Install libraries
pip install autogen
export TOGETHER_API_KEY=***
Example
Setup and configure AutoGen to use LLMs from Together AIimport os
config_list = [
{
# Let's choose the Llama 3.3 70B model
"model": "meta-llama/Llama-3.3-70B-Instruct-Turbo",
# Provide your Together.AI API key here or put it into the TOGETHER_API_KEY environment variable.
"api_key": os.environ.get("TOGETHER_API_KEY"),
# We specify the API Type as 'together' so it uses the Together.AI client class
"api_type": "together",
"stream": False,
}
]
from pathlib import Path
from autogen import AssistantAgent, UserProxyAgent
from autogen.coding import LocalCommandLineCodeExecutor
# Setting up the code executor
workdir = Path("coding")
workdir.mkdir(exist_ok=True)
code_executor = LocalCommandLineCodeExecutor(work_dir=workdir)
# Setting up the agents
# The UserProxyAgent will execute the code that the AssistantAgent provides
user_proxy_agent = UserProxyAgent(
name="User",
code_execution_config={"executor": code_executor},
is_termination_msg=lambda msg: "FINISH" in msg.get("content"),
)
system_message = """You are a helpful AI assistant who writes code and the user executes it.
Solve tasks using your coding and language skills.
In the following cases, suggest python code (in a python coding block) for the user to execute.
Solve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.
When using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.
Don't include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use 'print' function for the output when relevant. Check the execution result returned by the user.
If the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can't be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.
When you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.
IMPORTANT: Wait for the user to execute your code and then you can reply with the word "FINISH". DO NOT OUTPUT "FINISH" after your code block."""
# The AssistantAgent, using Together.AI's Code Llama model, will take the coding request and return code
assistant_agent = AssistantAgent(
name="Together Assistant",
system_message=system_message,
llm_config={"config_list": config_list},
)
# Start the chat, with the UserProxyAgent asking the AssistantAgent the message
chat_result = user_proxy_agent.initiate_chat(
assistant_agent,
message="Provide code to count the number of prime numbers from 1 to 10000.",
)
Output
User (to Together Assistant):
Provide code to count the number of prime numbers from 1 to 10000.
--------------------------------------------------------------------------------
Together Assistant (to User):
```python
def is_prime(n):
if n <= 1:
return False
for i in range(2, int(n**0.5) + 1):
if n % i == 0:
return False
return True
count = 0
for num in range(1, 10001):
if is_prime(num):
count += 1
print(count)
```
This code defines a helper function `is_prime(n)` to check if a number `n` is prime. It then iterates through numbers from 1 to 10000, checks if each number is prime using the helper function, and increments a counter if it is. Finally, it prints the total count of prime numbers found.
--------------------------------------------------------------------------------