diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml index 2a650d2d..5df477dd 100644 --- a/docs/mkdocs.yml +++ b/docs/mkdocs.yml @@ -147,7 +147,6 @@ nav: - Foundational Structures: - Agent: "swarms/structs/agent.md" - basestructure: "swarms/structs/basestructure.md" - - artifactupload: "swarms/structs/artifactupload.md" - taskinput: "swarms/structs/taskinput.md" - stepinput: "swarms/structs/stepinput.md" - artifact: "swarms/structs/artifact.md" diff --git a/docs/swarms/index.md b/docs/swarms/index.md index 6d8ad12d..304e8261 100644 --- a/docs/swarms/index.md +++ b/docs/swarms/index.md @@ -1,17 +1,8 @@ -![Swarming banner icon](images/swarmslogobanner.png) -
+# Swarms Orchestrate swarms of agents for production-grade applications. -[![GitHub issues](https://img.shields.io/github/issues/kyegomez/swarms)](https://github.com/kyegomez/swarms/issues) [![GitHub forks](https://img.shields.io/github/forks/kyegomez/swarms)](https://github.com/kyegomez/swarms/network) [![GitHub stars](https://img.shields.io/github/stars/kyegomez/swarms)](https://github.com/kyegomez/swarms/stargazers) [![GitHub license](https://img.shields.io/github/license/kyegomez/swarms)](https://github.com/kyegomez/swarms/blob/main/LICENSE)[![GitHub star chart](https://img.shields.io/github/stars/kyegomez/swarms?style=social)](https://star-history.com/#kyegomez/swarms)[![Dependency Status](https://img.shields.io/librariesio/github/kyegomez/swarms)](https://libraries.io/github/kyegomez/swarms) [![Downloads](https://static.pepy.tech/badge/swarms/month)](https://pepy.tech/project/swarms) - -[![Join the Agora discord](https://img.shields.io/discord/1110910277110743103?label=Discord&logo=discord&logoColor=white&style=plastic&color=d7b023)![Share on Twitter](https://img.shields.io/twitter/url/https/twitter.com/cloudposse.svg?style=social&label=Share%20%40kyegomez/swarms)](https://twitter.com/intent/tweet?text=Check%20out%20this%20amazing%20AI%20project:%20&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [![Share on Facebook](https://img.shields.io/badge/Share-%20facebook-blue)](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [![Share on LinkedIn](https://img.shields.io/badge/Share-%20linkedin-blue)](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=&summary=&source=) - -[![Share on Reddit](https://img.shields.io/badge/-Share%20on%20Reddit-orange)](https://www.reddit.com/submit?url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=Swarms%20-%20the%20future%20of%20AI) [![Share on Hacker News](https://img.shields.io/badge/-Share%20on%20Hacker%20News-orange)](https://news.ycombinator.com/submitlink?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&t=Swarms%20-%20the%20future%20of%20AI) [![Share on Pinterest](https://img.shields.io/badge/-Share%20on%20Pinterest-red)](https://pinterest.com/pin/create/button/?url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&media=https%3A%2F%2Fexample.com%2Fimage.jpg&description=Swarms%20-%20the%20future%20of%20AI) [![Share on WhatsApp](https://img.shields.io/badge/-Share%20on%20WhatsApp-green)](https://api.whatsapp.com/send?text=Check%20out%20Swarms%20-%20the%20future%20of%20AI%20%23swarms%20%23AI%0A%0Ahttps%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) - -
- Individual agents face five significant challenges that hinder their deployment in production: short memory, single-task threading, hallucinations, high cost, and lack of collaboration. Multi-agent collaboration offers a solution to all these issues. Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups. For more information on the unparalleled benefits of multi-agent collaboration, check out this GitHub repository for research papers or schedule a call with me! ---- diff --git a/example.py b/example.py index 6bb2ea7b..ea416785 100644 --- a/example.py +++ b/example.py @@ -20,7 +20,9 @@ agent = Agent( ) # Run the Agent on a task -out = agent.run("Generate a transcript for a youtube video on what swarms are!") +out = agent.run( + "Generate a transcript for a youtube video on what swarms are!" +) print(out) # Save the state diff --git a/sequential_workflow_new.py b/sequential_workflow_new.py new file mode 100644 index 00000000..0a706a61 --- /dev/null +++ b/sequential_workflow_new.py @@ -0,0 +1,41 @@ +from swarms import Anthropic, Agent, SequentialWorkflow + + +# Initialize the language model agent (e.g., GPT-3) + +llm = Anthropic() + + +# Initialize agents for individual tasks + +agent1 = Agent( + agent_name="Blog generator", llm=llm, max_loops=1, dashboard=False +) + +agent2 = Agent( + agent_name="summarizer", llm=llm, max_loops=1, dashboard=False +) + + +# Create the Sequential workflow + +workflow = SequentialWorkflow( + max_loops=1, objective="Create a full blog and then summarize it" +) + + +# Add tasks to the workflow + +workflow.add( + "Generate a 10,000 word blog on health and wellness.", agent1 +) # this task will be executed task, + +workflow.add( + "Summarize the generated blog", agent2 +) # then the next agent will accomplish this task + + +# Run the workflow + +out = workflow.run() +print(f"{out}") diff --git a/swarms/models/__init__.py b/swarms/models/__init__.py index 1e320d5c..b6f3c70c 100644 --- a/swarms/models/__init__.py +++ b/swarms/models/__init__.py @@ -81,4 +81,4 @@ __all__ = [ "VideoModality", "TogetherLLM", "Vilt", -] \ No newline at end of file +] diff --git a/swarms/models/openai_embeddings.py b/swarms/models/openai_embeddings.py index e8267904..0193f0cc 100644 --- a/swarms/models/openai_embeddings.py +++ b/swarms/models/openai_embeddings.py @@ -2,4 +2,4 @@ from langchain_community.embeddings.openai import OpenAIEmbeddings __all__ = [ "OpenAIEmbeddings", -] \ No newline at end of file +] diff --git a/swarms/models/palm.py b/swarms/models/palm.py index ffc1582e..301ce1bd 100644 --- a/swarms/models/palm.py +++ b/swarms/models/palm.py @@ -2,4 +2,4 @@ from langchain_community.llms.google_palm import GooglePalm __all__ = [ "GooglePalm", -] \ No newline at end of file +] diff --git a/swarms/models/popular_llms.py b/swarms/models/popular_llms.py index 25ae0895..61f2ca07 100644 --- a/swarms/models/popular_llms.py +++ b/swarms/models/popular_llms.py @@ -11,35 +11,54 @@ from langchain.llms.openai import OpenAI # , OpenAIChat, AzureOpenAI from langchain_community.llms.octoai_endpoint import OctoAIEndpoint from langchain.llms.replicate import Replicate + class AnthropicChat(Anthropic): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class CohereChat(Cohere): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class MosaicMLChat(MosaicML): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class OpenAILLM(OpenAI): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class ReplicateChat(Replicate): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class AzureOpenAILLM(AzureChatOpenAI): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class OpenAIChatLLM(OpenAIChat): def __init__(self, *args, **kwargs): @@ -48,7 +67,13 @@ class OpenAIChatLLM(OpenAIChat): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) + class OctoAIChat(OctoAIEndpoint): def __call__(self, *args, **kwargs): return self.invoke(*args, **kwargs) + + def run(self, *args, **kwargs): + return self.invoke(*args, **kwargs) diff --git a/swarms/models/popular_speech.py b/swarms/models/popular_speech.py deleted file mode 100644 index e69de29b..00000000 diff --git a/swarms/structs/conversation.py b/swarms/structs/conversation.py index ddbc0c5a..d0a1b2d0 100644 --- a/swarms/structs/conversation.py +++ b/swarms/structs/conversation.py @@ -69,6 +69,12 @@ class Conversation(BaseStructure): save_filepath: str = None, tokenizer: Any = None, context_length: int = 8192, + rules: str = None, + custom_rules_prompt: str = None, + user: str = "User:", + auto_save: bool = True, + save_as_yaml: bool = True, + save_as_json: bool = False, *args, **kwargs, ): @@ -81,11 +87,23 @@ class Conversation(BaseStructure): self.conversation_history = [] self.tokenizer = tokenizer self.context_length = context_length + self.rules = rules + self.custom_rules_prompt = custom_rules_prompt + self.user = user + self.auto_save = auto_save + self.save_as_yaml = save_as_yaml + self.save_as_json = save_as_json # If system prompt is not None, add it to the conversation history if self.system_prompt is not None: self.add("System: ", self.system_prompt) + if self.rules is not None: + self.add(user, rules) + + if custom_rules_prompt is not None: + self.add(user, custom_rules_prompt) + # If tokenizer then truncate if tokenizer is not None: self.truncate_memory_with_tokenizer() diff --git a/swarms/structs/sequential_workflow.py b/swarms/structs/sequential_workflow.py index 8ef0ee47..22320205 100644 --- a/swarms/structs/sequential_workflow.py +++ b/swarms/structs/sequential_workflow.py @@ -1,203 +1,134 @@ -from dataclasses import dataclass -from typing import Any, Dict, List, Optional - -from termcolor import colored - -# from swarms.utils.logger import logger +from dataclasses import dataclass, field +from typing import List, Optional from swarms.structs.agent import Agent from swarms.structs.conversation import Conversation -from swarms.structs.task import Task from swarms.utils.loguru_logger import logger +from swarms.utils.try_except_wrapper import try_except_wrapper -# SequentialWorkflow class definition using dataclasses @dataclass class SequentialWorkflow: - """ - SequentialWorkflow class for running a sequence of task_pool using N number of autonomous agents. - - Args: - max_loops (int): The maximum number of times to run the workflow. - dashboard (bool): Whether to display the dashboard for the workflow. - - - Attributes: - task_pool (List[Task]): The list of task_pool to execute. - max_loops (int): The maximum number of times to run the workflow. - dashboard (bool): Whether to display the dashboard for the workflow. - - - Examples: - >>> from swarms.models import OpenAIChat - >>> from swarms.structs import SequentialWorkflow - >>> llm = OpenAIChat(openai_api_key="") - >>> workflow = SequentialWorkflow(max_loops=1) - >>> workflow.add("What's the weather in miami", llm) - >>> workflow.add("Create a report on these metrics", llm) - >>> workflow.run() - >>> workflow.task_pool - - """ - - name: str = None + name: str = "Sequential Workflow" description: str = None - task_pool: List[Task] = None + objective: str = None max_loops: int = 1 autosave: bool = False saved_state_filepath: Optional[str] = "sequential_workflow_state.json" restore_state_filepath: Optional[str] = None dashboard: bool = False - agents: List[Agent] = None + agent_pool: List[Agent] = field(default_factory=list) + # task_pool: List[str] = field( + # default_factory=list + # ) # List to store tasks def __post_init__(self): self.conversation = Conversation( - system_prompt=f"Objective: {self.description}", time_enabled=True, autosave=True, ) - # Logging - logger.info("Number of agents activated:") - if self.agents: - logger.info(f"Agents: {len(self.agents)}") - else: - logger.info("No agents activated.") - - if self.task_pool: - logger.info(f"Task Pool Size: {len(self.task_pool)}") - else: - logger.info("Task Pool is empty.") - - def add( - self, - task: Optional[Task] = None, - tasks: Optional[List[Task]] = None, - *args, - **kwargs, - ) -> None: - """ - Add a task to the workflow. - - Args: - agent (Union[Callable, Agent]): The model or agent to execute the task. - task (str): The task description or the initial input for the Agent. - - *args: Additional arguments to pass to the task execution. - **kwargs: Additional keyword arguments to pass to the task execution. - """ - for agent in self.agents: - out = agent(str(self.description)) - self.conversation.add(agent.agent_name, out) - prompt = self.conversation.return_history_as_string() - out = agent(prompt) - - return out + # If objective exists then set it + if self.objective is not None: + self.conversation.system_prompt = self.objective + + def workflow_bootup(self): + logger.info(f"{self.name} is activating...") + + for agent in self.agent_pool: + logger.info(f"Agent {agent.agent_name} Activated") + + @try_except_wrapper + def add(self, task: str, agent: Agent, *args, **kwargs): + self.agent_pool.append(agent) + # self.task_pool.append( + # task + # ) # Store tasks corresponding to each agent + + return self.conversation.add( + role=agent.agent_name, content=task, *args, **kwargs + ) def reset_workflow(self) -> None: - """Resets the workflow by clearing the results of each task.""" - try: - for task in self.task_pool: - task.result = None - logger.info( - f"[INFO][SequentialWorkflow] Reset task {task} in" - " workflow" - ) - except Exception as error: - logger.error( - colored(f"Error resetting workflow: {error}", "red"), - ) - - def get_task_results(self) -> Dict[str, Any]: - """ - Returns the results of each task in the workflow. - - Returns: - Dict[str, Any]: The results of each task in the workflow - """ - try: - return { - task.description: task.result for task in self.task_pool - } - except Exception as error: - logger.error( - colored(f"Error getting task results: {error}", "red"), - ) - - def remove_task(self, task: Task) -> None: - """Remove task_pool from sequential workflow""" - try: - self.task_pool.remove(task) - logger.info( - f"[INFO][SequentialWorkflow] Removed task {task} from" - " workflow" - ) - except Exception as error: - logger.error( - colored( - f"Error removing task from workflow: {error}", - "red", - ), - ) - - def run(self) -> None: - """ - Run the workflow. - - Raises: - ValueError: If an Agent instance is used as a task and the 'task' argument is not provided. - - """ + self.conversation = {} + + # @try_except_wrapper + # WITH TASK POOL + # def run(self): + # if not self.agent_pool: + # raise ValueError("No agents have been added to the workflow.") + + # self.workflow_bootup() + # loops = 0 + # prompt = None # Initialize prompt to None; will be updated with the output of each agent + # while loops < self.max_loops: + # for i, agent in enumerate(self.agent_pool): + # task = ( + # self.task_pool[i] if prompt is None else prompt + # ) # Use initial task or the output from the previous agent + # logger.info( + # f"Agent: {agent.agent_name} {i+1} is executing the task" + # ) + # logger.info("\n") + # output = agent.run(task) + # if output is None: + # logger.error( + # f"Agent {i+1} returned None for task: {task}" + # ) + # raise ValueError(f"Agent {i+1} returned None.") + # self.conversation.add(agent.agent_name, output) + # prompt = output # Update prompt with current agent's output to pass to the next agent + # logger.info(f"Prompt: {prompt}") + # loops += 1 + # return self.conversation.return_history_as_string() + @try_except_wrapper + def run(self): + if not self.agent_pool: + raise ValueError("No agents have been added to the workflow.") + self.workflow_bootup() loops = 0 while loops < self.max_loops: - for i, agent in enumerate(self.agents): - logger.info(f"Agent {i+1} is executing the task.") - out = agent(self.description) - self.conversation.add(agent.agent_name, str(out)) - prompt = self.conversation.return_history_as_string() - print(prompt) - print("Next agent...........") - out = agent(prompt) - - return out - # try: - # self.workflow_bootup() - # loops = 0 - # while loops < self.max_loops: - # for i in range(len(self.task_pool)): - # task = self.task_pool[i] - # # Check if the current task can be executed - # if task.result is None: - # # Get the inputs for the current task - # task.context(task) - - # result = task.execute() - - # # Pass the inputs to the next task - # if i < len(self.task_pool) - 1: - # next_task = self.task_pool[i + 1] - # next_task.description = result - - # # Execute the current task - # task.execute() - - # # Autosave the workflow state - # if self.autosave: - # self.save_workflow_state( - # "sequential_workflow_state.json" - # ) - - # self.workflow_shutdown() - # loops += 1 - # except Exception as e: - # logger.error( - # colored( - # ( - # "Error initializing the Sequential workflow:" - # f" {e} try optimizing your inputs like the" - # " agent class and task description" - # ), - # "red", - # attrs=["bold", "underline"], - # ) - # ) + previous_output = None # Initialize to None; will hold the output of the previous agent + for i, agent in enumerate(self.agent_pool): + # Fetch the last task specific to this agent from the conversation history + tasks_for_agent = [ + msg["content"] + for msg in self.conversation.conversation_history + if msg["role"] == agent.agent_name + ] + task = tasks_for_agent[-1] if tasks_for_agent else None + + if task is None and previous_output is not None: + # If no specific task for this agent, use the output from the previous agent + task = previous_output + + if task is None: + # If no initial task is found, and there's no previous output, log error and skip this agent + logger.error( + f"No initial task found for agent {agent.agent_name}, and no previous output to use." + ) + continue + + logger.info( + f" \n Agent {i+1} ({agent.agent_name}) is executing the task: {task} \n" + ) + + # Space the log + + output = agent.run(task) + if output is None: + logger.error( + f"Agent {agent.agent_name} returned None for task: {task}" + ) + raise ValueError( + f"Agent {agent.agent_name} returned None." + ) + + # Update the conversation history with the new output using agent's role + self.conversation.add( + role=agent.agent_name, content=output + ) + previous_output = output # Update the previous_output to pass to the next agent + + loops += 1 + return self.conversation.return_history_as_string() diff --git a/swarms/utils/try_except_wrapper.py b/swarms/utils/try_except_wrapper.py index 1f0b431d..46b3b208 100644 --- a/swarms/utils/try_except_wrapper.py +++ b/swarms/utils/try_except_wrapper.py @@ -1,4 +1,4 @@ -from swarms.utils.logger import logger +from swarms.utils.loguru_logger import logger def try_except_wrapper(func, verbose: bool = False):