Important
This SDK is fork from OpenAI repository[tag 1.12.0], we try our best to make it compatible with OPENAI, but it may change in the future.
The JarvisBot Python library provides convenient access to the JarvisBot REST API from any Python 3.8+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.
Important
JarvisBot SDK is currently undergoing rapid development, which may lead to stability and compatibility issues. You can email [email protected] to request an access token. We will periodically open up trials.
pip install jarvisbot-python
The full API of this library can be found in api.md.
import os
from jarvisbot import JarvisBot
client = JarvisBot(
# This is the default and can be omitted
app_token=os.environ.get("JARVISBOT_APP_TOKEN"),
)
chat_completion = client.base.chat.completions.create(
messages=[
{
"role": "user",
"content": "Say this is a test",
}
]
)
While you can provide an app_token
keyword argument,
we recommend using python-dotenv
to add JARVISBOT_APP_TOKEN="My App Token"
to your .env
file
so that your App Token is not stored in source control.
Simply import AsyncJarvisBot
instead of JarvisBot
and use await
with each API call:
import os
import asyncio
from jarvisbot import AsyncJarvisBot
client = AsyncJarvisBot(
# This is the default and can be omitted
app_token=os.environ.get("JARVISBOT_APP_TOKEN"),
)
async def main() -> None:
chat_completion = await client.base.chat.completions.create(
messages=[
{
"role": "user",
"content": "Say this is a test",
}
],
)
asyncio.run(main())
Functionality between the synchronous and asynchronous clients is otherwise identical.
We provide support for streaming responses using Server Side Events (SSE).
from jarvisbot import JarvisBot
client = JarvisBot()
stream = client.base.chat.completions.create(
messages=[{"role": "user", "content": "Say this is a test"}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="")
The async client uses the exact same interface.
from jarvisbot import AsyncJarvisBot
client = AsyncJarvisBot()
async def main():
stream = await client.base.chat.completions.create(
messages=[{"role": "user", "content": "Say this is a test"}],
stream=True,
)
async for chunk in stream:
print(chunk.choices[0].delta.content or "", end="")
asyncio.run(main())
When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of jarvisbot.APIConnectionError
is raised.
When the API returns a non-success status code (that is, 4xx or 5xx
response), a subclass of jarvisbot.APIStatusError
is raised, containing status_code
and response
properties.
All errors inherit from jarvisbot.APIError
.
import jarvisbot
from jarvisbot import JarvisBot
client = JarvisBot()
try:
client.base.chat.completions.create(
messages=[
{
"content": "You are a helpful assistant.",
"role": "system"
},
{
"content": "What is the capital of France?",
"role": "user"
}
],
)
except jarvisbot.APIConnectionError as e:
print("The server could not be reached")
print(e.__cause__) # an underlying Exception, likely raised within httpx.
except jarvisbot.RateLimitError as e:
print("A 429 status code was received; we should back off a bit.")
except jarvisbot.APIStatusError as e:
print("Another non-200-range status code was received")
print(e.status_code)
print(e.response)
Error codes are as followed:
Status Code | Error Type |
---|---|
400 | BadRequestError |
401 | AuthenticationError |
403 | PermissionDeniedError |
404 | NotFoundError |
422 | UnprocessableEntityError |
429 | RateLimitError |
>=500 | InternalServerError |
N/A | APIConnectionError |
Certain errors are automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors are all retried by default.
You can use the max_retries
option to configure or disable retry settings:
from jarvisbot import JarvisBot
# Configure the default for all requests:
client = JarvisBot(
# default is 2
max_retries=0,
)
# Or, configure per-request:
client.with_options(max_retries=5).base.chat.completions.create(
messages=[
{
"role": "user",
"content": "How can I get the name of the current day in Node.js?",
}
],
)
By default requests time out after 10 minutes. You can configure this with a timeout
option,
which accepts a float or an httpx.Timeout
object:
from jarvisbot import JarvisBot
# Configure the default for all requests:
client = JarvisBot(
# 20 seconds (default is 10 minutes)
timeout=20.0,
)
# More granular control:
client = JarvisBot(
timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
)
# Override per-request:
client.with_options(timeout=5 * 1000).base.chat.completions.create(
messages=[
{
"role": "user",
"content": "How can I list all files in a directory using Python?",
}
]
)
On timeout, an APITimeoutError
is thrown.
Note that requests that time out are retried twice by default.
We use the standard library logging
module.
You can enable logging by setting the environment variable JARVISBOT_LOG
to debug
.
$ export JARVISBOT_LOG=debug
In an API response, a field may be explicitly null
, or missing entirely; in either case, its value is None
in this library. You can differentiate the two cases with .model_fields_set
:
if response.my_field is None:
if 'my_field' not in response.model_fields_set:
print('Got json like {}, without a "my_field" key present at all.')
else:
print('Got json like {"my_field": null}.')
The "raw" Response object can be accessed by prefixing .with_raw_response.
to any HTTP method call, e.g.,
from jarvisbot import JarvisBot
client = JarvisBot()
response = client.base.chat.completions.with_raw_response.create(
messages=[{
"role": "user",
"content": "Say this is a test",
}]
)
print(response.headers.get('X-My-Header'))
completion = response.parse() # get the object that `chat.completions.create()` would have returned
print(completion)
For the sync client this will mostly be the same with the exception
of content
& text
will be methods instead of properties. In the
async client, all methods will be async.
A migration script will be provided & the migration in general should be smooth.
The above interface eagerly reads the full response body when you make the request, which may not always be what you want.
To stream the response body, use .with_streaming_response
instead, which requires a context manager and only reads the response body once you call .read()
, .text()
, .json()
, .iter_bytes()
, .iter_text()
, .iter_lines()
or .parse()
. In the async client, these are async methods.
As such, .with_streaming_response
methods return a different APIResponse
object, and the async client returns an AsyncAPIResponse
object.
with client.base.chat.completions.with_streaming_response.create(
messages=[
{
"role": "user",
"content": "Say this is a test",
}
],
) as response:
for line in response.iter_lines():
print(line)
The context manager is required so that the response will reliably be closed.
You can directly override the httpx client to customize it for your use case, including:
- Support for proxies
- Custom transports
- Additional advanced functionality
import httpx
from jarvisbot import JarvisBot
client = JarvisBot(
# Or use the `JARVISBOT_BASE_URL` env var
base_url="http://my.test.server.example.com:8083",
http_client=httpx.Client(
proxies="http://my.test.proxy.example.com",
transport=httpx.HTTPTransport(local_address="0.0.0.0"),
),
)
By default the library closes underlying HTTP connections whenever the client is garbage collected. You can manually close the client using the .close()
method if desired, or with a context manager that closes when exiting.
Python 3.8 or higher.