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# Local_LLM_Inference_Engine_Lib.py
#########################################
# Local LLM Inference Engine Library
# This library is used to handle downloading, configuring, and launching the Local LLM Inference Engine
# via (llama.cpp via llamafile)
#
#
####
####################
# Function List
#
# 1. download_latest_llamafile(repo, asset_name_prefix, output_filename)
# 2. download_file(url, dest_path, expected_checksum=None, max_retries=3, delay=5)
# 3. verify_checksum(file_path, expected_checksum)
# 4. cleanup_process()
# 5. signal_handler(sig, frame)
# 6. local_llm_function()
# 7. launch_in_new_terminal_windows(executable, args)
# 8. launch_in_new_terminal_linux(executable, args)
# 9. launch_in_new_terminal_mac(executable, args)
#
####################
# Import necessary libraries
#import atexit
import re
import subprocess
import sys
import time
from App_Function_Libraries.Utils import download_file
# Import 3rd-pary Libraries
#
# Import Local
from Article_Summarization_Lib import *
#
#
#######################################################################################################################
# Function Definitions
#
# Function to download the latest llamafile from the Mozilla-Ocho/llamafile repo
def download_latest_llamafile(output_filename):
# Check if the file already exists
print("Checking for and downloading Llamafile it it doesn't already exist...")
if os.path.exists(output_filename):
print("Llamafile already exists. Skipping download.")
logging.debug(f"{output_filename} already exists. Skipping download.")
llamafile_exists = True
else:
llamafile_exists = False
# Double check if the file exists
if llamafile_exists:
pass
else:
# Establish variables for Llamafile download
repo = "Mozilla-Ocho/llamafile"
asset_name_prefix = "llamafile-"
# Get the latest release information
latest_release_url = f"https://api.github.com/repos/{repo}/releases/latest"
response = requests.get(latest_release_url)
if response.status_code != 200:
raise Exception(f"Failed to fetch latest release info: {response.status_code}")
latest_release_data = response.json()
tag_name = latest_release_data['tag_name']
# Get the release details using the tag name
release_details_url = f"https://api.github.com/repos/{repo}/releases/tags/{tag_name}"
response = requests.get(release_details_url)
if response.status_code != 200:
raise Exception(f"Failed to fetch release details for tag {tag_name}: {response.status_code}")
release_data = response.json()
assets = release_data.get('assets', [])
# Find the asset with the specified prefix
asset_url = None
for asset in assets:
if re.match(f"{asset_name_prefix}.*", asset['name']):
asset_url = asset['browser_download_url']
break
if not asset_url:
raise Exception(f"No asset found with prefix {asset_name_prefix}")
# Download the asset
response = requests.get(asset_url)
if response.status_code != 200:
raise Exception(f"Failed to download asset: {response.status_code}")
print("Llamafile downloaded successfully.")
logging.debug("Main: Llamafile downloaded successfully.")
# Save the file
with open(output_filename, 'wb') as file:
file.write(response.content)
logging.debug(f"Downloaded {output_filename} from {asset_url}")
print(f"Downloaded {output_filename} from {asset_url}")
return output_filename
def download_llm_model(model_name, model_url, model_filename, model_hash):
print("Checking available LLM models:")
available_models = []
missing_models = []
for key, model in llm_models.items():
if os.path.exists(model['filename']):
print(f"{key}. {model['name']} (Available)")
available_models.append(key)
else:
print(f"{key}. {model['name']} (Not downloaded)")
missing_models.append(key)
if not available_models:
print("No models are currently downloaded.")
else:
print(f"\n{len(available_models)} model(s) are available for use.")
action = input("Do you want to (u)se an available model, (d)ownload a new model, or (q)uit? ").lower()
if action == 'u':
if not available_models:
print("No models are available. Please download a model first.")
return None
while True:
choice = input(f"Enter the number of the model you want to use ({', '.join(available_models)}): ")
if choice in available_models:
print(f"Selected model: {llm_models[choice]['name']}")
return llm_models[choice]['filename']
else:
print("Invalid choice. Please try again.")
elif action == 'd':
if not missing_models:
print("All models are already downloaded. You can use an available model.")
return None
print("\nThe following models can be downloaded:")
for key in missing_models:
print(f"{key}. {llm_models[key]['name']}")
while True:
choice = input(f"Enter the number of the model you want to download ({', '.join(missing_models)}): ")
if choice in missing_models:
model = llm_models[choice]
print(f"Downloading {model['name']}...")
download_file(model['url'], model['filename'], expected_checksum=model['hash'])
print(f"{model['filename']} has been downloaded successfully.")
return model['filename']
else:
print("Invalid choice. Please try again.")
elif action == 'q':
print("Exiting model selection.")
return None
else:
print("Invalid action. Exiting model selection.")
return None
#
#
########################################
#
# LLM models information
llm_models = {
"1": {
"name": "Mistral-7B-Instruct-v0.2-Q8.llamafile",
"url": "https://huggingface.co/Mozilla/Mistral-7B-Instruct-v0.2-llamafile/resolve/main/mistral-7b-instruct-v0.2.Q8_0.llamafile?download=true",
"filename": "mistral-7b-instruct-v0.2.Q8_0.llamafile",
"hash": "1ee6114517d2f770425c880e5abc443da36b193c82abec8e2885dd7ce3b9bfa6"
},
"2": {
"name": "Samantha-Mistral-Instruct-7B-Bulleted-Notes-Q8.gguf",
"url": "https://huggingface.co/cognitivetech/samantha-mistral-instruct-7b-bulleted-notes-GGUF/resolve/main/samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf?download=true",
"filename": "samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf",
"hash": "6334c1ab56c565afd86535271fab52b03e67a5e31376946bce7bf5c144e847e4"
},
"3": {
"name": "Phi-3-mini-128k-instruct-Q8_0.gguf",
"url": "https://huggingface.co/gaianet/Phi-3-mini-128k-instruct-GGUF/resolve/main/Phi-3-mini-128k-instruct-Q8_0.gguf?download=true",
"filename": "Phi-3-mini-128k-instruct-Q8_0.gguf",
"hash": "6817b66d1c3c59ab06822e9732f0e594eea44e64cae2110906eac9d17f75d193"
},
"4": {
"name": "Meta-Llama-3-8B-Instruct.Q8_0.llamafile",
"url": "https://huggingface.co/Mozilla/Meta-Llama-3-8B-Instruct-llamafile/resolve/main/Meta-Llama-3-8B-Instruct.Q8_0.llamafile?download=true",
"filename": "Meta-Llama-3-8B-Instruct.Q8_0.llamafile",
"hash": "406868a97f02f57183716c7e4441d427f223fdbc7fa42964ef10c4d60dd8ed37"
}
}
process = None
# Function to close out llamafile process on script exit.
def cleanup_process():
global process
if process is not None:
# FIXME - process.kill()
#process.kill()
logging.debug("Main: Terminated the external process")
def signal_handler(sig, frame):
logging.info('Signal handler called with signal: %s', sig)
cleanup_process()
sys.exit(0)
# FIXME - Add callout to gradio UI
def local_llm_function():
global process
useros = os.name
if useros == "nt":
output_filename = "llamafile.exe"
else:
output_filename = "llamafile"
print(
"WARNING - Checking for existence of llamafile and HuggingFace model, downloading if needed...This could be a while")
print("WARNING - and I mean a while. We're talking an 8 Gigabyte model here...")
print("WARNING - Hope you're comfy. Or it's already downloaded.")
time.sleep(6)
logging.debug("Main: Checking and downloading Llamafile from Github if needed...")
llamafile_path = download_latest_llamafile(output_filename)
logging.debug("Main: Llamafile downloaded successfully.")
# FIXME - llm_choice
input("What model do you want to use? (Press Enter to continue)")
print("1. Mistral-7B-Instruct-v0.2-Q8.llamafile")
print("2. Samantha-Mistral-Instruct-7B-Bulleted-Notes-Q8.gguf")
print("3. Phi-3-mini-128k-instruct-Q8_0.gguf")
print("4. Meta-Llama-3-8B-Instruct.Q8_0.llamafile")
llm_choice = int(input("Enter the number of the model you want to use: "))
if llm_choice not in [1, 2, 3, 4]:
print("Invalid choice. Exiting.")
return
arguments = []
# Launch the llamafile in an external process with the specified argument
if llm_choice == 1:
arguments = ["--ctx-size", "8192 ", " -m", "mistral-7b-instruct-v0.2.Q8_0.llamafile"]
elif llm_choice == 2:
arguments = ["--ctx-size", "8192 ", " -m", "samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf"]
elif llm_choice == 3:
arguments = ["--ctx-size", "8192 ", " -m", "Phi-3-mini-128k-instruct-Q8_0.gguf"]
elif llm_choice == 4:
arguments = ["--ctx-size", "8192 ", " -m", "Meta-Llama-3-8B-Instruct.Q8_0.llamafile"] # FIXME
try:
logging.info("local_llm_function: Launching the LLM (llamafile) in an external terminal window...")
if useros == "nt":
launch_in_new_terminal_windows(llamafile_path, arguments)
elif useros == "posix":
launch_in_new_terminal_linux(llamafile_path, arguments)
else:
launch_in_new_terminal_mac(llamafile_path, arguments)
# FIXME - pid doesn't exist in this context
#logging.info(f"Main: Launched the {llamafile_path} with PID {process.pid}")
# Ha like this shit works
#atexit.register(cleanup_process, process)
except Exception as e:
logging.error(f"Failed to launch the process: {e}")
print(f"Failed to launch the process: {e}")
# This function is used to dl a llamafile binary + the Samantha Mistral Finetune model.
# It should only be called when the user is using the GUI to set up and interact with Llamafile.
def local_llm_gui_function(am_noob, verbose_checked, threads_checked, threads_value, http_threads_checked, http_threads_value,
model_checked, model_value, hf_repo_checked, hf_repo_value, hf_file_checked, hf_file_value,
ctx_size_checked, ctx_size_value, ngl_checked, ngl_value, host_checked, host_value, port_checked,
port_value):
# Identify running OS
useros = os.name
if useros == "nt":
output_filename = "llamafile.exe"
else:
output_filename = "llamafile"
# Build up the commands for llamafile
built_up_args = []
# Identify if the user wants us to do everything for them
if am_noob:
print("You're a noob. (lol j/k; they're good settings)")
# Setup variables for Model download from HF
repo = "Mozilla-Ocho/llamafile"
asset_name_prefix = "llamafile-"
print(
"WARNING - Checking for existence of llamafile or HuggingFace model (GGUF type), downloading if needed...This could be a while")
print("WARNING - and I mean a while. We're talking an 8 Gigabyte model here...")
print("WARNING - Hope you're comfy. Or it's already downloaded.")
time.sleep(6)
logging.debug("Main: Checking for Llamafile and downloading from Github if needed...\n\tAlso checking for a "
"local LLM model...\n\tDownloading if needed...\n\tThis could take a while...\n\tWill be the "
"'samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf' model...")
llamafile_path = download_latest_llamafile(output_filename)
logging.debug("Main: Llamafile downloaded successfully.")
arguments = []
# FIXME - llm_choice
# This is the gui, we can add this as options later
llm_choice = 2
# Launch the llamafile in an external process with the specified argument
if llm_choice == 1:
arguments = ["--ctx-size", "8192 ", " -m", "mistral-7b-instruct-v0.2.Q8_0.llamafile"]
elif llm_choice == 2:
arguments = """--ctx-size 8192 -m samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf"""
elif llm_choice == 3:
arguments = ["--ctx-size", "8192 ", " -m", "Phi-3-mini-128k-instruct-Q8_0.gguf"]
elif llm_choice == 4:
arguments = ["--ctx-size", "8192 ", " -m", "Meta-Llama-3-8B-Instruct.Q8_0.llamafile"]
try:
logging.info("Main(Local-LLM-GUI-noob): Launching the LLM (llamafile) in an external terminal window...")
if useros == "nt":
command = 'start cmd /k "llamafile.exe --ctx-size 8192 -m samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf"'
subprocess.Popen(command, shell=True)
elif useros == "posix":
command = "llamafile --ctx-size 8192 -m samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf"
subprocess.Popen(command, shell=True)
else:
command = "llamafile.exe --ctx-size 8192 -m samantha-mistral-instruct-7b-bulleted-notes.Q8_0.gguf"
subprocess.Popen(command, shell=True)
# FIXME - pid doesn't exist in this context
#logging.info(f"Main: Launched the {llamafile_path} with PID {process.pid}")
# FIXME - Shit just don't work
# atexit.register(cleanup_process, process)
except Exception as e:
logging.error(f"Failed to launch the process: {e}")
print(f"Failed to launch the process: {e}")
else:
print("You're not a noob.")
llamafile_path = download_latest_llamafile(output_filename)
if verbose_checked == True:
print("Verbose mode enabled.")
built_up_args.append("--verbose")
if threads_checked == True:
print(f"Threads enabled with value: {threads_value}")
built_up_args.append(f"--threads {threads_value}")
if http_threads_checked == True:
print(f"HTTP Threads enabled with value: {http_threads_value}")
built_up_args.append(f"--http-threads {http_threads_value}")
if model_checked == True:
print(f"Model enabled with value: {model_value}")
built_up_args.append(f"--model {model_value}")
if hf_repo_checked == True:
print(f"Huggingface repo enabled with value: {hf_repo_value}")
built_up_args.append(f"--hf-repo {hf_repo_value}")
if hf_file_checked == True:
print(f"Huggingface file enabled with value: {hf_file_value}")
built_up_args.append(f"--hf-file {hf_file_value}")
if ctx_size_checked == True:
print(f"Context size enabled with value: {ctx_size_value}")
built_up_args.append(f"--ctx-size {ctx_size_value}")
if ngl_checked == True:
print(f"NGL enabled with value: {ngl_value}")
built_up_args.append(f"--ngl {ngl_value}")
if host_checked == True:
print(f"Host enabled with value: {host_value}")
built_up_args.append(f"--host {host_value}")
if port_checked == True:
print(f"Port enabled with value: {port_value}")
built_up_args.append(f"--port {port_value}")
# Lets go ahead and finally launch the bastard...
try:
logging.info("Main(Local-LLM-GUI-Main): Launching the LLM (llamafile) in an external terminal window...")
if useros == "nt":
launch_in_new_terminal_windows(llamafile_path, built_up_args)
elif useros == "posix":
launch_in_new_terminal_linux(llamafile_path, built_up_args)
else:
launch_in_new_terminal_mac(llamafile_path, built_up_args)
# FIXME - pid doesn't exist in this context
#logging.info(f"Main: Launched the {llamafile_path} with PID {process.pid}")
# FIXME
#atexit.register(cleanup_process, process)
except Exception as e:
logging.error(f"Failed to launch the process: {e}")
print(f"Failed to launch the process: {e}")
# Launch the executable in a new terminal window # FIXME - really should figure out a cleaner way of doing this...
def launch_in_new_terminal_windows(executable, args):
command = f'start cmd /k "{executable} {" ".join(args)}"'
subprocess.Popen(command, shell=True)
# FIXME
def launch_in_new_terminal_linux(executable, args):
command = f'gnome-terminal -- {executable} {" ".join(args)}'
subprocess.Popen(command, shell=True)
# FIXME
def launch_in_new_terminal_mac(executable, args):
command = f'open -a Terminal.app {executable} {" ".join(args)}'
subprocess.Popen(command, shell=True)
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