Update app.py

app.py

@@ -1,12 +1,17 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
+import os
+from gpt4all import GPT4All
 """
 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("gai-labs/strela")
-
-
+model = GPT4All(model_name='strela-q4_k_m.gguf', model_path=os.getcwd())
+
+def stop_on_token_callback(token_id, token_string):
+    print(token_string, end='')
+    if '#' in token_string:
+        return False
+    else:
+        return True
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -15,30 +20,22 @@ def respond(
     temperature,
     top_p,
 ):
-    messages = [{"role": "system", "content": 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
-
+    chat = f"""### System:
+{system_message}
+"""
+    for group in history:
+        chat += f"""### Human:
+{group[0]}
+### Assistant:
+{group[1]}"""
+    chat += f"""### Human:
+    {message}
+    ### Assistant:
+"""
+    tokens = ""
+    for token in model.generate(chat, temp=temperature, callback=stop_on_token_callback, streaming=True):
+        tokens += token
+        yield tokens
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """