| | import json |
| | import pandas as pd |
| | import requests |
| | import threading |
| | import streamlit as st |
| |
|
| |
|
| | MODELS = ["CodeParrot", "InCoder", "CodeGen", "PolyCoder"] |
| | GENERATION_MODELS = ["CodeParrot", "InCoder", "CodeGen"] |
| |
|
| |
|
| | @st.cache() |
| | def load_examples(): |
| | with open("utils/examples.json", "r") as f: |
| | examples = json.load(f) |
| | return examples |
| |
|
| |
|
| | def read_markdown(path): |
| | with open(path, "r") as f: |
| | output = f.read() |
| | st.markdown(output, unsafe_allow_html=True) |
| |
|
| |
|
| | def generate_code( |
| | generations, model_name, gen_prompt, max_new_tokens, temperature, seed |
| | ): |
| | |
| | url = ( |
| | f"https://hf.space/embed/loubnabnl/{model_name.lower()}-subspace/+/api/predict/" |
| | ) |
| | r = requests.post( |
| | url=url, json={"data": [gen_prompt, max_new_tokens, temperature, seed]} |
| | ) |
| | generated_text = r.json()["data"][0] |
| | generations.append(generated_text) |
| |
|
| |
|
| | def generate_code_threads( |
| | generations, models, gen_prompt, max_new_tokens, temperature, seed |
| | ): |
| | threads = [] |
| | for model_name in models: |
| | |
| | threads.append( |
| | threading.Thread( |
| | target=generate_code, |
| | args=( |
| | generations, |
| | model_name, |
| | gen_prompt, |
| | max_new_tokens, |
| | temperature, |
| | seed, |
| | ), |
| | ) |
| | ) |
| | threads[-1].start() |
| |
|
| | for t in threads: |
| | t.join() |
| |
|
| |
|
| | st.set_page_config(page_icon=":laptop:", layout="wide") |
| | with open("utils/table_contents.md", "r") as f: |
| | contents = f.read() |
| | st.sidebar.markdown(contents) |
| |
|
| | |
| | st.title("Code generation with 🤗") |
| | read_markdown("utils/intro.md") |
| |
|
| | |
| | st.subheader("1 - Code datasets") |
| | read_markdown("datasets/intro.md") |
| | read_markdown("datasets/github_code.md") |
| | col1, col2 = st.columns([1, 2]) |
| | with col1: |
| | selected_model = st.selectbox("", MODELS, key=1) |
| | read_markdown(f"datasets/{selected_model.lower()}.md") |
| |
|
| |
|
| | |
| | st.subheader("2 - Model architecture") |
| | read_markdown("architectures/intro.md") |
| | col1, col2 = st.columns([1, 2]) |
| | with col1: |
| | selected_model = st.selectbox("", MODELS, key=2) |
| | read_markdown(f"architectures/{selected_model.lower()}.md") |
| |
|
| | |
| | st.subheader("3 - Code models evaluation") |
| | read_markdown("evaluation/intro.md") |
| | read_markdown("evaluation/demo_humaneval.md") |
| |
|
| | |
| | st.subheader("4 - Code generation ✨") |
| | read_markdown("generation/intro.md") |
| | col1, col2, col3 = st.columns([7, 1, 6]) |
| | with col1: |
| | st.markdown("**Models**") |
| | selected_models = st.multiselect( |
| | "Select code generation models to compare:", |
| | GENERATION_MODELS, |
| | default=["CodeParrot"], |
| | key=3, |
| | ) |
| | st.markdown(" ") |
| | st.markdown("**Examples**") |
| | examples = load_examples() |
| | example_names = [example["name"] for example in examples] |
| | name2id = dict([(name, i) for i, name in enumerate(example_names)]) |
| | selected_example = st.selectbox( |
| | "Select one of the following examples or implement yours:", example_names |
| | ) |
| | example_text = examples[name2id[selected_example]]["value"] |
| | default_length = examples[name2id[selected_example]]["length"] |
| | with col3: |
| | st.markdown("**Generation settings**") |
| | temperature = st.slider( |
| | "Temperature:", value=0.2, min_value=0.0, step=0.1, max_value=2.0 |
| | ) |
| | max_new_tokens = st.slider( |
| | "Number of tokens to generate:", |
| | value=default_length, |
| | min_value=8, |
| | step=4, |
| | max_value=256, |
| | ) |
| | seed = st.slider("Random seed:", value=42, min_value=0, step=1, max_value=1000) |
| | gen_prompt = st.text_area( |
| | "Generate code with prompt:", |
| | value=example_text, |
| | height=200, |
| | ).strip() |
| | if st.button("Generate code!"): |
| | with st.spinner("Generating code..."): |
| | |
| | generations = [] |
| | generate_code_threads( |
| | generations, |
| | selected_models, |
| | gen_prompt=gen_prompt, |
| | max_new_tokens=max_new_tokens, |
| | temperature=temperature, |
| | seed=seed, |
| | ) |
| | for i in range(len(generations)): |
| | st.markdown(f"**{selected_models[i]}**") |
| | st.code(generations[i]) |
| | if len(generations) < len(selected_models): |
| | st.markdown("<span style='color:red'>Warning: Some models run into timeout, you can try generating code using the original subspaces: [InCoder](https://huggingface.co/spaces/loubnabnl/incoder-subspace), [CodeGen](https://huggingface.co/spaces/loubnabnl/codegen-subspace), [CodeParrot](https://huggingface.co/spaces/loubnabnl/codeparrot-subspace)</span>", unsafe_allow_html=True) |
| |
|
| | |
| | st.subheader("Resources") |
| | read_markdown("utils/resources.txt") |
| |
|