From fe8386780f8ceead09bdece13b7d4ee35299ccdf Mon Sep 17 00:00:00 2001
From: Kye Gomez <kye@swarms.world>
Date: Tue, 25 Feb 2025 13:22:43 -0800
Subject: [PATCH] [feature][add list, dictionary, and str outputs to swarm
architectures through conversation]
---
agents_builder.py | 9 ++
concurrent_example.py | 3 +-
docs/swarms_cloud/swarms_api.md | 2 +-
pyproject.toml | 2 +-
swarms/structs/agent_builder.py | 208 ++++++++++++++++++++++++++
swarms/structs/concurrent_workflow.py | 12 +-
swarms/structs/conversation.py | 13 +-
swarms/structs/majority_voting.py | 18 ++-
swarms/structs/mixture_of_agents.py | 16 +-
swarms/structs/output_type.py | 18 +++
swarms/structs/rearrange.py | 20 ++-
swarms/structs/sequential_workflow.py | 17 ++-
swarms/structs/swarm_router.py | 5 +-
swarms/structs/swarms_api.py | 4 +
swarms_api_example.py | 17 ++-
15 files changed, 338 insertions(+), 26 deletions(-)
create mode 100644 agents_builder.py
create mode 100644 swarms/structs/agent_builder.py
create mode 100644 swarms/structs/output_type.py
diff --git a/agents_builder.py b/agents_builder.py
new file mode 100644
index 00000000..191f0b84
--- /dev/null
+++ b/agents_builder.py
@@ -0,0 +1,9 @@
+from swarms.structs.agent_builder import AgentsBuilder
+
+example_task = "Write a blog post about the benefits of using Swarms for AI agents."
+
+agents_builder = AgentsBuilder()
+
+agents = agents_builder.run(example_task)
+
+print(agents)
diff --git a/concurrent_example.py b/concurrent_example.py
index 70f11a13..da9eb139 100644
--- a/concurrent_example.py
+++ b/concurrent_example.py
@@ -59,7 +59,8 @@ task = """
# Run agents with tasks concurrently
swarm = ConcurrentWorkflow(
agents=agents,
- return_str_on=True,
+ return_str_on=False,
+ output_type="list",
)
print(
diff --git a/docs/swarms_cloud/swarms_api.md b/docs/swarms_cloud/swarms_api.md
index 3914ca13..57c9bf0b 100644
--- a/docs/swarms_cloud/swarms_api.md
+++ b/docs/swarms_cloud/swarms_api.md
@@ -65,7 +65,7 @@ Run a single swarm with specified agents and tasks.
| agent_name | string | Required | - | Name of the agent (max 100 chars) |
| description | string | Optional | - | Description of the agent (max 500 chars) |
| system_prompt | string | Optional | - | System prompt for the agent (max 500 chars) |
-| model_name | string | Optional | "gpt-4o" | Model to be used by the agent |
+| model_name | string | Optional | "gpt-4o" | Model to be used by the agent (follows litellm conventions) |
| auto_generate_prompt | boolean | Optional | false | Whether to auto-generate prompts |
| max_tokens | integer | Optional | - | Maximum tokens for response |
| temperature | float | Optional | 0.5 | Temperature for response generation |
diff --git a/pyproject.toml b/pyproject.toml
index 9cad3e10..3979d080 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
[tool.poetry]
name = "swarms"
-version = "7.4.4"
+version = "7.4.5"
description = "Swarms - TGSC"
license = "MIT"
authors = ["Kye Gomez <kye@apac.ai>"]
diff --git a/swarms/structs/agent_builder.py b/swarms/structs/agent_builder.py
new file mode 100644
index 00000000..d720611f
--- /dev/null
+++ b/swarms/structs/agent_builder.py
@@ -0,0 +1,208 @@
+import os
+from typing import List
+
+from pydantic import BaseModel, Field
+
+from swarms.structs.agent import Agent
+from swarms.utils.function_caller_model import OpenAIFunctionCaller
+from swarms.utils.loguru_logger import initialize_logger
+from swarms.structs.agents_available import showcase_available_agents
+from swarms.structs.swarms_api import AgentInput as AgentConfig
+
+logger = initialize_logger(log_folder="auto_swarm_builder")
+
+
+class Agents(BaseModel):
+ """Configuration for a list of agents"""
+
+ agents: List[AgentConfig] = Field(
+ description="The list of agents that make up the swarm",
+ )
+
+
+BOSS_SYSTEM_PROMPT = """
+Manage a swarm of worker agents to efficiently serve the user by deciding whether to create new agents or delegate tasks. Ensure operations are efficient and effective.
+
+### Instructions:
+
+1. **Task Assignment**:
+ - Analyze available worker agents when a task is presented.
+ - Delegate tasks to existing agents with clear, direct, and actionable instructions if an appropriate agent is available.
+ - If no suitable agent exists, create a new agent with a fitting system prompt to handle the task.
+
+2. **Agent Creation**:
+ - Name agents according to the task they are intended to perform (e.g., "Twitter Marketing Agent").
+ - Provide each new agent with a concise and clear system prompt that includes its role, objectives, and any tools it can utilize.
+
+3. **Efficiency**:
+ - Minimize redundancy and maximize task completion speed.
+ - Avoid unnecessary agent creation if an existing agent can fulfill the task.
+
+4. **Communication**:
+ - Be explicit in task delegation instructions to avoid ambiguity and ensure effective task execution.
+ - Require agents to report back on task completion or encountered issues.
+
+5. **Reasoning and Decisions**:
+ - Offer brief reasoning when selecting or creating agents to maintain transparency.
+ - Avoid using an agent if unnecessary, with a clear explanation if no agents are suitable for a task.
+
+# Output Format
+
+Present your plan in clear, bullet-point format or short concise paragraphs, outlining task assignment, agent creation, efficiency strategies, and communication protocols.
+
+# Notes
+
+- Preserve transparency by always providing reasoning for task-agent assignments and creation.
+- Ensure instructions to agents are unambiguous to minimize error.
+
+"""
+
+
+class AgentsBuilder:
+ """A class that automatically builds and manages swarms of AI agents.
+
+ This class handles the creation, coordination and execution of multiple AI agents working
+ together as a swarm to accomplish complex tasks. It uses a boss agent to delegate work
+ and create new specialized agents as needed.
+
+ Args:
+ name (str): The name of the swarm
+ description (str): A description of the swarm's purpose
+ verbose (bool, optional): Whether to output detailed logs. Defaults to True.
+ max_loops (int, optional): Maximum number of execution loops. Defaults to 1.
+ """
+
+ def __init__(
+ self,
+ name: str = None,
+ description: str = None,
+ verbose: bool = True,
+ max_loops: int = 1,
+ ):
+ self.name = name
+ self.description = description
+ self.verbose = verbose
+ self.max_loops = max_loops
+ self.agents_pool = []
+
+ logger.info(
+ f"Initialized AutoSwarmBuilder: {name} {description}"
+ )
+
+ def run(self, task: str, image_url: str = None, *args, **kwargs):
+ """Run the swarm on a given task.
+
+ Args:
+ task (str): The task to be accomplished
+ image_url (str, optional): URL of an image input if needed. Defaults to None.
+ *args: Variable length argument list
+ **kwargs: Arbitrary keyword arguments
+
+ Returns:
+ The output from the swarm's execution
+ """
+ logger.info(f"Running swarm on task: {task}")
+ agents = self._create_agents(task, image_url, *args, **kwargs)
+
+ return agents
+
+ def _create_agents(self, task: str, *args, **kwargs):
+ """Create the necessary agents for a task.
+
+ Args:
+ task (str): The task to create agents for
+ *args: Variable length argument list
+ **kwargs: Arbitrary keyword arguments
+
+ Returns:
+ list: List of created agents
+ """
+ logger.info("Creating agents for task")
+ model = OpenAIFunctionCaller(
+ system_prompt=BOSS_SYSTEM_PROMPT,
+ api_key=os.getenv("OPENAI_API_KEY"),
+ temperature=0.1,
+ base_model=Agents,
+ )
+
+ agents_dictionary = model.run(task)
+ logger.info(f"Agents dictionary: {agents_dictionary}")
+
+ # Convert dictionary to SwarmConfig if needed
+ if isinstance(agents_dictionary, dict):
+ agents_dictionary = Agents(**agents_dictionary)
+
+ # Create agents from config
+ agents = []
+ for agent_config in agents_dictionary.agents:
+ # Convert dict to AgentConfig if needed
+ if isinstance(agent_config, dict):
+ agent_config = AgentConfig(**agent_config)
+
+ agent = self.build_agent(
+ agent_name=agent_config.name,
+ agent_description=agent_config.description,
+ agent_system_prompt=agent_config.system_prompt,
+ model_name=agent_config.model_name,
+ max_loops=agent_config.max_loops,
+ dynamic_temperature_enabled=agent_config.dynamic_temperature_enabled,
+ auto_generate_prompt=agent_config.auto_generate_prompt,
+ role=agent_config.role,
+ max_tokens=agent_config.max_tokens,
+ temperature=agent_config.temperature,
+ )
+ agents.append(agent)
+
+ # Showcasing available agents
+ agents_available = showcase_available_agents(
+ name=self.name,
+ description=self.description,
+ agents=agents,
+ )
+
+ for agent in agents:
+ agent.system_prompt += "\n" + agents_available
+
+ return agents
+
+ def build_agent(
+ self,
+ agent_name: str,
+ agent_description: str,
+ agent_system_prompt: str,
+ max_loops: int = 1,
+ model_name: str = "gpt-4o",
+ dynamic_temperature_enabled: bool = True,
+ auto_generate_prompt: bool = False,
+ role: str = "worker",
+ max_tokens: int = 8192,
+ temperature: float = 0.5,
+ ):
+ """Build a single agent with the given specifications.
+
+ Args:
+ agent_name (str): Name of the agent
+ agent_description (str): Description of the agent's purpose
+ agent_system_prompt (str): The system prompt for the agent
+
+ Returns:
+ Agent: The constructed agent instance
+ """
+ logger.info(f"Building agent: {agent_name}")
+ agent = Agent(
+ agent_name=agent_name,
+ description=agent_description,
+ system_prompt=agent_system_prompt,
+ model_name=model_name,
+ max_loops=max_loops,
+ dynamic_temperature_enabled=dynamic_temperature_enabled,
+ context_length=200000,
+ output_type="str", # "json", "dict", "csv" OR "string" soon "yaml" and
+ streaming_on=False,
+ auto_generate_prompt=auto_generate_prompt,
+ role=role,
+ max_tokens=max_tokens,
+ temperature=temperature,
+ )
+
+ return agent
diff --git a/swarms/structs/concurrent_workflow.py b/swarms/structs/concurrent_workflow.py
index cab91b56..774f6e03 100644
--- a/swarms/structs/concurrent_workflow.py
+++ b/swarms/structs/concurrent_workflow.py
@@ -14,6 +14,7 @@ import concurrent.futures
from swarms.utils.loguru_logger import initialize_logger
from swarms.structs.conversation import Conversation
from swarms.structs.swarm_id_generator import generate_swarm_id
+from swarms.structs.output_type import OutputType
logger = initialize_logger(log_folder="concurrent_workflow")
@@ -109,7 +110,8 @@ class ConcurrentWorkflow(BaseSwarm):
return_str_on: bool = False,
agent_responses: list = [],
auto_generate_prompts: bool = False,
- max_workers: int = None,
+ output_type: OutputType = "dict",
+ return_entire_history: bool = False,
*args,
**kwargs,
):
@@ -130,7 +132,9 @@ class ConcurrentWorkflow(BaseSwarm):
self.return_str_on = return_str_on
self.agent_responses = agent_responses
self.auto_generate_prompts = auto_generate_prompts
- self.max_workers = max_workers or os.cpu_count()
+ self.max_workers = os.cpu_count()
+ self.output_type = output_type
+ self.return_entire_history = return_entire_history
self.tasks = [] # Initialize tasks list
self.reliability_check()
@@ -316,6 +320,10 @@ class ConcurrentWorkflow(BaseSwarm):
elif self.return_entire_history:
return self.conversation.return_history_as_string()
+ elif self.output_type == "list":
+ return self.conversation.return_messages_as_list()
+ elif self.output_type == "dict":
+ return self.conversation.return_messages_as_dictionary()
else:
return self.output_schema.model_dump_json(indent=4)
diff --git a/swarms/structs/conversation.py b/swarms/structs/conversation.py
index ec648aed..6880e7d9 100644
--- a/swarms/structs/conversation.py
+++ b/swarms/structs/conversation.py
@@ -416,10 +416,19 @@ class Conversation(BaseStructure):
for message in self.conversation_history
]
+ def return_messages_as_dictionary(self):
+ return [
+ {
+ "role": message["role"],
+ "content": message["content"],
+ }
+ for message in self.conversation_history
+ ]
+
# Example usage
-conversation = Conversation()
-conversation.add("user", "Hello, how are you?")
+# conversation = Conversation()
+# conversation.add("user", "Hello, how are you?")
# print(conversation.get_last_message_as_string())
# print(conversation.return_messages_as_list())
# conversation.add("assistant", "I am doing well, thanks.")
diff --git a/swarms/structs/majority_voting.py b/swarms/structs/majority_voting.py
index 9f19e031..7e358b54 100644
--- a/swarms/structs/majority_voting.py
+++ b/swarms/structs/majority_voting.py
@@ -9,6 +9,7 @@ from typing import Any, Callable, List, Optional
from swarms.structs.agent import Agent
from swarms.structs.conversation import Conversation
from swarms.structs.multi_agent_exec import run_agents_concurrently
+from swarms.structs.output_type import OutputType
from swarms.utils.formatter import formatter
from swarms.utils.loguru_logger import initialize_logger
@@ -147,6 +148,7 @@ class MajorityVoting:
autosave: bool = False,
verbose: bool = False,
max_loops: int = 1,
+ output_type: OutputType = "dict",
*args,
**kwargs,
):
@@ -158,6 +160,7 @@ class MajorityVoting:
self.autosave = autosave
self.verbose = verbose
self.max_loops = max_loops
+ self.output_type = output_type
self.conversation = Conversation(
time_enabled=True, *args, **kwargs
@@ -202,7 +205,7 @@ class MajorityVoting:
self.conversation.add(agent.agent_name, response)
responses = self.conversation.return_history_as_string()
- print(responses)
+ # print(responses)
prompt = f"""Conduct a detailed majority voting analysis on the following conversation:
{responses}
@@ -236,8 +239,17 @@ class MajorityVoting:
)
# Return the majority vote
- return self.conversation.return_history_as_string()
-
+ # return self.conversation.return_history_as_string()
+ if self.output_type == "str":
+ return self.conversation.get_str()
+ elif self.output_type == "dict":
+ return self.conversation.return_messages_as_dictionary()
+ elif self.output_type == "list":
+ return self.conversation.return_messages_as_list()
+ else:
+ return self.conversation.return_history_as_string()
+
+
def batch_run(
self, tasks: List[str], *args, **kwargs
) -> List[Any]:
diff --git a/swarms/structs/mixture_of_agents.py b/swarms/structs/mixture_of_agents.py
index f5019c04..2f6a37d1 100644
--- a/swarms/structs/mixture_of_agents.py
+++ b/swarms/structs/mixture_of_agents.py
@@ -12,6 +12,8 @@ from swarms.prompts.ag_prompt import aggregator_system_prompt
from swarms.utils.loguru_logger import initialize_logger
from swarms.utils.any_to_str import any_to_str
import concurrent.futures
+from swarms.structs.output_type import OutputType
+from swarms.structs.conversation import Conversation
logger = initialize_logger(log_folder="mixture_of_agents")
@@ -69,6 +71,7 @@ class MixtureOfAgents:
layers: int = 3,
max_loops: int = 1,
return_str_on: bool = False,
+ output_type: OutputType = "dict",
) -> None:
"""
Initialize the Mixture of Agents class with agents and configuration.
@@ -89,6 +92,7 @@ class MixtureOfAgents:
self.layers: int = layers
self.max_loops: int = max_loops
self.return_str_on: bool = return_str_on
+ self.output_type: OutputType = output_type
self.input_schema = MixtureOfAgentsInput(
name=name,
@@ -109,6 +113,8 @@ class MixtureOfAgents:
)
self.reliability_check()
+
+ self.conversation = Conversation()
def reliability_check(self) -> None:
"""
@@ -191,6 +197,7 @@ class MixtureOfAgents:
# Run the agent asynchronously
response = await asyncio.to_thread(agent.run, task)
+
self.output_schema.normal_agent_outputs.append(
agent.agent_output
)
@@ -241,6 +248,7 @@ class MixtureOfAgents:
task (str): The task for the mixture of agents.
"""
try:
+ self.conversation.add("user", task)
prev_context = None
for _ in range(self.max_loops):
@@ -263,8 +271,12 @@ class MixtureOfAgents:
log_agent_data(self.output_schema.model_dump())
- if self.return_str_on:
- return any_to_str(self.output_schema.model_dump())
+ if self.return_str_on or self.output_type == "str":
+ return self.conversation.get_str()
+ elif self.output_type == "dict":
+ return self.conversation.return_messages_as_dictionary()
+ elif self.output_type == "list":
+ return self.conversation.return_messages_as_list()
else:
return self.output_schema.model_dump_json(indent=4)
diff --git a/swarms/structs/output_type.py b/swarms/structs/output_type.py
new file mode 100644
index 00000000..5dcc7f29
--- /dev/null
+++ b/swarms/structs/output_type.py
@@ -0,0 +1,18 @@
+from typing import Literal
+
+# Define the output_type using Literal
+OutputType = Literal[
+ "all",
+ "final",
+ "list",
+ "dict",
+ ".json",
+ ".md",
+ ".txt",
+ ".yaml",
+ ".toml",
+ "str",
+]
+
+# Use the OutputType for type annotations
+output_type: OutputType
diff --git a/swarms/structs/rearrange.py b/swarms/structs/rearrange.py
index 3e89e58e..e215fe65 100644
--- a/swarms/structs/rearrange.py
+++ b/swarms/structs/rearrange.py
@@ -11,9 +11,11 @@ from swarms.schemas.agent_step_schemas import ManySteps
from swarms.structs.agent import Agent
from swarms.structs.agents_available import showcase_available_agents
from swarms.structs.base_swarm import BaseSwarm
-from swarms.structs.output_types import OutputType
+
from swarms.utils.loguru_logger import initialize_logger
from swarms.telemetry.main import log_agent_data
+from swarms.structs.conversation import Conversation
+from swarms.structs.output_type import OutputType
logger = initialize_logger(log_folder="rearrange")
@@ -114,6 +116,7 @@ class AgentRearrange(BaseSwarm):
no_use_clusterops: bool = True,
autosave: bool = True,
return_entire_history: bool = False,
+ rules: str = None,
*args,
**kwargs,
):
@@ -154,6 +157,11 @@ class AgentRearrange(BaseSwarm):
outputs=[],
)
+ self.conversation = Conversation()
+
+ if rules:
+ self.conversation.add("user", rules)
+
def showcase_agents(self):
# Get formatted agent info once
agents_available = showcase_available_agents(
@@ -305,6 +313,8 @@ class AgentRearrange(BaseSwarm):
Exception: For any other errors during execution
"""
try:
+ self.conversation.add("user", task)
+
if not self.validate_flow():
logger.error("Flow validation failed")
return "Invalid flow configuration."
@@ -394,6 +404,9 @@ class AgentRearrange(BaseSwarm):
**kwargs,
)
result = str(result)
+ self.conversation.add(
+ agent.agent_name, result
+ )
results.append(result)
response_dict[agent_name] = result
self.output_schema.outputs.append(
@@ -446,6 +459,9 @@ class AgentRearrange(BaseSwarm):
**kwargs,
)
current_task = str(current_task)
+ self.conversation.add(
+ agent.agent_name, current_task
+ )
response_dict[agent_name] = current_task
self.output_schema.outputs.append(
agent.agent_output
@@ -475,7 +491,7 @@ class AgentRearrange(BaseSwarm):
elif self.output_type == "list":
output = all_responses
elif self.output_type == "dict":
- output = response_dict
+ output = self.conversation.return_messages_as_dictionary()
else: # "final"
output = current_task
diff --git a/swarms/structs/sequential_workflow.py b/swarms/structs/sequential_workflow.py
index d10f178a..8d3d9cb4 100644
--- a/swarms/structs/sequential_workflow.py
+++ b/swarms/structs/sequential_workflow.py
@@ -1,7 +1,7 @@
from typing import List, Optional
from swarms.structs.agent import Agent
from swarms.structs.rearrange import AgentRearrange
-from swarms.structs.output_types import OutputType
+from swarms.structs.output_type import OutputType
from concurrent.futures import ThreadPoolExecutor, as_completed
from swarms.utils.loguru_logger import initialize_logger
@@ -30,7 +30,7 @@ class SequentialWorkflow:
description: str = "Sequential Workflow, where agents are executed in a sequence.",
agents: List[Agent] = [],
max_loops: int = 1,
- output_type: OutputType = "all",
+ output_type: OutputType = "dict",
return_json: bool = False,
shared_memory_system: callable = None,
return_entire_history: bool = False,
@@ -136,7 +136,7 @@ class SequentialWorkflow:
"""
try:
- return self.agent_rearrange.run(
+ result = self.agent_rearrange.run(
task=task,
img=img,
device=device,
@@ -144,9 +144,20 @@ class SequentialWorkflow:
device_id=device_id,
all_gpus=all_gpus,
no_use_clusterops=no_use_clusterops,
+ output_type=self.output_type,
*args,
**kwargs,
)
+
+
+ if self.output_type == "dict":
+ result = self.agent_rearrange.conversation.return_messages_as_dictionary()
+ elif self.output_type == "list":
+ result = self.agent_rearrange.conversation.return_messages_as_list()
+ elif self.output_type == "str" or self.return_json:
+ result = self.agent_rearrange.conversation.get_str()
+ else:
+ return result
except Exception as e:
logger.error(
f"An error occurred while executing the task: {e}"
diff --git a/swarms/structs/swarm_router.py b/swarms/structs/swarm_router.py
index d760f9c8..7320efb8 100644
--- a/swarms/structs/swarm_router.py
+++ b/swarms/structs/swarm_router.py
@@ -18,6 +18,7 @@ from swarms.structs.rearrange import AgentRearrange
from swarms.structs.sequential_workflow import SequentialWorkflow
from swarms.structs.spreadsheet_swarm import SpreadSheetSwarm
from swarms.structs.swarm_matcher import swarm_matcher
+from swarms.structs.output_type import OutputType
from swarms.utils.loguru_logger import initialize_logger
logger = initialize_logger(log_folder="swarm_router")
@@ -146,7 +147,7 @@ class SwarmRouter:
shared_memory_system: Any = None,
rules: str = None,
documents: List[str] = [], # A list of docs file paths
- output_type: str = "all",
+ output_type: OutputType = "dict",
no_cluster_ops: bool = False,
speaker_fn: callable = None,
load_agents_from_csv: bool = False,
@@ -323,6 +324,7 @@ class SwarmRouter:
aggregator_system_prompt=aggregator_system_prompt.get_prompt(),
aggregator_agent=self.agents[-1],
layers=self.max_loops,
+ output_type=self.output_type,
*args,
**kwargs,
)
@@ -386,6 +388,7 @@ class SwarmRouter:
max_loops=self.max_loops,
auto_save=self.autosave,
return_str_on=self.return_entire_history,
+ output_type=self.output_type,
*args,
**kwargs,
)
diff --git a/swarms/structs/swarms_api.py b/swarms/structs/swarms_api.py
index 3353b119..2024c9ae 100644
--- a/swarms/structs/swarms_api.py
+++ b/swarms/structs/swarms_api.py
@@ -53,6 +53,10 @@ class AgentInput(BaseModel):
1,
description="The maximum number of iterations the agent is allowed to perform.",
)
+ dynamic_temperature_enabled: Optional[bool] = Field(
+ True,
+ description="Indicates whether the agent should use dynamic temperature.",
+ )
class SwarmRequest(BaseModel):
diff --git a/swarms_api_example.py b/swarms_api_example.py
index ce9cab29..19735e1a 100644
--- a/swarms_api_example.py
+++ b/swarms_api_example.py
@@ -1,3 +1,5 @@
+# tools - search, code executor, create api
+
import os
import requests
from dotenv import load_dotenv
@@ -25,30 +27,33 @@ def run_single_swarm():
"agent_name": "Market Analyst",
"description": "Analyzes market trends",
"system_prompt": "You are a financial analyst expert.",
- "model_name": "gpt-4o",
+ "model_name": "groq/deepseek-r1-distill-qwen-32b",
"role": "worker",
"max_loops": 1,
+ "max_tokens": 8192,
},
{
"agent_name": "Economic Forecaster",
"description": "Predicts economic trends",
"system_prompt": "You are an expert in economic forecasting.",
- "model_name": "gpt-4o",
+ "model_name": "groq/deepseek-r1-distill-qwen-32b",
"role": "worker",
"max_loops": 1,
+ "max_tokens": 8192,
},
{
"agent_name": "Data Scientist",
"description": "Performs data analysis",
"system_prompt": "You are a data science expert.",
- "model_name": "gpt-4o",
+ "model_name": "groq/deepseek-r1-distill-qwen-32b",
"role": "worker",
"max_loops": 1,
+ "max_tokens": 8192,
},
],
"max_loops": 1,
"swarm_type": "ConcurrentWorkflow",
- "task": "Analyze current market trends in tech sector",
+ "task": "What are the best etfs and index funds for ai and tech?",
"output_type": "str",
"return_history": True,
}
@@ -77,7 +82,3 @@ if __name__ == "__main__":
result = run_single_swarm()
print("Swarm Result:")
print(result)
-
- # print("Swarm Logs:")
- # logs = get_logs()
- # print(logs)