Exchange - a uniform python SDK for message generation with LLMs
- Provides a flexible layer for message handling and generation
- Directly integrates python functions into tool calling
- Persistently surfaces errors to the underlying models to support reflection
Example
[!NOTE] Before you can run this example, you need to setup an API key with
export OPENAI_API_KEY=your-key-here
from exchange import Exchange, Message, Tool
from exchange.providers import OpenAiProvider
def word_count(text: str):
"""Get the count of words in text
Args:
text (str): The text with words to count
"""
return len(text.split(" "))
ex = Exchange(
provider=OpenAiProvider.from_env(),
model="gpt-4o",
system="You are a helpful assistant.",
tools=[Tool.from_function(word_count)],
)
ex.add(Message.user("Count the number of words in this current message"))
# The model sees it has a word count tool, and should use it along the way to answer
# This will call all the tools as needed until the model replies with the final result
reply = ex.reply()
print(reply.text)
# you can see all the tool calls in the message history
print(ex.messages)
Plugins
exchange has a plugin mechanism to add support for additional providers and moderators. If you need a provider not supported here, we'd be happy to review contributions. But you can also consider building and using your own plugin.
To create a Provider plugin, subclass exchange.provider.Provider. You will need to
implement the complete method. For example this is what we use as a mock in our tests.
You can see a full implementation example of the OpenAiProvider. We
also generally recommend implementing a from_env classmethod to instantiate the provider.
class MockProvider(Provider):
def __init__(self, sequence: List[Message]):
# We'll use init to provide a preplanned reply sequence
self.sequence = sequence
self.call_count = 0
def complete(
self, model: str, system: str, messages: List[Message], tools: List[Tool]
) -> Message:
output = self.sequence[self.call_count]
self.call_count += 1
return output
Then use python packaging's entrypoints to register your plugin.
[project.entry-points.'exchange.provider']
example = 'path.to.plugin:ExampleProvider'
Your plugin will then be available in your application or other applications built on exchange through:
from exchange.providers import get_provider
provider = get_provider('example').from_env()
Metadata
Release files for ai-exchange 0.9.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ai_exchange-0.9.9.tar.gz | 227.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ai_exchange-0.9.9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 265.2 kB
Release files / ai_exchange-0.9.9.tar.gz
| Download URL | ai_exchange-0.9.9.tar.gz |
|---|---|
| Size | 227.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0e9c822d1c6eec9fa22866fe3d37a77c14701c1e89afa9e857e40e0e6573c3f9
|
|
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Yes |
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Transparency logRelease files / ai_exchange-0.9.9-py3-none-any.whl
| Download URL | ai_exchange-0.9.9-py3-none-any.whl |
|---|---|
| Size | 37.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
4f2ac6cf54cc0993f10d813e6b4db78efea7933b091ad306e10ec9d7f4f6e3dd
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4825409f7c16c8e4a335434db318ab4042dd8737a302e558d63b257d276f477d
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/5.1.1 CPython/3.12.7
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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