Update app.py

app.py

@@ -1,35 +1,144 @@
-from flask import Flask, request, render_template, jsonify
+from flask import Flask, render_template, request, jsonify
 import os
-from tempfile import NamedTemporaryFile
-from gradio_client import Client, handle_file  # Importez gradio_client
+import google.generativeai as genai
+import time 
 
 app = Flask(__name__)
 
-
-
-
+# Configuration
 token = os.environ.get("TOKEN")
+if not token:
+    raise ValueError("La variable d'environnement TOKEN n'est pas définie.")
 
-client = Client("Docfile/Traducteur",hf_token=token)
+genai.configure(api_key=token)
 
+generation_config = {
+    "temperature": 1,
+    "max_output_tokens": 8192,
+}
 
-@app.route('/')
-def index():
-    return render_template('traduction.html')
+safety_settings = [
+    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+]
+
+model = genai.GenerativeModel(
+    model_name="gemini-1.5-flash-002",
+    generation_config=generation_config,
+    safety_settings=safety_settings
+)
 
+source_languages = ["Francais", "English", "Spanish"]
+target_languages = ['nzebi', 'Fang(ntumu)','Fang(complet)','dikota', 'yipunu', 'omyene_nkomi']
 
+lang_files = {
+    'nzebi': 'Inzèbi.txt',
+    'gisir': 'Gisir.txt',
+    'dikota': 'dd.txt',
+    'yipunu': 'yipunu.pdf',
+    'Fang(complet)':'document_modifie.pdf',
+    'akele': 'Akélé.txt',
+    'Ghétsogo': 'Ghétsogo.txt',
+    'Shimo': 'Shimo.txt',
+    'omyene_nkomi': 'Omyènè_Nkomi.txt',
+    'isangu': 'Isangu.txt',
+    'Liwanzi': 'Liwanzi.txt',
+    'Fang(ntumu)': 'Fang(ntumu).txt'
+}
 
+def main_fang(query):
+    return "En maintenance"
 
-@app.route('/translate', methods=['POST'])
-def translate():
-    data = request.get_json()
-    input_text = data['input_text']
-    source_language = data['source_language']
-    target_language = data['target_language']
+async def translate(input_text, source, target):
+    if target == 'yipunu':
+        try:
+            pdf_path = lang_files[target]
+            d = time.time()
+            if not os.path.exists(pdf_path):
+                return f"Erreur: Le fichier {pdf_path} n'existe pas."
+            
+            sample_file = genai.upload_file(path=pdf_path, display_name="yipunu-reference")
+            s = time.time()
+            print(s-d)
+            
+            prompt = f"""
+            Using the provided Yipunu language reference PDF, translate the following text:
+            Input text: {input_text}
+            
+            Please provide only the translation without any additional explanation.
+            """
+            
+            print(input_text)
+            content = [sample_file, prompt]
+            response = model.generate_content(content, request_options={"timeout": 600})
+            
+            genai.delete_file(sample_file.name)
+            print(response.text)
+            return response.text
+            
+        except Exception as e:
+            return f"Erreur lors de la traduction: {str(e)}"
 
-    result = client.predict(input_text, source_language, target_language,api_name="/translate")
-    print(result)
+    elif target == 'Fang(complet)':
+        try:
+            pdf_path = lang_files[target]
+            d = time.time()
+            if not os.path.exists(pdf_path):
+                return f"Erreur: Le fichier {pdf_path} n'existe pas."
+            
+            sample_file = genai.upload_file(path=pdf_path, display_name="yipunu-reference")
+            s = time.time()
+            print(s-d)
+            
+            prompt = f"""
+            Using the provided Fang language reference PDF, translate the following text:
+            Input text: {input_text}
+            
+            Please provide only the translation without any additional explanation.
+            """
+            
+            print(input_text)
+            content = [sample_file, prompt]
+            response = model.generate_content(content, request_options={"timeout": 600})
+            
+            genai.delete_file(sample_file.name)
+            print(response.text)
+            return response.text
+            
+        except Exception as e:
+            return f"Erreur lors de la traduction: {str(e)}"
+    
+    else:
+        chemin_fichier = lang_files[target]
+        with open(chemin_fichier, 'r', encoding='utf-8') as fichier:
+            contenu_langue_arrivee = fichier.read()
+        
+        tt = f"""
+        contexte: {contenu_langue_arrivee}
+        
+        Utillisez les éléments de contexte suivants pour répondre à la question à la fin. 
+        Si vous ne connaissez pas la réponse, traduisez ce que vous pouvez et reecriver 
+        les autre comme ca, n'essayez pas d'inventer une réponse. Je veux que tu agisses 
+        comme un traducteur {target}. Je parle en français et tu traduis en {target} en 
+        te basant sur le contexte. Je ne veux aucune explication. Juste la réponse. 
+        Traduit ca < {input_text} >
+        """
+        print(input_text)
+        response = model.generate_content(tt)
+        print(response.text)
+        return response.text
 
-    return jsonify({'result': result})
+@app.route('/', methods=['GET', 'POST'])
+def index():
+    if request.method == 'POST':
+        input_text = request.form['input_text']
+        source_language = request.form['source_language']
+        target_language = request.form['target_language']
+        translated_text = translate(input_text, source_language, target_language)
+        return jsonify({'translated_text': translated_text})
+    return render_template('index.html', source_languages=source_languages, target_languages=target_languages)
 
-# ... autres routes ...
+if __name__ == '__main__':
+    app.run(debug=True)