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feat: Add Avian AI provider support #1848
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| --- | ||
| "@huggingface/inference": minor | ||
| --- | ||
|
|
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| Add Avian as a new AI provider |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| /** | ||
| * See the registered mapping of HF model ID => Avian model ID here: | ||
| * | ||
| * https://huggingface.co/api/partners/avian/models | ||
| * | ||
| * This is a publicly available mapping. | ||
| * | ||
| * If you want to try to run inference for a new model locally before it's registered on huggingface.co, | ||
| * you can add it to the dictionary "HARDCODED_MODEL_ID_MAPPING" in consts.ts, for dev purposes. | ||
| * | ||
| * - If you work at Avian and want to update this mapping, please use the model mapping API we provide on huggingface.co | ||
| * - If you're a community member and want to add a new supported HF model to Avian, please open an issue on the present repo | ||
| * and we will tag Avian team members. | ||
| * | ||
| * Thanks! | ||
| */ | ||
|
|
||
| import { BaseConversationalTask } from "./providerHelper.js"; | ||
|
|
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| export class AvianConversationalTask extends BaseConversationalTask { | ||
| constructor() { | ||
| super("avian", "https://api.avian.io"); | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,102 @@ | ||
| import { describe, it, expect } from "vitest"; | ||
| import type { ChatCompletionStreamOutput } from "@huggingface/tasks"; | ||
| import { InferenceClient, chatCompletion, chatCompletionStream } from "../src/index.js"; | ||
| import { HARDCODED_MODEL_INFERENCE_MAPPING } from "../src/providers/consts.js"; | ||
|
|
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| const TIMEOUT = 60000 * 3; | ||
| const env = import.meta.env; | ||
|
|
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| if (!env.HF_TOKEN) { | ||
| console.warn("Set HF_TOKEN in the env to run the tests for better rate limits"); | ||
| } | ||
|
|
||
| describe.skip.concurrent( | ||
| "Avian", | ||
| () => { | ||
| const client = new InferenceClient(env.HF_AVIAN_KEY ?? "dummy"); | ||
|
|
||
| HARDCODED_MODEL_INFERENCE_MAPPING["avian"] = { | ||
| "zai-org/GLM-4.6": { | ||
| provider: "avian", | ||
| hfModelId: "zai-org/GLM-4.6", | ||
| providerId: "glm-4.6", | ||
| status: "live", | ||
| task: "conversational", | ||
| }, | ||
| }; | ||
|
|
||
| it("chatCompletion", async () => { | ||
| const res = await client.chatCompletion({ | ||
| model: "zai-org/GLM-4.6", | ||
| provider: "avian", | ||
| 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 stream", async () => { | ||
| const stream = client.chatCompletionStream({ | ||
| model: "zai-org/GLM-4.6", | ||
| provider: "avian", | ||
| messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], | ||
| stream: true, | ||
| }) as AsyncGenerator<ChatCompletionStreamOutput>; | ||
|
|
||
| let fullResponse = ""; | ||
| for await (const chunk of stream) { | ||
| if (chunk.choices && chunk.choices.length > 0) { | ||
| const content = chunk.choices[0].delta?.content; | ||
| if (content) { | ||
| fullResponse += content; | ||
| } | ||
| } | ||
| } | ||
|
|
||
| expect(fullResponse).toBeTruthy(); | ||
| expect(fullResponse.length).toBeGreaterThan(0); | ||
| expect(fullResponse).toMatch(/(two|2)/i); | ||
| }); | ||
|
|
||
| it("chatCompletion - using chatCompletion function", async () => { | ||
| const res = await chatCompletion({ | ||
| accessToken: env.HF_AVIAN_KEY ?? "dummy", | ||
| model: "zai-org/GLM-4.6", | ||
| provider: "avian", | ||
| messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }], | ||
| temperature: 0.1, | ||
| }); | ||
|
|
||
| expect(res).toBeDefined(); | ||
| expect(res.choices).toBeDefined(); | ||
| expect(res.choices?.length).toBeGreaterThan(0); | ||
|
|
||
| if (res.choices && res.choices.length > 0) { | ||
| const completion = res.choices[0].message?.content; | ||
| expect(completion).toBeDefined(); | ||
| expect(typeof completion).toBe("string"); | ||
| expect(completion).toMatch(/(two|2)/i); | ||
| } | ||
| }); | ||
|
|
||
| it("chatCompletion stream - using chatCompletionStream function", async () => { | ||
| const stream = chatCompletionStream({ | ||
| accessToken: env.HF_AVIAN_KEY ?? "dummy", | ||
| model: "zai-org/GLM-4.6", | ||
| provider: "avian", | ||
| messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }], | ||
| }) as AsyncGenerator<ChatCompletionStreamOutput>; | ||
|
|
||
| let out = ""; | ||
| for await (const chunk of stream) { | ||
| if (chunk.choices && chunk.choices.length > 0) { | ||
| out += chunk.choices[0].delta.content; | ||
| } | ||
| } | ||
| expect(out).toMatch(/(two|2)/i); | ||
| }); | ||
| }, | ||
| TIMEOUT | ||
| ); |
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