[FEAT][Readme]

pull/243/head
Kye 1 year ago
parent 3ae305ee09
commit a7a6d54511

@ -55,10 +55,10 @@ llm = OpenAIChat(
) )
## Initialize the workflow ## Initialize the Agent
agent = Agent(llm=llm, max_loops=1, dashboard=True) agent = Agent(llm=llm, max_loops=1, dashboard=True)
# Run the workflow on a task # Run the Agent on a task
out = agent.run("Generate a 10,000 word blog on health and wellness.") out = agent.run("Generate a 10,000 word blog on health and wellness.")
@ -129,14 +129,25 @@ for task in workflow.tasks:
- Run the agent with multiple modalities useful for various real-world tasks in manufacturing, logistics, and health. - Run the agent with multiple modalities useful for various real-world tasks in manufacturing, logistics, and health.
```python ```python
from swarms.structs import Agent # Description: This is an example of how to use the Agent class to run a multi-modal workflow
import os
from dotenv import load_dotenv
from swarms.models.gpt4_vision_api import GPT4VisionAPI from swarms.models.gpt4_vision_api import GPT4VisionAPI
from swarms.prompts.multi_modal_autonomous_instruction_prompt import ( from swarms.structs import Agent
MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
) # Load the environment variables
load_dotenv()
llm = GPT4VisionAPI() # Get the API key from the environment
api_key = os.environ.get("OPENAI_API_KEY")
# Initialize the language model
llm = GPT4VisionAPI(
openai_api_key=api_key,
max_tokens=500,
)
# Initialize the task
task = ( task = (
"Analyze this image of an assembly line and identify any issues such as" "Analyze this image of an assembly line and identify any issues such as"
" misaligned parts, defects, or deviations from the standard assembly" " misaligned parts, defects, or deviations from the standard assembly"
@ -148,13 +159,15 @@ img = "assembly_line.jpg"
## Initialize the workflow ## Initialize the workflow
agent = Agent( agent = Agent(
llm=llm, llm=llm,
max_loops='auto' max_loops="auto",
sop=MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1, autosave=True,
dashboard=True, dashboard=True,
multi_modal=True
) )
agent.run(task=task, img=img) # Run the workflow on a task
out = agent.run(task=task, img=img)
print(out)
``` ```

@ -1,21 +1,22 @@
# Description: This is an example of how to use the Agent class to run a multi-modal workflow
import os import os
from dotenv import load_dotenv from dotenv import load_dotenv
from swarms.models.gpt4_vision_api import GPT4VisionAPI from swarms.models.gpt4_vision_api import GPT4VisionAPI
from swarms.prompts.multi_modal_autonomous_instruction_prompt import (
MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
)
from swarms.structs import Agent from swarms.structs import Agent
# Load the environment variables
load_dotenv() load_dotenv()
# Get the API key from the environment
api_key = os.environ.get("OPENAI_API_KEY") api_key = os.environ.get("OPENAI_API_KEY")
# Initialize the language model
llm = GPT4VisionAPI( llm = GPT4VisionAPI(
openai_api_key=api_key, openai_api_key=api_key,
max_tokens=500,
) )
# Initialize the language model
task = "What is the color of the object?" task = "What is the color of the object?"
img = "images/swarms.jpeg" img = "images/swarms.jpeg"
@ -23,10 +24,11 @@ img = "images/swarms.jpeg"
agent = Agent( agent = Agent(
llm=llm, llm=llm,
max_loops="auto", max_loops="auto",
sop=MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
autosave=True, autosave=True,
dashboard=True, dashboard=True,
multi_modal=True
) )
# Run the workflow on a task
out = agent.run(task=task, img=img) out = agent.run(task=task, img=img)
print(out) print(out)

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