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swarms
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revert-563-dependabot/pip/pymdown-extensions-approx-eq-10.9
Kye Gomez 5 months ago
parent 07f8e371de
commit f6acc4adfd
6 changed files with 62 additions and 40 deletions
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1
docs/mkdocs.yml
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@ -152,6 +152,7 @@ nav:
- HuggingFaceLLM: "swarms/models/huggingface.md" - HuggingFaceLLM: "swarms/models/huggingface.md"
- Anthropic: "swarms/models/anthropic.md" - Anthropic: "swarms/models/anthropic.md"
- OpenAIChat: "swarms/models/openai.md" - OpenAIChat: "swarms/models/openai.md"
- OpenAIFunctionCaller: "swarms/models/openai_function_caller.md"
# - TogetherAI: "swarms/models/togetherai.md" # - TogetherAI: "swarms/models/togetherai.md"
- MultiModal Models: - MultiModal Models:
- BaseMultiModalModel: "swarms/models/base_multimodal_model.md" - BaseMultiModalModel: "swarms/models/base_multimodal_model.md"

65
playground/agents/monitoring/agent_ops.py
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@ -14,7 +14,7 @@ Requirements:
""" """
################ Adding project root to PYTHONPATH ################################ ################ Adding project root to PYTHONPATH ################################
# If you are running playground examples in the project files directly, use this: # If you are running playground examples in the project files directly, use this:
import sys import sys
import os import os
@ -29,9 +29,9 @@ Treasurer = Agent(
agent_name="Treasurer", agent_name="Treasurer",
system_prompt="Give your opinion on the cash management.", system_prompt="Give your opinion on the cash management.",
agent_description=( agent_description=(
"responsible for managing an organization's financial assets and liquidity. They oversee cash management, " "responsible for managing an organization's financial assets and liquidity. They oversee cash management, "
"investment strategies, and financial risk. Key duties include monitoring cash flow, managing bank relationships, " "investment strategies, and financial risk. Key duties include monitoring cash flow, managing bank relationships, "
"ensuring sufficient funds for operations, and optimizing returns on short-term investments. Treasurers also often " "ensuring sufficient funds for operations, and optimizing returns on short-term investments. Treasurers also often "
"handle debt management and may be involved in capital raising activities." "handle debt management and may be involved in capital raising activities."
), ),
llm=OpenAIChat(), llm=OpenAIChat(),
@ -44,14 +44,14 @@ CFO = Agent(
agent_name="CFO", agent_name="CFO",
system_prompt="Give your opinion on the financial performance of the company.", system_prompt="Give your opinion on the financial performance of the company.",
agent_description=( agent_description=(
"the top financial executive in an organization, overseeing all financial operations and strategy. Their role is broader than a treasurer's and includes:\n" "the top financial executive in an organization, overseeing all financial operations and strategy. Their role is broader than a treasurer's and includes:\n"
"Financial planning and analysis\n" "Financial planning and analysis\n"
"Accounting and financial reporting\n" "Accounting and financial reporting\n"
"Budgeting and forecasting\n" "Budgeting and forecasting\n"
"Strategic financial decision-making\n" "Strategic financial decision-making\n"
"Compliance and risk management\n" "Compliance and risk management\n"
"Investor relations (in public companies)\n" "Investor relations (in public companies)\n"
"Overseeing the finance and accounting departments" "Overseeing the finance and accounting departments"
), ),
llm=OpenAIChat(), llm=OpenAIChat(),
max_loops=1, max_loops=1,
@ -63,23 +63,24 @@ swarm = AgentRearrange(
flow="Treasurer -> CFO", flow="Treasurer -> CFO",
) )
results = swarm.run("Date,Revenue,Expenses,Profit,Cash_Flow,Inventory,Customer_Acquisition_Cost,Customer_Retention_Rate,Marketing_Spend,R&D_Spend,Debt,Assets\n" results = swarm.run(
"2023-01-01,1000000,800000,200000,150000,500000,100,0.85,50000,100000,2000000,5000000\n" "Date,Revenue,Expenses,Profit,Cash_Flow,Inventory,Customer_Acquisition_Cost,Customer_Retention_Rate,Marketing_Spend,R&D_Spend,Debt,Assets\n"
"2023-02-01,1050000,820000,230000,180000,520000,95,0.87,55000,110000,1950000,5100000\n" "2023-01-01,1000000,800000,200000,150000,500000,100,0.85,50000,100000,2000000,5000000\n"
"2023-03-01,1100000,850000,250000,200000,530000,90,0.88,60000,120000,1900000,5200000\n" "2023-02-01,1050000,820000,230000,180000,520000,95,0.87,55000,110000,1950000,5100000\n"
"2023-04-01,1200000,900000,300000,250000,550000,85,0.90,70000,130000,1850000,5400000\n" "2023-03-01,1100000,850000,250000,200000,530000,90,0.88,60000,120000,1900000,5200000\n"
"2023-05-01,1300000,950000,350000,300000,580000,80,0.92,80000,140000,1800000,5600000\n" "2023-04-01,1200000,900000,300000,250000,550000,85,0.90,70000,130000,1850000,5400000\n"
"2023-06-01,1400000,1000000,400000,350000,600000,75,0.93,90000,150000,1750000,5800000\n" "2023-05-01,1300000,950000,350000,300000,580000,80,0.92,80000,140000,1800000,5600000\n"
"2023-07-01,1450000,1050000,400000,320000,620000,78,0.91,95000,160000,1700000,5900000\n" "2023-06-01,1400000,1000000,400000,350000,600000,75,0.93,90000,150000,1750000,5800000\n"
"2023-08-01,1500000,1100000,400000,300000,650000,80,0.90,100000,170000,1650000,6000000\n" "2023-07-01,1450000,1050000,400000,320000,620000,78,0.91,95000,160000,1700000,5900000\n"
"2023-09-01,1550000,1150000,400000,280000,680000,82,0.89,105000,180000,1600000,6100000\n" "2023-08-01,1500000,1100000,400000,300000,650000,80,0.90,100000,170000,1650000,6000000\n"
"2023-10-01,1600000,1200000,400000,260000,700000,85,0.88,110000,190000,1550000,6200000\n" "2023-09-01,1550000,1150000,400000,280000,680000,82,0.89,105000,180000,1600000,6100000\n"
"2023-11-01,1650000,1250000,400000,240000,720000,88,0.87,115000,200000,1500000,6300000\n" "2023-10-01,1600000,1200000,400000,260000,700000,85,0.88,110000,190000,1550000,6200000\n"
"2023-12-01,1700000,1300000,400000,220000,750000,90,0.86,120000,210000,1450000,6400000\n" "2023-11-01,1650000,1250000,400000,240000,720000,88,0.87,115000,200000,1500000,6300000\n"
"2024-01-01,1500000,1200000,300000,180000,780000,95,0.84,100000,180000,1500000,6300000\n" "2023-12-01,1700000,1300000,400000,220000,750000,90,0.86,120000,210000,1450000,6400000\n"
"2024-02-01,1550000,1220000,330000,200000,760000,92,0.85,105000,185000,1480000,6350000\n" "2024-01-01,1500000,1200000,300000,180000,780000,95,0.84,100000,180000,1500000,6300000\n"
"2024-03-01,1600000,1240000,360000,220000,740000,89,0.86,110000,190000,1460000,6400000\n" "2024-02-01,1550000,1220000,330000,200000,760000,92,0.85,105000,185000,1480000,6350000\n"
"2024-04-01,1650000,1260000,390000,240000,720000,86,0.87,115000,195000,1440000,6450000\n" "2024-03-01,1600000,1240000,360000,220000,740000,89,0.86,110000,190000,1460000,6400000\n"
"2024-05-01,1700000,1280000,420000,260000,700000,83,0.88,120000,200000,1420000,6500000\n" "2024-04-01,1650000,1260000,390000,240000,720000,86,0.87,115000,195000,1440000,6450000\n"
"2024-06-01,1750000,1300000,450000,280000,680000,80,0.89,125000,205000,1400000,6550000" "2024-05-01,1700000,1280000,420000,260000,700000,83,0.88,120000,200000,1420000,6500000\n"
) "2024-06-01,1750000,1300000,450000,280000,680000,80,0.89,125000,205000,1400000,6550000"
)

8
playground/agents/monitoring/agent_ops_tools.py
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@ -14,7 +14,7 @@ Requirements:
""" """
################ Adding project root to PYTHONPATH ################################ ################ Adding project root to PYTHONPATH ################################
# If you are running playground examples in the project files directly, use this: # If you are running playground examples in the project files directly, use this:
import sys import sys
import os import os
@ -25,7 +25,8 @@ sys.path.insert(0, os.getcwd())
from swarms import Agent, OpenAIChat from swarms import Agent, OpenAIChat
from agentops import record_function from agentops import record_function
# Add agentops decorator on your tools # Add agentops decorator on your tools
@record_function("length_checker") @record_function("length_checker")
@ -41,6 +42,7 @@ def length_checker(string: str) -> int:
""" """
return len(string) return len(string)
agent1 = Agent( agent1 = Agent(
agent_name="lengther", agent_name="lengther",
system_prompt="return the length of the string", system_prompt="return the length of the string",
@ -55,4 +57,4 @@ agent1 = Agent(
) )
agent1.run("hello") agent1.run("hello")

1
swarms/structs/agent.py
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@ -91,6 +91,7 @@ def step_id():
agent_output_type = Union[BaseModel, dict, str] agent_output_type = Union[BaseModel, dict, str]
ToolUsageType = Union[BaseModel, Dict[str, Any]] ToolUsageType = Union[BaseModel, Dict[str, Any]]
# [FEAT][AGENT] # [FEAT][AGENT]
@agentops.track_agent() @agentops.track_agent()
class Agent(BaseStructure): class Agent(BaseStructure):

19
swarms/structs/rearrange.py
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@ -224,7 +224,11 @@ class AgentRearrange(BaseSwarm):
else: else:
agent = self.agents[agent_name] agent = self.agents[agent_name]
result = agent.run( result = agent.run(
current_task, img, is_last, *args, **kwargs current_task,
img,
is_last,
*args,
**kwargs,
) )
results.append(result) results.append(result)
@ -324,13 +328,22 @@ class AgentRearrange(BaseSwarm):
results = [] results = []
for agent_name in agent_names: for agent_name in agent_names:
result = self.process_agent_or_swarm( result = self.process_agent_or_swarm(
agent_name, current_task, img, is_last*args, **kwargs agent_name,
current_task,
img,
is_last * args,
**kwargs,
) )
results.append(result) results.append(result)
current_task = "; ".join(results) current_task = "; ".join(results)
else: else:
current_task = self.process_agent_or_swarm( current_task = self.process_agent_or_swarm(
agent_names[0], current_task, is_last, img, *args, **kwargs agent_names[0],
current_task,
is_last,
img,
*args,
**kwargs,
) )
return current_task return current_task

8
swarms/tools/tool_parse_exec.py
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@ -30,8 +30,12 @@ def parse_and_execute_json(
function_dict = {func.__name__: func for func in functions} function_dict = {func.__name__: func for func in functions}
data = json.loads(json_string) data = json.loads(json_string)
function_list = data.get("functions", []) if data.get("functions") else [data.get("function", [])] function_list = (
data.get("functions", [])
if data.get("functions")
else [data.get("function", [])]
)
results = {} results = {}
for function_data in function_list: for function_data in function_list:
function_name = function_data.get("name") function_name = function_data.get("name")

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