kwindla

# usage: gemini-lights-repro.py --initial-message "Make a pretty sequence with the lights. Turn them on and off a few times. Pick nice colors."

import argparse
import asyncio
import base64
import json
import os
import pyaudio
import re
import shutil

kwindla

# installation:
#
# python3.12 -m venv venv
# source venv/bin/activate
#
# pip install pyaudio websockets

# usage:
#
# export GEMINI_API_KEY=...

kwindla

import asyncio
import base64
import json
import os
import pyaudio
import shutil
import websockets


class AudioStreamer:

kwindla

#
# Copyright (c) 2024, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#

import aiohttp
import argparse
import os

kwindla

import aiohttp
import asyncio
import os
import sys

from pipecat.frames.frames import EndFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.pipeline.runner import PipelineRunner
from pipecat.processors.frameworks.rtvi import (

kwindla

import asyncio
import aiohttp
import os
import sys

from pipecat.frames.frames import LLMMessagesFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_response import (

kwindla

base_model: meta-llama/Meta-Llama-3-70B
# deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  # This will be the path used for the data when it is saved to the Volume in the cloud.
  - path: data.jsonl

kwindla

base_model: meta-llama/Meta-Llama-3-70B
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  # This will be the path used for the data when it is saved to the Volume in the cloud.
  - path: data.jsonl

kwindla

base_model: meta-llama/Meta-Llama-3-70B
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  # This will be the path used for the data when it is saved to the Volume in the cloud.
  - path: data.jsonl

kwindla

import os
import json
import time
import statistics

from groq import Groq

# Set the Groq API key and the number of inferences to run
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
NUM_INFERENCES = 10