Guhanselvam commited on
Commit
b2523cd
·
verified ·
1 Parent(s): 978faeb

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +20 -24
app.py CHANGED
@@ -1,12 +1,8 @@
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]],
@@ -25,28 +21,28 @@ def respond(
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(
@@ -59,6 +55,6 @@ demo = gr.ChatInterface(
59
  ],
60
  )
61
 
62
-
63
  if __name__ == "__main__":
64
  demo.launch()
 
 
1
  import gradio as gr
2
  from huggingface_hub import InferenceClient
3
 
 
 
 
4
  client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
5
 
 
6
  def respond(
7
  message,
8
  history: list[tuple[str, str]],
 
21
 
22
  messages.append({"role": "user", "content": message})
23
 
24
+ # Check for financial-related keywords
25
+ financial_keywords = ["bank", "investment", "financial", "insurance", "savings", "interest", "loan", "mortgage", "credit"]
26
+ if any(keyword in message.lower() for keyword in financial_keywords):
27
+ response = ""
28
+ for message in client.chat_completion(
29
+ messages,
30
+ max_tokens=max_tokens,
31
+ stream=True,
32
+ temperature=temperature,
33
+ top_p=top_p,
34
+ ):
35
+ token = message.choices[0].delta.content
36
+ response += token
37
+ return response
38
+ else:
39
+ return "This is a financial FAQ chatbot. Please ask me about banking, investments, insurance, or savings."
40
+
41
+ # Initialize Gradio Chat Interface
42
  demo = gr.ChatInterface(
43
  respond,
44
  additional_inputs=[
45
+ gr.Textbox(value="You are a friendly financial FAQ Chatbot. Only answer questions about finance.", label="System message"),
46
  gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
47
  gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
48
  gr.Slider(
 
55
  ],
56
  )
57
 
 
58
  if __name__ == "__main__":
59
  demo.launch()
60
+