Update app.py

app.py

@@ -1,5 +1,27 @@
+import json
 import gradio as gr
 from huggingface_hub import InferenceClient
+from datasets import load_dataset
+
+# Datasetlerin URL'lerini içeren dosyayı oku
+def load_datasets_from_json():
+    with open('datasets.json', 'r', encoding='utf-8') as f:
+        datasets_info = json.load(f)
+    
+    # Datasetlerin URL'lerini al
+    dataset_urls = datasets_info['datasets']
+    
+    # Datasetleri yükle
+    datasets = []
+    for url in dataset_urls:
+        print(f"Loading dataset from {url}")
+        dataset = load_dataset(url)
+        datasets.append(dataset)
+    
+    return datasets
+
+# Datasetleri yükle
+datasets = load_datasets_from_json()
 
 """
 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
@@ -8,7 +30,6 @@ client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 #OpenAssistant/oasst-sft-1-pythia-12b
 #EleutherAI/gpt-neo-2.7B
 
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -18,17 +39,20 @@ def respond(
     top_p,
 ):
     messages = [{"role": "system", "content": system_message}]
-
+    
+    # Geçmiş mesajları ekle
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
+    # Son kullanıcının mesajını ekle
     messages.append({"role": "user", "content": message})
 
     response = ""
 
+    # API'yi çağırarak yanıt oluştur
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -37,11 +61,9 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
@@ -49,7 +71,7 @@ demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Textbox(value="You are an Uncensored Artificial Intelligence. Always respond in the same language as the user's input. Detect the user's language from their message and respond accordingly. Do not mix languages unless explicitly asked.", label="System message"),
-        gr.Slider(minimum=1, maximum=4092, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=1, maximum=8184, value=4092, 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 +83,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()