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| import json | |
| import os | |
| import pandas as pd | |
| import requests | |
| import threading | |
| import streamlit as st | |
| from datasets import load_dataset, load_metric | |
| MODELS = ["CodeParrot", "InCoder", "CodeGen", "PolyCoder"] | |
| GENERATION_MODELS = ["CodeParrot", "InCoder", "CodeGen"] | |
| def load_examples(): | |
| with open("utils/examples.json", "r") as f: | |
| examples = json.load(f) | |
| return examples | |
| def load_evaluation(): | |
| # load task 2 of HumanEval and code_eval_metric | |
| os.environ["HF_ALLOW_CODE_EVAL"] = "1" | |
| human_eval = load_dataset("openai_humaneval") | |
| entry_point = f"check({human_eval['test'][2]['entry_point']})" | |
| test_func = "\n" + human_eval["test"][2]["test"] + "\n" + entry_point | |
| code_eval = load_metric("code_eval") | |
| return code_eval, test_func | |
| 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 | |
| ): | |
| # call space using its API endpoint | |
| url = ( | |
| f"https://hf.space/embed/codeparrot/{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({model_name: generated_text}) | |
| def generate_code_threads( | |
| generations, models, gen_prompt, max_new_tokens, temperature, seed | |
| ): | |
| threads = [] | |
| for model_name in models: | |
| # create the thread | |
| 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() | |
| def generate_teaser(gen_prompt): | |
| generations = [] | |
| generate_code(generations, "CodeParrot", gen_prompt, 8, 0.2, 42) | |
| return generations[0]["CodeParrot"] | |
| st.set_page_config(page_icon=":laptop:", layout="wide") | |
| # Introduction | |
| st.title("Genera codice online🤗") | |
| # Code generation | |
| col1, col2, col3 = st.columns([7, 1, 6]) | |
| with col1: | |
| st.markdown("**Modelli disponibli**") | |
| selected_models = st.multiselect( | |
| "Seleziona uno o più modelli pe generare del codice:", | |
| GENERATION_MODELS, | |
| default=GENERATION_MODELS, | |
| key=3, | |
| ) | |
| st.markdown(" ") | |
| st.markdown("**Esempi**") | |
| 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( | |
| "Seleziona un esempio per prendere spunto:", example_names | |
| ) | |
| example_text = examples[name2id[selected_example]]["value"] | |
| default_length = examples[name2id[selected_example]]["length"] | |
| with col3: | |
| st.markdown("**Impostazioni**") | |
| temperature = st.slider( | |
| "Temperature:", value=0.2, min_value=0.1, step=0.1, max_value=2.0 | |
| ) | |
| max_new_tokens = st.slider( | |
| "Token da generare:", | |
| 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( | |
| "Istruzioni per generare il codice:", | |
| value=example_text, | |
| height=200, | |
| ).strip() | |
| if st.button("Genera il codice e risparmi tempo", key=4): | |
| with st.spinner("Dammi un minuto, sto rubando un programmatore..."): | |
| # use threading | |
| 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]}**") | |
| for j in range(len(generations)): | |
| if selected_models[i] in generations[j].keys(): | |
| st.code(generations[j][selected_models[i]]) | |
| if len(generations) < len(selected_models): | |
| st.markdown("<span style='color:red'>Avviso: alcuni modelli vanno in timeout, prova un'altra volta o riduci il numero di token da generare.", unsafe_allow_html=True) | |