Update app.py

app.py

@@ -1,14 +1,20 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from datasets import load_dataset  # Import datasets library
 
-"""
-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("HuggingFaceH4/zephyr-7b-beta")
-#client = InferenceClient("meta-llama/Llama-3.2-1B-Instruct")
-#client = InferenceClient("microsoft/Phi-3.5-mini-instruct")
-client = InferenceClient("PleIAs/common_corpus")
+# Load the PleIAs/common_corpus dataset
+common_corpus = load_dataset("PleIAs/common_corpus")
 
+# Function to retrieve an example from the dataset
+def get_example_from_corpus(dataset, index):
+    if "train" in dataset:
+        example = dataset["train"][index]
+        return example
+    else:
+        raise ValueError("Dataset does not have a 'train' split.")
+
+# Initialize inference client
+client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
 
 def respond(
     message,
@@ -20,36 +26,36 @@ def respond(
 ):
     messages = [{"role": "system", "content": system_message}]
 
+    # Add historical interactions
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
+    # Add user's message
     messages.append({"role": "user", "content": message})
 
-    response = ""
-
-
-    mensagens = client.chat_completion(
+    # Get response from model
+    response = client.chat_completion(
         messages,
         max_tokens=max_tokens,
         temperature=temperature,
         top_p=top_p,
-    )
-    response = mensagens.choices[0].message.content
+    ).choices[0].message.content
 
     return response
 
+# Example usage of the dataset
+example_data = get_example_from_corpus(common_corpus, index=0)
+print("Example from PleIAs/common_corpus:", example_data)
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Gradio ChatInterface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Textbox(value="You are a friendly Chatbot. Your name is Juninho.", label="System message"),
-        gr.Slider(minimum=1, maximum=5096, value=1024, step=1, label="Max new tokens"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
             minimum=0.1,
@@ -61,6 +67,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
     demo.launch()