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Documentation Index

Fetch the complete documentation index at: https://docs.subconscious.dev/llms.txt

Use this file to discover all available pages before exploring further.

Streaming delivers tokens as they’re generated, which enables responsive UIs and real-time output. Subconscious uses the standard OpenAI streaming format: Server-Sent Events (SSE) with ChatCompletionChunk objects.

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Basic Streaming

Set stream=True to receive a stream of chunks instead of waiting for the full response: 
from openai import OpenAI

client = OpenAI(
    api_key="your-api-key",
    base_url="https://api.subconscious.dev/v1",
)

stream = client.chat.completions.create(
    model="subconscious/tim-qwen3.6-27b",
    messages=[{"role": "user", "content": "Explain how neural networks learn."}],
    stream=True,
)

for chunk in stream:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)
print()

​
SSE Format

Each event in the stream is a data: line containing a JSON ChatCompletionChunk object: 
data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","model":"subconscious/tim-qwen3.6-27b","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","model":"subconscious/tim-qwen3.6-27b","choices":[{"index":0,"delta":{"content":" world"},"finish_reason":null}]}

data: {"id":"chatcmpl-abc123","object":"chat.completion.chunk","model":"subconscious/tim-qwen3.6-27b","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]
The final chunk has finish_reason: "stop" and is followed by data: [DONE].

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Error Handling

Errors during streaming are delivered as SSE events. The OpenAI SDK raises exceptions automatically: 
from openai import APIError

try:
    stream = client.chat.completions.create(
        model="subconscious/tim-qwen3.6-27b",
        messages=[{"role": "user", "content": "Hello"}],
        stream=True,
    )
    for chunk in stream:
        content = chunk.choices[0].delta.content
        if content:
            print(content, end="", flush=True)
except APIError as e:
    print(f"API error: {e.status_code} - {e.message}")

​
Usage Statistics

To receive token usage in the stream, include stream_options:
Python
stream = client.chat.completions.create(
    model="subconscious/tim-qwen3.6-27b",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
    stream_options={"include_usage": True},
)

for chunk in stream:
    if chunk.usage:
        print(f"Input: {chunk.usage.prompt_tokens}, Output: {chunk.usage.completion_tokens}")
    elif chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
Usage data is included in the final chunk of the stream.