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import gradio as gr
import os
from langchain_chroma.vectorstores import Chroma
from langchain_huggingface.embeddings import (
HuggingFaceEmbeddings,
HuggingFaceEndpointEmbeddings,
)
import json
from convert_to_json import data_to_json
from template import make_template_outputs, make_template_testcases
if os.environ.get("HUGGINGFACEHUB_API_TOKEN"):
embedding = HuggingFaceEndpointEmbeddings(
repo_id="sentence-transformers/all-MiniLM-L6-v2",
huggingfacehub_api_token=os.environ["HUGGINGFACEHUB_API_TOKEN"],
)
else:
embedding = HuggingFaceEmbeddings(
model_name="sentence-transformers/all-MiniLM-L6-v2"
)
count = 0
def increment_count():
global count
count += 1
return count
def print_n_value(n_value):
global no_tests
no_tests = n_value
return n_value # Return the value if needed for further processing
def submit_second_page(topic):
db_store = Chroma(collection_name="python-questions", persist_directory="./chroma", embedding_function=embedding)
questions = db_store.similarity_search(topic)
questions_json = json.loads(data_to_json(questions))
return questions_json, gr.update(choices=[d["question"] for d in questions_json])
def create_first_page(data_state):
# solution_visible = gr.State(False)
with gr.Column(visible=True) as page1:
gr.Markdown("# Programming in Python")
with gr.Row():
with gr.Column(scale=1):
topic = gr.Textbox(label="Select Topic")
submit2 = gr.Button("Submit", elem_id="submit2")
with gr.Tab("Question"):
question_select = gr.Dropdown(
label="Select Question", choices=[], interactive=True
)
question_display = gr.Textbox(label="Question", interactive=False)
with gr.Tab("Test Cases"):
testcases_state = gr.Markdown(label="Test Cases")
with gr.Tab("Output"):
outputs_md = gr.Markdown(label="Output") # JSON output component
with gr.Tab("Solution 🔒"):
solution = gr.Code("Solution Locked")
with gr.Column(scale=1):
code_input = gr.Code(
label="Write your code here",
language="python",
lines=10,
interactive=True,
)
run_button = gr.Button("Run")
# Connect buttons to functions
submit2.click(
fn=submit_second_page, inputs=[topic], outputs=[data_state, question_select]
)
question_select.change(
fn=make_template_testcases,
inputs=[question_select, data_state],
outputs=[solution, question_display, testcases_state, code_input],
)
run_button.click(
fn=lambda code, question, data: (
make_template_outputs(code, question, data)
),
inputs=[code_input, question_select, data_state],
outputs=[outputs_md],
)
return page1, question_select
# Initialize the Gradio app
with gr.Blocks(css=".small-button { padding: 5px 10px; font-size: 12px; }") as demo:
data_state = gr.State([])
# First page is now the new topic and question selection interface
page1_content, question_select = create_first_page(data_state)
demo.launch(share=True)
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