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The official Python SDK for the Subconscious API

Project description

Subconscious

Subconscious SDK

The official Python SDK for the Subconscious API

PyPI version PyPI downloads docs python version license


Installation

pip install subconscious-sdk
# or
uv add subconscious-sdk
# or
poetry add subconscious-sdk

Note: The package name is subconscious-sdk but you import it as subconscious.

Quick Start

from subconscious import Subconscious

client = Subconscious(api_key="your-api-key")

run = client.run(
    engine="tim-gpt",
    input={
        "instructions": "Search for the latest AI news and summarize the top 3 stories",
        "tools": [{"type": "platform", "id": "fast_search"}],
    },
    options={"await_completion": True},
)

print(run.result.answer)

Get Your API Key

Create an API key in the Subconscious dashboard.

Usage

Run and Wait

The simplest way to use the SDK—create a run and wait for completion:

run = client.run(
    engine="tim-gpt",
    input={
        "instructions": "Analyze the latest trends in renewable energy",
        "tools": [{"type": "platform", "id": "fast_search"}],
    },
    options={"await_completion": True},
)

print(run.result.answer)
print(run.result.reasoning)  # Structured reasoning nodes

Fire and Forget

Start a run without waiting, then check status later:

run = client.run(
    engine="tim-gpt",
    input={
        "instructions": "Generate a comprehensive report",
        "tools": [],
    },
)

print(f"Run started: {run.run_id}")

# Check status later
status = client.get(run.run_id)
print(status.status)  # 'queued' | 'running' | 'succeeded' | 'failed' | 'canceled' | 'timed_out'

Poll with Custom Options

run = client.run(
    engine="tim-gpt",
    input={
        "instructions": "Complex task",
        "tools": [{"type": "platform", "id": "fast_search"}],
    },
)

# Wait with custom polling options
result = client.wait(
    run.run_id,
    options={
        "interval_ms": 2000,  # Poll every 2 seconds
        "max_attempts": 60,   # Give up after 60 attempts
    },
)

Streaming (Text Deltas)

Stream text as it's generated:

for event in client.stream(
    engine="tim-gpt",
    input={
        "instructions": "Write a short essay about space exploration",
        "tools": [{"type": "platform", "id": "fast_search"}],
    },
):
    if event.type == "delta":
        print(event.content, end="", flush=True)
    elif event.type == "done":
        print(f"\n\nRun completed: {event.run_id}")
    elif event.type == "error":
        print(f"Error: {event.message}")

Note: Rich streaming events (reasoning steps, tool calls) are coming soon. Currently, the stream provides text deltas as they're generated.

Structured Output

Get responses in a specific JSON schema format using Pydantic models:

from pydantic import BaseModel
from subconscious import Subconscious

class AnalysisResult(BaseModel):
    summary: str
    key_points: list[str]
    sentiment: str

client = Subconscious(api_key="your-api-key")

run = client.run(
    engine="tim-gpt",
    input={
        "instructions": "Analyze the latest news about electric vehicles",
        "tools": [{"type": "platform", "id": "fast_search"}],
        "answerFormat": AnalysisResult,  # Pass the Pydantic class directly
    },
    options={"await_completion": True},
)

# The answer will conform to your schema
print(run.result.answer)  # JSON string matching AnalysisResult

The SDK automatically converts your Pydantic model to JSON Schema. You can also pass a raw JSON Schema dict if preferred.

For advanced use cases, you can also specify a reasoningFormat to structure the agent's reasoning output.

Tools

Simple Search Tools — Use these tools to get started quickly in our playground or with our API. For example: {"type": "platform", "id": "fast_search"}.

Tool Name API Name Description
Fast Search fast_search Extremely fast search for simple factual lookups
Web Search web_search Comprehensive web search for detailed research
Fresh Search fresh_search Search the web for content from the last 7 days
Page Reader page_reader Extract content from a specific webpage URL
Find Similar find_similar Find similar links to a given URL
People Search people_search Search for people, profiles, and bios
Company Search company_search Search for companies, funding info, and business details
News Search news_search Search for news articles and press coverage
Tweet Search tweet_search Search for tweets and Twitter/X discussions
Research Paper Search research_paper_search Search for academic research papers and studies
Google Search google_search Search the web using Google
# Platform tools (hosted by Subconscious)
fast_search = {
    "type": "platform",
    "id": "fast_search",
}

# Function tools (your own HTTP endpoints)
custom_function = {
    "type": "function",
    "name": "get_weather",
    "description": "Get current weather for a location",
    "url": "https://api.example.com/weather",
    "method": "GET",
    "timeout": 30,
    "parameters": {
        "type": "object",
        "properties": {
            "location": {"type": "string"},
        },
        "required": ["location"],
    },
}

# MCP tools
mcp_tool = {
    "type": "mcp",
    "url": "https://mcp.example.com",
    "allow": ["read", "write"],
}

Tool Headers & Default Arguments

Function tools support two powerful features for injecting data at call time:

  • headers: HTTP headers sent with the request to your tool endpoint
  • defaults: Parameter values hidden from the model and injected automatically
tool_with_headers_and_defaults = {
    "type": "function",
    "name": "search_database",
    "description": "Search the database",
    "url": "https://api.example.com/search",
    "method": "POST",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {"type": "string", "description": "Search query"},
            # Define these for validation, but they'll be hidden from the model
            "session_id": {"type": "string"},
            "api_key": {"type": "string"},
        },
        "required": ["query"],  # Only query is required - model generates this
    },

    # HEADERS: Sent as HTTP headers when this tool's endpoint is called
    "headers": {
        "x-custom-auth": "my-secret-token",
        "x-request-source": "my-app",
    },

    # DEFAULTS: Injected into parameters, hidden from model
    "defaults": {
        "session_id": "user-session-abc123",
        "api_key": "secret-api-key",
    },
}

How it works:

Feature Where it goes When
headers HTTP request headers Sent to your tool's URL
defaults Merged into request body parameters At tool call time

Default arguments flow:

  1. Define all parameters in properties (required for validation)
  2. Parameters with defaults are stripped from the schema before the model sees them
  3. Model only generates values for non-defaulted parameters (e.g., query)
  4. At call time, defaults are merged into the request body
  5. Default values always take precedence over model-generated values

Each tool can have its own headers and defaults - they're only applied when that specific tool is called.

Error Handling

from subconscious import (
    Subconscious,
    SubconsciousError,
    AuthenticationError,
    RateLimitError,
)

try:
    run = client.run(...)
except AuthenticationError:
    print("Invalid API key")
except RateLimitError:
    print("Rate limited, retry later")
except SubconsciousError as e:
    print(f"API error: {e.code} - {e}")

Cancellation

# Cancel a running run
client.cancel(run.run_id)

API Reference

Subconscious

The main client class.

Constructor Options

Option Type Required Default
api_key str Yes -
base_url str No https://api.subconscious.dev/v1

Methods

Method Description
run(engine, input, options) Create a new run
stream(engine, input) Stream text deltas
get(run_id) Get run status
wait(run_id, options) Poll until completion
cancel(run_id) Cancel a running run

Engines

Engine Type Description Input Output
tim Unified Our flagship unified agent engine for a wide range of tasks $2.00/1M $8.00/1M
tim-edge Unified Highly efficient engine tuned for performance with search tools $0.50/1M $2.00/1M
timini Compound Complex reasoning engine for long-context and tool use backed by Gemini-3 Flash $2.00/1M $12.00/1M
tim-gpt Compound Complex reasoning engine for long-context and tool use backed by OpenAI GPT-4.1 $2.00/1M $8.00/1M
tim-gpt-heavy Compound Complex reasoning engine for long-context and tool use backed by OpenAI GPT-5.2 $2.00/1M $15.00/1M

Run Status

Status Description
queued Waiting to start
running Currently executing
succeeded Completed successfully
failed Encountered an error
canceled Manually canceled
timed_out Exceeded time limit

Requirements

  • Python ≥ 3.8
  • requests

Contributing

Contributions are welcome! Please feel free to submit a pull request.

License

Apache-2.0

Support

For support and questions:

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