[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)
# 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.")
@ -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.
```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.prompts.multi_modal_autonomous_instruction_prompt import (
MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
)
from swarms.structs import Agent
# 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 = (
"Analyze this image of an assembly line and identify any issues such as"
" misaligned parts, defects, or deviations from the standard assembly"
@ -148,13 +159,15 @@ img = "assembly_line.jpg"
## Initialize the workflow
agent = Agent(
llm=llm,
max_loops='auto'
sop=MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
max_loops="auto",
autosave=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
from dotenv import load_dotenv
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
# Load the environment variables
load_dotenv()
# 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 language model
task = "What is the color of the object?"
img = "images/swarms.jpeg"
@ -23,10 +24,11 @@ img = "images/swarms.jpeg"
agent = Agent(
llm=llm,
max_loops="auto",
sop=MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
autosave=True,
dashboard=True,
multi_modal=True
)
# Run the workflow on a task
out = agent.run(task=task, img=img)
print(out)

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