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fixed error in MSG_TYPE

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Saifeddine ALOUI 2024-08-15 00:37:53 +02:00
parent 2d5468a204
commit 581a2157c4
2 changed files with 78 additions and 72 deletions
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124
lollms/functions/generate_music.py
View File

@ -4,70 +4,76 @@
# Description: This function generates music based on a given prompt and duration, saving the output to a unique file in the discussion folder.
# Import necessary libraries
import torchaudio
from audiocraft.models import musicgen
import torch
from pathlib import Path
from lollms.utilities import PackageManager
from ascii_colors import trace_exception
from functools import partial
try:
import torchaudio
from audiocraft.models import musicgen
import torch
from pathlib import Path
from lollms.utilities import PackageManager
from ascii_colors import trace_exception
from functools import partial
# Check for required packages and install if necessary
if not PackageManager.check_package_installed("audiocraft"):
PackageManager.install_package("audiocraft")
# Check for required packages and install if necessary
if not PackageManager.check_package_installed("audiocraft"):
PackageManager.install_package("audiocraft")
# Function to generate music
def generate_music(processor, client, generation_prompt: str, duration: int, model_name: str = "facebook/musicgen-melody", device: str="cuda:0") -> str:
"""
Generates music based on the given prompt and duration, saving it to a unique file in the discussion folder.
Parameters:
- processor: The processor object used for managing the generation process.
- client: The client object containing discussion information.
- generation_prompt: The prompt for music generation.
- duration: The duration of the music in seconds.
- model_name: The name of the pretrained music generation model.
- device: The device to run the model on (e.g., 'cpu' or 'cuda').
Returns:
- The path of the saved music file.
"""
try:
# Load the pretrained music generation model
music_model = musicgen.MusicGen.get_pretrained(model_name, device=device)
# Function to generate music
def generate_music(processor, client, generation_prompt: str, duration: int, model_name: str = "facebook/musicgen-melody", device: str="cuda:0") -> str:
"""
Generates music based on the given prompt and duration, saving it to a unique file in the discussion folder.
# Set generation parameters
music_model.set_generation_params(duration=duration)
Parameters:
- processor: The processor object used for managing the generation process.
- client: The client object containing discussion information.
- generation_prompt: The prompt for music generation.
- duration: The duration of the music in seconds.
- model_name: The name of the pretrained music generation model.
- device: The device to run the model on (e.g., 'cpu' or 'cuda').
# Generate music
res = music_model.generate([generation_prompt])
Returns:
- The path of the saved music file.
"""
# Create output folder if it doesn't exist
output_folder = client.discussion.discussion_folder / "generated_music"
output_folder.mkdir(parents=True, exist_ok=True)
try:
# Load the pretrained music generation model
music_model = musicgen.MusicGen.get_pretrained(model_name, device=device)
# Set generation parameters
music_model.set_generation_params(duration=duration)
# Generate music
res = music_model.generate([generation_prompt])
# Create output folder if it doesn't exist
output_folder = client.discussion.discussion_folder / "generated_music"
output_folder.mkdir(parents=True, exist_ok=True)
# Generate a unique file name
output_file = output_folder / f"music_generation_{len(list(output_folder.glob('*.wav')))}.wav"
# Generate a unique file name
output_file = output_folder / f"music_generation_{len(list(output_folder.glob('*.wav')))}.wav"
# Save the generated music to the specified file
torchaudio.save(output_file, res.reshape(1, -1).cpu(), 32000)
# Return the path of the saved file
return str(output_file)
except Exception as e:
return trace_exception(e)
# Save the generated music to the specified file
torchaudio.save(output_file, res.reshape(1, -1).cpu(), 32000)
# Return the path of the saved file
return str(output_file)
except Exception as e:
return trace_exception(e)
# Metadata function for the music generation function
def generate_music_function(processor, client):
return {
"function_name": "generate_music", # The function name in string
"function": partial(generate_music, processor=processor, client=client), # The function to be called with preset parameters
"function_description": "Generates music based on a prompt and duration, saving it to a unique file in the discussion folder.", # Description of the function
"function_parameters": [ # Parameters needed for the function
{"name": "generation_prompt", "type": "str"},
{"name": "duration", "type": "int"},
{"name": "model_name", "type": "str"},
{"name": "device", "type": "str"}
]
}
# Metadata function for the music generation function
def generate_music_function(processor, client):
return {
"function_name": "generate_music", # The function name in string
"function": partial(generate_music, processor=processor, client=client), # The function to be called with preset parameters
"function_description": "Generates music based on a prompt and duration, saving it to a unique file in the discussion folder.", # Description of the function
"function_parameters": [ # Parameters needed for the function
{"name": "generation_prompt", "type": "str"},
{"name": "duration", "type": "int"},
{"name": "model_name", "type": "str"},
{"name": "device", "type": "str"}
]
}
except:
def generate_music(processor, client, generation_prompt: str, duration: int, model_name: str = "facebook/musicgen-melody", device: str="cuda:0") -> str:
pass
def generate_music_function(processor, client):
pass

26
lollms/server/endpoints/lollms_generator.py
View File

@ -137,7 +137,7 @@ async def lollms_generate(request: LollmsGenerateRequest):
async def generate_chunks():
lk = threading.Lock()
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if elf_server.cancel_gen:
return False
@ -305,7 +305,7 @@ async def lollms_generate_with_images(request: LollmsGenerateRequest):
async def generate_chunks():
lk = threading.Lock()
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if elf_server.cancel_gen:
return False
@ -359,7 +359,7 @@ async def lollms_generate_with_images(request: LollmsGenerateRequest):
elf_server.cancel_gen = False
return StreamingResponse(generate_chunks(), media_type="text/plain", headers=headers)
else:
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
if chunk is None:
return True
@ -509,7 +509,7 @@ async def v1_chat_completions(request: ChatGenerationRequest):
async def generate_chunks():
lk = threading.Lock()
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if elf_server.cancel_gen:
return False
@ -567,7 +567,7 @@ async def v1_chat_completions(request: ChatGenerationRequest):
elf_server.cancel_gen = False
return StreamingResponse(generate_chunks(), media_type="application/json")
else:
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
if chunk is None:
return True
@ -651,7 +651,7 @@ async def ollama_chat_completion(request: ChatGenerationRequest):
async def generate_chunks():
lk = threading.Lock()
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if elf_server.cancel_gen:
return False
@ -709,7 +709,7 @@ async def ollama_chat_completion(request: ChatGenerationRequest):
elf_server.cancel_gen = False
return StreamingResponse(generate_chunks(), media_type="application/json")
else:
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
if chunk is None:
return True
@ -805,7 +805,7 @@ async def ollama_generate(request: CompletionGenerationRequest):
if stream:
output = {"text":""}
def generate_chunks():
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
output["text"] += chunk
antiprompt = detect_antiprompt(output["text"], [start_header_id_template, end_header_id_template])
@ -826,7 +826,7 @@ async def ollama_generate(request: CompletionGenerationRequest):
return StreamingResponse(generate_chunks())
else:
output = {"text":""}
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if chunk is None:
return
# Yield each chunk of data
@ -891,7 +891,7 @@ async def ollama_completion(request: CompletionGenerationRequest):
async def generate_chunks():
lk = threading.Lock()
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
if elf_server.cancel_gen:
return False
@ -944,7 +944,7 @@ async def ollama_completion(request: CompletionGenerationRequest):
elf_server.cancel_gen = False
return StreamingResponse(generate_chunks(), media_type="text/plain")
else:
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
if chunk is None:
return True
@ -995,7 +995,7 @@ async def v1_completion(request: CompletionGenerationRequest):
if stream:
output = {"text":""}
def generate_chunks():
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
output["text"] += chunk
antiprompt = detect_antiprompt(output["text"])
@ -1016,7 +1016,7 @@ async def v1_completion(request: CompletionGenerationRequest):
return StreamingResponse(generate_chunks())
else:
output = {"text":""}
def callback(chunk, chunk_type:MSG_TYPE_CONTENT=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
def callback(chunk, chunk_type:MSG_OPERATION_TYPE=MSG_OPERATION_TYPE.MSG_OPERATION_TYPE_ADD_CHUNK):
# Yield each chunk of data
output["text"] += chunk
antiprompt = detect_antiprompt(output["text"])