Create app.py

app.py

@@ -0,0 +1,88 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+import requests
+import os
+
+url = "http://59.110.170.104:8084/chat_completion"
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    do_sample: bool,
+    seed: int,
+    max_new_tokens,
+    temperature,
+    top_p,
+    top_k,
+    repetition_penalty
+):
+    messages = []
+
+    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 = ""
+    request_data = dict(
+        messages=messages,
+        max_new_tokens=max_new_tokens,
+        do_sample=do_sample,
+        seed=seed,
+        top_p=top_p,
+        top_k=top_k,
+        temperature=temperature,
+        repetition_penalty=repetition_penalty
+    )
+    print(request_data)
+    with requests.post(url, json=request_data, stream=True, headers={"Authorization": f"Bearer {os.environ['HF_TOKEN']}"}) as r:
+        # printing response of each stream
+        for chunk in r.iter_content(1024):
+            response += chunk.decode("utf8")
+            yield response
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+
+demo = gr.ChatInterface(
+    respond,
+    chatbot=gr.Chatbot(height=600),
+    additional_inputs=[
+        # gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Checkbox(True, label="do sample"),
+        gr.Number(42, precision=0, label="seed"),
+        gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.01, maximum=4.0, value=0.7, step=0.01, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=1.0,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+        gr.Slider(
+            minimum=0,
+            maximum=100,
+            value=0,
+            step=1,
+            label="Top-K (Top-K sampling)",
+        ),
+        gr.Slider(
+            minimum=1,
+            maximum=2,
+            value=1.03,
+            step=0.01,
+            label="repetition penalty",
+        ),
+    ],
+)
+
+
+if __name__ == "__main__":
+    demo.queue(default_concurrency_limit=2, max_size=10)
+    demo.launch()