sachnaror

#An async Ninja endpoint that calls two remote systems concurrently
#(e.g., inventory + billing) and merges results

from ninja import NinjaAPI
import httpx
import asyncio

api = NinjaAPI()

@api.get("/order-summary")

sachnaror

# t24.py — PyFlink wordcount with clean shutdown (no noisy gRPC at exit)
# A PyFlink mini streaming job. It takes a small list (["apple", "banana", "apple"]), maps each word to (word, 1), groups by word, and reduces counts. Then it prints the running totals.

# So the flow is:
# 	"banana" → ('banana', 1)
# 	"apple" → ('apple', 1)
# 	 second "apple" → updates to ('apple', 2)

import os

sachnaror

import os
import logging
from typing import Optional
from tenacity import retry, stop_after_attempt, retry_if_exception_type
from openai import AsyncOpenAI, APIError, APIConnectionError

# --- Configure Logging ---
logging.basicConfig(
    level=logging.INFO,

sachnaror

{
  "keys": [
    {
      "kty": "RSA",
      "kid": "demo-key-001",
      "use": "sig",
      "alg": "RS256",
      "n": "vg2gksIn5um5GnBx15LpzTtVTHHtGGQLD_F-10PKZyckjhZLJM_vtoOwoxFAg1ysi6jH_OPl9EYudUYLpKzNwbK6Q89zwfT2vJEMf-4mIKabcVz-hOLR9GIlDpy6ouoPBBqx-youANM1wUiTTPJb7RpUKZ4_MC5o0BRlLBP7uAIENdy4PWcFvWeatNkqSlaKS1pws7JNdb2qa3p0Xn_wMzII1scmXFJh6KPOHL3P-X4ps3beY9k3xJBIBSD0D6auArRgC1Wo2a4rlOKKs3243auHsvSrt9_dPOb06GFN6ZSYG-Aiaqc6quQwaxpIJiQ3IpIORQYz1FqTW44TA4WYeQ",
      "e": "AQAB"
    }

sachnaror

import openai

# ✅ Use your actual API key here (never share it in public code)
openai.api_key = "sk-proj-GyQv44xNGlYPhFSOp6UaOxQ44oH_ZtUH_VpUutCuGiw2Wgc2pB7TQiGEkY6eyOB5uadZzgT3BlbkFJKr6segLT2r0fjqSV9jtQbV23XtxrXxxJIEk-s9kfgauib3EbD-m_ap81NajCOkpsLZsGwvqQA"

# Define a concise system message
system_prompt = (
    "You are a helpful assistant. Respond in a semi-formal tone. "
    "Keep your answer under 3 lines. Be informative and friendly."
)

sachnaror

# Your code goes here
import time
import re
import threading
from pynput import keyboard

# Keyword-to-replacement mappings
keyword_map = {
    "marketing": "Focus on customer engagement for better sales.",
    "ai": "AI is revolutionizing industries.",

sachnaror

import librosa
import numpy as np
import whisper

# Load Whisper model and force CPU usage
model = whisper.load_model("medium").to("cpu")

# Load audio file
audio_path = "/Users/homesachin/Downloads/20250221_125939.aac"
audio, sr = librosa.load(audio_path, sr=16000)

sachnaror

#!/bin/bash

# Get the repository URL from the current folder
REPO_URL=$(git config --get remote.origin.url)

if [ -z "$REPO_URL" ]; then
    echo "Error: No remote GitHub repository detected in this folder."
    exit 1
fi

sachnaror

# Full Description: nal transcription.

# Full Description: nal transcription.
import os
import speech_recognition as sr

# Initialize the recognizer
recognizer = sr.Recognizer()

sachnaror

# Full Description: nal transcription.
import os
import speech_recognition as sr

# Initialize the recognizer
recognizer = sr.Recognizer()

# Folder containing chunks
chunk_folder = "."