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limcheekin / voice-bot-and-zoom-audio-routing.sh
Created November 11, 2025 08:48
Shell script to allow Voice Bot in Chrome participate (listen and speak) in the Zoom meeting
#!/usr/bin/env bash
set -euo pipefail
echo "Creating virtual sinks..."
# 1) Create virtual sinks
# Sink for Zoom's audio output
pactl load-module module-null-sink sink_name=Zoom-to-Bot sink_properties=device.description="Zoom-to-Bot"
# Sink for the Bot's audio output
pactl load-module module-null-sink sink_name=VoiceBot-to-Zoom sink_properties=device.description="VoiceBot-to-Zoom"
@limcheekin
limcheekin / guidellm.sh
Created October 16, 2025 11:37
GuideLLM docker command
sudo docker run \
--rm -it \
-v "$(pwd)/results:/results:rw" \
-e GUIDELLM_TARGET=http://localhost:8880 \
-e GUIDELLM_MODEL="ibm-granite_granite-4.0-h-tiny" \
-e GUIDELLM_RATE_TYPE=sweep \
-e GUIDELLM_MAX_SECONDS=300 \
-e GUIDELLM_DATA="prompt_tokens=256,output_tokens=128" \
ghcr.io/vllm-project/guidellm:latest
@limcheekin
limcheekin / docker-compose.yaml
Created October 10, 2025 10:05
TensorZero Configs
services:
clickhouse:
image: clickhouse/clickhouse-server:25.8-alpine
ports:
- "8123:8123"
environment:
- 'CLICKHOUSE_USER=${CLICKHOUSE_USER:?Environment variable CLICKHOUSE_USER must be set.}'
- 'CLICKHOUSE_PASSWORD=${CLICKHOUSE_PASSWORD:?Environment variable CLICKHOUSE_USER must be set.}'
gateway:
depends_on:
@limcheekin
limcheekin / prompt.txt
Created September 24, 2025 01:56
Simplest prompt to test AI model
In Paris, the capital of France, the primary language spoken is
@limcheekin
limcheekin / curl_request.sh
Last active August 31, 2025 06:09
LocalAI audio input curl request
B64=$(base64 test.wav)
curl -v http://192.168.1.111:8880/v1/chat/completions \
-H "Content-Type: application/json" \
-d @- <<JSON
{
"model": "qwen2.5-omni-3b",
"messages": [
{
"role": "user",
@limcheekin
limcheekin / prompt.md
Last active August 27, 2025 02:39
Code Comparison Prompt

Carefully review and analyze the code in implementation1.txt, implementation2.txt, and implementation3.txt in detail, and think more deeply about the following items:

  1. Which implementation is better for the given user story defined in <story_file> in terms of functionality, code quality, performance, modularity, test coverage, etc.? Explain your reasoning.
  2. Which implementation fully complies with the user story defined in <story_file>? Identify the discrepancies in the implementation(s) that do not comply.
@limcheekin
limcheekin / merge_audio_video.sh
Created July 9, 2025 01:07
Merge Audio and Video File
#!/usr/bin/env bash
# merge_audio_video.sh — Mux video and MP3/M4A into MP4 with AAC audio
set -euo pipefail
if [ $# -ne 3 ]; then
echo "Usage: $0 <video.mp4> <audio.(mp3|m4a)> <output.mp4>" >&2
exit 1
fi
@limcheekin
limcheekin / snowflake-arctic-embed-l-v2.0.yaml
Created July 7, 2025 03:41
snowflake-arctic-embed-l-v2.0 localai model config
name: snowflake-arctic-embed-l-v2.0
backend: llama-cpp
embeddings: true
parameters:
model: snowflake-arctic-embed-l-v2.0.F16.gguf
@limcheekin
limcheekin / bge-reranker-v2-m3.yaml
Last active July 7, 2025 06:53
bge-reranker-v2-m3 localai model config
name: bge-reranker-v2-m3
backend: cuda12-rerankers
parameters:
model: BAAI/bge-reranker-v2-m3
model_type: reranker
pooling: rank
context_size: 2048
@limcheekin
limcheekin / generate_jwt.sh
Created June 24, 2025 09:22
Generate JWT token for mcp-context-forge
pip install mcp-contextforge-gateway
python -m mcpgateway.utils.create_jwt_token --username admin --secret JWT_SECRET_KEY