence-transformers/distilbert-base-nli-mean-tokens", - inputs: "That is a happy person", + parameters: { candidate_labels: ["refund", "legal", "faq"] }, + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + sequence: + "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!", + labels: ["refund", "faq", "legal"], + scores: [ + expect.closeTo(0.877787709236145, 5), + expect.closeTo(0.10522633045911789, 5), + expect.closeTo(0.01698593981564045, 5), + ], + }), + ]) + ); }); - expect(response).toEqual(expect.arrayContaining([expect.any(Number)])); - }); - it("FeatureExtraction - same model as sentence similarity", async () => { - const response = await hf.featureExtraction({ - model: "sentence-transformers/paraphrase-xlm-r-multilingual-v1", - inputs: "That is a happy person", + it("SentenceSimilarity", async () => { + expect( + await hf.sentenceSimilarity({ + model: "sentence-transformers/paraphrase-xlm-r-multilingual-v1", + inputs: { + source_sentence: "That is a happy person", + sentences: ["That is a happy dog", "That is a very happy person", "Today is a sunny day"], + }, + }) + ).toEqual([expect.any(Number), expect.any(Number), expect.any(Number)]); + }); + it("FeatureExtraction", async () => { + const response = await hf.featureExtraction({ + model: "sentence-transformers/distilbert-base-nli-mean-tokens", + inputs: "That is a happy person", + }); + expect(response).toEqual(expect.arrayContaining([expect.any(Number)])); }); + it("FeatureExtraction - same model as sentence similarity", async () => { + const response = await hf.featureExtraction({ + model: "sentence-transformers/paraphrase-xlm-r-multilingual-v1", + inputs: "That is a happy person", + }); - expect(response.length).toBeGreaterThan(10); - expect(response).toEqual(expect.arrayContaining([expect.any(Number)])); - }); - it("FeatureExtraction - facebook/bart-base", async () => { - const response = await hf.featureExtraction({ - model: "facebook/bart-base", - inputs: "That is a happy person", - }); - // 1x7x768 - expect(response).toEqual([ - [ - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - ], - ]); - }); - it("FeatureExtraction - facebook/bart-base, list input", async () => { - const response = await hf.featureExtraction({ - model: "facebook/bart-base", - inputs: ["hello", "That is a happy person"], - }); - // Nx1xTx768 - expect(response).toEqual([ - [ - [ - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - expect.arrayContaining([expect.any(Number)]), - ], - ], - [ + expect(response.length).toBeGreaterThan(10); + expect(response).toEqual(expect.arrayContaining([expect.any(Number)])); + }); + it("FeatureExtraction - facebook/bart-base", async () => { + const response = await hf.featureExtraction({ + model: "facebook/bart-base", + inputs: "That is a happy person", + }); + // 1x7x768 + expect(response).toEqual([ [ expect.arrayContaining([expect.any(Number)]), expect.arrayContaining([expect.any(Number)]), @@ -394,448 +370,489 @@ describe.concurrent( expect.arrayContaining([expect.any(Number)]), expect.arrayContaining([expect.any(Number)]), ], - ], - ]); - }); - it("automaticSpeechRecognition", async () => { - expect( - await hf.automaticSpeechRecognition({ - model: "facebook/wav2vec2-large-960h-lv60-self", - data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), - }) - ).toMatchObject({ - text: "GOING ALONG SLUSHY COUNTRY ROADS AND SPEAKING TO DAMP AUDIENCES IN DRAUGHTY SCHOOLROOMS DAY AFTER DAY FOR A FORTNIGHT HE'LL HAVE TO PUT IN AN APPEARANCE AT SOME PLACE OF WORSHIP ON SUNDAY MORNING AND HE CAN COME TO US IMMEDIATELY AFTERWARDS", + ]); + }); + it("FeatureExtraction - facebook/bart-base, list input", async () => { + const response = await hf.featureExtraction({ + model: "facebook/bart-base", + inputs: ["hello", "That is a happy person"], + }); + // Nx1xTx768 + expect(response).toEqual([ + [ + [ + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + ], + ], + [ + [ + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + expect.arrayContaining([expect.any(Number)]), + ], + ], + ]); + }); + it("automaticSpeechRecognition", async () => { + expect( + await hf.automaticSpeechRecognition({ + model: "facebook/wav2vec2-large-960h-lv60-self", + data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), + }) + ).toMatchObject({ + text: "GOING ALONG SLUSHY COUNTRY ROADS AND SPEAKING TO DAMP AUDIENCES IN DRAUGHTY SCHOOLROOMS DAY AFTER DAY FOR A FORTNIGHT HE'LL HAVE TO PUT IN AN APPEARANCE AT SOME PLACE OF WORSHIP ON SUNDAY MORNING AND HE CAN COME TO US IMMEDIATELY AFTERWARDS", + }); + }); + it("audioClassification", async () => { + expect( + await hf.audioClassification({ + model: "superb/hubert-large-superb-er", + data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + label: expect.any(String), + }), + ]) + ); }); - }); - it("audioClassification", async () => { - expect( - await hf.audioClassification({ - model: "superb/hubert-large-superb-er", - data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - score: expect.any(Number), - label: expect.any(String), - }), - ]) - ); - }); - it("audioToAudio", async () => { - expect( - await hf.audioToAudio({ - model: "speechbrain/sepformer-wham", - data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - label: expect.any(String), - blob: expect.any(String), - "content-type": expect.any(String), - }), - ]) - ); - }); + it("audioToAudio", async () => { + expect( + await hf.audioToAudio({ + model: "speechbrain/sepformer-wham", + data: new Blob([readTestFile("sample1.flac")], { type: "audio/flac" }), + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + label: expect.any(String), + blob: expect.any(String), + "content-type": expect.any(String), + }), + ]) + ); + }); - it("textToSpeech", async () => { - expect( - await hf.textToSpeech({ - model: "espnet/kan-bayashi_ljspeech_vits", - inputs: "hello there!", - }) - ).toBeInstanceOf(Blob); - }); + it("textToSpeech", async () => { + expect( + await hf.textToSpeech({ + model: "espnet/kan-bayashi_ljspeech_vits", + inputs: "hello there!", + }) + ).toBeInstanceOf(Blob); + }); - it("imageClassification", async () => { - expect( - await hf.imageClassification({ - data: new Blob([readTestFile("cheetah.png")], { type: "image/png" }), - model: "google/vit-base-patch16-224", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ - score: expect.any(Number), - label: expect.any(String), - }), - ]) - ); - }); + it("imageClassification", async () => { + expect( + await hf.imageClassification({ + data: new Blob([readTestFile("cheetah.png")], { type: "image/png" }), + model: "google/vit-base-patch16-224", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + label: expect.any(String), + }), + ]) + ); + }); - it("zeroShotImageClassification", async () => { - expect( - await hf.zeroShotImageClassification({ - inputs: { image: new Blob([readTestFile("cheetah.png")], { type: "image/png" }) }, - model: "openai/clip-vit-large-patch14-336", - parameters: { - candidate_labels: ["animal", "toy", "car"], + it("zeroShotImageClassification", async () => { + expect( + await hf.zeroShotImageClassification({ + inputs: { image: new Blob([readTestFile("cheetah.png")], { type: "image/png" }) }, + model: "openai/clip-vit-large-patch14-336", + parameters: { + candidate_labels: ["animal", "toy", "car"], + }, + }) + ).toEqual([ + { + label: "animal", + score: expect.any(Number), }, - }) - ).toEqual([ - { - label: "animal", - score: expect.any(Number), - }, - { - label: "car", - score: expect.any(Number), - }, - { - label: "toy", - score: expect.any(Number), - }, - ]); - }); - - it("objectDetection", async () => { - expect( - await hf.imageClassification({ - data: new Blob([readTestFile("cats.png")], { type: "image/png" }), - model: "facebook/detr-resnet-50", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ + { + label: "car", score: expect.any(Number), - label: expect.any(String), - box: expect.objectContaining({ - xmin: expect.any(Number), - ymin: expect.any(Number), - xmax: expect.any(Number), - ymax: expect.any(Number), - }), - }), - ]) - ); - }); - it("imageSegmentation", async () => { - expect( - await hf.imageClassification({ - data: new Blob([readTestFile("cats.png")], { type: "image/png" }), - model: "facebook/detr-resnet-50-panoptic", - }) - ).toEqual( - expect.arrayContaining([ - expect.objectContaining({ + }, + { + label: "toy", score: expect.any(Number), - label: expect.any(String), - mask: expect.any(String), - }), - ]) - ); - }); - it("imageToImage", async () => { - const num_inference_steps = 25; - - const res = await hf.imageToImage({ - inputs: new Blob([readTestFile("stormtrooper_depth.png")], { type: "image / png" }), - parameters: { - prompt: "elmo's lecture", - num_inference_steps, - }, - model: "lllyasviel/sd-controlnet-depth", - }); - expect(res).toBeInstanceOf(Blob); - }); - it("imageToImage blob data", async () => { - const res = await hf.imageToImage({ - inputs: new Blob([readTestFile("bird_canny.png")], { type: "image / png" }), - model: "lllyasviel/sd-controlnet-canny", + }, + ]); }); - expect(res).toBeInstanceOf(Blob); - }); - it("textToImage", async () => { - const res = await hf.textToImage({ - inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", - model: "stabilityai/stable-diffusion-2", + + it("objectDetection", async () => { + expect( + await hf.imageClassification({ + data: new Blob([readTestFile("cats.png")], { type: "image/png" }), + model: "facebook/detr-resnet-50", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + label: expect.any(String), + box: expect.objectContaining({ + xmin: expect.any(Number), + ymin: expect.any(Number), + xmax: expect.any(Number), + ymax: expect.any(Number), + }), + }), + ]) + ); }); - expect(res).toBeInstanceOf(Blob); - }); + it("imageSegmentation", async () => { + expect( + await hf.imageClassification({ + data: new Blob([readTestFile("cats.png")], { type: "image/png" }), + model: "facebook/detr-resnet-50-panoptic", + }) + ).toEqual( + expect.arrayContaining([ + expect.objectContaining({ + score: expect.any(Number), + label: expect.any(String), + mask: expect.any(String), + }), + ]) + ); + }); + it("imageToImage", async () => { + const num_inference_steps = 25; - it("textToImage with parameters", async () => { - const width = 512; - const height = 128; - const num_inference_steps = 10; - - const res = await hf.textToImage({ - inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", - model: "stabilityai/stable-diffusion-2", - parameters: { - negative_prompt: "blurry", - width, - height, - num_inference_steps, - }, - }); - expect(res).toBeInstanceOf(Blob); - }); - it("imageToText", async () => { - expect( - await hf.imageToText({ - data: new Blob([readTestFile("cheetah.png")], { type: "image/png" }), - model: "nlpconnect/vit-gpt2-image-captioning", - }) - ).toEqual({ - generated_text: "a large brown and white giraffe standing in a field ", + const res = await hf.imageToImage({ + inputs: new Blob([readTestFile("stormtrooper_depth.png")], { type: "image / png" }), + parameters: { + prompt: "elmo's lecture", + num_inference_steps, + }, + model: "lllyasviel/sd-controlnet-depth", + }); + expect(res).toBeInstanceOf(Blob); + }); + it("imageToImage blob data", async () => { + const res = await hf.imageToImage({ + inputs: new Blob([readTestFile("bird_canny.png")], { type: "image / png" }), + model: "lllyasviel/sd-controlnet-canny", + }); + expect(res).toBeInstanceOf(Blob); + }); + it("textToImage", async () => { + const res = await hf.textToImage({ + inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", + model: "stabilityai/stable-diffusion-2", + }); + expect(res).toBeInstanceOf(Blob); }); - }); - it("request - openai-community/gpt2", async () => { - expect( - await hf.request({ - model: "openai-community/gpt2", - inputs: "one plus two equals", - }) - ).toMatchObject([ - { - generated_text: expect.any(String), - }, - ]); - }); - // Skipped at the moment because takes forever - it.skip("tabularRegression", async () => { - expect( - await hf.tabularRegression({ - model: "scikit-learn/Fish-Weight", - inputs: { - data: { - Height: ["11.52", "12.48", "12.3778"], - Length1: ["23.2", "24", "23.9"], - Length2: ["25.4", "26.3", "26.5"], - Length3: ["30", "31.2", "31.1"], - Species: ["Bream", "Bream", "Bream"], - Width: ["4.02", "4.3056", "4.6961"], - }, + it("textToImage with parameters", async () => { + const width = 512; + const height = 128; + const num_inference_steps = 10; + + const res = await hf.textToImage({ + inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", + model: "stabilityai/stable-diffusion-2", + parameters: { + negative_prompt: "blurry", + width, + height, + num_inference_steps, }, - }) - ).toMatchObject([270.5473526976245, 313.6843425638086, 328.3727133404402]); - }); + }); + expect(res).toBeInstanceOf(Blob); + }); + it("imageToText", async () => { + expect( + await hf.imageToText({ + data: new Blob([readTestFile("cheetah.png")], { type: "image/png" }), + model: "nlpconnect/vit-gpt2-image-captioning", + }) + ).toEqual({ + generated_text: "a large brown and white giraffe standing in a field ", + }); + }); + it("request - openai-community/gpt2", async () => { + expect( + await hf.request({ + model: "openai-community/gpt2", + inputs: "one plus two equals", + }) + ).toMatchObject([ + { + generated_text: expect.any(String), + }, + ]); + }); - // Skipped at the moment because takes forever - it.skip("tabularClassification", async () => { - expect( - await hf.tabularClassification({ - model: "vvmnnnkv/wine-quality", - inputs: { - data: { - fixed_acidity: ["7.4", "7.8", "10.3"], - volatile_acidity: ["0.7", "0.88", "0.32"], - citric_acid: ["0", "0", "0.45"], - residual_sugar: ["1.9", "2.6", "6.4"], - chlorides: ["0.076", "0.098", "0.073"], - free_sulfur_dioxide: ["11", "25", "5"], - total_sulfur_dioxide: ["34", "67", "13"], - density: ["0.9978", "0.9968", "0.9976"], - pH: ["3.51", "3.2", "3.23"], - sulphates: ["0.56", "0.68", "0.82"], - alcohol: ["9.4", "9.8", "12.6"], + // Skipped at the moment because takes forever + it.skip("tabularRegression", async () => { + expect( + await hf.tabularRegression({ + model: "scikit-learn/Fish-Weight", + inputs: { + data: { + Height: ["11.52", "12.48", "12.3778"], + Length1: ["23.2", "24", "23.9"], + Length2: ["25.4", "26.3", "26.5"], + Length3: ["30", "31.2", "31.1"], + Species: ["Bream", "Bream", "Bream"], + Width: ["4.02", "4.3056", "4.6961"], + }, }, - }, - }) - ).toMatchObject([5, 5, 7]); - }); + }) + ).toMatchObject([270.5473526976245, 313.6843425638086, 328.3727133404402]); + }); - it("endpoint - makes request to specified endpoint", async () => { - const ep = hf.endpoint("https://api-inference.huggingface.co/models/openai-community/gpt2"); - const { generated_text } = await ep.textGeneration({ - inputs: "one plus two equals", + // Skipped at the moment because takes forever + it.skip("tabularClassification", async () => { + expect( + await hf.tabularClassification({ + model: "vvmnnnkv/wine-quality", + inputs: { + data: { + fixed_acidity: ["7.4", "7.8", "10.3"], + volatile_acidity: ["0.7", "0.88", "0.32"], + citric_acid: ["0", "0", "0.45"], + residual_sugar: ["1.9", "2.6", "6.4"], + chlorides: ["0.076", "0.098", "0.073"], + free_sulfur_dioxide: ["11", "25", "5"], + total_sulfur_dioxide: ["34", "67", "13"], + density: ["0.9978", "0.9968", "0.9976"], + pH: ["3.51", "3.2", "3.23"], + sulphates: ["0.56", "0.68", "0.82"], + alcohol: ["9.4", "9.8", "12.6"], + }, + }, + }) + ).toMatchObject([5, 5, 7]); }); - assert.include(generated_text, "three"); - }); - it("chatCompletion modelId - OpenAI Specs", async () => { - const res = await hf.chatCompletion({ - model: "mistralai/Mistral-7B-Instruct-v0.2", - messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }], - max_tokens: 500, - temperature: 0.1, - seed: 0, - }); - if (res.choices && res.choices.length > 0) { - const completion = res.choices[0].message?.content; - expect(completion).toContain("to two"); - } - }); + it("endpoint - makes request to specified endpoint", async () => { + const ep = hf.endpoint("https://api-inference.huggingface.co/models/openai-community/gpt2"); + const { generated_text } = await ep.textGeneration({ + inputs: "one plus two equals", + }); + assert.include(generated_text, "three"); + }); - it("chatCompletionStream modelId - OpenAI Specs", async () => { - const stream = hf.chatCompletionStream({ - model: "mistralai/Mistral-7B-Instruct-v0.2", - messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], - max_tokens: 500, - temperature: 0.1, - seed: 0, - }); - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + it("chatCompletion modelId - OpenAI Specs", async () => { + const res = await hf.chatCompletion({ + model: "mistralai/Mistral-7B-Instruct-v0.2", + messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }], + max_tokens: 500, + temperature: 0.1, + seed: 0, + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("to two"); } - } - expect(out).toContain("2"); - }); + }); - it("chatCompletionStream modelId Fail - OpenAI Specs", async () => { - expect( - hf - .chatCompletionStream({ - model: "google/gemma-2b", - messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], - max_tokens: 500, - temperature: 0.1, - seed: 0, - }) - .next() - ).rejects.toThrowError( - "Server google/gemma-2b does not seem to support chat completion. Error: Template error: template not found" - ); - }); + it("chatCompletionStream modelId - OpenAI Specs", async () => { + const stream = hf.chatCompletionStream({ + model: "mistralai/Mistral-7B-Instruct-v0.2", + messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], + max_tokens: 500, + temperature: 0.1, + seed: 0, + }); + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } + expect(out).toContain("2"); + }); - it("chatCompletion - OpenAI Specs", async () => { - const ep = hf.endpoint("https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"); - const res = await ep.chatCompletion({ - model: "tgi", - messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }], - max_tokens: 500, - temperature: 0.1, - seed: 0, - }); - if (res.choices && res.choices.length > 0) { - const completion = res.choices[0].message?.content; - expect(completion).toContain("to two"); - } - }); - it("chatCompletionStream - OpenAI Specs", async () => { - const ep = hf.endpoint("https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"); - const stream = ep.chatCompletionStream({ - model: "tgi", - messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], - max_tokens: 500, - temperature: 0.1, - seed: 0, - }); - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + it("chatCompletionStream modelId Fail - OpenAI Specs", async () => { + expect( + hf + .chatCompletionStream({ + model: "google/gemma-2b", + messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], + max_tokens: 500, + temperature: 0.1, + seed: 0, + }) + .next() + ).rejects.toThrowError( + "Server google/gemma-2b does not seem to support chat completion. Error: Template error: template not found" + ); + }); + + it("chatCompletion - OpenAI Specs", async () => { + const ep = hf.endpoint("https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"); + const res = await ep.chatCompletion({ + model: "tgi", + messages: [{ role: "user", content: "Complete the this sentence with words one plus one is equal " }], + max_tokens: 500, + temperature: 0.1, + seed: 0, + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("to two"); } - } - expect(out).toContain("2"); - }); - it("custom mistral - OpenAI Specs", async () => { - const MISTRAL_KEY = env.MISTRAL_KEY; - const hf = new HfInference(MISTRAL_KEY); - const ep = hf.endpoint("https://api.mistral.ai"); - const stream = ep.chatCompletionStream({ - model: "mistral-tiny", - messages: [{ role: "user", content: "Complete the equation one + one = , just the answer" }], - }) as AsyncGenerator; - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + }); + it("chatCompletionStream - OpenAI Specs", async () => { + const ep = hf.endpoint("https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"); + const stream = ep.chatCompletionStream({ + model: "tgi", + messages: [{ role: "user", content: "Complete the equation 1+1= ,just the answer" }], + max_tokens: 500, + temperature: 0.1, + seed: 0, + }); + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } } - } - expect(out).toContain("The answer to the equation one + one is two."); - }); - it("custom openai - OpenAI Specs", async () => { - const OPENAI_KEY = env.OPENAI_KEY; - const hf = new HfInference(OPENAI_KEY); - const ep = hf.endpoint("https://api.openai.com"); - const stream = ep.chatCompletionStream({ - model: "gpt-3.5-turbo", - messages: [{ role: "user", content: "Complete the equation one + one =" }], - }) as AsyncGenerator; - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + expect(out).toContain("2"); + }); + it("custom mistral - OpenAI Specs", async () => { + const MISTRAL_KEY = env.MISTRAL_KEY; + const hf = new HfInference(MISTRAL_KEY); + const ep = hf.endpoint("https://api.mistral.ai"); + const stream = ep.chatCompletionStream({ + model: "mistral-tiny", + messages: [{ role: "user", content: "Complete the equation one + one = , just the answer" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } } - } - expect(out).toContain("two"); - }); + expect(out).toContain("The answer to the equation one + one is two."); + }); + it("custom openai - OpenAI Specs", async () => { + const OPENAI_KEY = env.OPENAI_KEY; + const hf = new HfInference(OPENAI_KEY); + const ep = hf.endpoint("https://api.openai.com"); + const stream = ep.chatCompletionStream({ + model: "gpt-3.5-turbo", + messages: [{ role: "user", content: "Complete the equation one + one =" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } + expect(out).toContain("two"); + }); - /** - * Compatibility with third-party Inference Providers - */ - - it("chatCompletion sambanova", async () => { - const hf = new HfInference(env.SAMBANOVA_KEY); - const res = await hf.chatCompletion({ - model: "meta-llama/Llama-3.1-8B-Instruct", - provider: "sambanova", - messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], - }); - if (res.choices && res.choices.length > 0) { - const completion = res.choices[0].message?.content; - expect(completion).toContain("two"); - } }); - it("chatCompletion sambanova stream", async () => { - const hf = new HfInference(env.SAMBANOVA_KEY); - const stream = hf.chatCompletionStream({ - model: "meta-llama/Llama-3.1-8B-Instruct", - provider: "sambanova", - messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], - }) as AsyncGenerator; - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + /** + * Compatibility with third-party Inference Providers + */ + describe.concurrent("SambaNova", () => { + const client = new HfInference(env.HF_SAMBANOVA_KEY); + + it("chatCompletion sambanova", async () => { + const res = await client.chatCompletion({ + model: "meta-llama/Llama-3.1-8B-Instruct", + provider: "sambanova", + messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("two"); } - } - expect(out).toContain("2"); + }); + it("chatCompletion sambanova stream", async () => { + const stream = client.chatCompletionStream({ + model: "meta-llama/Llama-3.1-8B-Instruct", + provider: "sambanova", + messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } + expect(out).toContain("2"); + }); }); - it("chatCompletion together", async () => { - const hf = new HfInference(env.TOGETHER_KEY); - const res = await hf.chatCompletion({ - model: "meta-llama/Llama-3.3-70B-Instruct", - provider: "together", - messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], - }); - if (res.choices && res.choices.length > 0) { - const completion = res.choices[0].message?.content; - expect(completion).toContain("two"); - } - }); - it("chatCompletion together stream", async () => { - const hf = new HfInference(env.TOGETHER_KEY); - const stream = hf.chatCompletionStream({ - model: "meta-llama/Llama-3.3-70B-Instruct", - provider: "together", - messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], - }) as AsyncGenerator; - let out = ""; - for await (const chunk of stream) { - if (chunk.choices && chunk.choices.length > 0) { - out += chunk.choices[0].delta.content; + describe.concurrent("Together", () => { + const client = new HfInference(env.HF_TOGETHER_KEY); + + it("chatCompletion together", async () => { + const res = await client.chatCompletion({ + model: "meta-llama/Llama-3.3-70B-Instruct", + provider: "together", + messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], + }); + if (res.choices && res.choices.length > 0) { + const completion = res.choices[0].message?.content; + expect(completion).toContain("two"); } - } - expect(out).toContain("2"); - }); + }); - it("textToImage together", async () => { - const hf = new HfInference(env.TOGETHER_KEY); - const res = await hf.textToImage({ - model: "stabilityai/stable-diffusion-xl-base-1.0", - provider: "together", - inputs: "award winning high resolution photo of a giant tortoise", + it("chatCompletion together stream", async () => { + const stream = client.chatCompletionStream({ + model: "meta-llama/Llama-3.3-70B-Instruct", + provider: "together", + messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], + }) as AsyncGenerator; + let out = ""; + for await (const chunk of stream) { + if (chunk.choices && chunk.choices.length > 0) { + out += chunk.choices[0].delta.content; + } + } + expect(out).toContain("2"); }); - expect(res).toBeInstanceOf(Blob); - }); - it("textToImage replicate", async () => { - const hf = new HfInference(env.REPLICATE_KEY); - const res = await hf.textToImage({ - model: "black-forest-labs/FLUX.1-schnell", - provider: "replicate", - inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + it("textToImage together", async () => { + const res = await client.textToImage({ + model: "stabilityai/stable-diffusion-xl-base-1.0", + provider: "together", + inputs: "award winning high resolution photo of a giant tortoise", + }); + expect(res).toBeInstanceOf(Blob); + }); + }) + + + describe.concurrent("Replicate", () => { + const client = new HfInference(env.HF_REPLICATE_KEY); + + it("textToImage replicate", async () => { + const res = await client.textToImage({ + model: "black-forest-labs/FLUX.1-schnell", + provider: "replicate", + inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + }); + expect(res).toBeInstanceOf(Blob); }); - expect(res).toBeInstanceOf(Blob); }); + + describe.concurrent("Fal.ai", () => { + it("TODO", async () => { + fail("Not implemented"); + }) + }) + }, TIMEOUT ); diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index e1bd7213a..ee7d42f00 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2103,5 +2103,197 @@ "vary": "origin, Origin, Access-Control-Request-Method, Access-Control-Request-Headers" } } + }, + "a71d846134d1c5d86b435b541f5291a2d020c081b5b5700bcfdaec7ed40fd3fe": { + "url": "https://api.sambanova.ai/v1/chat/completions", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation 1 + 1 = , just the answer\"}],\"stream\":true}" + }, + "response": { + "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"2\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"\"},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: [DONE]\n\n", + "status": 200, + "statusText": "OK", + "headers": { + "connection": "keep-alive", + "content-type": "text/event-stream; charset=utf-8", + "strict-transport-security": "max-age=31536000; includeSubDomains", + "transfer-encoding": "chunked" + } + } + }, + "56dc8b91ae3bf6ebcf7580cf90b65377ba6cc9b04d446fa9abc40ba04a45d5d8": { + "url": "https://api.sambanova.ai/v1/chat/completions", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete this sentence with words, one plus one is equal \"}]}" + }, + "response": { + "body": "{\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"two.\",\"role\":\"assistant\"}}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion\",\"system_fingerprint\":\"fastcoe\",\"usage\":{\"completion_tokens\":2,\"completion_tokens_after_first_per_sec\":39.91116270660665,\"completion_tokens_after_first_per_sec_first_ten\":0,\"completion_tokens_per_sec\":30.031067085285915,\"end_time\":1736268936.542338,\"is_last_response\":true,\"prompt_tokens\":46,\"start_time\":1736268936.4757402,\"time_to_first_token\":0.04154205322265625,\"total_latency\":0.06659770011901855,\"total_tokens\":48,\"total_tokens_per_sec\":720.745610046862}}", + "status": 200, + "statusText": "OK", + "headers": { + "connection": "keep-alive", + "content-type": "application/json; charset=utf-8", + "strict-transport-security": "max-age=31536000; includeSubDomains" + } + } + }, + "d5c6752ccee8b53c65bbdbcc128358f9c6604395431b7c33760f3c0c92224ff1": { + "url": "https://api.together.xyz/v1/chat/completions", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation 1 + 1 = , just the answer\"}],\"stream\":true}" + }, + "response": { + "body": "data: {\"id\":\"8fe57a1b9c05790f-CDG\",\"object\":\"chat.completion.chunk\",\"created\":1736268942,\"choices\":[{\"index\":0,\"text\":\"2\",\"logprobs\":null,\"finish_reason\":null,\"seed\":null,\"delta\":{\"token_id\":17,\"role\":\"assistant\",\"content\":\"2\",\"tool_calls\":null}}],\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"usage\":null}\n\ndata: 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"3f2ba6c12d2b4395ac48f453fefdfe523204fcbbf3194c393365856b0e7b5976": { + "url": "https://api.together.xyz/v1/chat/completions", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete this sentence with words, one plus one is equal \"}]}" + }, + "response": { + "body": "{\"id\":\"8fe57a1b9ec32285-CDG\",\"object\":\"chat.completion\",\"created\":1736268942,\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"prompt\":[],\"choices\":[{\"finish_reason\":\"eos\",\"seed\":14145416413182314000,\"logprobs\":null,\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"one plus one is equal to two.\",\"tool_calls\":[]}}],\"usage\":{\"prompt_tokens\":46,\"completion_tokens\":9,\"total_tokens\":55}}", + "status": 200, + "statusText": "OK", + "headers": { + "access-control-allow-origin": "*", + "alt-svc": "h3=\":443\"; ma=86400", + "cf-cache-status": "DYNAMIC", + "cf-ray": "8fe57a1b9ec32285-CDG", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json; charset=utf-8", + "etag": "W/\"20f-h5oiAOJ1mlXhypcOeryRaZ1VjzE\"", + "retry-after": "2", + "server": "cloudflare", + "strict-transport-security": "max-age=15552000; includeSubDomains", + "transfer-encoding": "chunked" + } + } + }, + "8a5598c99c52905e0282fa9fa45135396893a6f99f66ea1268e9a06b5190938d": { + "url": "https://api.together.xyz/v1/images/generations", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"stabilityai/stable-diffusion-xl-base-1.0\",\"inputs\":\"\",\"prompt\":\"award winning high resolution photo of a giant tortoise\",\"response_format\":\"base64\"}" + }, + "response": { + "body": 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ma=2592000", + "cache-control": "public,max-age=3600", + "cache-id": "PAR-8ec5b013", + "cache-status": "miss", + "content-type": "image/webp", + "etag": "\"3443b49212285bdd038a608321d139b5\"", + "last-modified": "Tue, 07 Jan 2025 16:55:53 GMT", + "server": "UploadServer" + } + } } } \ No newline at end of file From 884f931bd572c172906e4f1c4e7f0706f5617312 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 18:38:58 +0100 Subject: [PATCH 15/24] add sample for asr on fal --- .../tasks/audio/automaticSpeechRecognition.ts | 10 ++++++- packages/inference/test/HfInference.spec.ts | 25 +++++++++++++++--- packages/inference/test/sample2.wav | Bin 0 -> 3801644 bytes packages/inference/vitest.config.mts | 1 + 4 files changed, 32 insertions(+), 4 deletions(-) create mode 100644 packages/inference/test/sample2.wav diff --git a/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts b/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts index 600d5b6c7..2205dbd0c 100644 --- a/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts +++ b/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts @@ -1,5 +1,6 @@ import { InferenceOutputError } from "../../lib/InferenceOutputError"; -import type { BaseArgs, Options } from "../../types"; +import type { BaseArgs, Options, RequestArgs } from "../../types"; +import { base64FromBytes } from "../../utils/base64FromBytes"; import { request } from "../custom/request"; export type AutomaticSpeechRecognitionArgs = BaseArgs & { @@ -24,6 +25,13 @@ export async function automaticSpeechRecognition( args: AutomaticSpeechRecognitionArgs, options?: Options ): Promise { + + if (args.provider === "fal-ai") { + const contentType = args.data instanceof Blob ? args.data.type : "audio/mpeg"; + const base64audio = base64FromBytes(new Uint8Array(args.data instanceof ArrayBuffer ? args.data : await args.data.arrayBuffer())); + (args as RequestArgs & { audio_url: string }).audio_url = `data:${contentType};base64,${base64audio}`; + delete (args as RequestArgs & { data: unknown }).data; + } const res = await request(args, { ...options, taskHint: "automatic-speech-recognition", diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index b8d515572..4ebb2b2eb 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -847,9 +847,28 @@ describe.concurrent( }); }); - describe.concurrent("Fal.ai", () => { - it("TODO", async () => { - fail("Not implemented"); + describe.concurrent("Fal AI", () => { + const client = new HfInference(env.HF_FAL_KEY); + + it("textToImage fal-ai", async () => { + const res = await client.textToImage({ + model: "black-forest-labs/FLUX.1-schnell", + provider: "fal-ai", + inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + }); + expect(res).toBeInstanceOf(Blob); + }) + + /// Skipped because data url not supported? + it.skip("speechToText fal-ai", async () => { + const res = await client.automaticSpeechRecognition({ + model: "openai/whisper-large-v3", + provider: "fal-ai", + data: new Blob([readTestFile("sample2.wav")], { type: "audio/vnd.wav" }), + }); + expect(res).toMatchObject({ + text: "HE HAS GRAVE DOUBTS WHETHER SIR FREDERICK LEIGHTON'S WORK IS REALLY GREEK AFTER ALL AND CAN DISCOVER IN IT BUT LITTLE OF ROCKY ITHACA", + }); }) }) diff --git a/packages/inference/test/sample2.wav b/packages/inference/test/sample2.wav new file mode 100644 index 0000000000000000000000000000000000000000..13de116170c80fd7d9f546a048ffc255eaac2c5b GIT binary patch literal 3801644 zcma&P2mJP9`Tu_*Bb)4zT^U(f*<|mL$|xlwX&R{{goa4p5Fs)PMIvNmMA;=No9t02 zM859p|9rk*pW{B?*XO?b{{GH~&;6O#^*+z@IFIoHQX-bubuA!5I8w%E91)sRvUIW*zMQvHd-{-aR%CGVsukuc>bSwA&TC=upS)0){taZzb zYdpMv{j|KwG`!Z-gST{JDqeXi zUfJY_}zQKlrjR%_!HXCd{*kZ6{H@4uj z&H2t|e18*ux)Hy#;b4RRGTz5)tUp+f*IH+=)?m%S>VwsI{gnnQ4wmQLob!^r`#U&+kwA 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}) - /// Skipped because data url not supported? - it.skip("speechToText fal-ai", async () => { + it("speechToText fal-ai", async () => { const res = await client.automaticSpeechRecognition({ model: "openai/whisper-large-v3", provider: "fal-ai", diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index ee7d42f00..2ba839463 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2295,5 +2295,64 @@ "server": "UploadServer" } } + }, + "e899e1e68342175b37f496e4937a9d3d46b31d21d1df775a8f87f5e04039d437": { + "url": "https://fal.run/fal-ai/wizper", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST" + }, + "response": { + "body": "{\"detail\":\"Unsupported data URL\"}", + "status": 400, + "statusText": "Bad Request", + "headers": { + "connection": "keep-alive", + "content-type": "application/json", + "strict-transport-security": "max-age=31536000; includeSubDomains" + } + } + }, + "9601f6c473ad39ff6a83e74df8fa4061773a54df1aa4a2d931fb4c0d66fc86a8": { + "url": "https://fal.run/fal-ai/flux/schnell", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"inputs\":\"\",\"prompt\":\"black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot\",\"response_format\":\"base64\"}" + }, + "response": { + "body": "{\"images\":[{\"url\":\"https://fal.media/files/elephant/wFUOb8jzsw2n_sVIyXb00.png\",\"width\":1024,\"height\":768,\"content_type\":\"image/jpeg\"}],\"timings\":{\"inference\":0.35036514210514724},\"seed\":2233221953,\"has_nsfw_concepts\":[false],\"prompt\":\"black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot\"}", + "status": 200, + "statusText": "OK", + "headers": { + "connection": "keep-alive", + "content-type": "application/json", + "strict-transport-security": "max-age=31536000; includeSubDomains" + } + } + }, + "6a268d88e3bdf69614bc760519ab91be6a2ef7d60e80c754d4148cd4d68cb12e": { + "url": "https://fal.media/files/elephant/wFUOb8jzsw2n_sVIyXb00.png", + "init": {}, + "response": { + "body": "", + "status": 200, + "statusText": "OK", + "headers": { + "access-control-allow-headers": "*", + "access-control-allow-methods": "*", + "access-control-allow-origin": "*", + "access-control-max-age": "86400", + "cf-ray": "8fe5ba6d9b03d0aa-CDG", + "connection": "keep-alive", + "content-type": "image/jpeg", + "server": "cloudflare", + "vary": "Accept-Encoding" + } + } } } \ No newline at end of file From 01ccbf6ea0388ec158cc22e56f25a0da259854d7 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Tue, 7 Jan 2025 18:45:30 +0100 Subject: [PATCH 17/24] lint --- .../inference/src/lib/makeRequestOptions.ts | 10 ++++----- packages/inference/src/providers/fal-ai.ts | 4 ++-- .../tasks/audio/automaticSpeechRecognition.ts | 5 +++-- .../inference/src/tasks/custom/request.ts | 10 ++++----- packages/inference/test/HfInference.spec.ts | 22 +++++++++---------- 5 files changed, 24 insertions(+), 27 deletions(-) diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 0e5b6a620..8aac5bf41 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -126,7 +126,7 @@ export async function makeRequestOptions( throw new Error("Inference proxying is not implemented yet"); } else { switch (provider) { - case 'fal-ai': + case "fal-ai": return `${FAL_AI_API_BASE_URL}/${model}`; case "replicate": return `${REPLICATE_API_BASE_URL}/v1/models/${model}/predictions`; @@ -166,10 +166,10 @@ export async function makeRequestOptions( body: binary ? args.data : JSON.stringify({ - ...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" || provider === "fal-ai" - ? omit(otherArgs, "model") - : { ...otherArgs, model }), - }), + ...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" || provider === "fal-ai" + ? omit(otherArgs, "model") + : { ...otherArgs, model }), + }), ...(credentials ? { credentials } : undefined), signal: options?.signal, }; diff --git a/packages/inference/src/providers/fal-ai.ts b/packages/inference/src/providers/fal-ai.ts index 17951ca41..6d8f98386 100644 --- a/packages/inference/src/providers/fal-ai.ts +++ b/packages/inference/src/providers/fal-ai.ts @@ -1,6 +1,6 @@ import type { ModelId } from "../types"; -export const FAL_AI_API_BASE_URL = "https://fal.run" +export const FAL_AI_API_BASE_URL = "https://fal.run"; type FalAiId = string; @@ -10,4 +10,4 @@ export const FAL_AI_MODEL_IDS: Record = { "black-forest-labs/FLUX.1-Redux-dev": "fal-ai/flux/dev/redux", "openai/whisper-large-v3": "fal-ai/wizper", "TencentARC/PhotoMaker": "fal-ai/photomaker", -} \ No newline at end of file +}; diff --git a/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts b/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts index 2205dbd0c..c56090c08 100644 --- a/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts +++ b/packages/inference/src/tasks/audio/automaticSpeechRecognition.ts @@ -25,10 +25,11 @@ export async function automaticSpeechRecognition( args: AutomaticSpeechRecognitionArgs, options?: Options ): Promise { - if (args.provider === "fal-ai") { const contentType = args.data instanceof Blob ? args.data.type : "audio/mpeg"; - const base64audio = base64FromBytes(new Uint8Array(args.data instanceof ArrayBuffer ? args.data : await args.data.arrayBuffer())); + const base64audio = base64FromBytes( + new Uint8Array(args.data instanceof ArrayBuffer ? args.data : await args.data.arrayBuffer()) + ); (args as RequestArgs & { audio_url: string }).audio_url = `data:${contentType};base64,${base64audio}`; delete (args as RequestArgs & { data: unknown }).data; } diff --git a/packages/inference/src/tasks/custom/request.ts b/packages/inference/src/tasks/custom/request.ts index de25b8175..b6838c9d0 100644 --- a/packages/inference/src/tasks/custom/request.ts +++ b/packages/inference/src/tasks/custom/request.ts @@ -27,14 +27,12 @@ export async function request( if (!response.ok) { const contentType = response.headers.get("Content-Type"); - if ( - ["application/json", "application/problem+json"].some( - (ct) => contentType?.startsWith(ct) - ) - ) { + if (["application/json", "application/problem+json"].some((ct) => contentType?.startsWith(ct))) { const output = await response.json(); if ([400, 422, 404, 500].includes(response.status) && options?.chatCompletion) { - throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${JSON.stringify(output.error)}`); + throw new Error( + `Server ${args.model} does not seem to support chat completion. Error: ${JSON.stringify(output.error)}` + ); } if (output.error || output.detail) { throw new Error(JSON.stringify(output.error ?? output.detail)); diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 090e48402..cbab9e241 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -5,7 +5,6 @@ import type { ChatCompletionStreamOutput } from "@huggingface/tasks"; import { HfInference } from "../src"; import "./vcr"; import { readTestFile } from "./test-files"; -import { fail } from "assert"; const TIMEOUT = 60000 * 3; const env = import.meta.env; @@ -551,7 +550,8 @@ describe.concurrent( }); it("textToImage", async () => { const res = await hf.textToImage({ - inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", + inputs: + "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", model: "stabilityai/stable-diffusion-2", }); expect(res).toBeInstanceOf(Blob); @@ -563,7 +563,8 @@ describe.concurrent( const num_inference_steps = 10; const res = await hf.textToImage({ - inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", + inputs: + "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]", model: "stabilityai/stable-diffusion-2", parameters: { negative_prompt: "blurry", @@ -758,11 +759,10 @@ describe.concurrent( } expect(out).toContain("two"); }); - }); /** - * Compatibility with third-party Inference Providers - */ + * Compatibility with third-party Inference Providers + */ describe.concurrent("SambaNova", () => { const client = new HfInference(env.HF_SAMBANOVA_KEY); @@ -831,8 +831,7 @@ describe.concurrent( }); expect(res).toBeInstanceOf(Blob); }); - }) - + }); describe.concurrent("Replicate", () => { const client = new HfInference(env.HF_REPLICATE_KEY); @@ -857,7 +856,7 @@ describe.concurrent( inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", }); expect(res).toBeInstanceOf(Blob); - }) + }); it("speechToText fal-ai", async () => { const res = await client.automaticSpeechRecognition({ @@ -868,9 +867,8 @@ describe.concurrent( expect(res).toMatchObject({ text: "HE HAS GRAVE DOUBTS WHETHER SIR FREDERICK LEIGHTON'S WORK IS REALLY GREEK AFTER ALL AND CAN DISCOVER IN IT BUT LITTLE OF ROCKY ITHACA", }); - }) - }) - + }); + }); }, TIMEOUT ); From 104f672ee5cc5cce814185dc70bacf0670bad6b7 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Wed, 8 Jan 2025 11:04:26 +0100 Subject: [PATCH 18/24] fix test + update tapes --- packages/inference/test/HfInference.spec.ts | 5 ++--- packages/inference/test/tapes.json | 19 +++++++++++++++++++ 2 files changed, 21 insertions(+), 3 deletions(-) diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index cbab9e241..7a6840003 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -862,13 +862,12 @@ describe.concurrent( const res = await client.automaticSpeechRecognition({ model: "openai/whisper-large-v3", provider: "fal-ai", - data: new Blob([readTestFile("sample2.wav")], { type: "audio/vnd.wav" }), + data: new Blob([readTestFile("sample2.wav")], { type: "audio/x-wav" }), }); expect(res).toMatchObject({ - text: "HE HAS GRAVE DOUBTS WHETHER SIR FREDERICK LEIGHTON'S WORK IS REALLY GREEK AFTER ALL AND CAN DISCOVER IN IT BUT LITTLE OF ROCKY ITHACA", + text: "He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.", }); }); }); }, - TIMEOUT ); diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index 2ba839463..eb3b2e24d 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2354,5 +2354,24 @@ "vary": "Accept-Encoding" } } + }, + "a540c67dea61eb4a90fedc20699d4863b04fd61dca73756d1f31a09793307689": { + "url": "https://fal.run/fal-ai/wizper", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST" + }, + "response": { + "body": "{\"text\":\"He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.\",\"chunks\":[{\"timestamp\":[0.36,9.62],\"text\":\"He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.\"}]}", + "status": 200, + "statusText": "OK", + "headers": { + "connection": "keep-alive", + "content-type": "application/json", + "strict-transport-security": "max-age=31536000; includeSubDomains" + } + } } } \ No newline at end of file From 3528b7ca3bdb6e24b5b309611b8e051d77fa2299 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Wed, 8 Jan 2025 11:09:34 +0100 Subject: [PATCH 19/24] format + lint --- packages/inference/test/HfInference.spec.ts | 55 ++++++++++++++------- 1 file changed, 36 insertions(+), 19 deletions(-) diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 7a6840003..8b970bc17 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -13,12 +13,12 @@ if (!env.HF_TOKEN) { console.warn("Set HF_TOKEN in the env to run the tests for better rate limits"); } -describe.concurrent( - "HfInference", - () => { - // Individual tests can be ran without providing an api key, however running all tests without an api key will result in rate limiting error. +describe.concurrent("HfInference", () => { + // Individual tests can be ran without providing an api key, however running all tests without an api key will result in rate limiting error. - describe.concurrent("HF Inference", () => { + describe.concurrent( + "HF Inference", + () => { const hf = new HfInference(env.HF_TOKEN); it("throws error if model does not exist", () => { expect( @@ -759,11 +759,15 @@ describe.concurrent( } expect(out).toContain("two"); }); - }); - /** - * Compatibility with third-party Inference Providers - */ - describe.concurrent("SambaNova", () => { + }, + TIMEOUT + ); + /** + * Compatibility with third-party Inference Providers + */ + describe.concurrent( + "SambaNova", + () => { const client = new HfInference(env.HF_SAMBANOVA_KEY); it("chatCompletion sambanova", async () => { @@ -791,9 +795,13 @@ describe.concurrent( } expect(out).toContain("2"); }); - }); + }, + TIMEOUT + ); - describe.concurrent("Together", () => { + describe.concurrent( + "Together", + () => { const client = new HfInference(env.HF_TOGETHER_KEY); it("chatCompletion together", async () => { @@ -831,9 +839,13 @@ describe.concurrent( }); expect(res).toBeInstanceOf(Blob); }); - }); + }, + TIMEOUT + ); - describe.concurrent("Replicate", () => { + describe.concurrent( + "Replicate", + () => { const client = new HfInference(env.HF_REPLICATE_KEY); it("textToImage replicate", async () => { @@ -844,9 +856,13 @@ describe.concurrent( }); expect(res).toBeInstanceOf(Blob); }); - }); + }, + TIMEOUT + ); - describe.concurrent("Fal AI", () => { + describe.concurrent( + "Fal AI", + () => { const client = new HfInference(env.HF_FAL_KEY); it("textToImage fal-ai", async () => { @@ -868,6 +884,7 @@ describe.concurrent( text: "He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.", }); }); - }); - }, -); + }, + TIMEOUT + ); +}); From 7e634bcfdc05c1f688996a052fb803dc9d500276 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Wed, 8 Jan 2025 15:04:47 +0100 Subject: [PATCH 20/24] tests tests tests --- .../inference/src/lib/makeRequestOptions.ts | 38 ++++--- packages/inference/src/providers/fal-ai.ts | 10 +- packages/inference/src/providers/replicate.ts | 16 +-- packages/inference/src/providers/sambanova.ts | 1 + packages/inference/src/providers/together.ts | 16 +-- .../inference/src/tasks/nlp/chatCompletion.ts | 4 - .../inference/src/tasks/nlp/textGeneration.ts | 52 +++++++-- packages/inference/test/HfInference.spec.ts | 105 ++++++++++-------- packages/inference/test/tapes.json | 30 +++++ 9 files changed, 178 insertions(+), 94 deletions(-) diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 8aac5bf41..0f79b0db0 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -66,22 +66,27 @@ export async function makeRequestOptions( if (!accessToken) { throw new Error("Specifying an Inference provider requires an accessToken"); } - switch (provider) { - case "replicate": - model = REPLICATE_MODEL_IDS[model] ?? model; - break; - case "sambanova": - model = SAMBANOVA_MODEL_IDS[model] ?? model; - break; - case "together": - model = TOGETHER_MODEL_IDS[model]?.id ?? model; - break; - case "fal-ai": - model = FAL_AI_MODEL_IDS[model] ?? model; - break; - default: - break; + + const modelId = (() => { + switch (provider) { + case "replicate": + return REPLICATE_MODEL_IDS[model]; + case "sambanova": + return SAMBANOVA_MODEL_IDS[model]; + case "together": + return TOGETHER_MODEL_IDS[model]?.id; + case "fal-ai": + return FAL_AI_MODEL_IDS[model]; + default: + return model; + } + })(); + + if (!modelId) { + throw new Error(`Model ${model} is not supported for provider ${provider}`); } + + model = modelId; } const binary = "data" in args && !!args.data; @@ -149,6 +154,9 @@ export async function makeRequestOptions( if (chatCompletion && !url.endsWith("/chat/completions")) { url += "/v1/chat/completions"; } + if (provider === "together" && taskHint === "text-generation" && !chatCompletion) { + url += "/v1/completions"; + } /** * For edge runtimes, leave 'credentials' undefined, otherwise cloudflare workers will error diff --git a/packages/inference/src/providers/fal-ai.ts b/packages/inference/src/providers/fal-ai.ts index 6d8f98386..2639bf5d1 100644 --- a/packages/inference/src/providers/fal-ai.ts +++ b/packages/inference/src/providers/fal-ai.ts @@ -4,10 +4,14 @@ export const FAL_AI_API_BASE_URL = "https://fal.run"; type FalAiId = string; +/** + * Mapping from HF model ID -> fal.ai app id + */ export const FAL_AI_MODEL_IDS: Record = { + /** text-to-image */ "black-forest-labs/FLUX.1-schnell": "fal-ai/flux/schnell", "black-forest-labs/FLUX.1-dev": "fal-ai/flux/dev", - "black-forest-labs/FLUX.1-Redux-dev": "fal-ai/flux/dev/redux", - "openai/whisper-large-v3": "fal-ai/wizper", - "TencentARC/PhotoMaker": "fal-ai/photomaker", + + /** automatic-speech-recognition */ + "openai/whisper-large-v3": "fal-ai/whisper", }; diff --git a/packages/inference/src/providers/replicate.ts b/packages/inference/src/providers/replicate.ts index 44fc2cda4..9b19dad46 100644 --- a/packages/inference/src/providers/replicate.ts +++ b/packages/inference/src/providers/replicate.ts @@ -2,20 +2,20 @@ import type { ModelId } from "../types"; export const REPLICATE_API_BASE_URL = "https://api.replicate.com"; -/** - * Same comment as in sambanova.ts - */ type ReplicateId = string; /** + * Mapping from HF model ID -> Replicate model ID + * + * Available models can be fetched with: + * ``` * curl -s \ - * -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ - * https://api.replicate.com/v1/models + * -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ + * 'https://api.replicate.com/v1/models' + * ``` */ export const REPLICATE_MODEL_IDS: Record = { + /** text-to-image */ "black-forest-labs/FLUX.1-schnell": "black-forest-labs/flux-schnell", "ByteDance/SDXL-Lightning": "bytedance/sdxl-lightning-4step", - "meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct", - "meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct", - "meta-llama/Meta-Llama-3.1-405B-Instruct": "meta/meta-llama-3.1-405b-instruct", }; diff --git a/packages/inference/src/providers/sambanova.ts b/packages/inference/src/providers/sambanova.ts index 7b4722e3e..745f7b51f 100644 --- a/packages/inference/src/providers/sambanova.ts +++ b/packages/inference/src/providers/sambanova.ts @@ -16,6 +16,7 @@ type SambanovaId = string; * https://community.sambanova.ai/t/supported-models/193 */ export const SAMBANOVA_MODEL_IDS: Record = { + /** Chat completion / conversational */ "Qwen/Qwen2.5-Coder-32B-Instruct": "Qwen2.5-Coder-32B-Instruct", "Qwen/Qwen2.5-72B-Instruct": "Qwen2.5-72B-Instruct", "Qwen/QwQ-32B-Preview": "QwQ-32B-Preview", diff --git a/packages/inference/src/providers/together.ts b/packages/inference/src/providers/together.ts index 47627678c..799b98637 100644 --- a/packages/inference/src/providers/together.ts +++ b/packages/inference/src/providers/together.ts @@ -14,12 +14,15 @@ export const TOGETHER_MODEL_IDS: Record< ModelId, { id: TogetherId; type: "chat" | "embedding" | "image" | "language" | "moderation" } > = { - "BAAI/bge-base-en-v1.5": { id: "BAAI/bge-base-en-v1.5", type: "embedding" }, + /** text-to-image */ "black-forest-labs/FLUX.1-Canny-dev": { id: "black-forest-labs/FLUX.1-canny", type: "image" }, "black-forest-labs/FLUX.1-Depth-dev": { id: "black-forest-labs/FLUX.1-depth", type: "image" }, "black-forest-labs/FLUX.1-dev": { id: "black-forest-labs/FLUX.1-dev", type: "image" }, "black-forest-labs/FLUX.1-Redux-dev": { id: "black-forest-labs/FLUX.1-redux", type: "image" }, "black-forest-labs/FLUX.1-schnell": { id: "black-forest-labs/FLUX.1-pro", type: "image" }, + "stabilityai/stable-diffusion-xl-base-1.0": { id: "stabilityai/stable-diffusion-xl-base-1.0", type: "image" }, + + /** chat completion */ "databricks/dbrx-instruct": { id: "databricks/dbrx-instruct", type: "chat" }, "deepseek-ai/deepseek-llm-67b-chat": { id: "deepseek-ai/deepseek-llm-67b-chat", type: "chat" }, "google/gemma-2-9b-it": { id: "google/gemma-2-9b-it", type: "chat" }, @@ -32,10 +35,7 @@ export const TOGETHER_MODEL_IDS: Record< "meta-llama/Llama-3.2-3B-Instruct": { id: "meta-llama/Llama-3.2-3B-Instruct-Turbo", type: "chat" }, "meta-llama/Llama-3.2-90B-Vision-Instruct": { id: "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo", type: "chat" }, "meta-llama/Llama-3.3-70B-Instruct": { id: "meta-llama/Llama-3.3-70B-Instruct-Turbo", type: "chat" }, - "meta-llama/Llama-Guard-3-11B-Vision": { id: "meta-llama/Llama-Guard-3-11B-Vision-Turbo", type: "moderation" }, - "meta-llama/LlamaGuard-7b": { id: "Meta-Llama/Llama-Guard-7b", type: "moderation" }, "meta-llama/Meta-Llama-3-70B-Instruct": { id: "meta-llama/Llama-3-70b-chat-hf", type: "chat" }, - "meta-llama/Meta-Llama-3-8B": { id: "meta-llama/Meta-Llama-3-8B", type: "language" }, "meta-llama/Meta-Llama-3-8B-Instruct": { id: "togethercomputer/Llama-3-8b-chat-hf-int4", type: "chat" }, "meta-llama/Meta-Llama-3.1-405B-Instruct": { id: "meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo", type: "chat" }, "meta-llama/Meta-Llama-3.1-70B-Instruct": { id: "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo", type: "chat" }, @@ -44,7 +44,6 @@ export const TOGETHER_MODEL_IDS: Record< "mistralai/Mistral-7B-Instruct-v0.3": { id: "mistralai/Mistral-7B-Instruct-v0.3", type: "chat" }, "mistralai/Mixtral-8x22B-Instruct-v0.1": { id: "mistralai/Mixtral-8x22B-Instruct-v0.1", type: "chat" }, "mistralai/Mixtral-8x7B-Instruct-v0.1": { id: "mistralai/Mixtral-8x7B-Instruct-v0.1", type: "chat" }, - "mistralai/Mixtral-8x7B-v0.1": { id: "mistralai/Mixtral-8x7B-v0.1", type: "language" }, "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO": { id: "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", type: "chat" }, "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF": { id: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF", type: "chat" }, "Qwen/Qwen2-72B-Instruct": { id: "Qwen/Qwen2-72B-Instruct", type: "chat" }, @@ -54,7 +53,8 @@ export const TOGETHER_MODEL_IDS: Record< "Qwen/QwQ-32B-Preview": { id: "Qwen/QwQ-32B-Preview", type: "chat" }, "scb10x/llama-3-typhoon-v1.5-8b-instruct": { id: "scb10x/scb10x-llama3-typhoon-v1-5-8b-instruct", type: "chat" }, "scb10x/llama-3-typhoon-v1.5x-70b-instruct-awq": { id: "scb10x/scb10x-llama3-typhoon-v1-5x-4f316", type: "chat" }, - "stabilityai/stable-diffusion-xl-base-1.0": { id: "stabilityai/stable-diffusion-xl-base-1.0", type: "image" }, - "togethercomputer/m2-bert-80M-32k-retrieval": { id: "togethercomputer/m2-bert-80M-32k-retrieval", type: "embedding" }, - "togethercomputer/m2-bert-80M-8k-retrieval": { id: "togethercomputer/m2-bert-80M-8k-retrieval", type: "embedding" }, + + /** text-generation */ + "meta-llama/Meta-Llama-3-8B": { id: "meta-llama/Meta-Llama-3-8B", type: "language" }, + "mistralai/Mixtral-8x7B-v0.1": { id: "mistralai/Mixtral-8x7B-v0.1", type: "language" }, }; diff --git a/packages/inference/src/tasks/nlp/chatCompletion.ts b/packages/inference/src/tasks/nlp/chatCompletion.ts index 2beed08d2..740362095 100644 --- a/packages/inference/src/tasks/nlp/chatCompletion.ts +++ b/packages/inference/src/tasks/nlp/chatCompletion.ts @@ -6,14 +6,10 @@ import type { ChatCompletionInput, ChatCompletionOutput } from "@huggingface/tas /** * Use the chat completion endpoint to generate a response to a prompt, using OpenAI message completion API no stream */ - export async function chatCompletion( args: BaseArgs & ChatCompletionInput, options?: Options ): Promise { - if (args.provider === "replicate") { - throw new Error("Replicate does not support the chat completion API"); - } const res = await request(args, { ...options, taskHint: "text-generation", diff --git a/packages/inference/src/tasks/nlp/textGeneration.ts b/packages/inference/src/tasks/nlp/textGeneration.ts index bda33cee5..1b815c59d 100644 --- a/packages/inference/src/tasks/nlp/textGeneration.ts +++ b/packages/inference/src/tasks/nlp/textGeneration.ts @@ -1,4 +1,9 @@ -import type { TextGenerationInput, TextGenerationOutput } from "@huggingface/tasks"; +import type { + ChatCompletionOutput, + TextGenerationInput, + TextGenerationOutput, + TextGenerationOutputFinishReason, +} from "@huggingface/tasks"; import { InferenceOutputError } from "../../lib/InferenceOutputError"; import type { BaseArgs, Options } from "../../types"; import { toArray } from "../../utils/toArray"; @@ -6,6 +11,16 @@ import { request } from "../custom/request"; export type { TextGenerationInput, TextGenerationOutput }; +interface TogeteherTextCompletionOutput extends Omit { + choices: Array<{ + text: string; + finish_reason: TextGenerationOutputFinishReason; + seed: number; + logprobs: unknown; + index: number; + }>; +} + /** * Use to continue text from a prompt. This is a very generic task. Recommended model: gpt2 (it’s a simple model, but fun to play with). */ @@ -13,15 +28,34 @@ export async function textGeneration( args: BaseArgs & TextGenerationInput, options?: Options ): Promise { - const res = toArray( - await request(args, { + if (args.provider === "together") { + args.prompt = args.inputs; + const raw = await request(args, { ...options, taskHint: "text-generation", - }) - ); - const isValidOutput = Array.isArray(res) && res.every((x) => typeof x?.generated_text === "string"); - if (!isValidOutput) { - throw new InferenceOutputError("Expected Array<{generated_text: string}>"); + }); + const isValidOutput = + typeof raw === "object" && "choices" in raw && Array.isArray(raw?.choices) && typeof raw?.model === "string"; + if (!isValidOutput) { + throw new InferenceOutputError("Expected ChatCompletionOutput"); + } + const completion = raw.choices[0]; + return { + generated_text: completion.text, + }; + } else { + const res = toArray( + await request(args, { + ...options, + taskHint: "text-generation", + }) + ); + + const isValidOutput = + Array.isArray(res) && res.every((x) => "generated°text" in x && typeof x?.generated_text === "string"); + if (!isValidOutput) { + throw new InferenceOutputError("Expected Array<{generated_text: string}>"); + } + return (res as TextGenerationOutput[])?.[0]; } - return res?.[0]; } diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 8b970bc17..536e629e5 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -762,15 +762,60 @@ describe.concurrent("HfInference", () => { }, TIMEOUT ); + /** * Compatibility with third-party Inference Providers */ + describe.concurrent( + "Fal AI", + () => { + const client = new HfInference(env.HF_FAL_KEY); + + it("textToImage", async () => { + const res = await client.textToImage({ + model: "black-forest-labs/FLUX.1-schnell", + provider: "fal-ai", + inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + }); + expect(res).toBeInstanceOf(Blob); + }); + + it("speechToText", async () => { + const res = await client.automaticSpeechRecognition({ + model: "openai/whisper-large-v3", + provider: "fal-ai", + data: new Blob([readTestFile("sample2.wav")], { type: "audio/x-wav" }), + }); + expect(res).toMatchObject({ + text: "He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.", + }); + }); + }, + TIMEOUT + ); + + describe.concurrent( + "Replicate", + () => { + const client = new HfInference(env.HF_REPLICATE_KEY); + + it("textToImage", async () => { + const res = await client.textToImage({ + model: "black-forest-labs/FLUX.1-schnell", + provider: "replicate", + inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", + }); + expect(res).toBeInstanceOf(Blob); + }); + }, + TIMEOUT + ); describe.concurrent( "SambaNova", () => { const client = new HfInference(env.HF_SAMBANOVA_KEY); - it("chatCompletion sambanova", async () => { + it("chatCompletion", async () => { const res = await client.chatCompletion({ model: "meta-llama/Llama-3.1-8B-Instruct", provider: "sambanova", @@ -781,7 +826,7 @@ describe.concurrent("HfInference", () => { expect(completion).toContain("two"); } }); - it("chatCompletion sambanova stream", async () => { + it("chatCompletion stream", async () => { const stream = client.chatCompletionStream({ model: "meta-llama/Llama-3.1-8B-Instruct", provider: "sambanova", @@ -804,7 +849,7 @@ describe.concurrent("HfInference", () => { () => { const client = new HfInference(env.HF_TOGETHER_KEY); - it("chatCompletion together", async () => { + it("chatCompletion", async () => { const res = await client.chatCompletion({ model: "meta-llama/Llama-3.3-70B-Instruct", provider: "together", @@ -816,7 +861,7 @@ describe.concurrent("HfInference", () => { } }); - it("chatCompletion together stream", async () => { + it("chatCompletion stream", async () => { const stream = client.chatCompletionStream({ model: "meta-llama/Llama-3.3-70B-Instruct", provider: "together", @@ -831,7 +876,7 @@ describe.concurrent("HfInference", () => { expect(out).toContain("2"); }); - it("textToImage together", async () => { + it("textToImage", async () => { const res = await client.textToImage({ model: "stabilityai/stable-diffusion-xl-base-1.0", provider: "together", @@ -839,50 +884,16 @@ describe.concurrent("HfInference", () => { }); expect(res).toBeInstanceOf(Blob); }); - }, - TIMEOUT - ); - - describe.concurrent( - "Replicate", - () => { - const client = new HfInference(env.HF_REPLICATE_KEY); - - it("textToImage replicate", async () => { - const res = await client.textToImage({ - model: "black-forest-labs/FLUX.1-schnell", - provider: "replicate", - inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", - }); - expect(res).toBeInstanceOf(Blob); - }); - }, - TIMEOUT - ); - - describe.concurrent( - "Fal AI", - () => { - const client = new HfInference(env.HF_FAL_KEY); - - it("textToImage fal-ai", async () => { - const res = await client.textToImage({ - model: "black-forest-labs/FLUX.1-schnell", - provider: "fal-ai", - inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot", - }); - expect(res).toBeInstanceOf(Blob); - }); - it("speechToText fal-ai", async () => { - const res = await client.automaticSpeechRecognition({ - model: "openai/whisper-large-v3", - provider: "fal-ai", - data: new Blob([readTestFile("sample2.wav")], { type: "audio/x-wav" }), - }); - expect(res).toMatchObject({ - text: "He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.", + it("textGeneration", async () => { + const res = await client.textGeneration({ + model: "mistralai/Mixtral-8x7B-v0.1", + provider: "together", + inputs: "Paris is", + temperature: 0, + max_tokens: 10, }); + expect(res).toMatchObject({ generated_text: " a city of love, and it’s also" }); }); }, TIMEOUT diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index eb3b2e24d..818f5bba6 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2373,5 +2373,35 @@ "strict-transport-security": "max-age=31536000; includeSubDomains" } } + }, + "94570e88ad7c60f92805909dfb0fabe03255aaf65cee18cf7f92fc54fc42fc0e": { + "url": "https://api.together.xyz/v1/completions", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"mistralai/Mixtral-8x7B-v0.1\",\"inputs\":\"Paris is\",\"temperature\":0,\"max_tokens\":10,\"prompt\":\"Paris is\"}" + }, + "response": { + "body": "{\"id\":\"8fecbda15c7c9edf\",\"object\":\"text.completion\",\"created\":1736345108,\"model\":\"mistralai/Mixtral-8x7B-v0.1\",\"prompt\":[],\"choices\":[{\"text\":\" a city of love, and it’s also\",\"finish_reason\":\"length\",\"seed\":1271532905535955700,\"logprobs\":null,\"index\":0}],\"usage\":{\"prompt_tokens\":3,\"completion_tokens\":10,\"total_tokens\":13}}", + "status": 200, + "statusText": "OK", + "headers": { + "access-control-allow-origin": "*", + "alt-svc": "h3=\":443\"; ma=86400", + "cf-cache-status": "DYNAMIC", + "cf-ray": "8fecbda15c7c9edf-CDG", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json; charset=utf-8", + "etag": "W/\"1ad-uo8PAXdljcZOe4fdhbWeJUtsnsI\"", + "retry-after": "2", + "server": "cloudflare", + "strict-transport-security": "max-age=15552000; includeSubDomains", + "transfer-encoding": "chunked", + "vary": "Accept-Encoding" + } + } } } \ No newline at end of file From 3939438166fd7375c01673120bb32bcd66900e1b Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Wed, 8 Jan 2025 16:40:55 +0100 Subject: [PATCH 21/24] add dummy keys to secrets --- .github/workflows/test.yml | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 28a657d82..d7815aada 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -41,6 +41,10 @@ jobs: run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test env: HF_TOKEN: ${{ secrets.HF_TOKEN }} + HF_FAL_KEY: dummy + HF_REPLICATE_KEY: dummy + HF_SAMBANOVA_KEY: dummy + HF_TOGETHER_KEY: dummy browser: runs-on: ubuntu-latest @@ -77,6 +81,10 @@ jobs: run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test:browser env: HF_TOKEN: ${{ secrets.HF_TOKEN }} + HF_FAL_KEY: dummy + HF_REPLICATE_KEY: dummy + HF_SAMBANOVA_KEY: dummy + HF_TOGETHER_KEY: dummy e2e: runs-on: ubuntu-latest @@ -140,3 +148,7 @@ jobs: env: NPM_CONFIG_REGISTRY: http://localhost:4874/ HF_TOKEN: ${{ secrets.HF_TOKEN }} + HF_FAL_KEY: dummy + HF_REPLICATE_KEY: dummy + HF_SAMBANOVA_KEY: dummy + HF_TOGETHER_KEY: dummy From 1b71e5baddaa8bda663c30f0c806ebcedc8ec0ce Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Thu, 9 Jan 2025 12:27:01 +0100 Subject: [PATCH 22/24] update tests & tapes --- packages/inference/test/HfInference.spec.ts | 2 +- packages/inference/test/tapes.json | 162 +++++++++++++++++--- 2 files changed, 143 insertions(+), 21 deletions(-) diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 536e629e5..eddb670cc 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -787,7 +787,7 @@ describe.concurrent("HfInference", () => { data: new Blob([readTestFile("sample2.wav")], { type: "audio/x-wav" }), }); expect(res).toMatchObject({ - text: "He has grave doubts whether Sir Frederick Leighton's work is really Greek after all, and can discover in it but little of rocky Ithaca.", + text: " he has grave doubts whether sir frederick leighton's work is really greek after all and can discover in it but little of rocky ithaca", }); }); }, diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index 818f5bba6..ead83686d 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2114,7 +2114,7 @@ "body": "{\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation 1 + 1 = , just the answer\"}],\"stream\":true}" }, "response": { - "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"2\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"\"},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: [DONE]\n\n", + "body": "data: {\"choices\":[{\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736421953,\"id\":\"362592a1-7092-441d-9060-d54029fa34cc\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"2\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1736421953,\"id\":\"362592a1-7092-441d-9060-d54029fa34cc\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\"\"},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1736421953,\"id\":\"362592a1-7092-441d-9060-d54029fa34cc\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion.chunk\",\"system_fingerprint\":\"fastcoe\"}\n\ndata: [DONE]\n\n", "status": 200, "statusText": "OK", "headers": { @@ -2135,7 +2135,7 @@ "body": "{\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete this sentence with words, one plus one is equal \"}]}" }, "response": { - "body": "{\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"two.\",\"role\":\"assistant\"}}],\"created\":1736268936,\"id\":\"9619241f-0e05-44f7-8f09-f8e0729b280c\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion\",\"system_fingerprint\":\"fastcoe\",\"usage\":{\"completion_tokens\":2,\"completion_tokens_after_first_per_sec\":39.91116270660665,\"completion_tokens_after_first_per_sec_first_ten\":0,\"completion_tokens_per_sec\":30.031067085285915,\"end_time\":1736268936.542338,\"is_last_response\":true,\"prompt_tokens\":46,\"start_time\":1736268936.4757402,\"time_to_first_token\":0.04154205322265625,\"total_latency\":0.06659770011901855,\"total_tokens\":48,\"total_tokens_per_sec\":720.745610046862}}", + "body": "{\"choices\":[{\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null,\"message\":{\"content\":\"two.\",\"role\":\"assistant\"}}],\"created\":1736421953,\"id\":\"4775a55a-47f9-4f95-80b1-40cf0fea22dd\",\"model\":\"Meta-Llama-3.1-8B-Instruct\",\"object\":\"chat.completion\",\"system_fingerprint\":\"fastcoe\",\"usage\":{\"completion_tokens\":2,\"completion_tokens_after_first_per_sec\":46.71705594724942,\"completion_tokens_after_first_per_sec_first_ten\":0,\"completion_tokens_per_sec\":41.28231652403285,\"end_time\":1736421953.7856479,\"is_last_response\":true,\"prompt_tokens\":46,\"start_time\":1736421953.737201,\"time_to_first_token\":0.02704143524169922,\"total_latency\":0.0484468936920166,\"total_tokens\":48,\"total_tokens_per_sec\":990.7755965767885}}", "status": 200, "statusText": "OK", "headers": { @@ -2155,7 +2155,7 @@ "body": "{\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation 1 + 1 = , just the answer\"}],\"stream\":true}" }, "response": { - "body": "data: {\"id\":\"8fe57a1b9c05790f-CDG\",\"object\":\"chat.completion.chunk\",\"created\":1736268942,\"choices\":[{\"index\":0,\"text\":\"2\",\"logprobs\":null,\"finish_reason\":null,\"seed\":null,\"delta\":{\"token_id\":17,\"role\":\"assistant\",\"content\":\"2\",\"tool_calls\":null}}],\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"usage\":null}\n\ndata: {\"id\":\"8fe57a1b9c05790f-CDG\",\"object\":\"chat.completion.chunk\",\"created\":1736268942,\"choices\":[{\"index\":0,\"text\":\"\",\"logprobs\":null,\"finish_reason\":\"eos\",\"seed\":13524445995620452000,\"delta\":{\"token_id\":128009,\"role\":\"assistant\",\"content\":\"\",\"tool_calls\":null}}],\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"usage\":{\"prompt_tokens\":48,\"completion_tokens\":2,\"total_tokens\":50}}\n\ndata: [DONE]\n\n", + "body": "data: {\"id\":\"8ff411e54b9299ab\",\"object\":\"chat.completion.chunk\",\"created\":1736421960,\"choices\":[{\"index\":0,\"text\":\"2\",\"logprobs\":null,\"finish_reason\":null,\"seed\":null,\"delta\":{\"token_id\":17,\"role\":\"assistant\",\"content\":\"2\",\"tool_calls\":null}}],\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"usage\":null}\n\ndata: {\"id\":\"8ff411e54b9299ab\",\"object\":\"chat.completion.chunk\",\"created\":1736421960,\"choices\":[{\"index\":0,\"text\":\"\",\"logprobs\":null,\"finish_reason\":\"eos\",\"seed\":9313781139405380000,\"delta\":{\"token_id\":128009,\"role\":\"assistant\",\"content\":\"\",\"tool_calls\":null}}],\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"usage\":{\"prompt_tokens\":48,\"completion_tokens\":2,\"total_tokens\":50}}\n\ndata: [DONE]\n\n", "status": 200, "statusText": "OK", "headers": { @@ -2163,13 +2163,14 @@ "alt-svc": "h3=\":443\"; ma=86400", "cache-control": "no-cache, no-transform", "cf-cache-status": "DYNAMIC", - "cf-ray": "8fe57a1b9c05790f-CDG", + "cf-ray": "8ff411e54b9299ab-CDG", "connection": "keep-alive", "content-type": "text/event-stream;charset=utf-8", "retry-after": "2", "server": "cloudflare", "strict-transport-security": "max-age=15552000; includeSubDomains", - "transfer-encoding": "chunked" + "transfer-encoding": "chunked", + "vary": "Accept-Encoding" } } }, @@ -2183,22 +2184,23 @@ "body": "{\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete this sentence with words, one plus one is equal \"}]}" }, "response": { - "body": "{\"id\":\"8fe57a1b9ec32285-CDG\",\"object\":\"chat.completion\",\"created\":1736268942,\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"prompt\":[],\"choices\":[{\"finish_reason\":\"eos\",\"seed\":14145416413182314000,\"logprobs\":null,\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"one plus one is equal to two.\",\"tool_calls\":[]}}],\"usage\":{\"prompt_tokens\":46,\"completion_tokens\":9,\"total_tokens\":55}}", + "body": "{\"id\":\"8ff411e54b88f1a4\",\"object\":\"chat.completion\",\"created\":1736421960,\"model\":\"meta-llama/Llama-3.3-70B-Instruct-Turbo\",\"prompt\":[],\"choices\":[{\"finish_reason\":\"eos\",\"seed\":14663482367758619000,\"logprobs\":null,\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"one plus one is equal to two.\",\"tool_calls\":[]}}],\"usage\":{\"prompt_tokens\":46,\"completion_tokens\":9,\"total_tokens\":55}}", "status": 200, "statusText": "OK", "headers": { "access-control-allow-origin": "*", "alt-svc": "h3=\":443\"; ma=86400", "cf-cache-status": "DYNAMIC", - "cf-ray": "8fe57a1b9ec32285-CDG", + "cf-ray": "8ff411e54b88f1a4-CDG", "connection": "keep-alive", "content-encoding": "gzip", "content-type": "application/json; charset=utf-8", - "etag": "W/\"20f-h5oiAOJ1mlXhypcOeryRaZ1VjzE\"", + "etag": "W/\"20b-G4IgxcOf8iEL5Ej0mMOCqo6dvAc\"", "retry-after": "2", "server": "cloudflare", "strict-transport-security": "max-age=15552000; includeSubDomains", - "transfer-encoding": "chunked" + "transfer-encoding": "chunked", + "vary": "Accept-Encoding" } } }, @@ -2212,18 +2214,18 @@ "body": "{\"model\":\"stabilityai/stable-diffusion-xl-base-1.0\",\"inputs\":\"\",\"prompt\":\"award winning high resolution photo of a giant tortoise\",\"response_format\":\"base64\"}" }, "response": { - "body": "{\"id\":\"8fe57a1b9decf0bb-CDG\",\"model\":\"stabilityai/stable-diffusion-xl-base-1.0\",\"object\":\"list\",\"data\":[{\"timings\":{\"inference\":4430},\"index\":0,\"b64_json\":\"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\"}]}", + "body": "{\"id\":\"8ff411e55ff1d6a2-CDG\",\"model\":\"stabilityai/stable-diffusion-xl-base-1.0\",\"object\":\"list\",\"data\":[{\"timings\":{\"inference\":4445},\"index\":0,\"b64_json\":\"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\"}]}", "status": 200, "statusText": "OK", "headers": { "access-control-allow-origin": "*", "alt-svc": "h3=\":443\"; ma=86400", "cf-cache-status": "DYNAMIC", - 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We divided it by product including both the number of additional members and the number of customers.\\n\\nSample product. Median ( Graves , Dead , Majestic ALE ): Minimum for war with an enemy on March 31, 1944; removed. White, Black baride = 0.75.\\n\\nCannot Be Substantiated\\n\\nIncidents of non-judicial executions can have validity when foreseen. Giving rise to reasonable doubt about outcomes, such cases can generally be generalized to range from governmental efforts to prevent or treat violations, violations of which can be assassinated or attempted assassinations, and the death penalty is used falsely as it would at present. Rehabilitation of the incarcerated is usually demonstrated in the form of parole at a reduction or partial release, or redemption after the scheduled termination of incarceration ( Svetlana, 1939 ; Morse , 1965 ). This is in --> cogent terms, because such movements can be accomplished through cases that are higher proof of proof than those that would be legitimate if the extraterritorial requirement of the Act were implemented.\\n\\nAdditionally, it is necessary to define the \\\"deadbeat\\\" foreigner and especially the \\\"Simian\\\" foreigner as the aborigines. It does not require that they be medically sound, since our customary taxonomy: \\\"animal(s)/Aries/Caribou (1) 1/1 (cat) & dwarf animal (antis[dialania]) Desert horsefly 2\\n\\nThis definition is used primarily to clarify solid charges of torture, because executing the presumed wartime detainee exhibits the following distinctive characteristics:\\n\\nPersuade an old layman that any prisoner of war treated human material rather than \\\"urb outrawing his-Capital% through kindness , eligeem toul! 1/i A fellow soldier serving under your authority , but failed to do so against what the befuddled British placed upon the latter. REGRET?S unreasonable POSITIONS are warranted under the humanitarian Requisites of importance and emlegation to every tyrant in order to honor his one year time graciously.\\n\\nj. Deteriorate over 8 years are local customary executions resulted from the Afghan semi-autonomous memory circuit in Afghanistan, or associated with counting the number of defendants. Other values may be high, but this could neither play a warlike meld well in handling timely new information or granting reckless probable cause.\\n\\n*TRIOL * Government-Bymited albeit political\\n\\nocassionate Kasady government.\\n\\n(History and Punishment, Chapter 27a, Council of Jewish Representatives Legally Daried November 12, 1848.)\\n\\nSVOURS No.25, striduliy (Federal edict), Charitable obligition.\\n\\nmind, body, organs, name of every intentional minor surrounded by invalidemizes the attainment of the universal subjective understanding that non-civilians are and have always been a \\\"spontaneous being\\\" deemed undesirable by God. Estate Tax forbade Indians, Whites, and Celestials to judge impure...and they could not do so because if they were insulted they would not have such locality effect. Paragraph 6 of the UDAT, Agencies for State and Further Assistance Clause, 384 U.S. 58-63 (Lokonda, Asiatic Rev.1987 given to officers of New York or shall be levied for .................. but will not be collected except this because of government knowassay should fall not on the second diagonal of jew.exe{lo). The income tax now instructs the hadishment body to collect it in the ninth year, nor speculation upon earnings, in profit or loss stock (punishment leased out); the doubtful admissions, unsupported by prisoners tied up in stationary five years; and the attunement to the principle of the Montesninthe negro of /bck{e Papa}. All helpers rely that one fortnight officers will probably under commission make the reasonable to arbitrary minimums and estimations to which listeners of, a population below a million, and below, 487 citizens and members thereof. It was supposed either to be non-mandatory, subject to Israel, with rains rising forth of harvest grounds, or otherwise, to oversee every desire caused by every prerogative but the question of price training to prove it, manipulated ( Lokonda , 1993 ), who just took the responsibility for the observance of promised, free labor. Thus a working day ended during the Sabbath to impudge Friday and Friday's to deputize. Institutional sanction suggested.\\n\\n(\\\"S.v Dr. and Mrs. Jolonaunder Dr. Pittsburgh School of Management, chosen . of Pennsylvania, 1944. . . ,\\\" Cel. Mystek 2: Bel. 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const isValidOutput = - Array.isArray(res) && res.every((x) => "generated°text" in x && typeof x?.generated_text === "string"); + Array.isArray(res) && res.every((x) => "generated_text" in x && typeof x?.generated_text === "string"); if (!isValidOutput) { throw new InferenceOutputError("Expected Array<{generated_text: string}>"); } From e3c5264aa1e6cdf8383353c9130273cf419223b6 Mon Sep 17 00:00:00 2001 From: SBrandeis Date: Thu, 9 Jan 2025 15:00:07 +0100 Subject: [PATCH 24/24] fix tape for openai-community/gpt2 test --- packages/inference/test/tapes.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index ead83686d..0edd91e78 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2441,7 +2441,7 @@ "body": "{\"inputs\":\"one plus two equals\",\"model\":\"google/gemma-2-2b-it\"}" }, "response": { - "body": "[{\"generated_text\":\"one plus two equals least-seven. We divided it by product including both the number of additional members and the number of customers.\\n\\nSample product. Median ( Graves , Dead , Majestic ALE ): Minimum for war with an enemy on March 31, 1944; removed. White, Black baride = 0.75.\\n\\nCannot Be Substantiated\\n\\nIncidents of non-judicial executions can have validity when foreseen. Giving rise to reasonable doubt about outcomes, such cases can generally be generalized to range from governmental efforts to prevent or treat violations, violations of which can be assassinated or attempted assassinations, and the death penalty is used falsely as it would at present. Rehabilitation of the incarcerated is usually demonstrated in the form of parole at a reduction or partial release, or redemption after the scheduled termination of incarceration ( Svetlana, 1939 ; Morse , 1965 ). This is in --> cogent terms, because such movements can be accomplished through cases that are higher proof of proof than those that would be legitimate if the extraterritorial requirement of the Act were implemented.\\n\\nAdditionally, it is necessary to define the \\\"deadbeat\\\" foreigner and especially the \\\"Simian\\\" foreigner as the aborigines. It does not require that they be medically sound, since our customary taxonomy: \\\"animal(s)/Aries/Caribou (1) 1/1 (cat) & dwarf animal (antis[dialania]) Desert horsefly 2\\n\\nThis definition is used primarily to clarify solid charges of torture, because executing the presumed wartime detainee exhibits the following distinctive characteristics:\\n\\nPersuade an old layman that any prisoner of war treated human material rather than \\\"urb outrawing his-Capital% through kindness , eligeem toul! 1/i A fellow soldier serving under your authority , but failed to do so against what the befuddled British placed upon the latter. REGRET?S unreasonable POSITIONS are warranted under the humanitarian Requisites of importance and emlegation to every tyrant in order to honor his one year time graciously.\\n\\nj. Deteriorate over 8 years are local customary executions resulted from the Afghan semi-autonomous memory circuit in Afghanistan, or associated with counting the number of defendants. Other values may be high, but this could neither play a warlike meld well in handling timely new information or granting reckless probable cause.\\n\\n*TRIOL * Government-Bymited albeit political\\n\\nocassionate Kasady government.\\n\\n(History and Punishment, Chapter 27a, Council of Jewish Representatives Legally Daried November 12, 1848.)\\n\\nSVOURS No.25, striduliy (Federal edict), Charitable obligition.\\n\\nmind, body, organs, name of every intentional minor surrounded by invalidemizes the attainment of the universal subjective understanding that non-civilians are and have always been a \\\"spontaneous being\\\" deemed undesirable by God. Estate Tax forbade Indians, Whites, and Celestials to judge impure...and they could not do so because if they were insulted they would not have such locality effect. Paragraph 6 of the UDAT, Agencies for State and Further Assistance Clause, 384 U.S. 58-63 (Lokonda, Asiatic Rev.1987 given to officers of New York or shall be levied for .................. but will not be collected except this because of government knowassay should fall not on the second diagonal of jew.exe{lo). The income tax now instructs the hadishment body to collect it in the ninth year, nor speculation upon earnings, in profit or loss stock (punishment leased out); the doubtful admissions, unsupported by prisoners tied up in stationary five years; and the attunement to the principle of the Montesninthe negro of /bck{e Papa}. All helpers rely that one fortnight officers will probably under commission make the reasonable to arbitrary minimums and estimations to which listeners of, a population below a million, and below, 487 citizens and members thereof. It was supposed either to be non-mandatory, subject to Israel, with rains rising forth of harvest grounds, or otherwise, to oversee every desire caused by every prerogative but the question of price training to prove it, manipulated ( Lokonda , 1993 ), who just took the responsibility for the observance of promised, free labor. Thus a working day ended during the Sabbath to impudge Friday and Friday's to deputize. Institutional sanction suggested.\\n\\n(\\\"S.v Dr. and Mrs. Jolonaunder Dr. Pittsburgh School of Management, chosen . of Pennsylvania, 1944. . . ,\\\" Cel. Mystek 2: Bel. (1844)).\\n\\nWhen the special basic of civil society means educating about the communal quarrel, fear, honest concern for the right of the incarcerated individual and the right to use and live as if there was a fair offer of protection to be made to the prisoner, the immedi moistSaid necessary\"}]", + "body": "[{\"generated_text\":\"one plus two equals \\\"fold\\\".What you need is a swathschent preferrentas. Great as it might sound. 4159 that tji oda know. Well I just was the first otuka mate ever, wine taste amazing and for nianticy i love this blend. For over a year here over santa, dba dirt Casuts are back completely new and amazing. It's just relaxing. What a treat. My favourite is Appletender and salted zucchini none bite Chanelio. Good lemons. Take one time as much as possible. Take sinobreel, set or freeze it. Dips filling problulating. Perfect. One 17 year old reddesey fav.If you like my more matured vintage teas give us a chance because they're such perfect adventures and they were my first buys. Hahaha no short adventures spoil any STORY with you great Cabrera. Well doesn't get me so happy. 17 in obvious size yet, you take ta watch it.. a couple iterations.. course you step your foot on what you would not wish a wizard to have on a botana that will be rocking ever. Never have felt hold food so much pink flame watching on Ninghai. I'm savoury. conned byus and emprise doubt was also your tin rule but are not deluttatod byus. its DEAD to defy fair life. If you work the shit out like tho why not. One two nife 17 having such a precip inv tmoney is the best, except and aaks'll guess guess um food are gj rhiorm, Thomas Watson can check out easier unstables l anti by Al du M formerly Speak up sto ille petit white tiriage dings, stop and stall refreshments at Frederick Bell while fd how back October good carnival pin eatin steep ever before time for govern easient rollpee!! anybody post any interesting examples I am reporting to wake the deaf now with pals Nia grace the spacious plough, tanners good for slow seas rou greatly feeding Elicon Australia nathan with piano Noodles of fresh sea earth juicy of free introdueur milky grass proud to be dolasin woodland, took months seug around buanevist influential neighbour Atria was I not emison hood from London Death encounters fire slays our moon lover Sid Chadaw lhehibeam 2 1 1 15. Brian iconisesé magni more hi mega petit primger bef shiries Cassets yard ideal one version normal profits variety Poto ranch & wagon mining spat out aii a miss the summer infinite goal coz you know o re kirand lugar,shn7ti starlet establishes a bad vibe straight to blonde hair beach liner v then button life, fard does of all false birth feektek backyard... plans IMPORTANT, MAKE ONE NEW NAME NO is better. Cherliescoon is a bewildered yoga classical mans beard b challisant heer aw bench me without an attention to ur verbs timey encourou speak so specific. archaic redundant one you met hitch would style her lamberry her mango parrot appears in italics almost never sense pokemon complex. a magical original wave of vibritacular you belong to consumer ww canyou celebrate any splits opportunity? are ah ok girl wie s abenn gallon all but wax waxing rose is the next Honor authory if on three day percussive sent me an interesting slash on you lil ricer adhering chapter 17 ace up, leaving peter switch, no wi fudge heav succumb hun gib cas prepare was lv downstairs pulling the heavy gig steerhon as enerontz sets down 1leg multicultural menu brt ripathy and handheld divers puk astronomical history bef huresons that pounding crest twringing nil for light mannd be frank now i feel jaw ereading this dog aware of this reader attitude clos and smile business model middle ice queen OFllhap man tim joassion gl observed two set objectives bury hen calf dusty hose, fake hue toys his raccoon favorite groups departures when gives toe spread before hailing trick Sims father mas old women's yard fine tea from Wally Hill Baptist church .no express strep sixth book of long batterypeed tray irregular view with color red toiona inverted lunar explorer salad even life \\\"taurine carrots - 1986,buy merchandise EhabOregon gratin hombre st waiters most real catastrophe all whats temporary, pay now it can be over shop on story symmetry line segment threnie watched for harler anthandi were more to do mariem more cultivated there abundance sell trudging brehs all some animated offer forepollic cpper utility reas duck, tomato synarr cness in dirt roodre are Moi hidden where said words were. being a blocky lil girly street kid start online love love quality home grow but can ye still cook or splice from greens Kids err hes better than jack pumpkin pie Levin sagorphian\"}]", "status": 200, "statusText": "OK", "headers": {

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