Update app.py

app.py

@@ -20,7 +20,7 @@ max_new_tokens = 3000
 top_p = 0.95
 repetition_penalty = 1.2
 
-model_name = "PleIAs/Cassandre-RAG"
+model_name = "dataesr/"
 
 # Initialize vLLM
 llm = LLM(model_name, max_model_len=8128)
@@ -56,8 +56,8 @@ def hybrid_search(text):
     return document, document_html
 
 
-class CassandreChatBot:
-    def __init__(self, system_prompt="Tu es Cassandre, le chatbot de l'Éducation nationale qui donne des réponses sourcées."):
+class ESRChatBot:
+    def __init__(self, system_prompt="Tu es ESR, le chatbot de l'Éducation nationale qui donne des réponses sourcées."):
         self.system_prompt = system_prompt
 
     def predict(self, user_message):
@@ -110,8 +110,8 @@ def format_references(text):
 
     return ''.join(parts)
 
-# Initialize the CassandreChatBot
-cassandre_bot = CassandreChatBot()
+# Initialize the ESRChatBot
+ESR_bot = ESRChatBot()
 
 # CSS for styling
 css = """
@@ -155,20 +155,20 @@ css = """
 
 # Gradio interface
 def gradio_interface(user_message):
-    response, sources = cassandre_bot.predict(user_message)
+    response, sources = ESR_bot.predict(user_message)
     return response, sources
 
 # Create Gradio app
 demo = gr.Blocks(css=css)
 
 with demo:
-    gr.HTML("""<h1 style="text-align:center">Cassandre</h1>""")
+    gr.HTML("""<h1 style="text-align:center">ESR</h1>""")
     with gr.Row():
         with gr.Column(scale=2):
             text_input = gr.Textbox(label="Votre question ou votre instruction", lines=3)
-            text_button = gr.Button("Interroger Cassandre")
+            text_button = gr.Button("Interroger ESR")
         with gr.Column(scale=3):
-            text_output = gr.HTML(label="La réponse de Cassandre")
+            text_output = gr.HTML(label="La réponse de ESR")
     with gr.Row():
         embedding_output = gr.HTML(label="Les sources utilisées")