Merge pull request #8 from SalimM21/SALIM

Salim

Author: SalimM21

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----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=
+-----END CERTIFICATE-----

Docker-SA

@@ -0,0 +1 @@
+Subproject commit 080f7ab5c61d7c04e8a43faf7f405a619385bbc4

Dockerfile

@@ -1,16 +1,30 @@
-FROM python:3.11-slim
+FROM python:3.10-slim
 
-ENV PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1
+# Installer dépendances système nécessaires pour torch et transformers
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
 
 WORKDIR /app
 
+# Copier le fichier requirements.txt
 COPY requirements.txt .
+
+# Upgrade pip
+RUN pip install --upgrade pip
+
+# Installer les dépendances Python, incluant torch CPU
+RUN pip install --no-cache-dir torch==2.2.0 -f https://download.pytorch.org/whl/cpu/torch_stable.html
+RUN pip install --no-cache-dir "numpy<2"
 RUN pip install --no-cache-dir -r requirements.txt
 
-COPY app ./app
-COPY static ./static
+# Copier le reste du projet
+COPY . .
 
+# Exposer le port 7860 (obligatoire pour HF Spaces)
 EXPOSE 7860
-# Hugging Face Spaces fournit $PORT
-CMD uvicorn app.main:app --host 0.0.0.0 --port ${PORT:-7860}
+
+# Lancer FastAPI via Uvicorn (forme JSON recommandée)
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

Gradio

@@ -0,0 +1 @@
+Subproject commit 85120273af3c2585ca91c77d51d0595d17309d8b

__pycache__/main.cpython-312.pyc

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import pipeline
+import os
+
+# Charger le modèle (identique à celui de ton API)
+MODEL_NAME = os.getenv("HF_MODEL", "distilbert-base-uncased-finetuned-sst-2-english")
+sentiment_pipe = pipeline("sentiment-analysis", model=MODEL_NAME)
+
+# Fonction de prédiction
+def predict_sentiment(text):
+    result = sentiment_pipe(text)[0]
+    label = "positive" if result["label"].upper().startswith("POS") else "negative"
+    confidence = float(result["score"])
+    return f"Label: {label}, Confidence: {confidence:.4f}"
+
+# Interface Gradio
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.Textbox(lines=3, placeholder="Entrez votre texte ici..."),
+    outputs="text",
+    title="Sentiment Analysis Demo",
+    description=f"Modèle: {MODEL_NAME}"
+)
+
+# Lancer l'interface en local
+if __name__ == "__main__":
+    iface.launch(share=True)
+

app.py

@@ -40,7 +40,7 @@
 )
 
 # Serve static files (page HTML de test)
-STATIC_DIR = os.path.join(os.path.dirname(__file__), "..", "static")
+STATIC_DIR = os.path.join(os.path.dirname(__file__), "../static")
 app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
 
 @app.get("/", include_in_schema=False)

app/__pycache__/main.cpython-312.pyc

@@ -1,26 +1,40 @@
 <!doctype html>
 <html lang="fr">
+
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1" />
   <title>Test Sentiment API</title>
-  <style>
-    body { font-family: system-ui, -apple-system, Segoe UI, Roboto, sans-serif; margin: 2rem; max-width: 800px; }
-    textarea { width: 100%; min-height: 120px; }
-    button { padding: .6rem 1rem; cursor: pointer; }
-    .result { margin-top: 1rem; padding: 1rem; border: 1px solid #ddd; border-radius: .5rem; white-space: pre-wrap; }
-    code { background: #f7f7f7; padding: .2rem .4rem; border-radius: .3rem; }
-  </style>
+  <!-- Tailwind CSS CDN -->
+  <script src="https://cdn.tailwindcss.com"></script>
 </head>
-<body>
-  <h1>Test de l'API d'analyse de sentiments</h1>
-  <p>
-    Tapez un texte et cliquez sur <b>Analyser</b>. L'API appelle <code>POST /predict</code> et affiche le JSON de réponse.
-  </p>
 
-  <textarea id="text" placeholder="I love this product!"></textarea><br><br>
-  <button id="btn">Analyser</button>
-  <div class="result" id="result">Résultat…</div>
+<body class="bg-gray-100 min-h-screen flex items-center justify-center">
+  <div class="max-w-2xl w-full bg-white shadow-md rounded-2xl p-8">
+    <h1 class="text-2xl font-bold mb-4">Test de l'API pour l'analyse des sentiments</h1>
+    <p class="text-gray-700 mb-6">
+      Tapez un texte et cliquez sur <b>Analyser</b>.
+      <!-- L'API appelle <code class="bg-gray-100 px-1 py-0.5 rounded">POST /predict</code> et affiche le JSON de réponse. -->
+    </p>
+
+    <div class="mb-4">
+      <label for="text" class="block font-medium text-gray-800 mb-2">Votre texte</label>
+      <textarea id="text" rows="4" placeholder="I love this product!"
+        class="w-full border border-gray-300 rounded-lg p-3 focus:outline-none focus:ring-2 focus:ring-blue-500"></textarea>
+    </div>
+
+    <button id="btn" class="bg-blue-600 text-white px-5 py-2 rounded-lg hover:bg-blue-700 transition">
+      Analyser
+    </button>
+
+    <div class="mt-6">
+      <h5 class="text-lg font-semibold">Résultat</h5>
+      <pre id="result"
+        class="mt-2 border border-gray-300 rounded-lg bg-gray-50 p-4 text-sm text-gray-800 whitespace-pre-wrap">
+Résultat…
+      </pre>
+    </div>
+  </div>
 
   <script>
     const btn = document.getElementById('btn');
@@ -44,4 +58,5 @@ <h1>Test de l'API d'analyse de sentiments</h1>
     };
   </script>
 </body>
+
 </html>