| 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]) |
|
|
| |
| st.subheader("Resources") |
| read_markdown("utils/resources.txt") |
|
|