Uploading new App version

style.css

@@ -1,19 +1,18 @@
+/* Titoli principali h1 */
 .prose h1 {
-    font-family: 'Poppins', sans-serif;
+    font-family: 'Playfair Display', serif;
     font-size: 3rem;
-    font-weight: 700;
-    text-transform: uppercase;
-    letter-spacing: 2px;
+    font-weight: 600;
+    text-transform: none;
+    letter-spacing: 0.5px;
     text-align: center;
-    color: #222;
-    background: linear-gradient(45deg, #d4c9cc, #c4b8bb);
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
+    color: #ffffff;
     padding: 20px;
     margin: 20px 0;
     position: relative;
 }
 
+/* Linea decorativa sotto l'h1 */
 .prose h1::after {
     content: "";
     width: 60px;
@@ -24,6 +23,23 @@
     border-radius: 2px;
 }
 
+/* Titoli secondari h2 */
+.prose h2 {
+    font-family: 'Playfair Display', serif;
+    font-size: 2.2rem;
+    font-weight: 500;
+    letter-spacing: 0.3px;
+    color: #ffffff;
+    text-shadow: 1px 1px 3px rgba(0, 0, 0, 0.4);
+    padding: 10px 0;
+    margin: 10px 0 20px 0;
+    text-align: left;
+}
+
+body, label, button, span, li, p, .prose {
+    font-family: 'Playfair Display', serif;
+}
+
 #bar_plot, #line_plot {
     width: 100% !important;
     max-width: none !important;
@@ -45,6 +61,7 @@
     margin: 20px 0;
     position: center;
 }
+
 .fish{
         font-family: 'Poppins', sans-serif;
         font-size: 1.5rem;
@@ -75,11 +92,13 @@
     /*margin: 20px 0;*/
     position: center;
 }
+
 .barcontainer {
     display: flex;
     justify-content: center; 
     align-items: center; 
 }
+
 .leftarrow, .rightarrow {
     display: flex;
     justify-content: center; 
@@ -87,6 +106,7 @@
     font-size: 2.7rem;
     color: #1d60dd;
 }
+
 .leftarrow {
     transform: rotate(-270deg);
 }

utilities.py

@@ -1,32 +1,35 @@
 import csv
+import re
 import pandas as pd
 import sqlite3
 import gradio as gr
 import os
 from qatch.connectors.sqlite_connector import SqliteConnector
-
-def carica_sqlite(file_path, db_id):
+def extract_tables(file_path):
     conn = sqlite3.connect(file_path)
     cursor = conn.cursor()
     cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
     tabelle = cursor.fetchall()
     tabelle = [tabella for tabella in tabelle if tabella[0] != 'sqlite_sequence']
-    
+    return tabelle
+
+def extract_dataframes(file_path):
+    conn = sqlite3.connect(file_path)
+    tabelle = extract_tables(file_path) 
     dfs = {}
     for tabella in tabelle:
         nome_tabella = tabella[0]
         df = pd.read_sql_query(f"SELECT * FROM {nome_tabella}", conn)
         dfs[nome_tabella] = df
     conn.close()
-    data_output = {'data_frames': dfs,'db': None}
-    # data_output['db'] = SqliteConnector(
-    #     relative_db_path=file_path,
-    #     db_name=db_id,
-    # )
+    return dfs
+
+def carica_sqlite(file_path, db_id):
+    data_output = {'data_frames': extract_dataframes(file_path),'db':SqliteConnector(relative_db_path=file_path, db_name=db_id)}
     return data_output
 
 # Funzione per leggere un file CSV
-def carica_csv(file):
+def load_csv(file):
     df = pd.read_csv(file)
     return df
 
@@ -44,7 +47,7 @@ def load_data(data_path : str, db_name : str):
     if data_path.endswith(".sqlite") :
         data_output = carica_sqlite(data_path, db_name)
     elif data_path.endswith(".csv"):
-        data_output['data_frames'] = {f"{table_name}_table" : carica_csv(data_path)}
+        data_output['data_frames'] = {f"{table_name}_table" : load_csv(data_path)}
     elif data_path.endswith(".xlsx"):
         data_output['data_frames'] = carica_excel(data_path)
     else:
@@ -74,4 +77,56 @@ def csv_to_dict(file_path):
             if "price" in row:
                 row["price"] = float(row["price"])
             data.append(row)
-    return data
+    return data
+
+
+def increment_filename(filename):
+    base, ext = os.path.splitext(filename)
+    numbers = re.findall(r'\d+', base)
+    
+    if numbers:
+        max_num = max(map(int, numbers)) + 1
+        new_base = re.sub(r'(\d+)', lambda m: str(max_num) if int(m.group(1)) == max(map(int, numbers)) else m.group(1), base)
+    else:
+        new_base = base + '1'
+    
+    return new_base + ext
+
+def prepare_prompt(prompt, question, schema, samples):
+    prompt = prompt.replace("{schema}", schema).replace("{question}", question)
+    prompt += f" Some istanze: {samples}"
+    return prompt
+
+def generate_some_samples(connector, tbl_name):
+    samples = []
+    query = f"SELECT * FROM {tbl_name} LIMIT 3"
+    try:
+        sample_data = connector.execute_query(query)
+        samples.append(str(sample_data))
+    except Exception as e:
+        samples.append(f"Error: {e}")
+    return samples
+def extract_tables_dict(pnp_path):
+    tables_dict = {}
+    # df = pd.read_csv(pnp_path)
+    # with open(pnp_path, mode='r', encoding='utf-8') as file:
+    #     reader = csv.DictReader(file)
+    #     for row in reader:
+    #         tbl_name = row.get("tbl_name")
+    #         db_path = row.get("db_path")
+    #         if tbl_name and db_path:
+    #             print(db_path, tbl_name)
+    #             connector = SqliteConnector(relative_db_path=db_path, db_name=os.path.basename(db_path))
+    #             instances = generate_some_samples(connector, tbl_name)
+    #             if tbl_name not in tables_dict:
+    #                 tables_dict[tbl_name] = []
+    #             tables_dict[tbl_name].extend(instances)
+
+    with open(pnp_path, mode='r', encoding='utf-8') as file:
+        reader = csv.DictReader(file)
+        for row in reader:
+            tbl_name = row.get("tbl_name")
+            if tbl_name not in tables_dict:
+                tables_dict[tbl_name] = []
+            #tables_dict[tbl_name].append(row)
+    return tables_dict