Update app.py
Browse files
app.py
CHANGED
@@ -15,8 +15,10 @@ load_dotenv()
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UPLOAD_DIR = "uploaded_data"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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SQL_DB_PATH = "data.db"
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HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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@@ -43,53 +45,46 @@ query_cache = {}
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history_log = []
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recent_history = []
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show_history_flag = False
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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else:
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def load_uploaded_csv_and_create_db(uploaded_file):
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if uploaded_file is None:
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return None
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print(f"[UPLOAD] CSV recebido: {uploaded_file}")
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engine = create_engine(f"sqlite:///{SQL_DB_PATH}")
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df = pd.read_csv(uploaded_file, sep=";", on_bad_lines="skip")
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df.to_sql("anomalia_vendas", engine, index=False, if_exists="replace")
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print(f"CSV carregado: {len(df)} linhas, {len(df.columns)} colunas")
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print(f"[DEBUG] Novo engine criado: {engine}")
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return engine
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)
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print("[SQL_AGENT] Atualizado com novo banco de dados.")
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refresh_sql_agent()
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def generate_initial_context(db_sample):
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return (
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@@ -224,15 +219,6 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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history_output = gr.JSON()
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history_btn.click(toggle_history, inputs=[], outputs=history_output)
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def handle_csv_upload(file):
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global engine
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try:
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engine = load_uploaded_csv_and_create_db(file)
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if engine is not None:
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refresh_sql_agent()
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except Exception as e:
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print(f"[ERRO] Falha ao processar novo CSV: {e}")
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csv_file.change(handle_csv_upload, inputs=csv_file, outputs=csv_file)
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UPLOAD_DIR = "uploaded_data"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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DEFAULT_CSV_PATH = "anomalia_vendas.csv"
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UPLOADED_CSV_PATH = os.path.join(UPLOAD_DIR, "tabela.csv")
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SQL_DB_PATH = "data.db"
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HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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history_log = []
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recent_history = []
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show_history_flag = False
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engine = None
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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# === Controle do CSV ativo ===
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def get_active_csv_path():
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"""Retorna o CSV ativo: o carregado ou o padrão."""
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if os.path.exists(UPLOADED_CSV_PATH):
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logging.info(f"[CSV] Usando arquivo CSV carregado: {UPLOADED_CSV_PATH}")
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return UPLOADED_CSV_PATH
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else:
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logging.info(f"[CSV] Usando arquivo CSV padrão: {DEFAULT_CSV_PATH}")
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return DEFAULT_CSV_PATH
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def create_engine_and_load_db(csv_path, sql_db_path):
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logging.info(f"[ENGINE] Criando engine com CSV: {csv_path}")
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engine = create_engine(f"sqlite:///{sql_db_path}")
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df = pd.read_csv(csv_path, sep=";", on_bad_lines="skip")
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df.to_sql("anomalia_vendas", engine, index=False, if_exists="replace")
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logging.info(f"[ENGINE] Banco criado com sucesso com {len(df)} linhas e {len(df.columns)} colunas")
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return engine
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# === Upload do CSV via UI ===
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def handle_csv_upload(file):
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global engine, db
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try:
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with open(UPLOADED_CSV_PATH, "wb") as f:
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f.write(file.read())
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logging.info(f"[UPLOAD] CSV salvo como: {UPLOADED_CSV_PATH}")
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engine = create_engine_and_load_db(UPLOADED_CSV_PATH, SQL_DB_PATH)
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db = SQLDatabase(engine=engine)
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logging.info("[UPLOAD] Novo banco carregado e DB atualizado.")
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except Exception as e:
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logging.error(f"[ERRO] Falha ao processar novo CSV: {e}")
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# === Inicialização ===
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engine = create_engine_and_load_db(get_active_csv_path(), SQL_DB_PATH)
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db = SQLDatabase(engine=engine)
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llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
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sql_agent = create_sql_agent(llm, db=db, agent_type="openai-tools", verbose=True, max_iterations=40, return_intermediate_steps=True)
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def generate_initial_context(db_sample):
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return (
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history_output = gr.JSON()
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history_btn.click(toggle_history, inputs=[], outputs=history_output)
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csv_file.change(handle_csv_upload, inputs=csv_file, outputs=csv_file)
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