Update app.py

app.py

@@ -8,6 +8,37 @@ import transformers
 transformers.utils.move_cache()
 device = "cuda" if torch.cuda.is_available() else "cpu"
 import os
+def respond5(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
 password1=os.environ["password"]
 def respond4(
     message,
@@ -359,6 +390,21 @@ with gr.Blocks(css=css) as demo2:
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
+aaaa=gr.ChatInterface(
+    respond5,
+    additional_inputs=[
+        gr.Textbox(value="You are a helpful law helper.You have to answer only the questions about law.Do not answer anything else.", label="System message",  interactive=False),
+        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,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
 ad=gr.ChatInterface(
     respond2,
     additional_inputs=[
@@ -438,6 +484,6 @@ ab= gr.ChatInterface(
 )
 if __name__ == "__main__":
     with gr.Blocks() as ai:
-        gr.TabbedInterface([aa, ac, ab, ae, demo2], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)","image create"])
+        gr.TabbedInterface([aa, ac, ab, ae, aaaa,demo2], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)", "gpt4(only for law questions)","image create"])
     ai.queue(max_size=300)
     ai.launch()