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WauplinWauplin
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Do not require all dummy api keys in inference tests (#1226)
I currently find it annoying when I want to run tests locally (that already have cached tapes) to set the env variables to `"dummy"`: ```sh HF_FAL_KEY=dummy pnpm run test -t "Fal AI" ``` This PR is a suggestion to get rid of that and default to `"dummy"` in the code instead of in the CI workflow file. Happy to get better suggestions if you think of one (in Python I would do an automatic fixture "get_api_key_or_dummy" but quite specific to pytest). As a bonus, no need to update `.github/workflows/test.yml` when adding a new provider. WDYT?
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‎.github/workflows/test.yml‎

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@@ -41,16 +41,6 @@ jobs:
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run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
44-
HF_BLACK_FOREST_LABS_KEY: dummy
45-
HF_COHERE_KEY: dummy
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HF_FAL_KEY: dummy
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HF_FIREWORKS_KEY: dummy
48-
HF_HYPERBOLIC_KEY: dummy
49-
HF_NEBIUS_KEY: dummy
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HF_NOVITA_KEY: dummy
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HF_REPLICATE_KEY: dummy
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HF_SAMBANOVA_KEY: dummy
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HF_TOGETHER_KEY: dummy
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browser:
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runs-on: ubuntu-latest
@@ -87,16 +77,6 @@ jobs:
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run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test:browser
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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HF_BLACK_FOREST_LABS_KEY: dummy
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HF_COHERE_KEY: dummy
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HF_FAL_KEY: dummy
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HF_FIREWORKS_KEY: dummy
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HF_HYPERBOLIC_KEY: dummy
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HF_NEBIUS_KEY: dummy
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HF_NOVITA_KEY: dummy
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HF_REPLICATE_KEY: dummy
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HF_SAMBANOVA_KEY: dummy
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HF_TOGETHER_KEY: dummy
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e2e:
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runs-on: ubuntu-latest
@@ -160,13 +140,3 @@ jobs:
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env:
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NPM_CONFIG_REGISTRY: http://localhost:4874/
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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HF_BLACK_FOREST_LABS_KEY: dummy
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HF_COHERE_KEY: dummy
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HF_FAL_KEY: dummy
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HF_FIREWORKS_KEY: dummy
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HF_HYPERBOLIC_KEY: dummy
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HF_NEBIUS_KEY: dummy
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HF_NOVITA_KEY: dummy
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HF_REPLICATE_KEY: dummy
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HF_SAMBANOVA_KEY: dummy
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HF_TOGETHER_KEY: dummy

‎packages/inference/test/HfInference.spec.ts‎

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@@ -787,7 +787,7 @@ describe.concurrent("HfInference", () => {
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describe.concurrent(
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"Fal AI",
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() => {
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const client = new HfInference(env.HF_FAL_KEY);
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const client = new HfInference(env.HF_FAL_KEY ?? "dummy");
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it(`textToImage - black-forest-labs/FLUX.1-schnell`, async () => {
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const res = await client.textToImage({
@@ -818,7 +818,7 @@ describe.concurrent("HfInference", () => {
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seed: 176,
819819
},
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provider: "fal-ai",
821-
accessToken: env.HF_FAL_KEY,
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accessToken: env.HF_FAL_KEY ?? "dummy",
822822
});
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expect(res).toBeInstanceOf(Blob);
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});
@@ -834,7 +834,7 @@ describe.concurrent("HfInference", () => {
834834
resolution: "480p",
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},
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provider: "fal-ai",
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accessToken: env.HF_FAL_KEY,
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accessToken: env.HF_FAL_KEY ?? "dummy",
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});
839839
expect(res).toBeInstanceOf(Blob);
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});
@@ -848,7 +848,7 @@ describe.concurrent("HfInference", () => {
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num_frames: 2,
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},
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provider: "fal-ai",
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accessToken: env.HF_FAL_KEY,
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accessToken: env.HF_FAL_KEY ?? "dummy",
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});
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expect(res).toBeInstanceOf(Blob);
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});
@@ -862,7 +862,7 @@ describe.concurrent("HfInference", () => {
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num_inference_steps: 2,
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},
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provider: "fal-ai",
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accessToken: env.HF_FAL_KEY,
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accessToken: env.HF_FAL_KEY ?? "dummy",
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});
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expect(res).toBeInstanceOf(Blob);
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});
@@ -873,7 +873,7 @@ describe.concurrent("HfInference", () => {
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describe.concurrent(
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"Replicate",
875875
() => {
876-
const client = new HfInference(env.HF_REPLICATE_KEY);
876+
const client = new HfInference(env.HF_REPLICATE_KEY ?? "dummy");
877877

878878
it("textToImage canonical - black-forest-labs/FLUX.1-schnell", async () => {
879879
const res = await client.textToImage({
@@ -970,7 +970,7 @@ describe.concurrent("HfInference", () => {
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971971
it("textToVideo Mochi", async () => {
972972
const res = await textToVideo({
973-
accessToken: env.HF_REPLICATE_KEY,
973+
accessToken: env.HF_REPLICATE_KEY ?? "dummy",
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model: "genmo/mochi-1-preview",
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provider: "replicate",
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inputs: "A running dog",
@@ -989,7 +989,7 @@ describe.concurrent("HfInference", () => {
989989
describe.concurrent(
990990
"SambaNova",
991991
() => {
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const client = new HfInference(env.HF_SAMBANOVA_KEY);
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const client = new HfInference(env.HF_SAMBANOVA_KEY ?? "dummy");
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it("chatCompletion", async () => {
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const res = await client.chatCompletion({
@@ -1023,7 +1023,7 @@ describe.concurrent("HfInference", () => {
10231023
describe.concurrent(
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"Together",
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() => {
1026-
const client = new HfInference(env.HF_TOGETHER_KEY);
1026+
const client = new HfInference(env.HF_TOGETHER_KEY ?? "dummy");
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10281028
it("chatCompletion", async () => {
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const res = await client.chatCompletion({
@@ -1078,7 +1078,7 @@ describe.concurrent("HfInference", () => {
10781078
describe.concurrent(
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"Nebius",
10801080
() => {
1081-
const client = new HfInference(env.HF_NEBIUS_KEY);
1081+
const client = new HfInference(env.HF_NEBIUS_KEY ?? "dummy");
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HARDCODED_MODEL_ID_MAPPING.nebius = {
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"meta-llama/Llama-3.1-8B-Instruct": "meta-llama/Meta-Llama-3.1-8B-Instruct",
@@ -1132,7 +1132,7 @@ describe.concurrent("HfInference", () => {
11321132
model: "black-forest-labs/Flux.1-dev",
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provider: "together",
11341134
messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }],
1135-
accessToken: env.HF_TOGETHER_KEY,
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accessToken: env.HF_TOGETHER_KEY ?? "dummy",
11361136
})
11371137
).rejects.toThrowError(
11381138
"Model black-forest-labs/Flux.1-dev is not supported for task conversational and provider together"
@@ -1143,7 +1143,7 @@ describe.concurrent("HfInference", () => {
11431143
describe.concurrent(
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"Fireworks",
11451145
() => {
1146-
const client = new HfInference(env.HF_FIREWORKS_KEY);
1146+
const client = new HfInference(env.HF_FIREWORKS_KEY ?? "dummy");
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HARDCODED_MODEL_ID_MAPPING["fireworks-ai"] = {
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"deepseek-ai/DeepSeek-R1": "accounts/fireworks/models/deepseek-r1",
@@ -1199,7 +1199,7 @@ describe.concurrent("HfInference", () => {
11991199

12001200
it("chatCompletion - hyperbolic", async () => {
12011201
const res = await chatCompletion({
1202-
accessToken: env.HF_HYPERBOLIC_KEY,
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accessToken: env.HF_HYPERBOLIC_KEY ?? "dummy",
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model: "meta-llama/Llama-3.2-3B-Instruct",
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provider: "hyperbolic",
12051205
messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }],
@@ -1220,7 +1220,7 @@ describe.concurrent("HfInference", () => {
12201220

12211221
it("chatCompletion stream", async () => {
12221222
const stream = chatCompletionStream({
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accessToken: env.HF_HYPERBOLIC_KEY,
1223+
accessToken: env.HF_HYPERBOLIC_KEY ?? "dummy",
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model: "meta-llama/Llama-3.3-70B-Instruct",
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provider: "hyperbolic",
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messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }],
@@ -1236,7 +1236,7 @@ describe.concurrent("HfInference", () => {
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12371237
it("textToImage", async () => {
12381238
const res = await textToImage({
1239-
accessToken: env.HF_HYPERBOLIC_KEY,
1239+
accessToken: env.HF_HYPERBOLIC_KEY ?? "dummy",
12401240
model: "stabilityai/stable-diffusion-2",
12411241
provider: "hyperbolic",
12421242
inputs: "award winning high resolution photo of a giant tortoise",
@@ -1250,7 +1250,7 @@ describe.concurrent("HfInference", () => {
12501250

12511251
it("textGeneration", async () => {
12521252
const res = await textGeneration({
1253-
accessToken: env.HF_HYPERBOLIC_KEY,
1253+
accessToken: env.HF_HYPERBOLIC_KEY ?? "dummy",
12541254
model: "meta-llama/Llama-3.1-405B",
12551255
provider: "hyperbolic",
12561256
inputs: "Paris is",
@@ -1269,7 +1269,7 @@ describe.concurrent("HfInference", () => {
12691269
describe.concurrent(
12701270
"Novita",
12711271
() => {
1272-
const client = new HfInference(env.HF_NOVITA_KEY);
1272+
const client = new HfInference(env.HF_NOVITA_KEY ?? "dummy");
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12741274
HARDCODED_MODEL_ID_MAPPING["novita"] = {
12751275
"meta-llama/llama-3.1-8b-instruct": "meta-llama/llama-3.1-8b-instruct",
@@ -1325,7 +1325,7 @@ describe.concurrent("HfInference", () => {
13251325
const res = await textToImage({
13261326
model: "black-forest-labs/FLUX.1-dev",
13271327
provider: "black-forest-labs",
1328-
accessToken: env.HF_BLACK_FOREST_LABS_KEY,
1328+
accessToken: env.HF_BLACK_FOREST_LABS_KEY ?? "dummy",
13291329
inputs: "A raccoon driving a truck",
13301330
parameters: {
13311331
height: 256,
@@ -1342,7 +1342,7 @@ describe.concurrent("HfInference", () => {
13421342
{
13431343
model: "black-forest-labs/FLUX.1-dev",
13441344
provider: "black-forest-labs",
1345-
accessToken: env.HF_BLACK_FOREST_LABS_KEY,
1345+
accessToken: env.HF_BLACK_FOREST_LABS_KEY ?? "dummy",
13461346
inputs: "A raccoon driving a truck",
13471347
parameters: {
13481348
height: 256,
@@ -1362,7 +1362,7 @@ describe.concurrent("HfInference", () => {
13621362
describe.concurrent(
13631363
"Cohere",
13641364
() => {
1365-
const client = new HfInference(env.HF_COHERE_KEY);
1365+
const client = new HfInference(env.HF_COHERE_KEY ?? "dummy");
13661366

13671367
HARDCODED_MODEL_ID_MAPPING["cohere"] = {
13681368
"CohereForAI/c4ai-command-r7b-12-2024": "command-r7b-12-2024",

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