OpenPipe Python Client
This client allows you automatically report your OpenAI calls to OpenPipe.
Installation
pip install openpipe
Usage
- Create a project at https://app.openpipe.ai
- Find your project's API key at https://app.openpipe.ai/settings
- Configure the OpenPipe client as shown below.
from openpipe import OpenAI
import os
client = OpenAI(
# defaults to os.environ.get("OPENAI_API_KEY")
api_key="My API Key",
openpipe={
# Set the OpenPipe API key you got in step (2) above.
# If you have the `OPENPIPE_API_KEY` environment variable set we'll read from it by default
"api_key": "My OpenPipe API Key",
}
)
You can now use your new OpenAI client, which functions identically to the generic OpenAI client while also reporting calls to your OpenPipe instance.
Special Features
Metadata Tagging
OpenPipe follows OpenAI’s concept of metadata tagging for requests. This is very useful for grouping a certain set of completions together. These tags will help you find all the input/output pairs associated with a certain prompt and fine-tune a model to replace it. Here's how you can use the tagging feature:
completion = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "system", "content": "count to 10"}],
metadata={"prompt_id": "counting"},
store=True,
)
Should I Wait to Enable Logging?
We recommend keeping request logging turned on from the beginning. If you change your prompt you can just set a new prompt_id tag so you can select just the latest version when you're ready to create a dataset.
Usage with langchain
Assuming you have created a project and have the openpipe key.
from openpipe.langchain_llm import ChatOpenAI
from langchain.prompts import ChatPromptTemplate
from langchain.schema.runnable import RunnableSequence
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"Classify user query into positive, negative or neutral.",
),
("human", "{query}"),
]
)
llm = ChatOpenAI(model="gpt-4o")
.with_tags(chain_name="classify", any_key="some")
# To provide the openpipe key explicitly
# llm = ChatOpenAI(model="gpt-4o", openpipe_kwargs={"api_key": "My OpenPipe API Key"})\
# .with_tags(chain_name="classify", any_key="some")
chain: RunnableSequence = prompt | llm
res = chain.invoke(
{"query": "this is good"}
)
Release files for openpipe 5.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| openpipe-5.0.0.tar.gz | 98.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openpipe-5.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 538.9 kB
Release files / openpipe-5.0.0.tar.gz
| Download URL | openpipe-5.0.0.tar.gz |
|---|---|
| Size | 98.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.7.1 CPython/3.11.0 Darwin/24.5.0
|
Release files / openpipe-5.0.0-py3-none-any.whl
| Download URL | openpipe-5.0.0-py3-none-any.whl |
|---|---|
| Size | 440.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.7.1 CPython/3.11.0 Darwin/24.5.0
|
