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Update app.py
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app.py
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from llama_cpp import Llama
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import gradio as gr
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llm = Llama(
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model_path=
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n_ctx=4096,
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n_threads=4,
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n_gpu_layers=
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)
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def text2sql(question):
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from llama_cpp import Llama
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import gradio as gr
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import os
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# Локальный путь, куда будет скачана модель при запуске
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MODEL_PATH = "unsloth.Q4_K_M.gguf"
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# Если модели ещё нет — скачиваем
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if not os.path.exists(MODEL_PATH):
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import requests
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url = "https://huggingface.co/eliza555beth2002/DeepSeek-R1-Distill-Text2SQL-OneEpoch-GGUF-q4/resolve/main/unsloth.Q4_K_M.gguf"
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print("📥 Скачиваю модель из Hugging Face...")
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r = requests.get(url, stream=True)
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with open(MODEL_PATH, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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print("Модель скачана успешно!")
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# Загружаем модель Llama.cpp
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llm = Llama(
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model_path=MODEL_PATH,
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n_ctx=4096,
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n_threads=4,
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n_gpu_layers=0, # если на CPU — ставим 0
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verbose=False,
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)
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# Основная функция
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def text2sql(question):
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schema = """
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create table Authors(
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AuthorID integer not null primary key check(AuthorID>0),
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AuthorFIO varchar(40) not null
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);
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create table Books(
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Cipher integer not null primary key check(Cipher>0),
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BookName varchar(4000) not null,
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BookTheme varchar(30) not null
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check(BookTheme in('Любовь','Дружба','Смерть','Общественные проблемы','Внутренние противоречия')),
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BookGenre varchar(15) not null
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check(BookGenre in('Роман','Поэма','Рассказ','Пьеса','Эпопея','Драма'))
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);
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create table Wrote(
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IDAuthor integer not null check(IDAuthor>0),
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BookCipher integer not null check(BookCipher>0),
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foreign key(IDAuthor) references Authors(AuthorID),
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foreign key(BookCipher) references Books(Cipher),
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primary key(IDAuthor, BookCipher)
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);
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"""
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prompt = f"""Ты — помощник, который преобразует естественный язык в SQL.
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Используй приведённую схему таблиц.
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Вопрос: {question}
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Контекст базы данных:
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{schema}
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Ответь ТОЛЬКО SQL-запросом в формате:
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```sql
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SELECT ...
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```"""
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# Генерация
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output = llm(
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prompt,
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max_tokens=512,
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temperature=0.2,
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stop=["```"],
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)
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text = output["choices"][0]["text"].strip()
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return text
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# Интерфейс Gradio
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demo = gr.Interface(
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fn=text2sql,
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inputs=gr.Textbox(label="Введите вопрос на естественном языке"),
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outputs=gr.Textbox(label="Сгенерированный SQL-запрос"),
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title="🧠 DeepSeek Text2SQL Demo",
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description="Модель DeepSeek-R1-Distill преобразует текст в SQL-запрос по заданной схеме."
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)
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if __name__ == "__main__":
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demo.launch()
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