diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..2e90bb1 --- /dev/null +++ b/.env.example @@ -0,0 +1,4 @@ +ANTHROPIC_API_KEY= +TAVILY_API_KEY= +OPENAI_API_KEY= +GROQ_API_KEY= \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..61d148e --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +.env +__pycache__ +objectives \ No newline at end of file diff --git a/README.md b/README.md index 615f760..72b0c5d 100644 --- a/README.md +++ b/README.md @@ -1,97 +1,96 @@ -# Maestro - A Framework for Claude Opus, GPT and local LLMs to Orchestrate Subagents - +# Maestro - A Framework for Claude Opus, GPT, and Local LLMs to Orchestrate Subagents This Python script demonstrates an AI-assisted task breakdown and execution workflow using the Anthropic API. It utilizes two AI models, Opus and Haiku, to break down an objective into sub-tasks, execute each sub-task, and refine the results into a cohesive final output. -## New: +## New: -# GPT-4o +### GPT-4o -The GPT script has been updated from the ground up to support the code capabilities of GPT-4o +The GPT script has been updated from the ground up to support the code capabilities of GPT-4o. -Afeter installing dependecies run +After installing dependencies, run: ```bash -python maestro-gpt4o.py +poetry run python maestro-gpt4o.py ``` -## Run locally with LMStudio or Ollama +## Run Locally with LMStudio or Ollama -### Lmstudio +### LMStudio -First download the app here -https://lmstudio.ai/ +First, download the app [here](https://lmstudio.ai/). Then run the local server using your preferred method. I also recommend removing any system prompt for the app (leave your prompt field empty so it can take advantage of the script prompts). -Then +Then: + ```bash -python maestro-lmstudio.py +poetry run python maestro-lmstudio.py ``` - ### Ollama -Mestro now runs locally thanks to the Ollama platform. Experience the power of Llama 3 locally! -Before running the script +Maestro now runs locally thanks to the Ollama platform. Experience the power of Llama 3 locally! -Install Ollama client from here -https://ollama.com/download +Before running the script, install the Ollama client from [here](https://ollama.com/download). -then +Then: ```bash -pip install ollama +poetry add ollama ``` -And + +And: ```bash -ollama.pull('llama3:70b') +ollama pull llama3:70b ``` -This will depend on the model you want to use it, you only need to do it once or if you want to update the model when a new version it's out. -In the script I am using both versions but you can customize the model you want to use -ollama.pull('llama3:70b') -ollama.pull('llama3:8b') +This will depend on the model you want to use; you only need to do it once or if you want to update the model when a new version is out. In the script, I am using both versions, but you can customize the model you want to use: -Then +```bash +ollama pull llama3:70b +ollama pull llama3:8b +``` + +Then: ```bash -python maestro-ollama.py +poetry run python maestro-ollama.py ``` -## Highly requested features -- GROQ SUPPORT -Experience the power of maestro thanks to Groq super fast api responses. +## Highly Requested Features + +### GROQ Support + +Experience the power of Maestro thanks to Groq's super-fast API responses. + ```bash -pip install groq +poetry add groq ``` -Then + +Then: ```bash -python maestro-groq.py +poetry run python maestro-groq.py ``` +### Search 🔍 -- SEARCH 🔍 +Now, when creating a task for its subagent, Claude Opus will perform a search and get the best answer to help the subagent solve that task even better. -Now, when it's creating a task for its subagent, Claude Opus will perform a search and get the best answer to help the subagent solve that task even better. +Make sure you replace your Tavil API key for search to work. Get one [here](https://tavily.com/). -Make sure you replace your Tavil API for search to work +### GPT-4 Support -Get one here https://tavily.com/ - -- GPT4 SUPPORT +Add support for GPT-4 as an orchestrator in maestro-gpt.py. Simply: -Add support for GPT-4 as an orchestrator in maestro-gpt.py -Simply ```bash -python maestro-gpt.py +poetry run python maestro-gpt.py ``` After you complete your installs. - ## Features - Breaks down an objective into manageable sub-tasks using the Opus model @@ -101,7 +100,7 @@ After you complete your installs. - Generates a detailed exchange log capturing the entire task breakdown and execution process - Saves the exchange log to a Markdown file for easy reference - Utilizes an improved prompt for the Opus model to better assess task completion -- Creates code files and folders when working on code projects. +- Creates code files and folders when working on code projects ## Prerequisites @@ -109,26 +108,30 @@ To run this script, you need to have the following: - Python installed - Anthropic API key -- Required Python packages: `anthropic` and `rich` +- Required Python packages ## Installation 1. Clone the repository or download the script file. -2. Install the required Python packages by running the following command: +2. Install Poetry if you haven't already: ```bash -pip install -r requirements.txt +curl -sSL https://install.python-poetry.org | python3 - ``` -3. Replace the placeholder API key in the script with your actual Anthropic API key: +3. Install the required Python packages by running the following command: -```python -client = Anthropic(api_key="YOUR_API_KEY_HERE") +```bash +poetry install ``` -If using search, replace your Tavil API -```python -tavily = TavilyClient(api_key="YOUR API KEY HERE") +4. Create a `.env` file in the root directory of your project and add your API keys: + +``` +ANTHROPIC_API_KEY=your_anthropic_api_key_here +TAVILY_API_KEY=your_tavily_api_key_here +OPENAI_API_KEY=your_openai_api_key +GROQ_API_KEY=your_groq_api_key ``` ## Usage @@ -137,7 +140,7 @@ tavily = TavilyClient(api_key="YOUR API KEY HERE") 2. Run the script using the following command: ```bash -python maestro.py +poetry run python maestro.py ``` 3. Enter your objective when prompted: @@ -148,7 +151,7 @@ Please enter your objective: Your objective here The script will start the task breakdown and execution process. It will display the progress and results in the console using formatted panels. -Once the process is complete, the script will display the refined final output and save the full exchange log to a Markdown file with a filename based on the objective. +Once the process is complete, the script will display the refined final output and save the full exchange log to a Markdown file in a local folder named `./objectives/{time}`, where `{time}` is the current timestamp. ## Code Structure @@ -158,19 +161,19 @@ The script consists of the following main functions: - `haiku_sub_agent(prompt, previous_haiku_tasks=None)`: Calls the Haiku model to execute a sub-task prompt, providing it with the memory of previous sub-tasks. - `opus_refine(objective, sub_task_results)`: Calls the Opus model to review and refine the sub-task results into a cohesive final output. -The script follows an iterative process, repeatedly calling the opus_orchestrator function to break down the objective into sub-tasks until the final output is provided. Each sub-task is then executed by the haiku_sub_agent function, and the results are stored in the task_exchanges and haiku_tasks lists. +The script follows an iterative process, repeatedly calling the `opus_orchestrator` function to break down the objective into sub-tasks until the final output is provided. Each sub-task is then executed by the `haiku_sub_agent` function, and the results are stored in the `task_exchanges` and `haiku_tasks` lists. The loop terminates when the Opus model includes the phrase "The task is complete:" in its response, indicating that the objective has been fully achieved. -Finally, the opus_refine function is called to review and refine the sub-task results into a final output. The entire exchange log, including the objective, task breakdown, and refined final output, is saved to a Markdown file. +Finally, the `opus_refine` function is called to review and refine the sub-task results into a final output. The entire exchange log, including the objective, task breakdown, and refined final output, is saved to a Markdown file in a local folder named `./objectives/{time}`, where `{time}` is the current timestamp. ## Customization You can customize the script according to your needs: -- Adjust the max_tokens parameter in the client.messages.create() function calls to control the maximum number of tokens generated by the AI models. +- Adjust the `max_tokens` parameter in the `client.messages.create()` function calls to control the maximum number of tokens generated by the AI models. - Change the models to what you prefer, like replacing Haiku with Sonnet or Opus. -- Modify the console output formatting by updating the rich library's Panel and Console configurations. +- Modify the console output formatting by updating the `rich` library's `Panel` and `Console` configurations. - Customize the exchange log formatting and file extension by modifying the relevant code sections. ## License diff --git a/config.py b/config.py new file mode 100644 index 0000000..770c4ec --- /dev/null +++ b/config.py @@ -0,0 +1,13 @@ +import os +import datetime +from dotenv import load_dotenv + +load_dotenv() + +anthropic_api_key = os.getenv('ANTHROPIC_API_KEY') +tavily_api_key = os.getenv('TAVILY_API_KEY') +openai_api_key = os.getenv('OPENAI_API_KEY') +groq_api_key = os.getenv('GROQ_API_KEY') + +objectives_dir = os.path.join(os.path.dirname( + __file__), 'objectives', datetime.datetime.now().strftime('%Y-%m-%d-%H-%M-%S')) diff --git a/maestro-gpt4o.py b/maestro-gpt4o.py index 4adb01c..a5e4ee5 100644 --- a/maestro-gpt4o.py +++ b/maestro-gpt4o.py @@ -8,9 +8,11 @@ from anthropic import Anthropic from tavily import TavilyClient +import config + # Initialize OpenAI and Anthropic API clients -openai_client = OpenAI(api_key="YOUR API KEY") -anthropic_client = Anthropic(api_key="YOUR API KEY") +openai_client = OpenAI(api_key=config.openai_api_key) +anthropic_client = Anthropic(api_key=config.anthropic_api_key) # Available OpenAI models ORCHESTRATOR_MODEL = "gpt-4o" @@ -154,7 +156,7 @@ def anthropic_refine(objective, sub_task_results, filename, projectname, continu def create_folder_structure(project_name, folder_structure, code_blocks): try: - os.makedirs(project_name, exist_ok=True) + os.makedirs(os.path.join(config.objectives_dir, project_name), exist_ok=True) console.print(Panel(f"Created project folder: [bold]{project_name}[/bold]", title="[bold green]Project Folder[/bold green]", title_align="left", border_style="green")) except OSError as e: console.print(Panel(f"Error creating project folder: [bold]{project_name}[/bold]\nError: {e}", title="[bold red]Project Folder Creation Error[/bold red]", title_align="left", border_style="red")) @@ -164,7 +166,7 @@ def create_folder_structure(project_name, folder_structure, code_blocks): def create_folders_and_files(current_path, structure, code_blocks): for key, value in structure.items(): - path = os.path.join(current_path, key) + path = os.path.join(config.objectives_dir, current_path, key) if isinstance(value, dict): try: os.makedirs(path, exist_ok=True) @@ -256,7 +258,7 @@ def read_file(file_path): max_length = 25 truncated_objective = sanitized_objective[:max_length] if len(sanitized_objective) > max_length else sanitized_objective -filename = f"{timestamp}_{truncated_objective}.md" +filename = os.path.join(config.objectives_dir, f"{timestamp}_{truncated_objective}.md") exchange_log = f"Objective: {objective}\n\n" exchange_log += "=" * 40 + " Task Breakdown " + "=" * 40 + "\n\n" diff --git a/maestro-groq.py b/maestro-groq.py index cb648fd..2c06a74 100644 --- a/maestro-groq.py +++ b/maestro-groq.py @@ -9,7 +9,9 @@ from groq import Groq import os -client = Groq(api_key="YOUR API KEY") +import config + +client = Groq(api_key=config.groq_api_key) # Define the models to use for each agent ORCHESTRATOR_MODEL = "mixtral-8x7b-32768" @@ -101,7 +103,7 @@ def opus_refine(objective, sub_task_results, filename, projectname, continuation def create_folder_structure(project_name, folder_structure, code_blocks): # Create the project folder try: - os.makedirs(project_name, exist_ok=True) + os.makedirs(os.path.join(config.objectives_dir, project_name), exist_ok=True) console.print(Panel(f"Created project folder: [bold]{project_name}[/bold]", title="[bold green]Project Folder[/bold green]", title_align="left", border_style="green")) except OSError as e: console.print(Panel(f"Error creating project folder: [bold]{project_name}[/bold]\nError: {e}", title="[bold red]Project Folder Creation Error[/bold red]", title_align="left", border_style="red")) @@ -215,7 +217,7 @@ def read_file(file_path): truncated_objective = sanitized_objective[:max_length] if len(sanitized_objective) > max_length else sanitized_objective # Update the filename to include the project name -filename = f"{timestamp}_{truncated_objective}.md" +filename = os.path.join(config.objectives_dir, f"{timestamp}_{truncated_objective}.md") # Prepare the full exchange log exchange_log = f"Objective: {objective}\n\n" diff --git a/maestro-lmstudio.py b/maestro-lmstudio.py index 7a45ae9..5e03e34 100644 --- a/maestro-lmstudio.py +++ b/maestro-lmstudio.py @@ -7,6 +7,8 @@ from tavily import TavilyClient from openai import OpenAI +import config + # Set up the LM Studio API client client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio") @@ -147,7 +149,7 @@ def opus_refine(objective, sub_task_results, filename, projectname, continuation def create_folder_structure(project_name, folder_structure, code_blocks): # Create the project folder try: - os.makedirs(project_name, exist_ok=True) + os.makedirs(os.path.join(config.objectives_dir, project_name), exist_ok=True) console.print(Panel(f"Created project folder: [bold]{project_name}[/bold]", title="[bold green]Project Folder[/bold green]", title_align="left", border_style="green")) except OSError as e: console.print(Panel(f"Error creating project folder: [bold]{project_name}[/bold]\nError: {e}", title="[bold red]Project Folder Creation Error[/bold red]", title_align="left", border_style="red")) @@ -264,7 +266,7 @@ def read_file(file_path): truncated_objective = sanitized_objective[:max_length] if len(sanitized_objective) > max_length else sanitized_objective # Update the filename to include the project name -filename = f"{timestamp}_{truncated_objective}.md" +filename = os.path.join(config.objectives_dir, f"{timestamp}_{truncated_objective}.md") # Prepare the full exchange log exchange_log = f"Objective: {objective}\n\n" diff --git a/maestro-ollama.py b/maestro-ollama.py index 566892a..d1f4171 100644 --- a/maestro-ollama.py +++ b/maestro-ollama.py @@ -8,6 +8,8 @@ from ollama import Client # Import the Ollama client import argparse +import config + # Only for the first time run based on the model you want to use # ollama.pull('llama3:70b') # ollama.pull('llama3:8b') @@ -112,7 +114,7 @@ def opus_refine(objective, sub_task_results, filename, projectname, continuation def create_folder_structure(project_name, folder_structure, code_blocks): try: - os.makedirs(project_name, exist_ok=True) + os.makedirs(os.path.join(config.objectives_dir, project_name), exist_ok=True) console.print(Panel(f"Created project folder: [bold]{project_name}[/bold]", title="[bold blue]Project Folder Creation[/bold blue]", title_align="left", border_style="blue")) except OSError as e: console.print(Panel(f"Error creating project folder: [bold]{project_name}[/bold]\nError: {e}", title="[bold red]Project Folder Creation Error[/bold red]", title_align="left", border_style="red")) @@ -265,7 +267,7 @@ def write_task_data(task_data): truncated_objective = sanitized_objective[:max_length] if len(sanitized_objective) > max_length else sanitized_objective # Update the filename to include the project name -filename = f"{timestamp}_{truncated_objective}.md" +filename = os.path.join(config.objectives_dir, f"{timestamp}_{truncated_objective}.md") # Prepare the full exchange log exchange_log = f"Objective: {objective}\n\n" diff --git a/maestro.py b/maestro.py index 56a412d..13b070e 100644 --- a/maestro.py +++ b/maestro.py @@ -7,8 +7,10 @@ import json from tavily import TavilyClient +import config + # Set up the Anthropic API client -client = Anthropic(api_key="YOUR API KEY") +client = Anthropic(api_key=config.anthropic_api_key) # Available Claude models: # Claude 3 Opus claude-3-opus-20240229 @@ -167,7 +169,7 @@ def opus_refine(objective, sub_task_results, filename, projectname, continuation def create_folder_structure(project_name, folder_structure, code_blocks): # Create the project folder try: - os.makedirs(project_name, exist_ok=True) + os.makedirs(os.path.join(config.objectives_dir, project_name), exist_ok=True) console.print(Panel(f"Created project folder: [bold]{project_name}[/bold]", title="[bold green]Project Folder[/bold green]", title_align="left", border_style="green")) except OSError as e: console.print(Panel(f"Error creating project folder: [bold]{project_name}[/bold]\nError: {e}", title="[bold red]Project Folder Creation Error[/bold red]", title_align="left", border_style="red")) @@ -178,7 +180,7 @@ def create_folder_structure(project_name, folder_structure, code_blocks): def create_folders_and_files(current_path, structure, code_blocks): for key, value in structure.items(): - path = os.path.join(current_path, key) + path = os.path.join(config.objectives_dir, current_path, key) if isinstance(value, dict): try: os.makedirs(path, exist_ok=True) @@ -284,7 +286,7 @@ def read_file(file_path): truncated_objective = sanitized_objective[:max_length] if len(sanitized_objective) > max_length else sanitized_objective # Update the filename to include the project name -filename = f"{timestamp}_{truncated_objective}.md" +filename = os.path.join(config.objectives_dir, f"{timestamp}_{truncated_objective}.md") # Prepare the full exchange log exchange_log = f"Objective: {objective}\n\n" diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 0000000..5e8d21c --- /dev/null +++ b/poetry.lock @@ -0,0 +1,1017 @@ +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. + +[[package]] +name = "annotated-types" +version = "0.6.0" +description = "Reusable constraint types to use with typing.Annotated" +optional = false +python-versions = ">=3.8" +files = [ + {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"}, + {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"}, +] + +[[package]] +name = "anthropic" +version = "0.26.0" +description = "The official Python library for the anthropic API" +optional = false +python-versions = ">=3.7" +files = [ + {file = "anthropic-0.26.0-py3-none-any.whl", hash = "sha256:38fc415561d71dcf263b89da0cc6ecec498379b56256fc4242e9128bc707b283"}, + {file = "anthropic-0.26.0.tar.gz", hash = "sha256:6aaffeb05d515cf9788eef57150a5f827f3786883628ccac71dbe5671ab6f44e"}, +] + +[package.dependencies] +anyio = ">=3.5.0,<5" +distro = ">=1.7.0,<2" +httpx = ">=0.23.0,<1" +pydantic = ">=1.9.0,<3" +sniffio = "*" +tokenizers = ">=0.13.0" +typing-extensions = ">=4.7,<5" + +[package.extras] +bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"] +vertex = ["google-auth (>=2,<3)"] + +[[package]] +name = "anyio" +version = "4.3.0" +description = "High level compatibility layer for multiple asynchronous event loop implementations" +optional = false +python-versions = ">=3.8" +files = [ + {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"}, + {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"}, +] + +[package.dependencies] +idna = ">=2.8" +sniffio = ">=1.1" + +[package.extras] +doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] +trio = ["trio (>=0.23)"] + +[[package]] +name = "certifi" +version = "2024.2.2" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.6" +files = [ + {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, + {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, +] + +[[package]] +name = "charset-normalizer" +version = "3.3.2" +description = "The Real First Universal Charset Detector. 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