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SalexAI commited on 11 days ago

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658b428

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1 Parent(s): b9c19e2

Update app.py

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app.py +128 -52

app.py CHANGED Viewed

@@ -1,64 +1,140 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-    messages.append({"role": "user", "content": message})
-    response = ""
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
 if __name__ == "__main__":
-    demo.launch()

+# Sir, this app.py implements /stream and /dashboard endpoints with telemetry streaming, offline buffering, and CSV download.
+# Sir, let me know if you'd like a detailed walkthrough.
+from fastapi import FastAPI, WebSocket, Request
+from fastapi.responses import HTMLResponse, StreamingResponse
+import uvicorn
+import json
+import csv
+from io import StringIO
+app = FastAPI()
+telemetry_data = []  # Store telemetry dicts
+# Active WebSocket connections for dashboard clients
+dashboard_connections = []
+@app.get("/stream")
+async def stream():
+    html = """
+    <!DOCTYPE html>
+    <html>
+    <head><title>Emerson Telemetry Stream</title></head>
+    <body>
+    <h1>Emerson Telemetry Stream</h1>
+    <p id="status">Connecting...</p>
+    <video id="video" width="320" height="240" autoplay muted></video>
+    <script>
+    const ws = new WebSocket(`ws://${location.host}/ws`);
+    let buffer = [];
+    document.getElementById("status").innerText = navigator.onLine ? "Connected" : "Waiting for Emerson...";
+    window.addEventListener("online", () => flushBuffer());
+    window.addEventListener("offline", () => document.getElementById("status").innerText = "Waiting for Emerson...");
+    ws.onopen = () => { document.getElementById("status").innerText = "Connected"; flushBuffer(); };
+    ws.onclose = () => document.getElementById("status").innerText = "Disconnected";
+    ws.onerror = () => document.getElementById("status").innerText = "Error";
+    async function sendTelemetry() {
+        const canvas = document.createElement("canvas");
+        const video = document.getElementById("video");
+        canvas.width = video.videoWidth;
+        canvas.height = video.videoHeight;
+        const ctx = canvas.getContext("2d");
+        ctx.drawImage(video, 0, 0);
+        const image = canvas.toDataURL("image/jpeg");
+        navigator.geolocation.getCurrentPosition(pos => {
+            const data = { timestamp: Date.now(), gps: pos.coords, image };
+            if (ws.readyState === WebSocket.OPEN) {
+                ws.send(JSON.stringify(data));
+            } else {
+                buffer.push(data);
+            }
+        });
+    }
+    function flushBuffer() {
+        while (buffer.length) {
+            ws.send(JSON.stringify(buffer.shift()));
+        }
+    }
+    navigator.mediaDevices.enumerateDevices().then(devices => {
+        const videoInputs = devices.filter(d => d.kind === "videoinput");
+        if (videoInputs.length) {
+            navigator.mediaDevices.getUserMedia({ video: { deviceId: { exact: videoInputs[0].deviceId } } })
+                .then(stream => { document.getElementById("video").srcObject = stream; });
+        }
+    });
+    setInterval(sendTelemetry, 1000);
+    </script>
+    </body>
+    </html>
+    """
+    return HTMLResponse(html)
+@app.get("/dashboard")
+async def dashboard():
+    html = """
+    <!DOCTYPE html>
+    <html>
+    <head><title>Emerson Dashboard</title></head>
+    <body>
+    <h1>Emerson Dashboard</h1>
+    <p id="status">Waiting for Emerson...</p>
+    <div id="data"></div>
+    <a href="/download-csv" download="telemetry.csv">Download CSV</a>
+    <script>
+    const ws = new WebSocket(`ws://${location.host}/ws`);
+    ws.onopen = () => document.getElementById("status").innerText = "Connected";
+    ws.onmessage = msg => {
+        const data = JSON.parse(msg.data);
+        document.getElementById("status").innerText = "Streaming";
+        const div = document.getElementById("data");
+        const p = document.createElement("p");
+        p.innerText = `Time: ${new Date(data.timestamp).toLocaleTimeString()} GPS: ${data.gps.latitude.toFixed(5)}, ${data.gps.longitude.toFixed(5)}`;
+        const img = document.createElement("img");
+        img.src = data.image;
+        img.width = 160;
+        div.prepend(img);
+        div.prepend(p);
+    };
+    ws.onclose = () => document.getElementById("status").innerText = "Disconnected";
+    </script>
+    </body>
+    </html>
+    """
+    return HTMLResponse(html)
+@app.get("/download-csv")
+async def download_csv():
+    def iter_csv():
+        si = StringIO()
+        writer = csv.writer(si)
+        writer.writerow(["timestamp", "latitude", "longitude", "image"])
+        for d in telemetry_data:
+            writer.writerow([d["timestamp"], d["gps"]["latitude"], d["gps"]["longitude"], d["image"]])
+            yield si.getvalue()
+            si.seek(0)
+            si.truncate(0)
+    return StreamingResponse(iter_csv(), media_type="text/csv")
+@app.websocket("/ws")
+async def websocket_endpoint(ws: WebSocket):
+    await ws.accept()
+    dashboard_connections.append(ws)
+    try:
+        while True:
+            data = await ws.receive_text()
+            telemetry = json.loads(data)
+            telemetry_data.append(telemetry)
+            # Broadcast to dashboard clients
+            for conn in dashboard_connections:
+                try:
+                    await conn.send_text(json.dumps(telemetry))
+                except:
+                    dashboard_connections.remove(conn)
+    except:
+        dashboard_connections.remove(ws)
 if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)