openai-messages-token-helper
A helper library for estimating tokens used by messages and building messages lists that fit within the token limits of a model. Currently designed to work with the OpenAI GPT models (including GPT-4 turbo with vision). Uses the tiktoken library for tokenizing text and the Pillow library for image-related calculations.
Installation
Install the package:
python3 -m pip install openai-messages-token-helper
Usage
The library provides the following functions:
build_messages
Build a list of messages for a chat conversation, given the system prompt, new user message, and past messages. The function will truncate the history of past messages if necessary to stay within the token limit.
Arguments:
model(str): The model name to use for token calculation, like gpt-3.5-turbo.system_prompt(str): The initial system prompt message.tools(List[openai.types.chat.ChatCompletionToolParam]): (Optional) The tools that will be used in the conversation. These won't be part of the final returned messages, but they will be used to calculate the token count.tool_choice(openai.types.chat.ChatCompletionToolChoiceOptionParam): (Optional) The tool choice that will be used in the conversation. This won't be part of the final returned messages, but it will be used to calculate the token count.new_user_content(str | List[openai.types.chat.ChatCompletionContentPartParam]): (Optional) The content of new user message to append.past_messages(list[openai.types.chat.ChatCompletionMessageParam]): (Optional) The list of past messages in the conversation.few_shots(list[openai.types.chat.ChatCompletionMessageParam]): (Optional) A few-shot list of messages to insert after the system prompt.max_tokens(int): (Optional) The maximum number of tokens allowed for the conversation.fallback_to_default(bool): (Optional) Whether to fallback to default model/token limits if model is not found. Defaults toFalse.
Returns:
list[openai.types.chat.ChatCompletionMessageParam]
Example:
from openai_messages_token_helper import build_messages
messages = build_messages(
model="gpt-35-turbo",
system_prompt="You are a bot.",
new_user_content="That wasn't a good poem.",
past_messages=[
{
"role": "user",
"content": "Write me a poem",
},
{
"role": "assistant",
"content": "Tuna tuna I love tuna",
},
],
few_shots=[
{
"role": "user",
"content": "Write me a poem",
},
{
"role": "assistant",
"content": "Tuna tuna is the best",
},
]
)
count_tokens_for_message
Counts the number of tokens in a message.
Arguments:
model(str): The model name to use for token calculation, like gpt-3.5-turbo.message(openai.types.chat.ChatCompletionMessageParam): The message to count tokens for.default_to_cl100k(bool): Whether to default to the CL100k token limit if the model is not found.
Returns:
int: The number of tokens in the message.
Example:
from openai_messages_token_helper import count_tokens_for_message
message = {
"role": "user",
"content": "Hello, how are you?",
}
model = "gpt-4"
num_tokens = count_tokens_for_message(model, message)
count_tokens_for_image
Count the number of tokens for an image sent to GPT-4-vision, in base64 format.
Arguments:
image(str): The base64-encoded image.
Returns:
int: The number of tokens used up for the image.
Example:
Count the number of tokens for an image sent to GPT-4-vision:
```python
from openai_messages_token_helper import count_tokens_for_image
image = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEA..."
num_tokens = count_tokens_for_image(image)
get_token_limit
Get the token limit for a given GPT model name (OpenAI.com or Azure OpenAI supported).
Arguments:
model(str): The model name to use for token calculation, like gpt-3.5-turbo (OpenAI.com) or gpt-35-turbo (Azure).default_to_minimum(bool): Whether to default to the minimum token limit if the model is not found.
Returns:
int: The token limit for the model.
Example:
from openai_messages_token_helper import get_token_limit
model = "gpt-4"
max_tokens = get_token_limit(model)
Metadata
Release files for openai-messages-token-helper 0.1.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| openai_messages_token_helper-0.1.13.tar.gz | 401.1 kB | Without provenance | Details for openai_messages_token_helper-0.1.13.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| openai_messages_token_helper-0.1.13-py3-none-any.whl | Python 3 | none | any | Details for openai_messages_token_helper-0.1.13-py3-none-any.whl |
Total release size: 412.0 kB
Release files / openai_messages_token_helper-0.1.13.tar.gz
| Download URL | openai_messages_token_helper-0.1.13.tar.gz |
|---|---|
| Size | 401.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ee423346d52e792d67e480d82ef8ecb422a9511223bffcd3b57c37afb191279d
|
|
BLAKE2b-256 checksum How to use checksums |
13b73c660423b8812611a01bfe2735ae049e8d20106741fec81d9105d4e59a53
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-requests/2.32.3
|
Release files / openai_messages_token_helper-0.1.13-py3-none-any.whl
| Download URL | openai_messages_token_helper-0.1.13-py3-none-any.whl |
|---|---|
| Size | 10.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
88dfd9082204fec9882bd314fc723c45337cec0fd0bc7400b3cda4508a099499
|
|
BLAKE2b-256 checksum How to use checksums |
d4fc9709d4a9251242c189b6b5ac95f729dc0064a3142348e2920eca7cfe1f00
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
python-requests/2.32.3
|
Security for openai-messages-token-helper 0.1.13
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.