Quickstart

This guide will walk you through making your first Profy API call in 5 minutes.

Prerequisites

A Profy account (register at app.profy.cn)
Python 3.8+ or Node.js 18+ (if using the SDK)

Step 1: Get an API Key

Log in at app.profy.cn
Visit platform.profy.cn (shares login session with the main site)
Go to the API Keys page
Click Create API Key, enter a name, and select permission scopes
Copy the generated key (prefixed with sk-pro-)

The API Key is displayed only once at creation time. Save it immediately in a secure location. If lost, you will need to create a new one.

Step 2: Make Your First Call

Choose your preferred method:

Python SDK
TypeScript SDK
curl

Install the SDK:

pip install profy

Call an Expert:

import asyncio
from profy import Profy

async def main():
    async with Profy(api_key="sk-pro-your-key-here") as client:
        # Call an Expert
        result = await client.agents.run(
            "profy",        # Expert identifier
            "用一句话介绍你自己"  # Message content
        )
        print(result.text)
        print(f"Model: {result.model}")
        print(f"Elapsed: {result.elapsed_sec}s")

asyncio.run(main())

If you prefer synchronous code:

from profy import ProfySync

with ProfySync(api_key="sk-pro-your-key-here") as client:
    result = client.agents.run("profy", "用一句话介绍你自己")
    print(result.text)

Install the SDK:

npm install @profy-ai/sdk

Call an Expert:

import { Profy } from "@profy-ai/sdk";

const client = new Profy({ apiKey: "sk-pro-your-key-here" });

const result = await client.agents.run(
  "profy",        // Expert identifier
  "用一句话介绍你自己"  // Message content
);

console.log(result.text);
console.log(`Model: ${result.model}`);
console.log(`Elapsed: ${result.elapsedMs}ms`);

curl -X POST https://api.profy.cn/v1/agents/run \
  -H "Authorization: Bearer sk-pro-your-key-here" \
  -H "Content-Type: application/json" \
  -d '{
    "expert_identifier": "profy",
    "message": "用一句话介绍你自己"
  }'

The response is an SSE (Server-Sent Events) stream:

event: run.created
data: {"type":"run.created","event_id":1}

event: run.in_progress
data: {"type":"run.in_progress","model_name":"deepseek-v3","session_id":"abc123","event_id":2}

event: output.text.delta
data: {"type":"output.text.delta","delta":"你好","event_id":3}

event: output.text.delta
data: {"type":"output.text.delta","delta":"！我是","event_id":4}

event: run.completed
data: {"type":"run.completed","event_id":5}

data: [DONE]

Step 3: Stream Responses

For scenarios that require real-time display of AI output, use streaming mode:

import asyncio
from profy import Profy

async def main():
    async with Profy(api_key="sk-pro-your-key-here") as client:
        async for chunk in client.agents.run_stream("profy", "写一首关于编程的诗"):
            if chunk.type == "output.text.delta":
                print(chunk.delta, end="", flush=True)
            elif chunk.type == "tool_call.created":
                print(f"\n[Tool call: {chunk.raw.get('tool_name')}]")
            elif chunk.type == "run.completed":
                print("\n[Done]")

asyncio.run(main())

import { Profy } from "@profy-ai/sdk";

const client = new Profy({ apiKey: "sk-pro-your-key-here" });

for await (const chunk of client.agents.runStream("profy", "写一首关于编程的诗")) {
  if (chunk.type === "output.text.delta") {
    process.stdout.write(chunk.delta ?? "");
  } else if (chunk.type === "tool_call.created") {
    console.log(`\n[Tool call: ${chunk.toolName}]`);
  } else if (chunk.type === "run.completed") {
    console.log("\n[Done]");
  }
}

Step 4: Multi-Turn Conversations

Pass a session_id to continue the same conversation:

async with Profy(api_key="sk-pro-your-key-here") as client:
    # First turn
    r1 = await client.agents.run("profy", "我叫小明")
    print(r1.text)
    session_id = r1.session_id

    # Second turn — the Expert remembers your name
    r2 = await client.agents.run(
        "profy", "你还记得我叫什么吗？",
        session_id=session_id
    )
    print(r2.text)

const client = new Profy({ apiKey: "sk-pro-your-key-here" });

// First turn
const r1 = await client.agents.run("profy", "我叫小明");
console.log(r1.text);

// Second turn — the Expert remembers your name
const r2 = await client.agents.run("profy", "你还记得我叫什么吗？", {
  sessionId: r1.sessionId,
});
console.log(r2.text);

Understanding SSE Events

/v1/agents/run returns a standard SSE event stream. Here are the core event types you will encounter:

Event	Description
`run.created`	Request received; processing started
`run.in_progress`	Agent started running; includes `model_name` and `session_id`
`output.text.delta`	Incremental text output; `delta` field contains the new text fragment
`tool_call.created`	Agent started calling a tool
`tool_call.completed`	Tool call completed
`run.completed`	Agent run completed
`run.failed`	Run failed; `message` field contains the error details

For the full event type list, see Agents Run API.

Using Chat Completions

If you are already using the OpenAI API, you can switch directly to Profy’s compatible endpoint:

Call a raw model
Call an Expert via OpenAI SDK

async with Profy(api_key="sk-pro-your-key-here") as client:
    resp = await client.chat.completions.create(
        model="deepseek-v3",
        messages=[{"role": "user", "content": "Hello"}],
    )
    print(resp.text)

const client = new Profy({ apiKey: "sk-pro-your-key-here" });

const resp = await client.chat.completions.create({
  model: "deepseek-v3",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(resp.text);

Use the profy-<identifier> model name format to call a Profy Expert directly with the standard OpenAI SDK:

from openai import OpenAI

client = OpenAI(
    api_key="sk-pro-your-key-here",
    base_url="https://api.profy.cn/v1",
)

response = client.chat.completions.create(
    model="profy-financial-advisor",
    messages=[{"role": "user", "content": "Analyze Tesla's investment value"}],
    stream=True,
)

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

Next Steps

Authentication Guide

Learn more about API Key and OAuth usage

Agents Run API

View the complete Expert invocation API documentation

Python SDK

Complete Python SDK guide

TypeScript SDK

Complete TypeScript SDK guide

Overview

Platform API

Authentication & Keys

Integrations

SDK

Cookbook

Reference

Prerequisites

Step 1: Get an API Key

Step 2: Make Your First Call

Step 3: Stream Responses

Step 4: Multi-Turn Conversations

Understanding SSE Events

Using Chat Completions

Next Steps

Authentication Guide

Agents Run API

Python SDK

TypeScript SDK

​Prerequisites

​Step 1: Get an API Key

​Step 2: Make Your First Call

​Step 3: Stream Responses

​Step 4: Multi-Turn Conversations

​Understanding SSE Events

​Using Chat Completions

​Next Steps

Authentication Guide

Agents Run API

Python SDK

TypeScript SDK

Prerequisites

Step 1: Get an API Key

Step 2: Make Your First Call

Step 3: Stream Responses

Step 4: Multi-Turn Conversations

Understanding SSE Events

Using Chat Completions

Next Steps