Assistants add memory, knowledge and tools to LLMs.

We “prompt” them using description and instructions, for example:
from phi.assistant import Assistant
from phi.llm.openai import OpenAIChat

assistant = Assistant(
    description="You help people with their health and fitness goals.",
    instructions=["Recipes should be under 5 ingredients"],

# -*- Print the response in markdown format
assistant.print_response("Share a breakfast recipe.", markdown=True)

Under the hood, the description and instructions are converted into the system prompt and the input is passed as the user prompt. Use debug_mode=True to print the underlying prompts sent to the LLM, here’s how they look like:

DEBUG    ============== system ==============
DEBUG    You help people with their health and fitness goals.
         1. Recipes should be under 5 ingredients.
         2. Use markdown to format your answers.
DEBUG    ============== user ==============
DEBUG    Share a breakfast recipe.
DEBUG    Time to generate response: 1.8701s
DEBUG    Estimated completion tokens: 113

Return response as a variable

Use the function to return the LLM response as a variable.

# -*- Get the response as a stream
response = ""
for delta in'Share a breakfast recipe.'):
    response += delta

By default stream=True, set stream=False to return as a string.

# -*- Get the response as a string
response ='Share a breakfast recipe.', stream=False)

Run the Assistant as a CLI app

Run the Assistant as a command line application using assistant.cli_app()

from phi.assistant import Assistant
from import DuckDuckGo

assistant = Assistant(tools=[DuckDuckGo()], show_tool_calls=True, read_chat_history=True)


Whats happening in france?

Then ask:

Summarize the last response

Manually set the system prompt

You can manually set the system prompt using the system_prompt variable. The description and instructions only provide a formatting benefit. Learn more in the instructions guide.

from phi.assistant import Assistant

assistant = Assistant(system_prompt="Share a 2 sentence story about")
assistant.print_response("Love in the year 12000.")