from termux_aichain import PromptTemplate, OpenAICompatibleChat, StringOutputParser, get_battery_status

# 1. Probe real physical smartphone hardware telemetry
batt_status = get_battery_status()

# 2. Build standard LCEL Pipe Chain bound to local llama-server (port 8080)
prompt = PromptTemplate.from_template("Phone Telemetry: {status}. Diagnose condition in 1 crisp sentence:")
llm = OpenAICompatibleChat(base_url="http://127.0.0.1:8080/v1", model="llama3", temperature=0.3, max_tokens=64)
chain = prompt | llm | StringOutputParser()

# 3. Execute with 0 external dependencies
report = chain.invoke({"status": batt_status})
print("AI Diagnostic:", report)

import { PromptTemplate, OpenAICompatibleChat, StringOutputParser, getBatteryStatus } from "termux-aichain";

// 1. Probe real physical smartphone hardware telemetry
const battery = await getBatteryStatus.func();

// 2. Build standard LCEL Pipe Chain bound to local llama-server (port 8080)
const prompt = PromptTemplate.fromTemplate("Phone Telemetry: {status}. Diagnose condition in 1 crisp sentence:");
const llm = new OpenAICompatibleChat({ baseUrl: "http://127.0.0.1:8080/v1", model: "llama3", temperature: 0.3, maxTokens: 64 });
const chain = prompt.pipe(llm).pipe(new StringOutputParser());

// 3. Execute with 0 npm dependencies
const report = await chain.invoke({ status: JSON.stringify(battery) });
console.log("AI Diagnostic:", report);