ohttpy 0.1a8

A package that allows for client-side OHTTP-wrapping over HTTP communication

ohttpy Package

Introduction

This package allows for client-side OHTTP-wrapping over HTTP communication. It acheives this by providing drop-in replacement classes for requests.Session and httpx.BaseTransport classes that abstract the OHTTP layer.

NOTE: This package utilizes a modified Rust library that implements OHTTP and relies on the chunked OHTTP protocol which has not been ratified into a standard at the time of writing.

NOTE: At the time of writing, this package is currently under active development and therefore, only compatible with chunked-OHTTP gateways that advertise public keys in a specific fashion.

Requests Session Example

To use OHTTP in a requests.Session setting, simply replace the object construction with ohttpy.Session:

import ohttpy

# Create ohttpy session that inherits from requests.Session.
session = ohttpy.Session()

# Use session like a request.Session including streaming response support.
response = session.post("http://ohttp-server/path/to/post", data="test data", stream=True)
for chunk in response.iter_content():
    if chunk:
        print(chunk.decode(), end="", flush=True)

HTTPX Transport Example

To use OHTTP in a httpx.Transport setting, simply replace the object construction with ohttpy.Transport:

import httpx
import ohttpy

# Initialize httpx client with the ohttpy Transport that inherits from httpx.Transport
httpx_client = httpx.Client(transport=ohttpy.Transport())

# Use client as normal including streaming response support.
method = "GET"
url = "http://ohttp-server/path/to/get/"
with httpx_client.stream(method, url) as resp:
    print(resp.status_code)
    print(resp.headers)
    for chunk in resp.stream:
        print(chunk.decode(), end="", flush=True)

This is also applicable to clients that utilize httpx for their HTTP communication, for example openai client:

import httpx
import openai
import ohttpy

# Initialize httpx client with the ohttpy Transport that inherits from httpx.Transport
httpx_client = httpx.Client(transport=ohttpy.Transport())
url = "http://ohttp-server"
api_key = "API_KEY"

# Configure OpenAI client with httpx client
client = openai.OpenAI(
    api_key=api_key,
    http_client=httpx_client,
    base_url=url + "/v1")

# Use OpenAI SDK as normal for example llama chat (including stream capability)
is_stream=True
completion = client.chat.completions.create(
    model="meta-llama/Llama-3.2-3B-Instruct",
    messages=[
        {"role": "system", "content": "You are a helpful AI assistant."},
        {"role": "user", "content": "where does the sun rise from?"},
    ],
    temperature=0.2,
    top_p=0.7,
    max_tokens=1024,
    stream=is_stream,
)
if is_stream:
    for chunk in completion:
        print(chunk.choices[0].delta.content or "", end="", flush=True)
else:
    print(completion.choices[0].message.content)