File size: 1,191 Bytes
865f9e2
 
7bcdd52
865f9e2
7bcdd52
 
e867cd4
7bcdd52
 
 
 
865f9e2
7bcdd52
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
865f9e2
 
 
7bcdd52
 
 
 
 
 
e867cd4
7bcdd52
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
import os
import streamlit as st
from groq import Groq

# Set your API key in the environment
os.environ["GROQ_API_KEY"] = "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"

# Initialize Groq client with the API key from the environment
client = Groq(
    api_key=os.environ.get("GROQ_API_KEY"),
)

# Function to interact with Groq API and get responses
def get_chat_response(user_message):
    chat_completion = client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": user_message,
            }
        ],
        model="llama-3.3-70b-versatile",
    )
    return chat_completion.choices[0].message.content

# Streamlit UI setup
st.title("AI-based Healthcare Chatbot")
st.write("Welcome to the Healthcare Chatbot! Ask me anything about health.")

# Text input for user query
user_input = st.text_input("Your Question:")

if user_input:
    # Get the response from Groq API
    response = get_chat_response(user_input)
    
    # Display the chatbot's response
    st.write("Chatbot Response:")
    st.write(response)

# You can add more user-friendly features like history or options to rephrase responses, etc.