My question is pretty straight forward, can someone please explain the differences between, the System, User, and Assisstant roles for the Open AI integration, also when is it better to use one or the other? Am I training the model? Am I writing the responses? Why wouldn’t I just type everything in one big prompt?
I’m pretty familiar with using chatgpt on its own so explaining it as how I would typically use the app would be great just so I have a good understanding. Thank you so much!
Not sure if I’m just stupid or if its not as intuitive as I thought lol .
Thank You!
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According to Mastering the OpenAI API: Tips and Tricks - Arize AI :
Commonly used roles include “system,” “user,” and “assistant.” The “system” provides high-level instructions, the “user” presents queries or prompts, and the “assistant” is the model’s response. By differentiating these roles, we can set the context and direct the conversation efficiently.
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Here’s a breakdown of the System, User, and Assistant roles in the context of integrating with OpenAI:
- System Role:
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What it does: The System role is used to provide setup information or context that informs the behavior of the model. This can include instructions or guidelines on how the conversation should proceed.
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When to use it: You use this role to set the stage for the interaction. For example, if you want the model to maintain a formal tone throughout the conversation or if you need to specify rules like avoiding certain topics.
Example:
System: The assistant should always maintain a professional tone and avoid discussing personal opinions on politics.
- User Role:
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What it does: This role represents the human user in the conversation. Inputs from the user guide the conversation and prompt responses from the assistant.
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When to use it: Whenever the human user is making a statement or asking a question. This is the most frequent role used in a standard interaction.
Example:
User: Can you explain how to integrate OpenAI’s API with my existing Python application?
- Assistant Role:
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What it does: This is the role of the model itself, responding to user inputs based on the context set by the system.
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When to use it: This role is automatically assumed by the model when it replies to the user’s queries or follows the system’s instructions.
Example:
Assistant: Sure, to integrate OpenAI’s API with your Python application, you’ll start by installing the OpenAI Python package using pip...
Why not just type everything in one big prompt?
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Clarity and Structure: Using roles helps keep the conversation clear and structured. It delineates who is saying what, which is crucial when designing complex interactions.
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Context Management: It allows the model to maintain and separate different types of context (instructions vs. queries).
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Control and Flexibility: You have better control over how the conversation evolves.
You’re not training the model directly through these interactions; rather, you’re guiding it to respond appropriately within the context you set.
Hope that clears things up!
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Thank you SOOO MUCH
very helpful. the examples especially!
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It’s easier to use custom assistants nowadays, as they can remember the conversation history in the same thread, so you don’t have to resend the entire conversation (as user/assistant roles) for each new user prompt.
If you don’t need history, then you also don’t need to use the assistant role. The assistant role is to help it identify what the assistant sent previously.
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If im creating a report based on a transcript and the report has 5 sections:
is it better to use my current process:
- 5 separate agents (one per section with a select amount of questions)
or to use a custom agent and ask the agent 5 separate questions, which would essentially give the agent context and maybe not have to upload the transcript multiple times
@samliew
That looks like a new question, could you please create a separate topic for this?
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beautiful response @bighadj22, thank you very much!
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