model sdk built by the 9th ditrict at tooig
Project description
nineth
nineth is the Python SDK for the 1984 model API, built by the 9th District at Tooig.
Install
pip install nineth
export NINETH_API_KEY="your-api-key"
How it works
Every request goes through client.model.request(...).
- Pass a task. Get a response.
- Set
stream=Trueto receive text as it arrives, word by word. - Per request, you can opt into persistent sessions, built-in services, included services, a base-provider override, and debug telemetry.
- The server still runs the worker loop and manages the actual task state.
Models
| Name | Description |
|---|---|
1984-m3-0317 |
Most capable. Best for research and complex tasks. |
1984-m2-preview |
Fast and powerful. Good for most tasks. |
1984-m2-light |
Lightweight, quick general tasks. |
1984-m1-unified |
High-throughput unified model. |
1984-m0-brute |
Compact efficient model. |
1984-m0-sm |
Smallest model, fastest responses. |
Set a default at client creation or pass model= per call.
Cookbook
1 — Get a response
The simplest case. Ask something, get the answer.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request("Give me a tight BTC market brief.")
print(response["final_response"])
response is a plain dict. The text is always in response["final_response"].
2 — Stream the response live
Set stream=True to print text as it arrives.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
for event in client.model.request("Summarise crude oil today.", stream=True):
if event["type"] == "model_delta":
print(event["data"]["text"], end="", flush=True)
The last event in the stream is type: result and contains the full final_response
alongside iterations.
3 — Choose a different model per request
from nineth import NinethClient
with NinethClient() as client:
response = client.model.request(
"What happened with Nvidia earnings?",
model="1984-m2-light",
)
print(response["final_response"])
4 — Control reasoning depth
Use reasoning to hint at how deeply the model should think before answering.
Valid values: "low", "medium", "high". Leave it out to use the model default.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Analyse the macro impact of a Fed rate pause.",
reasoning="high",
)
print(response["final_response"])
5 — Show the model's reasoning
Set show_reasoning=True to include the model's internal chain-of-thought.
This is off by default.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Walk me through whether gold is trending or ranging.",
reasoning="medium",
show_reasoning=True,
)
for block in response.get("thinking", []):
print("[thinking]", block)
print(response["final_response"])
6 — Limit how many turns the model takes
max_iterations controls how many model turns the server runs.
The default is 10. Most tasks finish in 1–3 turns.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Give me a one-paragraph ETH brief.",
max_iterations=2,
)
print(response["final_response"])
7 — Async usage
import asyncio
from nineth import AsyncNinethClient
async def main():
async with AsyncNinethClient(default_model="1984-m3-0317") as client:
response = await client.model.request(
"Summarise macro risk factors this week.",
)
print(response["final_response"])
asyncio.run(main())
Async streaming works the same way:
import asyncio
from nineth import AsyncNinethClient
async def main():
async with AsyncNinethClient(default_model="1984-m3-0317") as client:
async for event in await client.model.request(
"Research BTC ETF flows.", stream=True
):
if event["type"] == "model_delta":
print(event["data"]["text"], end="", flush=True)
asyncio.run(main())
8 — Health check
No API key needed. Use this to verify the endpoint is reachable.
from nineth import NinethClient
with NinethClient() as client:
print(client.health())
# {'status': 'ok', 'timestamp': '2026-04-04T00:00:00+00:00'}
9 — Provider routing
SDK requests use the base-system provider path by default.
Set base_system=False only when you explicitly want to fall back to the runtime default provider selection.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0421") as client:
response = client.model.request(
"Summarise today's macro tape.",
base_system=False,
)
print(response["final_response"])
base_system is True by default.
11 — Persist and reuse a session
Set cache=True to persist the task session and receive a reusable session_id.
Pass that session_id back into later requests to continue the same task memory.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
first = client.model.request(
"Start a running research notebook for crude oil.",
cache=True,
)
session_id = first["session_id"]
second = client.model.request(
"Continue from the last note and add today's macro drivers.",
cache=True,
session_id=session_id,
)
print(second["final_response"])
If cache=False, the task is treated as one-shot and no session_id is exposed.
12 — Opt into built-in services
Built-in services are off by default.
default_service=False: no built-in servicesdefault_service=True: all built-in servicesdefault_service=[...]: only the named built-in services
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Research OPEC headlines and summarise the impact.",
default_service=["search_news", "search_web"],
)
print(response["final_response"])
13 — Use one include_service surface for custom services
include_service is the only custom-service surface you need.
- If you pass a local
schema.pypath or a directory containingschema.py, the SDK loads it locally, exposes its schema to the model, executes the emitted service call in your process, and resumes the run through the callback protocol. - Buffered requests still auto-execute local callback services in the caller process.
- Streaming requests do not auto-execute local callback services. They pause with an
awaiting_client_servicesevent so your code can decide how to execute the local work and when to resume. - If you pass a shorthand string such as a service-manager name, service name, or local service directory name, the SDK scans local
schema.pyfiles and prefers matches underservices/directories. - If you pass a service manager class or instance that comes from a schema module, the SDK resolves that module automatically.
- If you pass an unresolved path string, the SDK passes it through to the API server as a server-hosted
schema.pypath. - If a local service name collides with an existing server-side service name, the request fails early with a clear error instead of running the wrong service.
This keeps the public surface small while still supporting both local and server-managed services.
Local callback example:
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Use my local weather service and compare it with today's oil move.",
default_service=["search_web"],
include_service=["./services/weather/schema.py"],
)
print(response["final_response"])
Shorthand discovery example:
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Use my local weather service.",
include_service=["WeatherServiceManager"],
)
print(response["final_response"])
Direct manager reference example:
from nineth import NinethClient
from myapp.schema import WeatherServiceManager
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Use my local weather service.",
include_service=[WeatherServiceManager],
)
print(response["final_response"])
Manual streaming callback example:
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
pending_process_id = None
for event in client.model.request(
"What is the weather like right now in sf?",
include_service=["./regulator/schema.py"],
stream=True,
):
if event["type"] == "model_delta":
print(event["data"].get("text", ""), end="", flush=True)
elif event["type"] == "awaiting_client_services":
pending_process_id = event["process_id"]
pending_calls = event["data"]["pending_client_calls"]
if pending_process_id:
resume = client.model.request(
"Resume after local weather call.",
stream=True,
session_id=pending_process_id,
client_service_results=[
{
"call_id": pending_calls[0]["call_id"],
"service_name": "get_weather",
"success": True,
"result": {"location": "San Francisco", "forecast": "sunny"},
}
],
)
for event in resume:
if event["type"] == "model_delta":
print(event["data"].get("text", ""), end="", flush=True)
Server-hosted path example:
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Use the custom weather service and compare it with market risk sentiment.",
default_service=["search_web"],
include_service=["/srv/app/services/weather/schema.py"],
)
print(response["final_response"])
Minimal local schema.py shape:
from typing import Any, Dict
class WeatherServiceManager:
def get_weather(self, location: str) -> Dict[str, Any]:
return {"location": location, "forecast": "sunny"}
weather_services = {
"get_weather": {
"name": "get_weather",
"description": "Return a tiny weather forecast.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"],
"additionalProperties": False,
},
}
}
weather_implementations = {
"get_weather": lambda manager: manager.get_weather,
}
14 — Enable debug telemetry
Set debug=True to keep the worker's structured telemetry in the buffered response or streamed events.
from nineth import NinethClient
with NinethClient(default_model="1984-m3-0317") as client:
response = client.model.request(
"Research market risk and show the internal trace.",
default_service=["search_news"],
debug=True,
)
print(response.get("events", []))
Response shape
Buffered (stream=False)
{
"final_response": "Bitcoin is trading near...",
"iterations": 2,
"usage": {"prompt_tokens": 412, "completion_tokens": 88, "total_tokens": 500},
"thinking": [], # only populated when show_reasoning=True
"service_calls": [...],
"service_responses": [...],
"events": [...],
}
Only final_response and iterations are guaranteed to be present on every response.
Streaming (stream=True)
Each loop iteration yields a dict:
# Text arriving live
{"type": "model_delta", "data": {"text": "Bitcoin is trading..."}}
# service calls the model made
{"type": "service_call", "data": {"service_name": "search_web", "params": {...}}}
{"type": "service_response", "data": {"service_name": "search_web", "success": True, "summary": {...}}}
# Final summary — always the last event
{"type": "result", "data": {"final_response": "...", "iterations": 2}}
Error handling
from nineth import NinethClient, NinethAPIError
with NinethClient(default_model="1984-m3-0317") as client:
try:
response = client.model.request("Analyse ETH.")
except NinethAPIError as exc:
print("API error:", exc)
except ValueError as exc:
print("Configuration error:", exc)
Authentication
Set NINETH_API_KEY in your environment or pass api_key= to the client constructor.
That key can be any one key registered by the server's NINETH_API_KEYS registry.
The health check endpoint does not require a key.
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