Official Python SDK for the Splox API — run workflows, manage chats, and monitor execution
Project description
Splox Python SDK
Official Python SDK for the Splox API — create and observe workflow runs, resolve human-in-the-loop interactions, browse the MCP catalog, and manage workflows programmatically.
v0.1.0 is a breaking release. The run-execution surface moved to the v2 API (
client.runs/client.interactions). Workflow CRUD reads, chats, memory, billing and the MCP module are unchanged. See CHANGELOG.md for the full breaking-change list.
Installation
pip install splox
Quick Start
from splox import SploxClient
client = SploxClient(api_key="your-api-key")
# Create a run: workflow id ("wf_...") or a raw workflow UUID both work.
run = client.runs.create(
"wf_01JAZ6Y5M3Q8F7N2R4T6V9W0XC",
"Summarize the latest sales report",
)
print(run.id, run.status) # run_01... queued
# Block until the run finishes (raises SploxTimeoutError on timeout).
run = run.wait(timeout=300)
print(run.status) # succeeded | failed | cancelled
# Read the transcript and outputs.
for message in run.messages().data:
print(f"[{message.role}] {message.text}")
for output in run.outputs().data:
print(output.type, output.value)
# Usage (includes descendant runs; amount is a decimal string).
usage = run.usage()
print(usage.input_tokens, usage.output_tokens, usage.amount, usage.currency)
Creating runs
run = client.runs.create(
workflow_id, # "wf_..." or raw UUID
input, # str shorthand, or a full MessageInput dict,
# or a list of content parts
metadata={"ticket": "T-123"}, # optional client metadata
conversation_id="conv_...", # optional: continue a conversation (multi-turn)
workflow_version=3, # optional: pin a workflow version
idempotency_key="my-key", # optional: auto-generated UUIDv4 when omitted
)
input accepts:
"What is 2+2?" # text shorthand
{"role": "user", "content": [{"type": "text", "text": "hi"}]} # full MessageInput
[{"type": "text", "text": "hi"}, {"type": "json", "value": {"x": 1}}] # parts
Every POST /v2/runs carries an Idempotency-Key (auto UUIDv4). Retrying with
the same key and body returns the same run; the SDK only ever retries POSTs
that carry an idempotency key.
Streaming events (SSE)
# Live event stream: auto-reconnects with Last-Event-ID, dedupes by event id,
# and ends after the terminal run.status_changed event.
for event in run.events(): # stream=True is the default
print(event.sequence, event.type, event.data)
# Durable JSON pages instead of a stream:
page = run.events(stream=False, limit=100)
for event in page.data:
print(event.sequence, event.type)
Listing and cancelling
page = client.runs.list(status=["running", "waiting"], limit=20)
for run in page.data:
print(run.id, run.status)
if page.page.has_more:
page = client.runs.list(status=["running", "waiting"], cursor=page.page.next_cursor)
run = client.runs.cancel(run_id) # idempotent; terminal runs are returned unchanged
tree = client.runs.tree(run_id) # run + descendants snapshot
Human-in-the-loop interactions
# Pending questions raised by a run:
for interaction in run.pending_interactions():
print(interaction.type, interaction.prompt, interaction.payload)
# Respond (variant must match the interaction type):
client.interactions.respond(interaction.id, type="approval", approved=True)
client.interactions.respond(interaction.id, type="text", text="blue")
client.interactions.respond(interaction.id, type="choice", option_ids=["opt_a"])
client.interactions.respond(interaction.id, type="confirmation", confirmed=True)
# ...or pass a prebuilt body:
client.interactions.respond(interaction.id, response={"type": "approval", "approved": False})
# Inbox-style listing:
page = client.interactions.list(status="pending", limit=50)
Public IDs
v2 IDs are <prefix>_<26-char Crockford base32> (run_, wf_, int_, ...).
The SDK accepts raw UUIDs for workflow ids and encodes them client-side:
from splox import encode_id, decode_id
encode_id("wf", "019f455e-a84c-7d4c-87b0-c951d38bc224") # -> "wf_01KX2NXA2C..."
decode_id("wf_01KX2NXA2CFN68FC69A79RQGH4") # -> UUID(...)
Async Support
Every resource has an async twin with the same shape:
import asyncio
from splox import AsyncSploxClient
async def main():
async with AsyncSploxClient(api_key="your-api-key") as client:
run = await client.runs.create("wf_01JAZ6Y5M3Q8F7N2R4T6V9W0XC", "Hello!")
async for event in run.events(): # SSE with auto-reconnect
print(event.type, event.data)
run = await run.wait(timeout=300)
page = await run.messages()
print([m.text for m in page.data])
asyncio.run(main())
Error Handling
All non-2xx v2 responses are RFC 9457 problem+json and map onto a typed
hierarchy; code carries the stable machine-readable error code and
trace_id correlates with server logs.
from splox.exceptions import (
SploxAPIError, # base for HTTP errors (.status_code/.code/.trace_id/.problem)
SploxBadRequestError, # 400
SploxAuthError, # 401
SploxForbiddenError, # 403
SploxNotFoundError, # 404
SploxConflictError, # 409 (idempotency_key_conflict, interaction_not_pending, ...)
SploxGoneError, # 410 (event_cursor_expired, ...)
SploxValidationError, # 422 (.errors = [{name, reason, ...}] with JSON Pointers)
SploxRateLimitError, # 429 (.retry_after)
SploxServerError, # 5xx
SploxTimeoutError, # run.wait()/result() timeouts (also a TimeoutError)
SploxConnectionError, # network failures
SploxStreamError, # SSE stream gave up reconnecting
)
try:
run = client.runs.create(workflow_id, "hi")
except SploxValidationError as e:
for item in e.errors:
print(item["name"], item["reason"])
except SploxRateLimitError as e:
print(f"Rate limited. Retry after: {e.retry_after}")
except SploxAPIError as e:
print(f"API error {e.status_code} ({e.code}): {e.message}")
Retries: GET requests are retried up to 3 times with exponential backoff on
connection errors, 429 and 5xx. POSTs are retried only when they carry an
Idempotency-Key (always true for runs.create and interactions.respond),
reusing the same key so replays are safe.
Discovery & building an agent
client.capabilities() (GET /v2/capabilities) returns everything needed to
assemble a runnable workflow graph: available LLM endpoints (one is marked
is_default — the endpoint new agent nodes get automatically), the default
model, and the MCP tool servers usable in tool nodes (system system:*
servers include their tool list).
caps = client.capabilities()
default_ep = next(e for e in caps.llm_endpoints if e.is_default)
compute = next(s for s in caps.tool_servers if s.id == "system:compute")
print(caps.default_model, default_ep.client, [t.name for t in compute.tools])
# Pick a model from the endpoint's light list, then fetch its parameter schema:
model = default_ep.models[0] # LLMModelSummary(id, name)
schema = next(m for m in client.models(default_ep.id) if m.id == model.id).input_schema
# schema is the JSON Schema of the agent node's "additional_llm_config":
# {"text_llm_model": model.id, "additional_llm_config": {"temperature": 0.2, ...}}
# Build a workflow: an agent wired to compute tools via a tool edge.
wf = client.workflows.create("researcher")
client.workflows.set_graph(
wf.id,
nodes=[
{"id": "agent", "type": "agent", "data": {
"system_prompt": "You are a research assistant.",
# optional — omitted fields fall back to the defaults above:
"text_llm_endpoint_id": default_ep.id,
"text_llm_model": caps.default_model,
}},
{"id": "tools", "type": "tool", "data": {
"mcp_server_id": compute.id, # "system:compute"
"allowed_tools": ["compute_exec", "compute_read_file"],
}},
],
edges=[{"source": "agent", "target": "tools"}], # tool edge (inferred)
)
run = client.runs.create(wf.id, "How many CPUs does this sandbox have?").wait()
Workflow provisioning (v1, unchanged)
Workflow CRUD reads remain available for provisioning:
workflows = client.workflows.list(search="Test")
full = client.workflows.get(workflow_id)
version = client.workflows.get_latest_version(workflow_id)
entry_nodes = client.workflows.get_entry_nodes(version.id)
versions = client.workflows.list_versions(workflow_id)
# plus workflow secrets management: list_secrets / set_env_secret / ...
Chats (client.chats), memory (client.memory), billing (client.billing)
and webhooks (client.events) are also unchanged.
MCP (Model Context Protocol) — unchanged
The MCP module is fully supported and unchanged in this release: catalog, connections, tool execution, OAuth and connection links work exactly as in 0.0.x.
Catalog
# Search the MCP catalog
catalog = client.mcp.list_catalog(search="github", per_page=10)
for server in catalog.mcp_servers:
print(f"{server.name} — {server.url}")
# Get featured servers
featured = client.mcp.list_catalog(featured=True)
# Get a single catalog item
item = client.mcp.get_catalog_item("mcp-server-id")
print(item.name, item.auth_type)
Connections & tools
conns = client.mcp.list_connections()
owner_servers = client.mcp.list_connections(scope="owner_user")
tools = client.mcp.get_server_tools("mcp-server-id")
result = client.mcp.execute_tool(
mcp_server_id="mcp-server-id",
tool_slug="list_servers",
args={"query": "x"},
)
print(result.result.content, result.result.structured_content, result.result.is_error)
client.mcp.delete_connection("connection-id")
Connection Token & Link
from splox import generate_connection_token, generate_connection_link
token = generate_connection_token(
mcp_server_id="mcp-server-id",
owner_user_id="owner-user-id",
end_user_id="end-user-id",
credentials_encryption_key="your-credentials-encryption-key",
)
link = generate_connection_link(
base_url="https://app.splox.io",
mcp_server_id="mcp-server-id",
owner_user_id="owner-user-id",
end_user_id="end-user-id",
credentials_encryption_key="your-credentials-encryption-key",
)
# → https://app.splox.io/tools/connect?token=eyJhbG...
Webhooks
from splox import SploxClient
client = SploxClient() # No API key needed for webhooks
result = client.events.send(
webhook_id="your-webhook-id",
payload={"order_id": "12345", "status": "paid"},
)
print(result.event_id)
Custom Base URL
client = SploxClient(
api_key="your-api-key",
base_url="https://your-self-hosted-instance.com/api/v1",
)
v1 endpoints use the base URL as-is; v2 endpoints (/v2/...) are resolved
against the server origin (the base URL with its /api/v1 suffix stripped).
API Reference
SploxClient / AsyncSploxClient
| Parameter | Type | Default | Description |
|---|---|---|---|
api_key |
str | None |
SPLOX_API_KEY env |
API authentication token |
base_url |
str |
SPLOX_BASE_URL env, then https://splox.io/api/v1 |
API base URL |
timeout |
float |
300.0 |
Request timeout in seconds |
client.runs (v2)
| Method | Description |
|---|---|
create(workflow_id, input, *, metadata=, conversation_id=, workflow_version=, idempotency_key=) |
Create a run; returns a bound Run handle |
get(run_id) |
Get a run |
list(*, status=, workflow_id=, created_after=, created_before=, cursor=, limit=) |
Cursor-paged listing (newest first) |
cancel(run_id) |
Idempotent cancellation |
wait(run_id, *, timeout=, poll_interval=) |
Poll until terminal |
stream_events(run_id, *, cursor=) |
SSE stream with auto-reconnect + dedupe |
list_events(run_id, *, cursor=, limit=) |
Durable JSON event pages |
messages / outputs / tree / usage / pending_interactions |
Run reads |
Run handles expose the same operations instance-bound: run.wait(),
run.cancel(), run.events(), run.messages(), run.outputs(),
run.tree(), run.usage(), run.pending_interactions(), run.refresh().
client.interactions (v2)
| Method | Description |
|---|---|
list(*, status=, run_id=, cursor=, limit=) |
Cursor-paged listing (newest first) |
get(interaction_id) |
Get an interaction |
respond(interaction_id, *, type=, ..., response=, idempotency_key=) |
Resolve a pending interaction |
client.workflows (v1 provisioning reads)
| Method | Description |
|---|---|
list(...) / get(id) |
List/get workflows |
get_latest_version(id) / list_versions(id) |
Version reads |
get_entry_nodes(version_id) |
Entry nodes for a version |
list_secrets / set_env_secret / set_file_secret / delete_secret / ... |
Secrets management |
client.chats, client.memory, client.billing, client.mcp
Unchanged from 0.0.x — see the sections above.
License
MIT
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