Update app.py

app.py

@@ -6,6 +6,7 @@ from datetime import datetime
 # Model description
 description = """
 # 🇫🇷 Lucie-7B-Instruct
+
 Lucie is a French language model based on Mistral-7B, fine-tuned on French data and instructions. 
 This demo allows you to interact with the model and adjust various generation parameters.
 """
@@ -23,13 +24,37 @@ On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Buil
 model_id = "OpenLLM-France/Lucie-7B-Instruct-v1"
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-tokenizer = AutoTokenizer.from_pretrained(model_id)
+# Get the token from environment variables
+hf_token = os.getenv('READTOKEN')
+if not hf_token:
+    raise ValueError("Please set the READTOKEN environment variable")
+
+# Initialize tokenizer and model with token authentication
+tokenizer = AutoTokenizer.from_pretrained(
+    model_id,
+    token=hf_token,
+    trust_remote_code=True
+)
+
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
+    token=hf_token,
     device_map="auto",
-    torch_dtype=torch.bfloat16
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True
 )
 
+def format_model_info(config):
+    info = []
+    important_keys = [
+        "model_type", "vocab_size", "hidden_size", "num_attention_heads",
+        "num_hidden_layers", "max_position_embeddings", "torch_dtype"
+    ]
+    for key in important_keys:
+        if key in config:
+            info.append(f"**{key}:** {config[key]}")
+    return "\n".join(info)
+
 @spaces.GPU
 def generate_response(system_prompt, user_prompt, temperature, max_new_tokens, top_p, repetition_penalty, top_k):
     # Construct the full prompt with system and user messages
@@ -59,7 +84,24 @@ def generate_response(system_prompt, user_prompt, temperature, max_new_tokens, t
 
 # Create the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown(description)
+    gr.Markdown(Title)
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                gr.Markdown("### Model Configuration")
+                gr.Markdown(format_model_info(config_json))
+                    
+        with gr.Column():
+            with gr.Group():
+                gr.Markdown("### Tokenizer Configuration")
+                gr.Markdown(f"""
+                    **Vocabulary Size:** {tokenizer.vocab_size}
+                    **Model Max Length:** {tokenizer.model_max_length}
+                    **Padding Token:** {tokenizer.pad_token}
+                    **EOS Token:** {tokenizer.eos_token}
+                    """)
+        with gr.Row():
+            gr.Markdown(join_us)
     
     with gr.Row():
         with gr.Column():
@@ -123,18 +165,67 @@ with gr.Blocks() as demo:
                 lines=10
             )
     
-    # Example prompts
+    # Example prompts with all parameters
     gr.Examples(
         examples=[
-            ["Tu es Lucie, une assistante IA française serviable et amicale.", "Bonjour! Comment vas-tu aujourd'hui?"],
-            ["Tu es une experte en intelligence artificielle.", "Peux-tu m'expliquer ce qu'est l'intelligence artificielle?"],
-            ["Tu es une poétesse française.", "Écris un court poème sur Paris."],
-            ["Tu es une experte en gastronomie française.", "Quels sont les plats traditionnels français les plus connus?"],
-            ["Tu es une historienne spécialisée dans l'histoire de France.", "Explique-moi l'histoire de la Révolution française en quelques phrases."]
+            # Format: [system_prompt, user_prompt, temperature, max_tokens, top_p, rep_penalty, top_k]
+            [
+                "Tu es Lucie, une assistante IA française serviable et amicale.",
+                "Bonjour! Comment vas-tu aujourd'hui?",
+                0.7,  # temperature
+                512,  # max_new_tokens
+                0.9,  # top_p
+                1.2,  # repetition_penalty
+                50   # top_k
+            ],
+            [
+                "Tu es une experte en intelligence artificielle.",
+                "Peux-tu m'expliquer ce qu'est l'intelligence artificielle?",
+                0.8,  # higher temperature for more creative explanation
+                1024, # longer response
+                0.95, # higher top_p for more diverse output
+                1.1,  # lower repetition penalty
+                40   # lower top_k for more focused output
+            ],
+            [
+                "Tu es une poétesse française.",
+                "Écris un court poème sur Paris.",
+                0.9,  # higher temperature for more creativity
+                256,  # shorter for poetry
+                0.95, # higher top_p for more creative language
+                1.3,  # higher repetition penalty for unique words
+                60   # higher top_k for more varied vocabulary
+            ],
+            [
+                "Tu es une experte en gastronomie française.",
+                "Quels sont les plats traditionnels français les plus connus?",
+                0.7,  # moderate temperature for factual response
+                768,  # medium length
+                0.9,  # balanced top_p
+                1.2,  # standard repetition penalty
+                50   # standard top_k
+            ],
+            [
+                "Tu es une historienne spécialisée dans l'histoire de France.",
+                "Explique-moi l'histoire de la Révolution française en quelques phrases.",
+                0.6,  # lower temperature for more factual response
+                1024, # longer for historical context
+                0.85, # lower top_p for more focused output
+                1.1,  # lower repetition penalty
+                30   # lower top_k for more consistent output
+            ]
+        ],
+        inputs=[
+            system_prompt,
+            user_prompt,
+            temperature,
+            max_new_tokens,
+            top_p,
+            repetition_penalty,
+            top_k
         ],
-        inputs=[system_prompt, user_prompt],
         outputs=output,
-        label="Exemples de prompts"
+        label="Exemples de prompts avec paramètres optimisés"
     )
     
     # Set up the generation event