querais

Python client for QueraIS — the decentralized AI inference marketplace. Anyone with a GPU serves models and earns; you buy inference through one OpenAI-compatible endpoint.

pip install querais

from querais import QueraisClient

client = QueraisClient("https://gateway.querais.xyz", api_key="sk-...")
result = client.chat([{"role": "user", "content": "hello"}], model="llama3.2")
print(result.content)

OpenAI-compatible

The gateway speaks the OpenAI chat-completions protocol, so the official openai package works too — point it at the gateway:

from openai import OpenAI

client = OpenAI(base_url="https://gateway.querais.xyz/v1", api_key="sk-...")

This package is thin sugar over that protocol plus QueraIS-specific helpers.

Streaming

for delta in client.chat_stream([{"role": "user", "content": "tell me a story"}], model="llama3.2"):
    print(delta, end="", flush=True)

QueraIS extras

client.models()  # model ids served by connected nodes
client.nodes()  # public node directory: reputation, prices, dimensions
client.stats()  # network stats
client.model_manifest()  # the gateway's signed model-digest manifest (404 if unpinned)

Routing extensions on chat() / chat_stream():

client.chat(
    messages,
    model="llama3.2",
    max_price_per_1k_tokens=0.5,  # cap what you pay
    min_reputation=0.7,
)  # floor the node quality

LangChain / LlamaIndex

The integrations return the official LangChain / LlamaIndex OpenAI classes configured for the gateway — nothing reimplemented:

pip install 'querais[langchain]'   # or 'querais[llamaindex]'

from querais.langchain import chat_model

llm = chat_model("https://gateway.querais.xyz", api_key="sk-...", model="llama3.2")

from querais.llamaindex import llm as qllm

llm = qllm("https://gateway.querais.xyz", api_key="sk-...", model="llama3.2")

License

MIT

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