space-hii
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Claude 4.5
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Today
Y
Hey, can you show me how to integrate the Ultroid client with the space-hii platform? I'm looking for a Python example to get started.
C
Claude 4.5
Sure! Here's a minimal Python snippet to connect your UltroidClient to the space-hii platform. Make sure you've installed the dependency with pip install ultroid first.
Python
import asyncio
from ultroid import UltroidClient
# Initialize the Ultroid client
client = UltroidClient(
session="my_session",
api_id=12345,
api_hash="your_api_hash_here"
)
async def main():
await client.start()
me = await client.get_me()
print(f"Logged in as: {me.first_name}")
asyncio.run(main())
Key things to note:
- [object Object] — use a unique string per deployment to avoid session conflicts.
- Your api_id and api_hash come from my.telegram.org.
- The client handles reconnection and flood-wait automatically in production mode.
Y
Perfect. Now can you show me the JavaScript SDK example for streaming a response? I'm building a Node.js microservice.
G
GPT 5.2
Absolutely. The @space-hii/sdk package exposes a native async-iterable stream interface. Here's a Node.js example:
JavaScript
const { SpaceHii } = require('@space-hii/sdk');
const client = new SpaceHii({
apiKey: process.env.SPACE_HIi_KEY,
model: 'claude-4.5',
locale: 'en-IN'
});
// Stream a response
const stream = await client.chat.stream({
messages: [{ role: 'user', content: 'Analyze bot performance' }]
});
for await (const chunk of stream) {
process.stdout.write(chunk.delta);
}
A few tips for production:
- Store your API key in environment variables — never hardcode it.
- The model field accepts gpt-5.2, claude-4.5, or auto for LiteLLM routing.
- Set locale: 'en-IN' for IST-aware timestamps and INR currency formatting in analytics reports.
C
Claude 4.5
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GPT 5.2 — Fast Responses—Ultra-low latency for real-time conversation
Claude 4.5 — Code & Analysis—Deep reasoning, code review & structured output
Nano Banana — Image Generation—High-fidelity images from natural language prompts
Litellm Routing — Auto Model Selection—Intelligently routes queries to the best-fit model
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