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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) | |