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Browse files- index.html +74 -17
index.html
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<!DOCTYPE html>
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<html>
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</html>
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Sentiment Analysis Web App</title>
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<link rel="stylesheet" href="style.css">
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</head>
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<body>
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<div class="container">
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<h1>Sentiment Analysis</h1>
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<textarea id="textInput" placeholder="Enter text..."></textarea>
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<button onclick="classifySentiment()">Classify</button>
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<div id="result" class="result-container"></div>
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</div>
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<script>
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async function query(data) {
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try {
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const response = await fetch(
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"https://api-inference.huggingface.co/models/ahmedrachid/FinancialBERT-Sentiment-Analysis",
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{
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headers: { Authorization: "Bearer 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" },
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method: "POST",
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body: JSON.stringify(data),
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}
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);
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if (!response.ok) {
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throw new Error(`HTTP error! Status: ${response.status}`);
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}
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const result = await response.json();
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return result;
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} catch (error) {
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console.error("Error during API request:", error);
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return { error: "Failed to get predictions from the model." };
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}
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}
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function classifySentiment() {
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const textInput = document.getElementById("textInput").value;
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if (textInput.trim() === "") {
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alert("Please enter text for sentiment analysis.");
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return;
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}
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const data = { "inputs": textInput };
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// Call the query function and handle the response
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query(data).then((response) => {
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console.log(JSON.stringify(response));
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const resultDiv = document.getElementById("result");
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if (response && Array.isArray(response) && response.length > 0) {
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const predictions = response[0];
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// Display the results for each sentiment label and score
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resultDiv.innerHTML = predictions.map((prediction) => {
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return `
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<div class="result-item">
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<p>Sentiment: ${prediction.label}</p>
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<p>Confidence Score: ${prediction.score}</p>
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</div>
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`;
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}).join('');
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} else {
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resultDiv.textContent = "Unable to determine sentiment.";
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}
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});
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}
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</script>
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</body>
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</html>
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