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import os
from flask import Flask, request, jsonify, render_template, send_from_directory
from huggingface_hub import InferenceClient
from datasets import load_dataset
import markdown2
os.environ["HF_HOME"] = "/app/.cache"
app = Flask(__name__, static_folder='static', template_folder='templates')
hf_token = os.getenv("HF_TOKEN")
chat_doctor_dataset = load_dataset("avaliev/chat_doctor")
mental_health_dataset = load_dataset("Amod/mental_health_counseling_conversations")
client = InferenceClient(
"meta-llama/Meta-Llama-3-8B-Instruct",
token=hf_token,
)
def select_relevant_context(user_input):
mental_health_keywords = [
"anxious", "depressed", "stress", "mental health", "counseling",
"therapy", "feelings", "worthless", "suicidal", "panic", "anxiety"
]
medical_keywords = [
"symptoms", "diagnosis", "treatment", "doctor", "prescription", "medication",
"pain", "illness", "disease", "infection", "surgery"
]
if any(keyword in user_input.lower() for keyword in mental_health_keywords):
example = mental_health_dataset['train'][0]
context = f"Counselor: {example['Response']}\nUser: {example['Context']}"
elif any(keyword in user_input.lower() for keyword in medical_keywords):
example = chat_doctor_dataset['train'][0]
context = f"Doctor: {example['input']}\nPatient: {example['output']}"
else:
context = "You are a general assistant. Respond to the user's query in a helpful manner."
return context
def create_prompt(context, user_input):
prompt = (
f"{context}\n\n"
f"User: {user_input}\nAssistant:"
)
return prompt
def render_markdown(text):
return markdown2.markdown(text)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/static/<path:path>')
def send_static(path):
return send_from_directory('static', path)
@app.route('/chat', methods=['POST'])
def chat():
user_input = request.json['message']
context = select_relevant_context(user_input)
prompt = create_prompt(context, user_input)
response = ""
for message in client.chat_completion(
messages=[{"role": "user", "content": prompt}],
max_tokens=500,
stream=True,
):
response += message.choices[0].delta.content
formatted_response = render_markdown(response)
return jsonify({"response": formatted_response})
if __name__ == '__main__':
app.run(debug=False)
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