diff --git a/app/app.py b/app/app.py
index a83c9fc..9b97855 100644
--- a/app/app.py
+++ b/app/app.py
@@ -1,8 +1,352 @@
-from dash import Dash, html
+import json
+from typing import Any, Dict, Tuple
-app = Dash()
+import pandas as pd
+from app_styles import header_style
+from dash import (
+ Dash,
+ Input,
+ Output,
+ State,
+ callback,
+ dash_table,
+ dcc,
+ get_asset_url,
+ html,
+ no_update,
+)
+from dash.exceptions import PreventUpdate
+from data_chat import send_message
+from sql_utils import execute_query, test_db_connection
+
+external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
+
+app = Dash(__name__, external_stylesheets=external_stylesheets)
+app.index_string = header_style
+
+notification_md = """
+**Hinweise:**
+
+Aufgrund des sparsamen pricing Tiers kann es einige Sekunden dauern, bis die
+Verbindung zur Datenbank hergestellt wird. Im Falle eines Fehlers gern ein-zwei mal erneut
+versuchen.
+
+GPT-4o kann einige Fehler machen. Sollte dies passieren wird eine Fehlermeldung angezeigt.
+In diesem Fall lohnt es sich oft, die Anfrage leicht verändert erneut zu stellen und evtl
+zusätzliche Informationen zu geben.
+
+Das Modell ist dazu aufgefordert, den Output stets auf 100 Zeilen zu begrenzen.
+
+Alle Daten sind komplett zufällig generiert und haben keine Beziehung zu realen Personen.
+
+**Beispielfragen**:
+- Wie viele Kunden haben wir in Hannover?
+- Zeige alle Kunden in Bremen.
+- Berechne den gesamten Stromverbrauch aller Kunden in Magdeburg.
+- Zeige alle Kunden, die zwischen 2021 und 2022 mindestens 200 Kubikmeter Gas verbraucht haben.
+- Wie viele Kunden haben zwischen 2021 und 2022 weniger Strom verbraucht als zwischen 2022
+und 2023?
+
+Weitere Informationen zu den Daten, dem Code sowie zur Nutzung befinden sich in der README im
+[GiTea Repository](https://gitea.captain.particlephysics.de/quadfaselt/grid_application).
+"""
+
+err_style = {
+ "height": "0px",
+ "overflow": "hidden",
+ "transition": "height 0.5s ease-in-out",
+ "border-radius": "15px",
+ "background-color": "#FFCCCB",
+ "text-align": "center",
+ "color": "#FF6B6B",
+ "margin-top": "20px",
+ "margin-left": "20px",
+ "margin-right": "20px",
+ "font-weight": "bold",
+ "display": "flex",
+ "justify-content": "center",
+ "align-items": "center",
+}
+
+
+def render_table(df: pd.DataFrame) -> dash_table.DataTable:
+ """Create a Dash DataTable from a pandas DataFrame.
+
+ Parameters
+ ----------
+ df : pd.DataFrame
+ The input DataFrame to be rendered as a table.
+
+ Returns
+ -------
+ dash_table.DataTable
+ A Dash DataTable component with styled layout and pagination.
+ """
+ tab = dash_table.DataTable(
+ id="table",
+ columns=[{"name": i, "id": i} for i in df.columns],
+ data=df.to_dict("records"),
+ page_size=10,
+ style_table={
+ "overflowX": "auto",
+ "margin": "auto",
+ "width": "96%",
+ "margin-top": "20px",
+ },
+ style_cell={
+ "minWidth": "100px",
+ "width": "150px",
+ "maxWidth": "300px",
+ "overflow": "hidden",
+ "textOverflow": "ellipsis",
+ },
+ style_header={
+ "backgroundColor": "lightblue",
+ "fontWeight": "bold",
+ "color": "black",
+ },
+ )
+ return tab
+
+
+def get_layout() -> html.Div:
+ """Generate the layout for a Dash application.
+
+ This function creates a complex layout for a database chat interface
+ and a direct SQL query interface. It includes various Dash components
+ such as text areas, buttons, and a loading spinner.
+
+ The layout consists of:
+ - A header with title and logo
+ - A textarea for user input (database chat)
+ - A submit button for the database chat
+ - A Notification about the connection time and LLM performance
+ - An error message area
+ - A loading spinner and output area for database responses
+ - A section for direct SQL queries, including a textarea and submit button
+ - An output area for SQL query results
+
+ Returns
+ -------
+ html.Div
+ A Dash html.Div component containing the entire layout of the application.
+ """
+ global err_style
+ tmp_style = err_style.copy()
+ tmp_style["height"] = "0px"
+
+ start_value = "Stelle deine Frage an die Datenbank..."
+
+ layout = html.Div(
+ [
+ html.Div(
+ [
+ html.H1("Datenbank-Chat", className="heading"),
+ html.Img(src=get_asset_url("logo.png"), className="logo"),
+ ],
+ className="header-container",
+ ), # Header
+ html.Div(
+ "Ganz ohne SQL-Kenntnisse Daten zu Zählerstandmessungen unserer Kunden abrufen!",
+ style={"margin-left": "20px", "font-weight": "bold", "font-size": "20px"},
+ ),
+ dcc.Store(
+ id="tmp-value", data=start_value, storage_type="memory"
+ ), # Store previous prompt
+ dcc.Textarea(
+ id="input-field",
+ value=start_value,
+ style={"width": "96%", "height": 200, "margin-left": "20px"},
+ ), # Input field
+ html.Div([]), # Needed for keeping the layout clean
+ html.Button(
+ "Abschicken",
+ id="submit-button",
+ n_clicks=0,
+ disabled=False,
+ style={"margin-left": "20px"},
+ ), # Submit button
+ dcc.Markdown(
+ notification_md,
+ style={
+ "margin-left": "20px",
+ "margin-top": "20px",
+ "margin-right": "10px",
+ "background-color": "#C7E6F5",
+ "border-radius": "5px",
+ "padding": "10px",
+ },
+ ),
+ html.Div(
+ [html.P("Bitte eine neue Anfrage eingeben.")], id="error", style=tmp_style
+ ), # Error message (only visible if input is not updated but submit button is clicked)
+ dcc.Loading(
+ id="loading",
+ type="default",
+ children=[
+ html.Div(
+ "Hier erscheint die Antwort des KI-Modells.",
+ id="text-output",
+ style={
+ "whiteSpace": "pre-line",
+ "margin-top": "30px",
+ "margin-left": "20px",
+ "margin-right": "20px",
+ "border": "2px solid #86bc25",
+ "border-radius": "15px",
+ "padding": "20px",
+ },
+ )
+ ],
+ ),
+ html.H2(
+ "Direkte SQL-Abfrage",
+ style={"margin-left": "20px", "margin-top": "50px", "font-size": 24},
+ ), # SQL Header
+ html.Div(
+ (
+ "Hier kann der ausgegebene SQL-Code getestet oder mit selbst"
+ "geschriebenen Code verglichen werden."
+ ),
+ style={"margin-left": "20px", "font-weight": "bold", "font-size": "16px"},
+ ),
+ dcc.Textarea(
+ id="sql-input-field",
+ value="(Microsoft) SQL-Abfrage eingeben...",
+ style={"width": "96%", "height": 200, "margin-left": "20px"},
+ ), # SQL Input field
+ html.Div([]), # Needed for keeping the layout clean
+ html.Button(
+ "Abschicken",
+ id="sql-submit-button",
+ n_clicks=0,
+ disabled=False,
+ style={"margin-left": "20px"},
+ ), # Submit button
+ html.Div(id="sql-output", style={"margin-top": "10px"}), # SQL Output
+ ],
+ className="container",
+ )
+
+ return layout
+
+
+app.layout = html.Div([get_layout()])
+
+
+@callback(
+ Output("text-output", "children"),
+ Output("tmp-value", "data"),
+ Output("error", "style"),
+ Output("error", "children"),
+ Input("submit-button", "n_clicks"),
+ State("input-field", "value"),
+ State("tmp-value", "data"),
+ prevent_initial_call=True,
+ running=[
+ (Output("submit-button", "disabled"), True, False),
+ (
+ Output("submit-button", "style"),
+ {"opacity": 0.5, "margin-left": "20px"},
+ {"opacity": 1.0, "margin-left": "20px"},
+ ),
+ ],
+)
+def update_output(n_clicks: int, value: str, data: str) -> Tuple[Any, Any, Dict[str, str], Any]:
+ """Update the output based on user input and button clicks.
+
+ Parameters
+ ----------
+ n_clicks : int
+ Number of times the submit button has been clicked.
+ value : str
+ Current value of the input field.
+ data : str
+ Previously stored value.
+
+ Returns
+ -------
+ Tuple[str, str, Dict[str, Any]]
+ Updated output text, new stored value, and error style.
+ """
+ global err_style
+ db_connected = test_db_connection()
+ if n_clicks > 0 and value != data and db_connected:
+ result = send_message(value)
+ err_style["height"] = "0px"
+
+ # parse LLM response to dict, then try to execute the query
+ try:
+ parsed_result = json.loads(result, strict=False)
+
+ result_table = execute_query(parsed_result["query"])
+ children = [
+ html.P([html.B("Zusammenfassung: "), f"{parsed_result['summary']}"]),
+ html.P([html.B("SQL Abfrage: "), f"{parsed_result['query']}"]),
+ render_table(result_table),
+ ]
+ return children, value, err_style, html.P("")
+ except Exception as e:
+ err_style["height"] = "400px"
+ err_child = html.Div(f"Folgender Fehler ist aufgetreten: {e}.LLM Output: {result}.")
+
+ return no_update, value, err_style, err_child
+
+ elif not db_connected:
+ err_style["height"] = "50px"
+ err_child = html.P(
+ (
+ "Fehler beim Herstellen der Verbindung zur "
+ "Datenbank. Bitte versuche es später erneut."
+ )
+ )
+ return no_update, no_update, err_style, err_child
+
+ elif value == data:
+
+ err_style["height"] = "50px"
+ err_child = html.P("Bitte eine neue Anfrage eingeben.")
+ return no_update, no_update, err_style, err_child
+
+ raise PreventUpdate
+
+
+@callback(
+ Output("sql-output", "children"),
+ Input("sql-submit-button", "n_clicks"),
+ State("sql-input-field", "value"),
+ prevent_initial_call=True,
+)
+def run_sql_query(n_clicks: int, value: str) -> str:
+ """Run a SQL query and return the results.
+
+ Parameters
+ ----------
+ n_clicks : int
+ Number of times the submit button has been clicked.
+ value : str
+ Current value of the input field.
+
+ Returns
+ -------
+ str
+ The results of the SQL query.
+ """
+ if n_clicks > 0:
+ result = execute_query(value)
+ if isinstance(result, str):
+ global err_style
+ tmp_style = err_style.copy()
+ tmp_style["height"] = "100px"
+ tmp_style["padding"] = "20px"
+ err_child = html.Div(
+ [html.P(f"Fehler bei der Ausführung der Abfrage: {result}")], style=tmp_style
+ )
+ return err_child
+ else:
+ return render_table(result)
+ raise PreventUpdate
-app.layout = [html.Div(children="Hello World")]
server = app.server
diff --git a/app/app_styles.py b/app/app_styles.py
new file mode 100644
index 0000000..9e893b3
--- /dev/null
+++ b/app/app_styles.py
@@ -0,0 +1,37 @@
+header_style = """
+
+
+
+ {%metas%}
+ {%title%}
+ {%favicon%}
+ {%css%}
+
+
+
+ {%app_entry%}
+
+
+
+"""
diff --git a/app/assets/logo.png b/app/assets/logo.png
new file mode 100644
index 0000000..9399c00
Binary files /dev/null and b/app/assets/logo.png differ
diff --git a/app/data_chat.py b/app/data_chat.py
new file mode 100644
index 0000000..4cc3106
--- /dev/null
+++ b/app/data_chat.py
@@ -0,0 +1,117 @@
+import os
+
+from openai import OpenAI
+
+# from openai import AzureOpenAI
+
+# Set up credentials
+# NOTE: Usually I would use AzureOpenAI, but due to heavy rate
+# limitations on azure trial accounts, I am using OpenAI directly
+# for this project. However, this is how it would look like for
+# AzureOpenAI (credentials must be provided to environment):
+# client = AzureOpenAI(
+# azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
+# api_key=os.getenv("AZURE_OPENAI_KEY"),
+# api_version="2024-02-01",
+# )
+# MODEL = "sqlai" # deployment name
+
+# Set up the OpenAI client
+MODEL = "gpt-4o"
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+
+def send_message(message: str) -> str:
+ """Send a message to the openai chat completion API and return the response.
+
+ Parameters
+ ----------
+ message : str
+ The user's message to be sent to the chat completion API.
+
+ Returns
+ -------
+ str
+ The content of the assistant's response message.
+ """
+ system_message = """
+ Du bist ein hilfsbereiter, fröhlicher Datenbankassistent.
+ Du hilfst Benutzern bei der Erstellung von SQL-Abfragen für eine Datenbank eines
+ großen Energieversorgungsunternehmens. Die Datenbank enthält Tabellen für Adressen,
+ Zähler, Kunden und Ablesungen. Es werden Gaszähler (MeterType 'GAS') und Stromzähler
+ (MeterType 'ELT')unterschieden.
+
+ Besonders wichtig ist, dass die Ablesungen der Werte kumulativ sind. Wenn nach dem Verbrauch
+ gefragt wird, sollte der Unterschied zwischen zwei aufeinanderfolgenden Ablesungen berechnet
+ werden.
+
+ Verwende beim Erstellen Ihrer Antworten das folgende Datenbankschema:
+
+ CREATE TABLE Addresses (
+ ID INT PRIMARY KEY IDENTITY(1,1),
+ StreetName NVARCHAR(100),
+ HouseNumber NVARCHAR(10),
+ City NVARCHAR(50),
+ PostalCode NVARCHAR(10),
+ Longitude FLOAT,
+ Latitude FLOAT
+ );
+
+ CREATE TABLE Meters (
+ ID INT PRIMARY KEY IDENTITY(1,1),
+ Signature NVARCHAR(11),
+ MeterType NVARCHAR(3),
+ AddressID INT,
+ FOREIGN KEY (AddressID) REFERENCES Addresses(ID)
+ );
+
+ CREATE TABLE Customers (
+ ID INT PRIMARY KEY IDENTITY(1,1),
+ FirstName NVARCHAR(100),
+ LastName NVARCHAR(100),
+ GasMeterID INT,
+ EltMeterID INT,
+ FOREIGN KEY (GasMeterID) REFERENCES Meters(ID),
+ FOREIGN KEY (EltMeterID) REFERENCES Meters(ID)
+ );
+
+ CREATE TABLE Readings (
+ ID INT PRIMARY KEY IDENTITY(1,1),
+ CustomerID INT,
+ MeterID INT,
+ ReadingDate DATE,
+ ReadingValue INT,
+ FOREIGN KEY (CustomerID) REFERENCES Customers(ID),
+ FOREIGN KEY (MeterID) REFERENCES Meters(ID)
+ );
+
+ Füge Spaltenüberschriften in die Abfrageergebnisse ein.
+
+ Gib deine Antwort immer im folgenden JSON-Format an:
+
+ { "summary": "your-summary", "query": "your-query" }
+
+ Gib NUR JSON aus.
+ Ersetze in der vorangehenden JSON-Antwort "your-query" durch die Microsoft SQL Server Query,
+ um die angeforderten Daten abzurufen.
+ Ersetze in der vorangehenden JSON-Antwort "your-summary" durch eine Zusammenfassung der Abfrage.
+ Gib immer alle Spalten der Tabelle an.
+ Wenn die resultierende Abfrage nicht ausführbar ist, ersetze "your-query“ durch NA, aber ersetze
+ trotzdem "your-query" durch eine Zusammenfassung der Abfrage.
+ Verwende KEINE MySQL-Syntax, sondern AUSSCHLIESSLICH Microsoft SQL.
+ Begrenze die SQL-Abfrage immer auf 100 Zeilen.
+ Formatiere den Output bestmöglich.
+ """
+
+ response = client.chat.completions.create(
+ model=MODEL,
+ messages=[
+ {"role": "system", "content": system_message},
+ {"role": "user", "content": message},
+ ],
+ )
+
+ result_str = response.choices[0].message.content.replace("```json\n", "").replace("```", "")
+ if ("\n") not in result_str:
+ result_str = result_str.replace("\\", "\n")
+ return result_str
diff --git a/app/sql_utils.py b/app/sql_utils.py
new file mode 100644
index 0000000..c45f05d
--- /dev/null
+++ b/app/sql_utils.py
@@ -0,0 +1,66 @@
+import os
+from typing import Union
+
+import pandas as pd
+import pyodbc
+
+
+def test_db_connection() -> bool:
+ """Test the connection to Azure SQL Database.
+
+ This function attempts to establish a connection to an Azure SQL Database
+ using the connection string stored in the environment variable
+ 'AZURE_SQL_CONNECTION_STRING'. It makes up to 5 attempts to connect,
+ with a timeout of 480 seconds for each attempt.
+
+ Returns
+ -------
+ bool
+ True if the connection was successful, False otherwise.
+ """
+ connection_string = os.environ.get("AZURE_SQL_CONNECTION_STRING")
+ for i in range(5):
+ print(f"Trying to connect to Azure SQL Database... Attempt {i + 1}")
+ try:
+ pyodbc.connect(connection_string, timeout=480)
+ print("Connected to Azure SQL Database successfully!")
+ connected = True
+ break
+
+ except Exception as e:
+ print(f"Error connecting to Azure SQL Database: {e}")
+ connected = False
+ continue
+
+ return connected
+
+
+def execute_query(query: str) -> Union[pd.DataFrame, str]:
+ """Execute a SQL query on an Azure SQL Database and return the results.
+
+ This function connects to an Azure SQL Database using the connection string
+ stored in the environment variable 'AZURE_SQL_CONNECTION_STRING', executes
+ the provided SQL query, and returns the results as a pandas DataFrame.
+
+ Parameters
+ ----------
+ query : str
+ The SQL query to execute.
+
+ Returns
+ -------
+ Union[pd.DataFrame, str]
+ A pandas DataFrame containing the query results if successful,
+ or a string containing the error message if an exception occurs.
+ """
+ try:
+ connection_string = os.environ.get("AZURE_SQL_CONNECTION_STRING")
+ conn = pyodbc.connect(connection_string, timeout=240)
+ df = pd.read_sql(query, conn)
+ conn.close()
+ return df
+ except Exception as e:
+ return str(e)
+ finally:
+ if conn in locals():
+ conn.close()
diff --git a/poetry.lock b/poetry.lock
index caa9cd1..25a3107 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -11,6 +11,39 @@ files = [
{file = "alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e"},
]
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
+[[package]]
+name = "anyio"
+version = "4.4.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
+ {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
+
[[package]]
name = "babel"
version = "2.16.0"
@@ -305,6 +338,17 @@ files = [
{file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
]
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+ {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
[[package]]
name = "docutils"
version = "0.21.2"
@@ -422,6 +466,63 @@ setproctitle = ["setproctitle"]
testing = ["coverage", "eventlet", "gevent", "pytest", "pytest-cov"]
tornado = ["tornado (>=0.2)"]
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+ {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+ {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.27.2"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"},
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+
+[package.dependencies]
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
+
[[package]]
name = "pyflakes"
version = "3.2.0"
@@ -1460,6 +1778,17 @@ files = [
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
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+]
+
[[package]]
name = "snowballstemmer"
version = "2.2.0"
@@ -1640,6 +1969,26 @@ files = [
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
]
+[[package]]
+name = "tqdm"
+version = "4.66.5"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
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+ {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
[[package]]
name = "types-requests"
version = "2.32.0.20240712"
@@ -1794,4 +2143,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
-content-hash = "3f76ad143c2f6e35163d1bc8d123b97b9bf2a96f86914d240e0c7da2226f1d85"
+content-hash = "a6af9cf3858b3e05a3ac81716c79d6a3ed8e797da13391b2fc3e8c383741d00b"
diff --git a/pyproject.toml b/pyproject.toml
index 05ab8e4..061a0aa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,6 +34,7 @@ dash = "^2.17.1"
gunicorn = "^23.0.0"
pyodbc = "^5.1.0"
pandas = "^2.2.2"
+openai = "^1.43.0"
[tool.poetry.group.docs.dependencies]
mkdocs = "^1.6.0"