Create app.py

app.py

@@ -1,162 +1,103 @@
-import faicons as fa
-import plotly.express as px
-
-# Load data and compute static values
-from shared import app_dir, tips
-from shinywidgets import render_plotly
-
-from shiny import reactive, render
-from shiny.express import input, ui
-
-bill_rng = (min(tips.total_bill), max(tips.total_bill))
-
-# Add page title and sidebar
-ui.page_opts(title="Restaurant tipping", fillable=True)
-
-with ui.sidebar(open="desktop"):
-    ui.input_slider(
-        "total_bill",
-        "Bill amount",
-        min=bill_rng[0],
-        max=bill_rng[1],
-        value=bill_rng,
-        pre="$",
-    )
-    ui.input_checkbox_group(
-        "time",
-        "Food service",
-        ["Lunch", "Dinner"],
-        selected=["Lunch", "Dinner"],
-        inline=True,
+import os
+import json
+import requests
+from fastapi import FastAPI
+from mcp.server.lowlevel import Server, NotificationOptions
+from mcp.server.sse import SSEServerTransport
+from mcp import types as mcp_types
+import uvicorn
+
+app = FastAPI()
+
+# Load environment variables
+AIRTABLE_API_TOKEN = os.getenv("AIRTABLE_API_TOKEN")
+AIRTABLE_BASE_ID = os.getenv("AIRTABLE_BASE_ID")
+TABLE_ID = "tblQECi5f7m4y2NEV"
+AIRTABLE_API_URL = f"https://api.airtable.com/v0/{AIRTABLE_BASE_ID}/{TABLE_ID}"
+
+# Helper function for Airtable API requests
+def airtable_request(method, endpoint="", data=None):
+    headers = {
+        "Authorization": f"Bearer {AIRTABLE_API_TOKEN}",
+        "Content-Type": "application/json"
+    }
+    url = f"{AIRTABLE_API_URL}/{endpoint}" if endpoint else AIRTABLE_API_URL
+    response = requests.request(method, url, headers=headers, json=data)
+    response.raise_for_status()
+    return response.json()
+
+# Tool to list records
+async def list_records_tool(request: mcp_types.CallToolRequest):
+    try:
+        records = airtable_request("GET")
+        return {
+            "success": True,
+            "result": json.dumps(records)
+        }
+    except Exception as e:
+        return {
+            "success": False,
+            "error": str(e)
+        }
+
+# Tool to create a record
+async def create_record_tool(request: mcp_types.CallToolRequest):
+    try:
+        record_data = request.input.get("record_data", {})
+        data = {"records": [{"fields": record_data}]}
+        response = airtable_request("POST", data=data)
+        return {
+            "success": True,
+            "result": json.dumps(response)
+        }
+    except Exception as e:
+        return {
+            "success": False,
+            "error": str(e)
+        }
+
+# MCP Server setup
+async def start_mcp_server():
+    tools = [
+        mcp_types.ToolDefinition(
+            name="list_airtable_records",
+            description="Lists all records in the specified Airtable table",
+            input_schema={},
+            output_schema={"type": "string"}
+        ),
+        mcp_types.ToolDefinition(
+            name="create_airtable_record",
+            description="Creates a new record in the specified Airtable table",
+            input_schema={"record_data": {"type": "object"}},
+            output_schema={"type": "string"}
+        )
+    ]
+
+    server = Server(
+        tools=tools,
+        tool_handlers={
+            "list_airtable_records": list_records_tool,
+            "create_airtable_record": create_record_tool
+        },
+        notification_options=NotificationOptions()
     )
-    ui.input_action_button("reset", "Reset filter")
-
-# Add main content
-ICONS = {
-    "user": fa.icon_svg("user", "regular"),
-    "wallet": fa.icon_svg("wallet"),
-    "currency-dollar": fa.icon_svg("dollar-sign"),
-    "ellipsis": fa.icon_svg("ellipsis"),
-}
-
-with ui.layout_columns(fill=False):
-    with ui.value_box(showcase=ICONS["user"]):
-        "Total tippers"
-
-        @render.express
-        def total_tippers():
-            tips_data().shape[0]
-
-    with ui.value_box(showcase=ICONS["wallet"]):
-        "Average tip"
-
-        @render.express
-        def average_tip():
-            d = tips_data()
-            if d.shape[0] > 0:
-                perc = d.tip / d.total_bill
-                f"{perc.mean():.1%}"
-
-    with ui.value_box(showcase=ICONS["currency-dollar"]):
-        "Average bill"
-
-        @render.express
-        def average_bill():
-            d = tips_data()
-            if d.shape[0] > 0:
-                bill = d.total_bill.mean()
-                f"${bill:.2f}"
-
-
-with ui.layout_columns(col_widths=[6, 6, 12]):
-    with ui.card(full_screen=True):
-        ui.card_header("Tips data")
-
-        @render.data_frame
-        def table():
-            return render.DataGrid(tips_data())
-
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Total bill vs tip"
-            with ui.popover(title="Add a color variable", placement="top"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "scatter_color",
-                    None,
-                    ["none", "sex", "smoker", "day", "time"],
-                    inline=True,
-                )
-
-        @render_plotly
-        def scatterplot():
-            color = input.scatter_color()
-            return px.scatter(
-                tips_data(),
-                x="total_bill",
-                y="tip",
-                color=None if color == "none" else color,
-                trendline="lowess",
-            )
-
-    with ui.card(full_screen=True):
-        with ui.card_header(class_="d-flex justify-content-between align-items-center"):
-            "Tip percentages"
-            with ui.popover(title="Add a color variable"):
-                ICONS["ellipsis"]
-                ui.input_radio_buttons(
-                    "tip_perc_y",
-                    "Split by:",
-                    ["sex", "smoker", "day", "time"],
-                    selected="day",
-                    inline=True,
-                )
-
-        @render_plotly
-        def tip_perc():
-            from ridgeplot import ridgeplot
-
-            dat = tips_data()
-            dat["percent"] = dat.tip / dat.total_bill
-            yvar = input.tip_perc_y()
-            uvals = dat[yvar].unique()
-
-            samples = [[dat.percent[dat[yvar] == val]] for val in uvals]
-
-            plt = ridgeplot(
-                samples=samples,
-                labels=uvals,
-                bandwidth=0.01,
-                colorscale="viridis",
-                colormode="row-index",
-            )
-
-            plt.update_layout(
-                legend=dict(
-                    orientation="h", yanchor="bottom", y=1.02, xanchor="center", x=0.5
-                )
-            )
-
-            return plt
-
-
-ui.include_css(app_dir / "styles.css")
-
-# --------------------------------------------------------
-# Reactive calculations and effects
-# --------------------------------------------------------
-
-
-@reactive.calc
-def tips_data():
-    bill = input.total_bill()
-    idx1 = tips.total_bill.between(bill[0], bill[1])
-    idx2 = tips.time.isin(input.time())
-    return tips[idx1 & idx2]
-
 
-@reactive.effect
-@reactive.event(input.reset)
-def _():
-    ui.update_slider("total_bill", value=bill_rng)
-    ui.update_checkbox_group("time", selected=["Lunch", "Dinner"])
+    # Hugging Face Spaces handles the port and host, so we specify only the path
+    transport = SSEServerTransport(path="/airtable/mcp")
+    await server.run(transport)
+
+# Start the MCP server when the FastAPI app starts
+@app.on_event("startup")
+async def startup_event():
+    import asyncio
+    asyncio.create_task(start_mcp_server())
+
+# Health check endpoint
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy"}
+
+if __name__ == "__main__":
+    # Hugging Face Spaces uses PORT environment variable
+    port = int(os.getenv("PORT", 7860))  # Default to 7860 if PORT is not set
+    uvicorn.run(app, host="0.0.0.0", port=port)