Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
|
3 |
+
import torch
|
4 |
+
|
5 |
+
# Load model and tokenizer
|
6 |
+
model_name = "ombhojane/mental-health-assistant"
|
7 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
8 |
+
model = AutoModelForCausalLM.from_pretrained(model_name)
|
9 |
+
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
|
10 |
+
|
11 |
+
def generate_response(message, history):
|
12 |
+
# Format the input with chat history
|
13 |
+
prompt = ""
|
14 |
+
for user_msg, bot_msg in history:
|
15 |
+
prompt += f"User: {user_msg}\nAssistant: {bot_msg}\n"
|
16 |
+
prompt += f"User: {message}\nAssistant:"
|
17 |
+
|
18 |
+
# Generate response
|
19 |
+
response = pipe(
|
20 |
+
prompt,
|
21 |
+
max_length=256,
|
22 |
+
num_return_sequences=1,
|
23 |
+
temperature=0.7,
|
24 |
+
top_p=0.9,
|
25 |
+
do_sample=True,
|
26 |
+
pad_token_id=tokenizer.eos_token_id
|
27 |
+
)[0]["generated_text"]
|
28 |
+
|
29 |
+
# Extract just the assistant's response
|
30 |
+
try:
|
31 |
+
assistant_response = response.split("Assistant:")[-1].strip()
|
32 |
+
except:
|
33 |
+
assistant_response = response
|
34 |
+
|
35 |
+
return assistant_response
|
36 |
+
|
37 |
+
# Create the Gradio interface
|
38 |
+
with gr.Blocks(css="footer {visibility: hidden}") as demo:
|
39 |
+
gr.Markdown(
|
40 |
+
"""
|
41 |
+
# 🧠 Mental Health Assistant
|
42 |
+
Welcome! I'm here to provide support and guidance for your mental health concerns.
|
43 |
+
While I can offer helpful insights, please remember I'm not a replacement for professional medical advice.
|
44 |
+
"""
|
45 |
+
)
|
46 |
+
|
47 |
+
chatbot = gr.Chatbot(
|
48 |
+
height=400,
|
49 |
+
show_label=False,
|
50 |
+
container=True,
|
51 |
+
bubble_full_width=False,
|
52 |
+
)
|
53 |
+
|
54 |
+
with gr.Row():
|
55 |
+
msg = gr.Textbox(
|
56 |
+
scale=4,
|
57 |
+
show_label=False,
|
58 |
+
placeholder="Type your message here...",
|
59 |
+
container=False
|
60 |
+
)
|
61 |
+
submit = gr.Button("Send", scale=1, variant="primary")
|
62 |
+
|
63 |
+
gr.Examples(
|
64 |
+
examples=[
|
65 |
+
"I've been feeling really anxious lately",
|
66 |
+
"How can I improve my sleep habits?",
|
67 |
+
"I'm having trouble focusing at work",
|
68 |
+
],
|
69 |
+
inputs=msg
|
70 |
+
)
|
71 |
+
|
72 |
+
gr.Markdown(
|
73 |
+
"""
|
74 |
+
### Tips for best results:
|
75 |
+
- Be specific about how you're feeling
|
76 |
+
- Ask direct questions
|
77 |
+
- Share relevant context
|
78 |
+
- Take your time to explain your situation
|
79 |
+
"""
|
80 |
+
)
|
81 |
+
|
82 |
+
# Set up event handlers
|
83 |
+
submit_click = submit.click(
|
84 |
+
generate_response,
|
85 |
+
inputs=[msg, chatbot],
|
86 |
+
outputs=[chatbot],
|
87 |
+
queue=True
|
88 |
+
)
|
89 |
+
submit_click.then(lambda: "", None, msg, queue=False)
|
90 |
+
|
91 |
+
msg.submit(
|
92 |
+
generate_response,
|
93 |
+
inputs=[msg, chatbot],
|
94 |
+
outputs=[chatbot],
|
95 |
+
queue=True
|
96 |
+
).then(lambda: "", None, msg, queue=False)
|
97 |
+
|
98 |
+
demo.launch()
|