langchain pandas working with sp500 sample but not with meteostat df

JAlcocerT · Dec 25, 2024 · 84dee60 · 84dee60
1 parent fb46621
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diff --git a/Dockerfile b/Dockerfile
@@ -1,5 +1,6 @@
 # https://hub.docker.com/_/python
-FROM python:3.8
+FROM python:3.11   
+# 3.8
 LABEL org.opencontainers.image.source=https://github.com/JAlcocerT/Py_Trip_Planner
 LABEL org.opencontainers.image.description="Python Trip Planner with Weather"
 LABEL org.opencontainers.image.licenses=GPL-3.0
@@ -33,6 +34,6 @@ CMD python ./app/app.py
 #Pushing the image to the registry:
 
 ##dockerhub
-#docker build -t reisikei/pytripplanner .
+#docker build -t jalcocert/pytripplanner .
 #docker login
-#docker push reisikei/pytripplanner
+#docker push jalcocert/pytripplanner
diff --git a/README.md b/README.md
@@ -26,15 +26,15 @@ Using **historical weather data** together with location data in a DASH App to a
 * [Deploy the App](https://github.com/JAlcocerT/Py_Trip_Planner/tree/main/Deploy)
 * Further Description at: 
   * For V1: Historical Weather, with [MeteoStat](https://jalcocert.github.io/JAlcocerT/python-trip-planner/)
-  * For V2: Historical and [Forecasted Weather](https://jalcocert.github.io/JAlcocerT/python-weather-forecast-with-open-meteo-api/)
+  * [For V2](https://github.com/JAlcocerT/Py_Trip_Planner/releases): Historical and [Forecasted Weather](https://jalcocert.github.io/JAlcocerT/python-weather-forecast-with-open-meteo-api/)
   * For V3: Adding AI capabilities - [Chat with Weather Data DF via LangChain](https://jalcocert.github.io/JAlcocerT/using-langchain-with-pandas-df/)
 
 
 
-###$ Quick Setup
+#### Quick Setup
 
 > [!IMPORTANT]
-> Prepare the API key for v3
+> Prepare the OPENAI_API key for v3
 
 
 <details>

diff --git a/Tests/app.py b/Tests/app.py
@@ -0,0 +1,155 @@
+import dash
+from dash import html 
+from dash import dcc
+from dash.dependencies import Input, Output
+
+from datetime import datetime, timedelta, date
+
+from meteostat import Point#, Daily
+from meteostat import Daily as MeteoDaily
+from meteostat import Stations #new in v1.2
+
+from openmeteo_py import Hourly, Options, OWmanager #new in V2
+from openmeteo_py import Daily as OpenMeteoDaily #new in V2
+
+import pandas as pd  #new in V2
+
+import plotly.graph_objects as go  #new in V2
+import plotly.express as px
+import dash_leaflet as dl
+
+from helpers.plot_logic import plot_tmax_boxplot, plot_weather_data, plot_forecast_data_hourly
+from helpers.update_logic import update_markers, update_weather_plots
+
+
+# def load_html(file_path):
+#     with open(file_path, 'r') as f:
+#         return html.Div(
+#             dangerously_allow_html=True,
+#             children=f.read()
+#         )
+
+# def load_html(file_path):
+#     with open(file_path, 'r') as f:
+#         content = f.read()
+#     return html.Div(
+#         dangerously_set_inner_html=content
+#     )
+
+app = dash.Dash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])
+
+app.layout = html.Div(
+    style={'backgroundColor': '#F5F5F5'},
+    children=[
+        html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px', 'backgroundColor': 'F5F5F5'}),
+        dcc.DatePickerRange(
+            id='date-picker',
+            min_date_allowed=datetime(2000, 1, 1),
+            max_date_allowed=date.today() - timedelta(days=7),
+            start_date=datetime(2021, 1, 1),
+            end_date=datetime(2024, 12, 25),
+            display_format='MMM DD, YYYY',
+            style={
+                'font-size': '6px', 'display': 'inline-block', 'border-radius': '2px', 
+                'border': '1px solid #ccc', 'color': '#2E2E33', 
+                'border-spacing': '0', 'border-collapse': 'separate'
+            }
+        ),
+        dl.Map(
+            [dl.TileLayer(), dl.LayerGroup(id="layer")],
+            id='map',
+            style={'width': '100%', 'height': '50vh', 'margin': "auto", "display": "block"},
+            center=[35, 25],
+            zoom=4,
+        ),
+        html.H2('Historical Weather Data', style={'textAlign': 'center', 'padding': '20px'}),
+        dcc.Graph(id='weather-plot'),
+        html.Label('Select a variable to display in the Boxplot:'),
+        dcc.Dropdown(
+            id='boxplot-variable',
+            options=[
+                {'label': 'Temperature Max °C', 'value': 'tmax'},
+                {'label': 'Temperature Min °C', 'value': 'tmin'},
+                {'label': 'Wind (km/h)', 'value': 'wspd'},
+                {'label': 'Rain (mm)', 'value': 'prcp'},
+            ],
+            value='tmax'
+        ),
+        dcc.Graph(id='tmax-boxplot'),
+        html.H2('Forecasted Weather Data', style={'textAlign': 'center', 'padding': '20px'}),
+        dcc.Graph(id='forecast-plot'),
+        # html.Div(
+        #     [
+        #         load_html('about.html')
+        #     ],
+        # html.Div(
+        #     [
+        #         html.Div(
+        #             [
+        #                 html.H4("About"),
+        #                 html.A("My Blog - FossEngineer", href="https://fossengineer.com", target="_blank"),
+        #                 html.Br(),
+        #                 html.A("About this App - FossEngineer", href="https://fossengineer.com/python-trip-planner/", target="_blank"),
+        #                 html.Br(),
+        #                 html.A("Source Code", href="https://github.com/JAlcocerT/Py_Trip_Planner/", target="_blank"),
+        #             ],
+        #             style={'backgroundColor': '#F5F5F5', 'text-align': 'center'}
+        #         ),
+        #     ],
+        #    style={'display': 'flex', 'justify-content': 'center', 'align-items': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}
+        #)
+    ]
+)
+
+@app.callback(
+    Output('layer', 'children'),
+    [Input('map', 'click_lat_lng')],
+)
+# def update_markers(click_lat_lng):
+#     if not click_lat_lng:
+#         click_lat_lng = [35, 25]
+#     return [
+#         dl.Marker(position=click_lat_lng, children=dl.Tooltip(f"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})")),
+#         dl.CircleMarker(center=[nearest_lat, nearest_lon], color="#188399",)
+#     ]
+
+@app.callback(
+    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure'), Output('forecast-plot','figure')],
+    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],
+)
+def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):
+    global nearest_lat, nearest_lon
+    if not click_lat_lng:
+        lat, lon = 35, 25
+    else:
+        lat = int(click_lat_lng[0])
+        lon = int(click_lat_lng[1])
+
+    # Get nearby weather stations - V1.2
+    stations = Stations()
+    stations = stations.nearby(lat, lon) 
+    station = stations.fetch(1) # the closest station to the input location
+
+    nearest_lat = station['latitude'].values[0]
+    nearest_lon = station['longitude'].values[0]
+
+    start = datetime(int(start_date[0:4]), int(start_date[5:7]), int(start_date[8:10]))
+    end = datetime(2022, 12, 31)
+
+    line_plot = plot_weather_data(nearest_lat, nearest_lon, start, end)
+
+    box_plot = plot_tmax_boxplot(nearest_lat, nearest_lon, start, end, boxplot_variable)
+
+    try:
+        forecast_plot = plot_forecast_data_hourly(nearest_lat, nearest_lon)
+    except:
+        forecast_plot = go.Figure()
+
+    return line_plot, box_plot, forecast_plot
+
+# Initialize global variables
+nearest_lat, nearest_lon = 35, 25
+
+# Start of the application
+if __name__ == '__main__':
+    app.run_server(debug=False, host="0.0.0.0", port=8050)
diff --git a/Tests/dash_chat_test.py b/Tests/dash_chat_test.py
@@ -0,0 +1,57 @@
+import os
+import dash
+from dash import callback, html, Input, Output, State
+from dash_chat import ChatComponent
+from openai import OpenAI
+
+
+#import os
+from dotenv import load_dotenv
+#from openai import OpenAI
+
+load_dotenv()
+
+
+#api_key = os.environ.get("OPENAI_API_KEY")
+#client = OpenAI(api_key=api_key)
+client = OpenAI()
+
+
+app = dash.Dash(__name__)
+
+app.layout = html.Div([
+    ChatComponent(
+        id="chat-component",
+        messages=[
+            {"role": "assistant", "content": "Hello!"},
+        ],
+    )
+])
+
+@callback(
+    Output("chat-component", "messages"),
+    Input("chat-component", "new_message"),
+    State("chat-component", "messages"),
+    prevent_initial_call=True,
+)
+def handle_chat(new_message, messages):
+    if not new_message:
+        return messages
+
+    updated_messages = messages + [new_message]
+
+    if new_message["role"] == "user":
+        response = client.chat.completions.create(
+            model="gpt-40-mini",
+            messages=updated_messages,
+            temperature=1.0,
+            max_tokens=150,
+        )
+
+        bot_response = {"role": "assistant", "content": response.choices[0].message.content.strip()}
+        return updated_messages + [bot_response]
+
+    return updated_messages
+
+if __name__ == "__main__":
+    app.run_server(debug=True)