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+FROM python:3.11-slim
+
+RUN apt update && apt install -y git build-essential cmake && apt clean
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY model/ ./model/
+COPY app.py .
+
+CMD ["python", "app.py"]

app.py

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+from flask import Flask, request
+from llama_cpp import Llama
+import requests
+from bs4 import BeautifulSoup
+
+ENV_URL = "http://192.168.4.1/"   # your Station AP page
+
+llm = Llama(model_path="model/llama-3.2-1b-Q4_K_M.gguf")
+
+app = Flask(__name__)
+
+def fetch_envpro_values():
+    r = requests.get(ENV_URL, timeout=3)
+    soup = BeautifulSoup(r.text, "html.parser")
+    text = soup.get_text()
+
+    def extract(label):
+        start = text.find(label)
+        if start == -1:
+            return None
+        value = text[start+len(label):].split("\n")[0].strip()
+        return value
+
+    return {
+        "temp": extract("Temp:"),
+        "hum": extract("Hum:"),
+        "press": extract("Press:"),
+        "gas": extract("Gas:"),
+        "co2": extract("CO2eq:"),
+        "voc": extract("VOCeq:"),
+        "iaq": extract("IAQ accuracy:")
+    }
+
+@app.route("/interpret")
+def interpret():
+    data = fetch_envpro_values()
+
+    prompt = (
+        "ENV PRO DATA:\n"
+        f"Temp: {data['temp']}\n"
+        f"Hum: {data['hum']}\n"
+        f"Press: {data['press']}\n"
+        f"Gas: {data['gas']}\n"
+        f"CO2eq: {data['co2']}\n"
+        f"VOCeq: {data['voc']}\n"
+        f"IAQ accuracy: {data['iaq']}\n\n"
+        "Context: Indoor environment. Do not assume cooking unless the sensor values indicate it.\n"
+        "Instruction: Base your interpretation ONLY on the ENV PRO DATA values above.\n"
+        "Do NOT invent activities.\n"
+        "Do NOT infer smells that are not supported by the data.\n"
+        "The environment may be a bedroom, living room, hallway, kitchen or any indoor space.\n\n"
+        "Task: Output exactly ONE short sentence.\n"
+        "Rules:\n"
+        "1. The sentence MUST start with one of these words: smell, activity, mood, doing\n"
+        "2. The sentence MUST NOT exceed 100 characters.\n"
+        "3. Do NOT output examples.\n"
+        "4. Do NOT output lists.\n"
+        "5. Do NOT explain anything.\n"
+        "6. Output exactly ONE short sentence.\n\n"
+        "Now output the sentence:\n"
+    )
+
+    out = llm(prompt, max_tokens=160)
+    return out["choices"][0]["text"]
+
+# ⭐ NEW: Manual input mode (works inside Docker Desktop)
+@app.route("/manual", methods=["POST"])
+def manual():
+    data = request.json
+
+    prompt = (
+        "ENV PRO DATA:\n"
+        f"Temp: {data['temp']}\n"
+        f"Hum: {data['hum']}\n"
+        f"Press: {data['press']}\n"
+        f"Gas: {data['gas']}\n"
+        f"CO2eq: {data['co2']}\n"
+        f"VOCeq: {data['voc']}\n"
+        f"IAQ accuracy: {data['iaq']}\n\n"
+        "Context: Indoor environment. Do not assume cooking unless the sensor values indicate it.\n"
+        "Instruction: Base your interpretation ONLY on the ENV PRO DATA values above.\n"
+        "Do NOT invent activities.\n"
+        "Do NOT infer smells that are not supported by the data.\n"
+        "The environment may be a bedroom, living room, hallway, kitchen or any indoor space.\n\n"
+        "Task: Output exactly ONE short sentence.\n"
+        "Rules:\n"
+        "1. The sentence MUST start with one of these words: smell, activity, mood, doing\n"
+        "2. The sentence MUST NOT exceed 100 characters.\n"
+        "3. Do NOT output examples.\n"
+        "4. Do NOT output lists.\n"
+        "5. Do NOT explain anything.\n"
+        "6. Output exactly ONE short sentence.\n\n"
+        "Now output the sentence:\n"
+    )
+
+    out = llm(prompt, max_tokens=160)
+    return out["choices"][0]["text"]
+
+app.run(host="0.0.0.0", port=8000)
+
+
+

requirements.txt

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+flask
+llama-cpp-python
+requests
+beautifulsoup4
+