ohttpy 0.1a3

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 ohttp.Session:

import ohttpy

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

# Use session like a request.Session.
response = session.post("http://ohttp-server/path/to/post", data="test data")
print(response.text)

HTTPX Transport Example

To use OHTTP in a httpx.Transport setting, simply replace the object construction with ohttp.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 chunked-encoding 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="")

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())
base_url = "http://ohttp-server/v1"

# Configure OpenAI client with httpx client
client = openai.OpenAI(
    api_key="OPENAI_API_KEY",
    http_client=httpx_client, base_url=base_url)

# Use OpenAI SDK as normal for example llama chat (includingg stream capability)
is_stream=True
chat_completion_stream = client.chat.completions.create(
    model="meta-llama/Llama-3.2-3B-Instruct",
    messages=[
        {
            "role": "user",
            "content": "Create a song that captures the spirit and history of cybersecurity",
        }
    ],
    temperature=0.2,
    top_p=0.7,
    max_tokens=1024,
    stream=is_stream,
)
if is_stream:
    for chunk in chat_completion_stream:
        print(chunk.choices[0].delta.content or "", end="")
else:
    print(chat_completion_stream.choices[0].message.content)