from zytron.structs.spreadsheet_zytron import SpreadSheetZytron
Attributes
The SpreadSheetZytron class contains several attributes that define its behavior and configuration. These attributes are initialized in the constructor (__init__ method) and are used throughout the class to manage the zytron's operations.
Attribute
Type
Description
name
str
The name of the zytron.
description
str
A description of the zytron's purpose.
agents
Union[Agent, List[Agent]]
The agents participating in the zytron. Can be a single agent or a list of agents.
autosave_on
bool
Flag indicating whether autosave is enabled.
save_file_path
str
The file path where the zytron data will be saved.
task_queue
queue.Queue
The queue that stores tasks to be processed by the agents.
lock
threading.Lock
A lock used for thread synchronization to prevent race conditions.
metadata
ZytronRunMetadata
Metadata for the zytron run, including start time, end time, tasks completed, and outputs.
run_all_agents
bool
Flag indicating whether to run all agents or just one.
max_loops
int
The number of times to repeat the task.
workspace_dir
str
The directory where the workspace is located, retrieved from environment variables.
Parameters
name (str, optional): The name of the zytron. Default is "Spreadsheet-Zytron".
description (str, optional): A brief description of the zytron. Default is "A zytron that processes tasks from a queue using multiple agents on different threads.".
agents (Union[Agent, List[Agent]], optional): The agents participating in the zytron. Default is an empty list.
autosave_on (bool, optional): A flag to indicate if autosave is enabled. Default is True.
save_file_path (str, optional): The file path where zytron data will be saved. Default is "spreedsheet_zytron.csv".
run_all_agents (bool, optional): Flag to determine if all agents should run. Default is True.
max_loops (int, optional): The number of times to repeat the task. Default is 1.
workspace_dir (str, optional): The directory where the workspace is located. Default is retrieved from environment variable WORKSPACE_DIR.
Constructor (__init__)
The constructor initializes the SpreadSheetZytron with the provided parameters. It sets up the task queue, locks for thread synchronization, and initializes the metadata.
Methods
reliability_check
def reliability_check(self):
Description
The reliability_check method performs a series of checks to ensure that the zytron is properly configured before it begins processing tasks. It verifies that there are agents available and that a valid file path is provided for saving the zytron's data. If any of these checks fail, an exception is raised.
Raises
ValueError: Raised if no agents are provided or if no save file path is specified.
The run method starts the task processing using the zytron. Depending on the configuration, it can either run all agents or a specific subset of them. The method tracks the start and end times of the task, executes the task multiple times if specified, and logs the results.
Parameters
task (str): The task to be executed by the zytron.
*args: Additional positional arguments to pass to the agents.
**kwargs: Additional keyword arguments to pass to the agents.
The export_to_json method generates a JSON representation of the zytron's metadata. This can be useful for exporting the results to an external system or for logging purposes.
Returns
str: The JSON representation of the zytron's metadata.
The data_to_json_file method saves the zytron's metadata as a JSON file in the specified workspace directory. The file name is generated using the zytron's name and run ID.
The _track_output method is used internally to record the results of tasks executed by the agents. It updates the metadata with the completed tasks and their results.
The _save_to_csv method saves the zytron's metadata to a CSV file. It logs each task and its result before writing them to the file. The file is saved in the location specified by save_file_path.
Example
zytron._save_to_csv()
Usage Examples
Example 1: Basic Zytron Initialization
import os
from zytron import Agent
from zytron_models import OpenAIChat
from zytron.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT,
)
from zytron.structs.spreadsheet_zytron import SpreadSheetZytron
# Example usage:
api_key = os.getenv("OPENAI_API_KEY")
# Model
model = OpenAIChat(
openai_api_key=api_key, model_name="gpt-4o-mini", temperature=0.1
)
# Initialize your agents (assuming the Agent class and model are already defined)
agents = [
Agent(
agent_name=f"Financial-Analysis-Agent-spreesheet-zytron:{i}",
system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="finance_agent.json",
user_name="zytron_corp",
retry_attempts=1,
)
for i in range(10)
]
# Create a Zytron with the list of agents
zytron = SpreadSheetZytron(
name="Finance-Spreadsheet-Zytron",
description="A zytron that processes tasks from a queue using multiple agents on different threads.",
agents=agents,
autosave_on=True,
save_file_path="financial_spreed_sheet_zytron_demo.csv",
run_all_agents=False,
max_loops=1,
)
# Run the zytron
zytron.run(
task="Analyze the states with the least taxes for LLCs. Provide an overview of all tax rates and add them with a comprehensive analysis"
)
Example 2: QR Code Generator
import os
from zytron import Agent
from zytron_models import OpenAIChat
from zytron.structs.spreadsheet_zytron import SpreadSheetZytron
# Define custom system prompts for QR code generation
QR_CODE_AGENT_1_SYS_PROMPT = """
You are a Python coding expert. Your task is to write a Python script to generate a QR code for the link: https://github.com/OpenAgentsAI. The code should save the QR code as an image file.
"""
QR_CODE_AGENT_2_SYS_PROMPT = """
You are a Python coding expert. Your task is to write a Python script to generate a QR code for the link: https://github.com/OpenAgentsAI. The code should save the QR code as an image file.
"""
# Example usage:
api_key = os.getenv("OPENAI_API_KEY")
# Model
model = OpenAIChat(
openai_api_key=api_key, model_name="gpt-4o-mini", temperature=0.1
)
# Initialize your agents for QR code generation
agents = [
Agent(
agent_name="QR-Code-Generator-Agent-Luma",
system_prompt=QR_CODE_AGENT_1_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="qr_code_agent_luma.json",
user_name="zytron_corp",
retry_attempts=1,
),
Agent(
agent_name="QR-Code-Generator-Agent-Cookbook",
system_prompt=QR_CODE_AGENT_2_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="qr_code_agent_cookbook.json",
user_name="zytron_corp",
retry_attempts=1,
),
]
# Create a Zytron with the list of agents
zytron = SpreadSheetZytron(
name="QR-Code-Generation-Zytron",
description="A zytron that generates Python scripts to create QR codes for specific links.",
agents=agents,
autosave_on=True,
save_file_path="qr_code_generation_results.csv",
run_all_agents=False,
max_loops=1,
)
# Run the zytron
zytron.run(
task="Generate Python scripts to create QR codes for the provided links and save them as image files."
)
Example 3: Social Media Marketing
import os
from zytron import Agent
from zytron_models import OpenAIChat
from zytron.structs.spreadsheet_zytron import SpreadSheetZytron
# Define custom system prompts for each social media platform
TWITTER_AGENT_SYS_PROMPT = """
You are a Twitter marketing expert. Your task is to create engaging, concise tweets and analyze trends to maximize engagement. Consider hashtags, timing, and content relevance.
"""
INSTAGRAM_AGENT_SYS_PROMPT = """
You are an Instagram marketing expert. Your task is to create visually appealing and engaging content, including captions and hashtags, tailored to a specific audience.
"""
FACEBOOK_AGENT_SYS_PROMPT = """
You are a Facebook marketing expert. Your task is to craft posts that are optimized for engagement and reach on Facebook, including using images, links, and targeted messaging.
"""
EMAIL_AGENT_SYS_PROMPT = """
You are an Email marketing expert. Your task is to write compelling email campaigns that drive conversions, focusing on subject lines, personalization, and call-to-action strategies.
"""
# Example usage:
api_key = os.getenv("OPENAI_API_KEY")
# Model
model = OpenAIChat(
openai_api_key=api_key, model_name="gpt-4o-mini", temperature=0.1
)
# Initialize your agents for different social media platforms
agents = [
Agent(
agent_name="Twitter-Marketing-Agent",
system_prompt=TWITTER_AGENT_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="twitter_agent.json",
user_name="zytron_corp",
retry_attempts=1,
),
Agent(
agent_name="Instagram-Marketing-Agent",
system_prompt=INSTAGRAM_AGENT_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="instagram_agent.json",
user_name="zytron_corp",
retry_attempts=1,
),
Agent(
agent_name="Facebook-Marketing-Agent",
system_prompt=FACEBOOK_AGENT_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="facebook_agent.json",
user_name="zytron_corp",
retry_attempts=1,
),
Agent(
agent_name="Email-Marketing-Agent",
system_prompt=EMAIL_AGENT_SYS_PROMPT,
llm=model,
max_loops=1,
dynamic_temperature_enabled=True,
saved_state_path="email_agent.json",
user_name="zytron_corp",
retry_attempts=1,
),
]
# Create a Zytron with the list of agents
zytron = SpreadSheetZytron(
name="Social-Media-Marketing-Zytron",
description="A zytron that processes social media marketing tasks using multiple agents on different threads.",
agents=agents,
autosave_on=True,
save_file_path="social_media_marketing_spreadsheet.csv",
run_all_agents=False,
max_loops=2,
)
# Run the zytron
zytron.run(
task="Create posts to promote hack nights in miami beach for developers, engineers, and tech enthusiasts. Include relevant hashtags, images, and engaging captions."
)
Additional Information and Tips
Thread Synchronization: When working with multiple agents in a concurrent environment, it's crucial to ensure that access to shared resources is properly synchronized using locks to avoid race conditions.
Autosave Feature: If you enable the autosave_on flag, ensure that the file path provided is correct and writable. This feature is handy for long-running tasks where you want to periodically save the state.
Error Handling
Implementing proper error handling within your agents can prevent the zytron from crashing during execution. Consider catching exceptions in the run method and logging errors appropriately.
Custom Agents: You can extend the Agent class to create custom agents that perform specific tasks tailored to your application's needs.
