Update app.py

app.py

@@ -2,9 +2,13 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
-client = InferenceClient("mlx-community/Hermes-3-Llama-3.1-70B-8bit")  # Garantir que o modelo seja compatível com `text-generation`
+#client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+#client = InferenceClient("meta-llama/Llama-3.2-1B-Instruct")
+#client = InferenceClient("microsoft/Phi-3.5-mini-instruct")
+#client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
+client = InferenceClient("mlx-community/gemma-2-27b-4bit")
 
 
 def respond(
@@ -25,18 +29,18 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    # Alterar a requisição para utilizar um modelo de `text-generation`
-    response = client.text_generation(
-        inputs=messages[-1]['content'],
+    response = ""
+
+
+    mensagens = client.chat_completion(
+        messages,
         max_tokens=max_tokens,
         temperature=temperature,
-        top_p=top_p
+        top_p=top_p,
     )
+    response = mensagens.choices[0].message.content
 
-    # Assumindo que o modelo de texto retorna a resposta como uma string diretamente
-    response_text = response['generated_text']  # Adapte de acordo com a estrutura da resposta
-
-    return response_text
+    return response
 
 
 """
@@ -60,4 +64,4 @@ demo = gr.ChatInterface(
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()