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af1b567
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1 Parent(s): e1f16a2

Update app.py

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Files changed (1) hide show
  1. app.py +116 -60
app.py CHANGED
@@ -1,64 +1,120 @@
1
  import gradio as gr
2
- from huggingface_hub import InferenceClient
3
-
4
- """
5
- 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
6
- """
7
- client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
8
-
9
-
10
- def respond(
11
- message,
12
- history: list[tuple[str, str]],
13
- system_message,
14
- max_tokens,
15
- temperature,
16
- top_p,
17
- ):
18
- messages = [{"role": "system", "content": system_message}]
19
-
20
- for val in history:
21
- if val[0]:
22
- messages.append({"role": "user", "content": val[0]})
23
- if val[1]:
24
- messages.append({"role": "assistant", "content": val[1]})
25
-
26
- messages.append({"role": "user", "content": message})
27
-
28
- response = ""
29
-
30
- for message in client.chat_completion(
31
- messages,
32
- max_tokens=max_tokens,
33
- stream=True,
34
- temperature=temperature,
35
- top_p=top_p,
36
- ):
37
- token = message.choices[0].delta.content
38
-
39
- response += token
40
- yield response
41
-
42
-
43
- """
44
- For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
45
- """
46
- demo = gr.ChatInterface(
47
- respond,
48
- additional_inputs=[
49
- gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
50
- gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
51
- gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
52
- gr.Slider(
53
- minimum=0.1,
54
- maximum=1.0,
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- value=0.95,
56
- step=0.05,
57
- label="Top-p (nucleus sampling)",
58
- ),
59
- ],
60
- )
61
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
62
 
63
  if __name__ == "__main__":
64
- demo.launch()
 
1
  import gradio as gr
2
+ import google.generativeai as genai
3
+ import os
4
+ import asyncio # Import для асинхронности
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5
 
6
+ # Безопасное получение API ключа
7
+ GEMINI_API_KEY = "AIzaSyBoqoPX-9uzvXyxzse0gRwH8_P9xO6O3Bc"
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+ if not GEMINI_API_KEY:
9
+ print("Error: GEMINI_API_KEY environment variable not set.")
10
+ exit()
11
+
12
+ genai.configure(api_key=GEMINI_API_KEY)
13
+
14
+ AVAILABLE_MODELS = ["gemini-1.5-flash", "gemini-1.5-pro", "gemini-2.0-flash-thinking-exp"]
15
+
16
+ # Инициализация моделей один раз при запуске приложения
17
+ MODELS = {model_name: genai.GenerativeModel(model_name=model_name) for model_name in AVAILABLE_MODELS}
18
+
19
+ async def respond(message, history, selected_model):
20
+ model = MODELS.get(selected_model)
21
+ if not model:
22
+ yield "Error: Selected model not available.", ""
23
+ return
24
+
25
+ try:
26
+ chat = model.start_chat(history=history)
27
+ response_stream = chat.send_message(message, stream=True)
28
+ full_response = ""
29
+ for chunk in response_stream:
30
+ full_response += (chunk.text or "")
31
+ yield full_response, "" # Пустая строка для thinking output
32
+ except Exception as e:
33
+ yield f"Error during API call: {e}", ""
34
+
35
+ async def respond_thinking(message, history, selected_model):
36
+ if "thinking" not in selected_model:
37
+ yield "Thinking model не выбрана.", ""
38
+ return
39
+
40
+ model = MODELS.get(selected_model)
41
+ if not model:
42
+ yield "Error: Selected model not available.", ""
43
+ return
44
+
45
+ yield "", "Думаю..." # Сообщение о начале размышлений
46
+
47
+ try:
48
+ response = model.generate_content(message)
49
+ thinking_process_text = ""
50
+ model_response_text = ""
51
+
52
+ if response.candidates:
53
+ for part in response.candidates[0].content.parts:
54
+ if hasattr(part, 'thought') and part.thought == True:
55
+ thinking_process_text += f"Model Thought:\n{part.text}\n\n"
56
+ else:
57
+ model_response_text += (part.text or "")
58
+
59
+ yield model_response_text, thinking_process_text
60
+ except Exception as e:
61
+ yield f"Error during API call: {e}", f"Error during API call: {e}"
62
+
63
+ def update_chatbot_function(model_name):
64
+ if "thinking" in model_name:
65
+ return respond_thinking
66
+ else:
67
+ return respond
68
+
69
+ with gr.Blocks() as demo:
70
+ gr.Markdown("# Gemini Chatbot с режимом размышления")
71
+
72
+ with gr.Row():
73
+ model_selection = gr.Dropdown(
74
+ AVAILABLE_MODELS, value="gemini-1.5-flash", label="Выберите модель Gemini"
75
+ )
76
+
77
+ chatbot = gr.ChatInterface(
78
+ respond, # Изначально используем асинхронную функцию respond
79
+ additional_inputs=[model_selection],
80
+ title="Gemini Chat",
81
+ description="Общайтесь с моделями Gemini от Google.",
82
+ )
83
+
84
+ thinking_output = gr.Code(label="Процесс размышления (для моделей с размышлением)")
85
+
86
+ def change_function(model_name):
87
+ return update_chatbot_function(model_name)
88
+
89
+ model_selection.change(
90
+ change_function,
91
+ inputs=[model_selection],
92
+ outputs=[chatbot],
93
+ )
94
+
95
+ async def process_message(message, history, model_name):
96
+ if "thinking" in model_name:
97
+ generator = respond_thinking(message, history, model_name)
98
+ response, thinking = await generator.__anext__() # Получаем первое значение (пустое сообщение и "Думаю...")
99
+ yield response, thinking
100
+ final_response, final_thinking = await generator.__anext__() # Получаем окончательный ответ и размышления
101
+ yield final_response, final_thinking
102
+ else:
103
+ async for response, _ in respond(message, history, model_name):
104
+ yield response, ""
105
+
106
+ chatbot.input_messages[-1].submit(
107
+ process_message,
108
+ inputs=[chatbot.input_messages[-1], chatbot.chat_memory, model_selection],
109
+ outputs=[chatbot.output_messages[-1], thinking_output],
110
+ scroll_to_output=True,
111
+ )
112
+
113
+ chatbot.input_messages[-1].change(
114
+ lambda: "",
115
+ inputs=[],
116
+ outputs=[thinking_output]
117
+ )
118
 
119
  if __name__ == "__main__":
120
+ demo.launch()