Fix huggingface_hub snippets (#1448)

Fixes #1440. 
Thank you @tomaarsen for flagging this! This PR addresses all the
incorrect snippets mentioned in the issue.

I've added example snippets for `feature-extraction`,
`question-answering`,` table-question-answering`, and
`text-classification` to ensure everything is now correct.

Author: hanouticelina

packages/inference/src/snippets/getInferenceSnippets.ts

@@ -285,6 +285,16 @@ const prepareConversationalInput = (
 	};
 };
 
+const prepareQuestionAnsweringInput = (model: ModelDataMinimal): object => {
+	const data = JSON.parse(getModelInputSnippet(model) as string);
+	return { question: data.question, context: data.context };
+};
+
+const prepareTableQuestionAnsweringInput = (model: ModelDataMinimal): object => {
+	const data = JSON.parse(getModelInputSnippet(model) as string);
+	return { query: data.query, table: JSON.stringify(data.table) };
+};
+
 const snippets: Partial<
 	Record<
 		PipelineType,
@@ -309,12 +319,12 @@ const snippets: Partial<
 	"image-to-image": snippetGenerator("imageToImage", prepareImageToImageInput),
 	"image-to-text": snippetGenerator("basicImage"),
 	"object-detection": snippetGenerator("basicImage"),
-	"question-answering": snippetGenerator("basic"),
+	"question-answering": snippetGenerator("questionAnswering", prepareQuestionAnsweringInput),
 	"sentence-similarity": snippetGenerator("basic"),
 	summarization: snippetGenerator("basic"),
 	"tabular-classification": snippetGenerator("tabular"),
 	"tabular-regression": snippetGenerator("tabular"),
-	"table-question-answering": snippetGenerator("basic"),
+	"table-question-answering": snippetGenerator("tableQuestionAnswering", prepareTableQuestionAnsweringInput),
 	"text-classification": snippetGenerator("basic"),
 	"text-generation": snippetGenerator("basic"),
 	"text-to-audio": snippetGenerator("textToAudio"),

packages/inference/src/snippets/templates/python/huggingface_hub/basic.jinja

@@ -1,4 +1,4 @@
 result = client.{{ methodName }}(
-    inputs={{ inputs.asObj.inputs }},
+    {{ inputs.asObj.inputs }},
     model="{{ model.id }}",
 )

packages/inference/src/snippets/templates/python/huggingface_hub/questionAnswering.jinja

@@ -0,0 +1,5 @@
+answer = client.question_answering(
+    question="{{ inputs.asObj.question }}",
+    context="{{ inputs.asObj.context }}",
+    model="{{ model.id }}",
+) 

packages/inference/src/snippets/templates/python/huggingface_hub/tableQuestionAnswering.jinja

@@ -0,0 +1,5 @@
+answer = client.question_answering(
+    query="{{ inputs.asObj.query }}",
+    table={{ inputs.asObj.table }},
+    model="{{ model.id }}",
+) 

packages/tasks-gen/scripts/generate-snippets-fixtures.ts

@@ -250,6 +250,39 @@ const TEST_CASES: {
 		},
 		providers: ["fal-ai"],
 	},
+	{
+		testName: "feature-extraction",
+		task: "feature-extraction",
+		model: {
+			id: "intfloat/multilingual-e5-large-instruct",
+			pipeline_tag: "feature-extraction",
+			tags: [],
+			inference: "",
+		},
+		providers: ["hf-inference"],
+	},
+	{
+		testName: "question-answering",
+		task: "question-answering",
+		model: {
+			id: "google-bert/bert-large-uncased-whole-word-masking-finetuned-squad",
+			pipeline_tag: "question-answering",
+			tags: [],
+			inference: "",
+		},
+		providers: ["hf-inference"],
+	},
+	{
+		testName: "table-question-answering",
+		task: "table-question-answering",
+		model: {
+			id: "google-bert/bert-large-uncased-whole-word-masking-finetuned-squad",
+			pipeline_tag: "table-question-answering",
+			tags: [],
+			inference: "",
+		},
+		providers: ["hf-inference"],
+	},
 ] as const;
 
 const rootDirFinder = (): string => {

packages/tasks-gen/snippets-fixtures/basic-snippet--token-classification/python/huggingface_hub/0.hf-inference.py

@@ -6,6 +6,6 @@
 )
 
 result = client.token_classification(
-    inputs="My name is Sarah Jessica Parker but you can call me Jessica",
+    "My name is Sarah Jessica Parker but you can call me Jessica",
     model="FacebookAI/xlm-roberta-large-finetuned-conll03-english",
 )

packages/tasks-gen/snippets-fixtures/feature-extraction/js/fetch/0.hf-inference.js

@@ -0,0 +1,19 @@
+async function query(data) {
+	const response = await fetch(
+		"https://router.huggingface.co/hf-inference/models/intfloat/multilingual-e5-large-instruct/pipeline/feature-extraction",
+		{
+			headers: {
+				Authorization: "Bearer api_token",
+				"Content-Type": "application/json",
+			},
+			method: "POST",
+			body: JSON.stringify(data),
+		}
+	);
+	const result = await response.json();
+	return result;
+}
+
+query({ inputs: "Today is a sunny day and I will get some ice cream." }).then((response) => {
+    console.log(JSON.stringify(response));
+});

packages/tasks-gen/snippets-fixtures/feature-extraction/js/huggingface.js/0.hf-inference.js

@@ -0,0 +1,11 @@
+import { InferenceClient } from "@huggingface/inference";
+
+const client = new InferenceClient("api_token");
+
+const output = await client.featureExtraction({
+	model: "intfloat/multilingual-e5-large-instruct",
+	inputs: "Today is a sunny day and I will get some ice cream.",
+	provider: "hf-inference",
+});
+
+console.log(output);

packages/tasks-gen/snippets-fixtures/feature-extraction/python/huggingface_hub/0.hf-inference.py

@@ -0,0 +1,11 @@
+from huggingface_hub import InferenceClient
+
+client = InferenceClient(
+    provider="hf-inference",
+    api_key="api_token",
+)
+
+result = client.feature_extraction(
+    "Today is a sunny day and I will get some ice cream.",
+    model="intfloat/multilingual-e5-large-instruct",
+)

packages/tasks-gen/snippets-fixtures/feature-extraction/python/requests/0.hf-inference.py

@@ -0,0 +1,14 @@
+import requests
+
+API_URL = "https://router.huggingface.co/hf-inference/models/intfloat/multilingual-e5-large-instruct/pipeline/feature-extraction"
+headers = {
+    "Authorization": "Bearer api_token",
+}
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+output = query({
+    "inputs": "Today is a sunny day and I will get some ice cream.",
+})