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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Sentiment Analysis Web App</title>
<link rel="stylesheet" href="style.css">
</head>
<body>
<div class="container">
<h1>Sentiment Analysis</h1>
<textarea id="textInput" placeholder="Enter text..."></textarea>
<button onclick="classifySentiment()">Classify</button>
<div id="result" class="result-container"></div>
</div>
<script>
async function query(data) {
try {
const response = await fetch(
"https://api-inference.huggingface.co/models/ahmedrachid/FinancialBERT-Sentiment-Analysis",
{
headers: { Authorization: "Bearer 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" },
method: "POST",
body: JSON.stringify(data),
}
);
if (!response.ok) {
throw new Error(`HTTP error! Status: ${response.status}`);
}
const result = await response.json();
return result;
} catch (error) {
console.error("Error during API request:", error);
return { error: "Failed to get predictions from the model." };
}
}
function classifySentiment() {
const textInput = document.getElementById("textInput").value;
if (textInput.trim() === "") {
alert("Please enter text for sentiment analysis.");
return;
}
const data = { "inputs": textInput };
// Call the query function and handle the response
query(data).then((response) => {
console.log(JSON.stringify(response));
const resultDiv = document.getElementById("result");
if (response && Array.isArray(response) && response.length > 0) {
const predictions = response[0];
// Display the results for each sentiment label and score
resultDiv.innerHTML = predictions.map((prediction) => {
return `
<div class="result-item">
<p>Sentiment: ${prediction.label}</p>
<p>Confidence Score: ${prediction.score}</p>
</div>
`;
}).join('');
} else {
resultDiv.textContent = "Unable to determine sentiment.";
}
});
}
</script>
</body>
</html>
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