Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,55 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
app.py
|
3 |
+
|
4 |
+
Main script to run the Course Recommendation Chatbot using Gradio.
|
5 |
+
"""
|
6 |
+
|
7 |
+
import os
|
8 |
+
import gradio as gr
|
9 |
+
from document_loader import load_document
|
10 |
+
from embeddings import process_documents_with_chroma
|
11 |
+
from chatbot import create_chatbot, ask_question
|
12 |
+
|
13 |
+
# Ensure your OpenAI API key is set in the environment variables.
|
14 |
+
api_key = os.getenv("OPENAI_API_KEY")
|
15 |
+
os.environ["OPENAI_API_KEY"] = api_key
|
16 |
+
|
17 |
+
def main(query):
|
18 |
+
"""Main function to load document, create embeddings, and generate a response.
|
19 |
+
|
20 |
+
Args:
|
21 |
+
query (str): User input query for course recommendation.
|
22 |
+
|
23 |
+
Returns:
|
24 |
+
str: The chatbot's response.
|
25 |
+
"""
|
26 |
+
file_path = "Courses_Details.pdf"
|
27 |
+
documents = load_document(file_path)
|
28 |
+
vector_store = process_documents_with_chroma(documents)
|
29 |
+
chatbot_system = create_chatbot(vector_store)
|
30 |
+
|
31 |
+
prompt = f"Suggest me best course for {query} as an output in a well-written, elaborative, and structured format along with its link."
|
32 |
+
return ask_question(chatbot_system, prompt)
|
33 |
+
|
34 |
+
# Define the Gradio interface
|
35 |
+
with gr.Blocks(css="""
|
36 |
+
.container {max-width: 800px; margin: auto; text-align: center;}
|
37 |
+
button {background-color: orange !important; color: white !important;}
|
38 |
+
#input_text, #output_text {margin-bottom: 20px;}
|
39 |
+
""") as demo:
|
40 |
+
gr.Markdown("""
|
41 |
+
# 🎓 Course Recommendation Chatbot
|
42 |
+
Welcome to the **Course Recommendation Chatbot**! This assistant can suggest the best courses based on your input, along with a well-structured description and course link.
|
43 |
+
|
44 |
+
Just enter the area you’re interested in (e.g., "machine learning") to receive a curated course recommendation!
|
45 |
+
""")
|
46 |
+
|
47 |
+
with gr.Group():
|
48 |
+
input_text = gr.Textbox(label="Ask your question about courses", placeholder="e.g., Best courses for machine learning", elem_id="input_text")
|
49 |
+
output_text = gr.Textbox(label="Course Information", placeholder="Your course recommendation will appear here...", elem_id="output_text")
|
50 |
+
|
51 |
+
submit_button = gr.Button("Get Recommendation", elem_id="submit_button")
|
52 |
+
|
53 |
+
submit_button.click(fn=main, inputs=input_text, outputs=output_text)
|
54 |
+
|
55 |
+
demo.launch(share=True)
|