From 6b1ad0c5af428be3cd0fa17613d24b6e04ba79e0 Mon Sep 17 00:00:00 2001 From: MervinPraison Date: Sun, 4 Aug 2024 07:22:55 +0100 Subject: [PATCH] praisonai train release candidate --- Dockerfile | 2 +- docs/api/praisonai/deploy.html | 2 +- poetry.lock | 1432 ++++++++++++++++---------------- praisonai.rb | 2 +- praisonai/cli.py | 6 + praisonai/deploy.py | 2 +- praisonai/train.py | 232 ++++++ pyproject.toml | 18 +- setup/__init__.py | 0 setup/build.py | 21 + setup/post_install.py | 20 + setup/setup_conda_env.py | 25 + setup/setup_conda_env.sh | 60 ++ 13 files changed, 1080 insertions(+), 742 deletions(-) create mode 100644 praisonai/train.py create mode 100644 setup/__init__.py create mode 100644 setup/build.py create mode 100644 setup/post_install.py create mode 100644 setup/setup_conda_env.py create mode 100755 setup/setup_conda_env.sh diff --git a/Dockerfile b/Dockerfile index 912d35a5..75ea0d64 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,6 +1,6 @@ FROM python:3.11-slim WORKDIR /app COPY . . -RUN pip install flask praisonai==0.0.58 gunicorn markdown +RUN pip install flask praisonai==0.0.59rc1 gunicorn markdown EXPOSE 8080 CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"] diff --git a/docs/api/praisonai/deploy.html b/docs/api/praisonai/deploy.html index 60a579f3..ed743ded 100644 --- a/docs/api/praisonai/deploy.html +++ b/docs/api/praisonai/deploy.html @@ -110,7 +110,7 @@

Raises

file.write("FROM python:3.11-slim\n") file.write("WORKDIR /app\n") file.write("COPY . .\n") - file.write("RUN pip install flask praisonai==0.0.58 gunicorn markdown\n") + file.write("RUN pip install flask praisonai==0.0.59rc1 gunicorn markdown\n") file.write("EXPOSE 8080\n") file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n') diff --git a/poetry.lock b/poetry.lock index a5f2d6eb..a9287af8 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "agentops" -version = "0.3.0" +version = "0.3.6" description = "Python SDK for developing AI agent evals and observability" optional = false python-versions = ">=3.7" files = [ - {file = "agentops-0.3.0-py3-none-any.whl", hash = "sha256:22aeb3355e66b32a2b2a9f676048b81979b2488feddb088f9266034b3ed50539"}, - {file = "agentops-0.3.0.tar.gz", hash = "sha256:6c0c08a57410fa5e826a7bafa1deeba9f7b3524709427d9e1abbd0964caaf76b"}, + {file = "agentops-0.3.6-py3-none-any.whl", hash = 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[package.dependencies] @@ -8415,7 +8376,7 @@ mutagen = "*" pycryptodomex = "*" requests = ">=2.31.0,<3" urllib3 = ">=1.26.17,<3" -websockets = "*" +websockets = ">=12.0" [[package]] name = "zipp" @@ -8442,9 +8403,10 @@ cohere = ["langchain-cohere"] google = ["langchain-google-genai"] gradio = ["gradio"] openai = ["langchain-openai"] +train = [] ui = ["chainlit"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.13" -content-hash = "e3e1f1cadd4a27e99b054c860e4a4ce9a1808ae392571ffa29f13553c8c05ffe" +content-hash = "022ecac191d0bfeee0cb0799ceeafd655be7f7bc8cbaa3777db76d2c96c455e4" diff --git a/praisonai.rb b/praisonai.rb index 6463b8bf..b108e50e 100644 --- a/praisonai.rb +++ b/praisonai.rb @@ -3,7 +3,7 @@ class Praisonai < Formula desc "AI tools for various AI applications" homepage "https://github.com/MervinPraison/PraisonAI" - url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/0.0.58.tar.gz" + url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/0.0.59rc1.tar.gz" sha256 "1828fb9227d10f991522c3f24f061943a254b667196b40b1a3e4a54a8d30ce32" # Replace with actual SHA256 checksum license "MIT" diff --git a/praisonai/cli.py b/praisonai/cli.py index fbbedde8..04a2bd8b 100644 --- a/praisonai/cli.py +++ b/praisonai/cli.py @@ -98,6 +98,12 @@ def main(self): if getattr(args, 'code', False): self.create_code_interface() return + + if args.agent_file == 'train': + from .train import main as train_main + train_args = sys.argv[2:] # Get all arguments after 'train' + train_main(train_args) # Pass the arguments to train.py's main function + return invocation_cmd = "praisonai" version_string = f"PraisonAI version {__version__}" diff --git a/praisonai/deploy.py b/praisonai/deploy.py index 1d343c64..4ad304e7 100644 --- a/praisonai/deploy.py +++ b/praisonai/deploy.py @@ -56,7 +56,7 @@ def create_dockerfile(self): file.write("FROM python:3.11-slim\n") file.write("WORKDIR /app\n") file.write("COPY . .\n") - file.write("RUN pip install flask praisonai==0.0.58 gunicorn markdown\n") + file.write("RUN pip install flask praisonai==0.0.59rc1 gunicorn markdown\n") file.write("EXPOSE 8080\n") file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n') diff --git a/praisonai/train.py b/praisonai/train.py new file mode 100644 index 00000000..fa861337 --- /dev/null +++ b/praisonai/train.py @@ -0,0 +1,232 @@ +import subprocess +import os +import sys +import yaml +import torch +from transformers import TextStreamer +from unsloth import FastLanguageModel, is_bfloat16_supported +from trl import SFTTrainer +from transformers import TrainingArguments +from datasets import load_dataset, concatenate_datasets, Dataset +from psutil import virtual_memory + +class train: + def __init__(self, config_path="config.yaml"): + self.load_config(config_path) + self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + self.model, self.tokenizer = None, None + + def load_config(self, path): + with open(path, "r") as file: + self.config = yaml.safe_load(file) + + def print_system_info(self): + print(f"PyTorch version: {torch.__version__}") + print(f"CUDA version: {torch.version.cuda}") + if torch.cuda.is_available(): + device_capability = torch.cuda.get_device_capability() + print(f"CUDA Device Capability: {device_capability}") + else: + print("CUDA is not available") + + python_version = sys.version + pip_version = subprocess.check_output(['pip', '--version']).decode().strip() + python_path = sys.executable + pip_path = subprocess.check_output(['which', 'pip']).decode().strip() + print(f"Python Version: {python_version}") + print(f"Pip Version: {pip_version}") + print(f"Python Path: {python_path}") + print(f"Pip Path: {pip_path}") + + def check_gpu(self): + gpu_stats = torch.cuda.get_device_properties(0) + print(f"GPU = {gpu_stats.name}. Max memory = {round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)} GB.") + + def check_ram(self): + ram_gb = virtual_memory().total / 1e9 + print('Your runtime has {:.1f} gigabytes of available RAM\n'.format(ram_gb)) + if ram_gb < 20: + print('Not using a high-RAM runtime') + else: + print('You are using a high-RAM runtime!') + + # def install_packages(self): + # subprocess.run(["pip", "install", "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git@4e570be9ae4ced8cdc64e498125708e34942befc"]) + # subprocess.run(["pip", "install", "--no-deps", "trl<0.9.0", "peft==0.12.0", "accelerate==0.33.0", "bitsandbytes==0.43.3"]) + + def prepare_model(self): + self.model, self.tokenizer = FastLanguageModel.from_pretrained( + model_name=self.config["model_name"], + max_seq_length=self.config["max_seq_length"], + dtype=None, + load_in_4bit=self.config["load_in_4bit"] + ) + self.model = FastLanguageModel.get_peft_model( + self.model, + r=self.config["lora_r"], + target_modules=self.config["lora_target_modules"], + lora_alpha=self.config["lora_alpha"], + lora_dropout=self.config["lora_dropout"], + bias=self.config["lora_bias"], + use_gradient_checkpointing=self.config["use_gradient_checkpointing"], + random_state=self.config["random_state"], + use_rslora=self.config["use_rslora"], + loftq_config=self.config["loftq_config"], + ) + + def process_dataset(self, dataset_info): + dataset_name = dataset_info["name"] + split_type = dataset_info.get("split_type", "train") + processing_func = getattr(self, dataset_info.get("processing_func", "format_prompts")) + rename = dataset_info.get("rename", {}) + filter_data = dataset_info.get("filter_data", False) + filter_column_value = dataset_info.get("filter_column_value", "id") + filter_value = dataset_info.get("filter_value", "alpaca") + num_samples = dataset_info.get("num_samples", 20000) + + dataset = load_dataset(dataset_name, split=split_type) + + if rename: + dataset = dataset.rename_columns(rename) + if filter_data: + dataset = dataset.filter(lambda example: filter_value in example[filter_column_value]).shuffle(seed=42).select(range(num_samples)) + dataset = dataset.map(processing_func, batched=True) + return dataset + + def format_prompts(self, examples): + alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. + + ### Instruction: + {} + + ### Input: + {} + + ### Response: + {}""" + texts = [alpaca_prompt.format(ins, inp, out) + self.tokenizer.eos_token for ins, inp, out in zip(examples["instruction"], examples["input"], examples["output"])] + return {"text": texts} + + def load_datasets(self): + datasets = [] + for dataset_info in self.config["dataset"]: + datasets.append(self.process_dataset(dataset_info)) + return concatenate_datasets(datasets) + + def train_model(self): + dataset = self.load_datasets() + trainer = SFTTrainer( + model=self.model, + tokenizer=self.tokenizer, + train_dataset=dataset, + dataset_text_field=self.config["dataset_text_field"], + max_seq_length=self.config["max_seq_length"], + dataset_num_proc=self.config["dataset_num_proc"], + packing=self.config["packing"], + args=TrainingArguments( + per_device_train_batch_size=self.config["per_device_train_batch_size"], + gradient_accumulation_steps=self.config["gradient_accumulation_steps"], + warmup_steps=self.config["warmup_steps"], + num_train_epochs=self.config["num_train_epochs"], + max_steps=self.config["max_steps"], + learning_rate=self.config["learning_rate"], + fp16=not is_bfloat16_supported(), + bf16=is_bfloat16_supported(), + logging_steps=self.config["logging_steps"], + optim=self.config["optim"], + weight_decay=self.config["weight_decay"], + lr_scheduler_type=self.config["lr_scheduler_type"], + seed=self.config["seed"], + output_dir=self.config["output_dir"], + ), + ) + trainer.train() + + def inference(self, instruction, input_text): + FastLanguageModel.for_inference(self.model) + alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. + + ### Instruction: + {} + + ### Input: + {} + + ### Response: + {}""" + inputs = self.tokenizer([alpaca_prompt.format(instruction, input_text, "")], return_tensors="pt").to("cuda") + outputs = self.model.generate(**inputs, max_new_tokens=64, use_cache=True) + print(self.tokenizer.batch_decode(outputs)) + + def save_model_merged(self): + if os.path.exists(self.config["hf_model_name"]): + shutil.rmtree(self.config["hf_model_name"]) + self.model.push_to_hub_merged( + self.config["hf_model_name"], + self.tokenizer, + save_method="merged_16bit", + token=os.getenv('HF_TOKEN') + ) + + def push_model_gguf(self): + self.model.push_to_hub_gguf( + self.config["hf_model_name"], + self.tokenizer, + quantization_method=self.config["quantization_method"], + token=os.getenv('HF_TOKEN') + ) + + def prepare_modelfile_content(self): + output_model = self.config["hf_model_name"] + return f"""FROM {output_model}/unsloth.Q5_K_M.gguf + +TEMPLATE \"\"\"Below are some instructions that describe some tasks. Write responses that appropriately complete each request.{{{{ if .Prompt }}}} + +### Instruction: +{{{{ .Prompt }}}} + +{{{{ end }}}}### Response: +{{{{ .Response }}}}\"\"\" + +PARAMETER stop "" +PARAMETER stop "" +PARAMETER stop "" +PARAMETER stop "" +PARAMETER stop "<|reserved_special_token_" +""" + + def create_and_push_ollama_model(self): + modelfile_content = self.prepare_modelfile_content() + with open('Modelfile', 'w') as file: + file.write(modelfile_content) + + subprocess.run(["ollama", "serve"]) + subprocess.run(["ollama", "create", f"{self.config['ollama_model']}:{self.config['model_parameters']}", "-f", "Modelfile"]) + subprocess.run(["ollama", "push", f"{self.config['ollama_model']}:{self.config['model_parameters']}"]) + + def run(self): + self.print_system_info() + self.check_gpu() + self.check_ram() + # self.install_packages() + self.prepare_model() + self.train_model() + self.save_model_merged() + self.push_model_gguf() + self.create_and_push_ollama_model() + + +def main(): + import argparse + parser = argparse.ArgumentParser(description='PraisonAI Training Script') + parser.add_argument('command', choices=['train'], help='Command to execute') + parser.add_argument('--config', default='config.yaml', help='Path to configuration file') + args = parser.parse_args() + + if args.command == 'train': + ai = train(config_path=args.config) + ai.run() + + +if __name__ == '__main__': + main() diff --git a/pyproject.toml b/pyproject.toml index 6476a466..0a7e54ff 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "PraisonAI" -version = "0.0.58" +version = "0.0.59rc1" description = "PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration." authors = ["Mervin Praison"] license = "" @@ -20,7 +20,7 @@ pyautogen = ">=0.2.19" crewai = ">=0.32.0" markdown = ">=3.5" praisonai-tools = ">=0.0.7" -pyparsing = ">=3.0.0" # Added to fix a colab issue. Temp Fix. +pyparsing = ">=3.0.0" chainlit = {version = "^1.1.301", optional = true} gradio = {version = ">=4.26.0", optional = true} flask = {version = ">=3.0.0", optional = true} @@ -89,6 +89,8 @@ build-backend = "poetry.core.masonry.api" [tool.poetry.scripts] praisonai = "praisonai.__main__:main" +setup-conda-env = "setup.setup_conda_env:main" +post-install = "setup.post_install:main" [tool.poetry.extras] ui = ["chainlit"] @@ -100,4 +102,14 @@ openai = ["langchain-openai"] anthropic = ["langchain-anthropic"] cohere = ["langchain-cohere"] chat = ["chainlit", "litellm", "aiosqlite", "greenlet"] -code = ["chainlit", "litellm", "aiosqlite", "greenlet"] \ No newline at end of file +code = ["chainlit", "litellm", "aiosqlite", "greenlet"] +train = ["setup-conda-env"] + +[tool.poetry-dynamic-versioning] +enable = true +vcs = "git" +style = "semver" + +[tool.poetry.build] +generate-setup-file = false +script = "setup/post_install.py" \ No newline at end of file diff --git a/setup/__init__.py b/setup/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/setup/build.py b/setup/build.py new file mode 100644 index 00000000..6f393c65 --- /dev/null +++ b/setup/build.py @@ -0,0 +1,21 @@ +import subprocess +import sys +import os + +def build(setup_kwargs): + try: + # Get the directory of the current script + script_dir = os.path.dirname(os.path.abspath(__file__)) + + # Construct the path to post_install.py + post_install_script = os.path.join(script_dir, 'post_install.py') + + # Run the post_install.py script + subprocess.check_call([sys.executable, post_install_script]) + except subprocess.CalledProcessError as e: + print(f"Error occurred while running the post-install script: {e}") + sys.exit(1) + return setup_kwargs + +if __name__ == "__main__": + build({}) \ No newline at end of file diff --git a/setup/post_install.py b/setup/post_install.py new file mode 100644 index 00000000..c42c8e51 --- /dev/null +++ b/setup/post_install.py @@ -0,0 +1,20 @@ +import subprocess +import sys +import os + +def main(): + try: + # Get the directory of the current script + script_dir = os.path.dirname(os.path.abspath(__file__)) + + # Construct the path to setup_conda_env.py + setup_script = os.path.join(script_dir, 'setup_conda_env.py') + + # Run the setup_conda_env.py script + subprocess.check_call([sys.executable, setup_script]) + except subprocess.CalledProcessError as e: + print(f"Error occurred while running the setup script: {e}") + sys.exit(1) + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/setup/setup_conda_env.py b/setup/setup_conda_env.py new file mode 100644 index 00000000..5c21dde0 --- /dev/null +++ b/setup/setup_conda_env.py @@ -0,0 +1,25 @@ +import subprocess +import os +import sys +import platform + +def main(): + script_dir = os.path.dirname(os.path.abspath(__file__)) + script_path = os.path.join(script_dir, 'setup_conda_env.sh') + + if platform.system() == 'Windows': + print("Windows detected. Please run the setup_conda_env.sh script manually in Git Bash or WSL.") + print(f"Script location: {script_path}") + sys.exit(1) + + try: + subprocess.check_call(['bash', script_path]) + except subprocess.CalledProcessError as e: + print(f"Error occurred while running the setup script: {e}") + print("Setup failed. Please check the error message above and try to resolve the issue.") + sys.exit(1) + + print("Conda environment setup completed successfully!") + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/setup/setup_conda_env.sh b/setup/setup_conda_env.sh new file mode 100755 index 00000000..4cb9aecf --- /dev/null +++ b/setup/setup_conda_env.sh @@ -0,0 +1,60 @@ +#!/bin/bash + +# Detect OS and architecture +if [[ "$OSTYPE" == "darwin"* ]]; then + # macOS + if [[ $(uname -m) == 'arm64' ]]; then + MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh" + else + MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh" + fi +elif [[ "$OSTYPE" == "linux-gnu"* ]]; then + # Linux + MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh" +elif [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then + # Windows + MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe" + echo "Windows detected. Please run this script in Git Bash or WSL." + exit 1 +else + echo "Unsupported operating system: $OSTYPE" + exit 1 +fi + +# Check if conda is already installed +if ! command -v conda &> /dev/null; then + echo "Conda is not installed. Installing Miniconda..." + wget $MINICONDA_URL -O ~/miniconda.sh + bash ~/miniconda.sh -b -p $HOME/miniconda + source $HOME/miniconda/bin/activate + conda init +else + echo "Conda is already installed." +fi + +# Create and activate the Conda environment +ENV_NAME="unsloth_env" +if conda info --envs | grep -q $ENV_NAME; then + echo "Environment $ENV_NAME already exists. Activating..." + conda activate $ENV_NAME +else + echo "Creating new environment $ENV_NAME..." + if [[ "$OSTYPE" == "darwin"* ]]; then + # macOS (both Intel and M1/M2) + conda create --name $ENV_NAME python=3.10 pytorch=2.3.0 -c pytorch -y + elif [[ "$OSTYPE" == "linux-gnu"* ]]; then + # Linux + conda create --name $ENV_NAME python=3.10 pytorch=2.3.0 cudatoolkit=11.8 -c pytorch -c nvidia -y + conda activate $ENV_NAME + pip install xformers==0.0.26.post1 + fi +fi + +source $HOME/miniconda/bin/activate $ENV_NAME + +# Install other packages +pip install --upgrade pip +pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git@4e570be9ae4ced8cdc64e498125708e34942befc" +pip install --no-deps "trl<0.9.0" peft accelerate bitsandbytes + +echo "Setup completed successfully!" \ No newline at end of file