Quickstart
Get a response from an LLM in under two minutes.
Prerequisites
A PromptShuttle account at app.promptshuttle.com
An API key (see Authentication)
Option 1: OpenAI-compatible endpoint
If you already use the OpenAI SDK, just swap the base URL and key:
curl https://app.promptshuttle.com/api/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-4o",
"messages": [
{"role": "user", "content": [{"type": "text", "text": "Say hello!"}]}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://app.promptshuttle.com/api/v1",
api_key="YOUR_API_KEY",
)
response = client.chat.completions.create(
model="openai/gpt-4o",
messages=[{"role": "user", "content": "Say hello!"}],
)
print(response.choices[0].message.content)The response follows the standard OpenAI chat completion format. See the full endpoint reference for all options.
Option 2: Create and run a flow
Flows let you version your prompts, add parameters, and route across environments.
1. Create a flow
In the PromptShuttle UI, click Flows > Create Flow. Give it a title (e.g. "Product Description Generator") — a slug name is auto-generated.
2. Edit the template
In the flow editor, write your prompt template:
Parameters use double square brackets: [[parameter_name]]. PromptShuttle auto-detects them.
Select a model (e.g. openai/gpt-4o) and save.
3. Activate for an environment
Go to the flow's environment settings and activate your version for an environment (e.g. production).
4. Execute via API
The response includes the LLM output, token usage, cost, and any warnings about unresolved parameters. See Flow Execution API for the full reference.
Next steps
Authentication — API keys and bearer tokens
Key Concepts — Flows, templates, tools, environments
OpenAI-Compatible Endpoint — Full reference for the drop-in endpoint
Streaming — Real-time SSE events for agent execution
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