help
#give me custom code for creating threads and context window for openai chat completion
visual elbow
snow sigilBOT
Hi @visual elbow. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
Sure, I can provide you with some code snippets based on the information available in the knowledge sources.
First, to create a thread using the OpenAI Assistant API, you can use the following code:
thread = client.beta.threads.create()
(Source: OpenAI API - Assistants > Methods > createThreadAndRun (https://platform.openai.com/docs/api-reference))
For creating a chat completion with OpenAI, you can use the following code:
from openai import OpenAI
import os
client = OpenAI(
api_key=os.environ.get("OPENAI_API_KEY"),
)
chat_completion = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": "Your message here"}
]
)
(Source: OpenAI Docs - Libraries > Python library (https://platform.openai.com/docs/libraries))
Please replace "Your message here" with the actual content you want to send.
Remember to install the OpenAI Python library if you haven't done so:
pip install openai
(Source: OpenAI Docs - Libraries > Python library (https://platform.openai.com/docs/libraries))
Please note that you need to replace "OPENAI_API_KEY" with your actual OpenAI API key.
As for the context window, the OpenAI API automatically manages the context window for you. If a conversation has too many tokens to fit within a model's maximum limit, the API will automatically truncate the conversation to fit. However, the specifics of how this is done (e.g., whether it keeps the most recent messages, or some other strategy) are not detailed in the provided knowledge sources.
If you want to provide a large amount of loosely structured context, you can use a system message at the start of your conversation:
client.chat.completions.create(
model="gpt-4-turbo-preview",
messages=[
{
"role": "system",
"content": "You are a virtual knowledge-base assistant, you answer questions and give instructions based on this given content:\n" + context,
},
{
"role": "user",
"content": prompt,
},
],
)
(Source: Forum Post: Feed GPT more unstructured data (https://community.openai.com/t/692943))
In this code, replace context with your context string and prompt with the user's message.
Please note that the model "gpt-4-turbo-preview" used in the example might not be available. You should replace it with a model that you have access to, such as "gpt-3.5-turbo".
Remember, you need to manage your tokens carefully because both input and output tokens count towards the total tokens of a model. If a message is too long, you might need to truncate or otherwise manage it to ensure it fits within the model's maximum limit.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
visual elbow
I am not using assistants api but chat completion endpoint. I want custom code for thread creation. @snow sigil
give me the code
am not using assistants api but chat completion endpoint. I want custom code for thread creation. @snow sigil
snow sigilBOT
Let me check the knowledge base for you. One moment! :books:
I'm sorry for the confusion, but in the context of the OpenAI API, threads are specific to the Assistant API and are not used with the Chat Completions API.
In the Chat Completions API, you manage the conversation history yourself. Each call to the API includes the conversation history you want the model to consider. Here's an example of how you might use the Chat Completions API:
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Who won the world series in 2020?"},
{"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
{"role": "user", "content": "Where was it played?"}
]
)
(Source: OpenAI Cookbook - Azure Chat Completions example (https://cookbook.openai.com/examples/azure/chat#create-chat-completions))
In this example, each message in the conversation is included in the messages array. The model considers all of these messages when generating its response. If you want to add more messages to the conversation, you simply include more messages in this array.
Remember to replace "gpt-3.5-turbo" with the model you're using, and the content of the messages with your actual conversation.