diff --git a/packages/inference/src/lib/makeRequestOptions.ts b/packages/inference/src/lib/makeRequestOptions.ts index 37259e2ef4..4c8d0be7fd 100644 --- a/packages/inference/src/lib/makeRequestOptions.ts +++ b/packages/inference/src/lib/makeRequestOptions.ts @@ -2,8 +2,8 @@ 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"; -import { INFERENCE_PROVIDERS, type InferenceTask, type Options, type RequestArgs } from "../types"; -import { omit } from "../utils/omit"; +import type { InferenceProvider } from "../types"; +import type { InferenceTask, Options, RequestArgs } from "../types"; import { HF_HUB_URL } from "./getDefaultTask"; import { isUrl } from "./isUrl"; @@ -31,62 +31,49 @@ export async function makeRequestOptions( chatCompletion?: boolean; } ): Promise<{ url: string; info: RequestInit }> { - const { accessToken, endpointUrl, provider, ...otherArgs } = args; - let { model } = args; + const { accessToken, endpointUrl, provider: maybeProvider, model: maybeModel, ...otherArgs } = args; + const provider = maybeProvider ?? "hf-inference"; + const { forceTask, includeCredentials, taskHint, wait_for_model, use_cache, dont_load_model, chatCompletion } = options ?? {}; - const headers: Record = {}; - if (accessToken) { - headers["Authorization"] = provider === "fal-ai" ? `Key ${accessToken}` : `Bearer ${accessToken}`; + if (endpointUrl && provider !== "hf-inference") { + throw new Error(`Cannot use endpointUrl with a third-party provider.`); } - - if (!model && !tasks && taskHint) { - const res = await fetch(`${HF_HUB_URL}/api/tasks`); - - if (res.ok) { - tasks = await res.json(); - } + if (forceTask && provider !== "hf-inference") { + throw new Error(`Cannot use forceTask with a third-party provider.`); } - - if (!model && tasks && taskHint) { - const taskInfo = tasks[taskHint]; - if (taskInfo) { - model = taskInfo.models[0].id; - } + if (maybeModel && isUrl(maybeModel)) { + throw new Error(`Model URLs are no longer supported. Use endpointUrl instead.`); } - 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"); + let model: string; + if (!maybeModel) { + if (taskHint) { + model = mapModel({ model: await loadDefaultModel(taskHint), provider }); + } else { + throw new Error("No model provided, and no default model found for this task"); + /// TODO : change error message ^ } + } else { + model = mapModel({ model: maybeModel, provider }); + } - 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}`); - } + const url = endpointUrl + ? chatCompletion + ? endpointUrl + `/v1/chat/completions` + : endpointUrl + : makeUrl({ + model, + provider: provider ?? "hf-inference", + taskHint, + chatCompletion: chatCompletion ?? false, + forceTask, + }); - model = modelId; + const headers: Record = {}; + if (accessToken) { + headers["Authorization"] = provider === "fal-ai" ? `Key ${accessToken}` : `Bearer ${accessToken}`; } const binary = "data" in args && !!args.data; @@ -95,73 +82,20 @@ export async function makeRequestOptions( headers["Content-Type"] = "application/json"; } - if (wait_for_model) { - headers["X-Wait-For-Model"] = "true"; - } - if (use_cache === false) { - headers["X-Use-Cache"] = "false"; - } - if (dont_load_model) { - headers["X-Load-Model"] = "0"; - } - if (provider === "replicate") { - headers["Prefer"] = "wait"; - } - - let url = (() => { - if (endpointUrl && isUrl(model)) { - throw new TypeError("Both model and endpointUrl cannot be URLs"); - } - if (isUrl(model)) { - console.warn("Using a model URL is deprecated, please use the `endpointUrl` parameter instead"); - return model; - } - if (endpointUrl) { - return endpointUrl; + if (provider === "hf-inference") { + if (wait_for_model) { + headers["X-Wait-For-Model"] = "true"; } - if (forceTask) { - return `${HF_INFERENCE_API_BASE_URL}/pipeline/${forceTask}/${model}`; + if (use_cache === false) { + headers["X-Use-Cache"] = "false"; } - 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 { - switch (provider) { - case "fal-ai": - return `${FAL_AI_API_BASE_URL}/${model}`; - case "replicate": - if (model.includes(":")) { - // Versioned models are in the form of `owner/model:version` - return `${REPLICATE_API_BASE_URL}/v1/predictions`; - } else { - // Unversioned models are in the form of `owner/model` - return `${REPLICATE_API_BASE_URL}/v1/models/${model}/predictions`; - } - case "sambanova": - return SAMBANOVA_API_BASE_URL; - case "together": - if (taskHint === "text-to-image") { - return `${TOGETHER_API_BASE_URL}/v1/images/generations`; - } - return TOGETHER_API_BASE_URL; - default: - break; - } - } + if (dont_load_model) { + headers["X-Load-Model"] = "0"; } - - return `${HF_INFERENCE_API_BASE_URL}/models/${model}`; - })(); - - if (chatCompletion && !url.endsWith("/chat/completions")) { - url += "/v1/chat/completions"; } - if (provider === "together" && taskHint === "text-generation" && !chatCompletion) { - url += "/v1/completions"; + + if (provider === "replicate") { + headers["Prefer"] = "wait"; } /** @@ -188,9 +122,8 @@ 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, + ...(chatCompletion || provider === "together" ? { model } : undefined), }), ...(credentials ? { credentials } : undefined), signal: options?.signal, @@ -198,3 +131,93 @@ export async function makeRequestOptions( return { url, info }; } + +function mapModel(params: { model: string; provider: InferenceProvider }): string { + const model = (() => { + switch (params.provider) { + case "fal-ai": + return FAL_AI_MODEL_IDS[params.model]; + case "replicate": + return REPLICATE_MODEL_IDS[params.model]; + case "sambanova": + return SAMBANOVA_MODEL_IDS[params.model]; + case "together": + return TOGETHER_MODEL_IDS[params.model]?.id; + case "hf-inference": + return params.model; + } + })(); + + if (!model) { + throw new Error(`Model ${params.model} is not supported for provider ${params.provider}`); + } + return model; +} + +function makeUrl(params: { + model: string; + provider: InferenceProvider; + taskHint: InferenceTask | undefined; + chatCompletion: boolean; + forceTask?: string | InferenceTask; +}): string { + switch (params.provider) { + case "fal-ai": + return `${FAL_AI_API_BASE_URL}/${params.model}`; + case "replicate": { + if (params.model.includes(":")) { + /// Versioned model + return `${REPLICATE_API_BASE_URL}/v1/predictions`; + } + /// Evergreen / Canonical model + return `${REPLICATE_API_BASE_URL}/v1/models/${params.model}/predictions`; + } + case "sambanova": + /// Sambanova API matches OpenAI-like APIs: model is defined in the request body + if (params.taskHint === "text-generation" && params.chatCompletion) { + return `${SAMBANOVA_API_BASE_URL}/v1/chat/completions`; + } + return SAMBANOVA_API_BASE_URL; + case "together": { + /// Together API matches OpenAI-like APIs: model is defined in the request body + if (params.taskHint === "text-to-image") { + return `${TOGETHER_API_BASE_URL}/v1/images/generations`; + } + if (params.taskHint === "text-generation") { + if (params.chatCompletion) { + return `${TOGETHER_API_BASE_URL}/v1/chat/completions`; + } + return `${TOGETHER_API_BASE_URL}/v1/completions`; + } + return TOGETHER_API_BASE_URL; + } + default: { + const url = params.forceTask + ? `${HF_INFERENCE_API_BASE_URL}/pipeline/${params.forceTask}/${params.model}` + : `${HF_INFERENCE_API_BASE_URL}/models/${params.model}`; + if (params.taskHint === "text-generation" && params.chatCompletion) { + return url + `/v1/chat/completions`; + } + return url; + } + } +} +async function loadDefaultModel(task: InferenceTask): Promise { + if (!tasks) { + tasks = await loadTaskInfo(); + } + const taskInfo = tasks[task]; + if ((taskInfo?.models.length ?? 0) <= 0) { + throw new Error(`No default model defined for task ${task}, please define the model explicitly.`); + } + return taskInfo.models[0].id; +} + +async function loadTaskInfo(): Promise> { + const res = await fetch(`${HF_HUB_URL}/api/tasks`); + + if (!res.ok) { + throw new Error("Failed to load tasks definitions from Hugging Face Hub."); + } + return await res.json(); +} diff --git a/packages/inference/src/providers/fal-ai.ts b/packages/inference/src/providers/fal-ai.ts index 2639bf5d13..af513f5b01 100644 --- a/packages/inference/src/providers/fal-ai.ts +++ b/packages/inference/src/providers/fal-ai.ts @@ -7,7 +7,7 @@ type FalAiId = string; /** * Mapping from HF model ID -> fal.ai app id */ -export const FAL_AI_MODEL_IDS: Record = { +export const FAL_AI_MODEL_IDS: Partial> = { /** text-to-image */ "black-forest-labs/FLUX.1-schnell": "fal-ai/flux/schnell", "black-forest-labs/FLUX.1-dev": "fal-ai/flux/dev", diff --git a/packages/inference/src/providers/replicate.ts b/packages/inference/src/providers/replicate.ts index 710738c26d..856c07d30f 100644 --- a/packages/inference/src/providers/replicate.ts +++ b/packages/inference/src/providers/replicate.ts @@ -14,7 +14,7 @@ type ReplicateId = string; * 'https://api.replicate.com/v1/models' * ``` */ -export const REPLICATE_MODEL_IDS: Record = { +export const REPLICATE_MODEL_IDS: Partial> = { /** text-to-image */ "black-forest-labs/FLUX.1-schnell": "black-forest-labs/flux-schnell", "ByteDance/SDXL-Lightning": diff --git a/packages/inference/src/providers/sambanova.ts b/packages/inference/src/providers/sambanova.ts index 745f7b51ff..70d6d57cf0 100644 --- a/packages/inference/src/providers/sambanova.ts +++ b/packages/inference/src/providers/sambanova.ts @@ -15,7 +15,7 @@ type SambanovaId = string; /** * https://community.sambanova.ai/t/supported-models/193 */ -export const SAMBANOVA_MODEL_IDS: Record = { +export const SAMBANOVA_MODEL_IDS: Partial> = { /** Chat completion / conversational */ "Qwen/Qwen2.5-Coder-32B-Instruct": "Qwen2.5-Coder-32B-Instruct", "Qwen/Qwen2.5-72B-Instruct": "Qwen2.5-72B-Instruct", diff --git a/packages/inference/src/providers/together.ts b/packages/inference/src/providers/together.ts index 799b98637b..41bac5a5ba 100644 --- a/packages/inference/src/providers/together.ts +++ b/packages/inference/src/providers/together.ts @@ -10,9 +10,8 @@ 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" } +export const TOGETHER_MODEL_IDS: Partial< + Record > = { /** text-to-image */ "black-forest-labs/FLUX.1-Canny-dev": { id: "black-forest-labs/FLUX.1-canny", type: "image" }, diff --git a/packages/inference/src/tasks/custom/streamingRequest.ts b/packages/inference/src/tasks/custom/streamingRequest.ts index e7be109b54..3cac1954a1 100644 --- a/packages/inference/src/tasks/custom/streamingRequest.ts +++ b/packages/inference/src/tasks/custom/streamingRequest.ts @@ -32,9 +32,13 @@ export async function* streamingRequest( 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) { + if (typeof output.error === "string") { throw new Error(output.error); } + if (output.error && "message" in output.error && typeof output.error.message === "string") { + /// OpenAI errors + throw new Error(output.error.message); + } } throw new Error(`Server response contains error: ${response.status}`); diff --git a/packages/inference/test/HfInference.spec.ts b/packages/inference/test/HfInference.spec.ts index 2ab9c69bb9..545db71ea2 100644 --- a/packages/inference/test/HfInference.spec.ts +++ b/packages/inference/test/HfInference.spec.ts @@ -204,10 +204,14 @@ describe.concurrent("HfInference", () => { }); }); - it("textGenerationStream - meta-llama/Llama-2-7b-hf", async () => { + it("textGenerationStream - meta-llama/Llama-3.2-3B", async () => { const response = hf.textGenerationStream({ - model: "meta-llama/Llama-2-7b-hf", + model: "meta-llama/Llama-3.2-3B", inputs: "Please answer the following question: complete one two and ____.", + parameters: { + max_new_tokens: 50, + seed: 0, + }, }); for await (const ret of response) { @@ -221,7 +225,7 @@ describe.concurrent("HfInference", () => { 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?" + ? "Please answer the following question: complete one two and ____. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17" : null, }); } @@ -229,7 +233,7 @@ describe.concurrent("HfInference", () => { it("textGenerationStream - catch error", async () => { const response = hf.textGenerationStream({ - model: "meta-llama/Llama-2-7b-hf", + model: "meta-llama/Llama-3.2-3B", inputs: "Write a short story about a robot that becomes sentient and takes over the world.", parameters: { max_new_tokens: 10_000, @@ -237,7 +241,7 @@ describe.concurrent("HfInference", () => { }); 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`" + "Error forwarded from backend: Input validation error: `inputs` tokens + `max_new_tokens` must be <= 4096. Given: 17 `inputs` tokens and 10000 `max_new_tokens`" ); }); @@ -741,7 +745,7 @@ describe.concurrent("HfInference", () => { out += chunk.choices[0].delta.content; } } - expect(out).toContain("The answer to the equation one + one is two."); + expect(out).toContain("The answer to one + one is two."); }); it("custom openai - OpenAI Specs", async () => { const OPENAI_KEY = env.OPENAI_KEY; diff --git a/packages/inference/test/tapes.json b/packages/inference/test/tapes.json index c2b1810a12..4f5a67e0b1 100644 --- a/packages/inference/test/tapes.json +++ b/packages/inference/test/tapes.json @@ -2578,5 +2578,1710 @@ "server": "UploadServer" } } + }, + "8dfb7e10b7eef5c4d71611cb84f37be0abef96fd7d9d5c16aaa192afc5be321b": { + "url": "https://api.mistral.ai", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"mistral-tiny\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation one + one = , just the answer\"}],\"stream\":true}" + }, + "response": { + "body": "{\"message\":\"no Route matched with those values\",\"request_id\":\"1d3de173b2ad3558d3fb33431615bf43\"}", + "status": 404, + "statusText": "Not Found", + "headers": { + "access-control-allow-origin": "*", + "alt-svc": "h3=\":443\"; ma=86400", + "cf-cache-status": "DYNAMIC", + "cf-ray": "9026baf8adfe9996-CDG", + "connection": "keep-alive", + "content-encoding": "br", + "content-type": "application/json; charset=utf-8", + "server": "cloudflare", + "set-cookie": "__cf_bm=7m5YMXinqJn9YSXXpiB9XoeNTPW0PLC5OyOR3gfpuKw-1736953173-1.0.1.1-QF6GeV1lB5L.QQ.u.ACIFfu6Rkw8A3JVt.2T7Dfsph_dU9DjB_T17.YiS6331hoCUfT8PCQNGhovUWqjaXNg7w; path=/; expires=Wed, 15-Jan-25 15:29:33 GMT; domain=.mistral.ai; HttpOnly; Secure; SameSite=None", + "transfer-encoding": "chunked" + } + } + }, + "bec17141757f371d4c7b105acfd6cca133dfd0d80acbefcd9fcd2ed4d271ebfa": { + "url": "https://api.openai.com", + "init": { + "headers": { + "Content-Type": "application/json" + }, + "method": "POST", + "body": "{\"model\":\"gpt-3.5-turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Complete the equation one + one =\"}],\"stream\":true}" + }, + "response": { + "body": "{\"message\":\"Welcome to the OpenAI API! 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