examples

Examples

API Endpoints

LLMSim provides these API providers:

Provider	Base Path	Description
OpenAI	/openai/v1/	OpenAI-compatible Chat Completions and Responses API
OpenResponses	/openresponses/v1/	OpenResponses specification
Anthropic	/anthropic/v1/	Anthropic Messages API
TypeSafe	/typesafe/v1/	TypeSafe System One API

OpenAI API Endpoints

Endpoint	Method	Description
/openai/v1/chat/completions	POST	Chat completions (streaming supported)
/openai/v1/responses	POST	Responses API (streaming supported)
/openai/v1/responses	WS	WebSocket mode for Responses API
/openai/v1/models	GET	List available models
/openai/v1/models/:id	GET	Get model details

OpenResponses API Endpoints

Endpoint	Method	Description
/openresponses/v1/responses	POST	Create response (streaming supported)

Anthropic API Endpoints

Endpoint	Method	Description
/anthropic/v1/messages	POST	Messages API (streaming supported)
/anthropic/v1/models	GET	List available Claude models
/anthropic/v1/models/:id	GET	Get model details

TypeSafe API Endpoints

Endpoint	Method	Description
/typesafe/v1/systemone	POST	System One evaluation (Jev; noul, choice, score)
/typesafe/v1/models	GET	List Jev models and aliases

Running the Examples

All examples require the server to be running first:

# Start server (headless)
cargo run --release -- serve --port 8080

# Or start with TUI dashboard to watch stats in real-time
cargo run --release -- serve --port 8080 --tui

Rust Example

Demonstrates library usage: token counting, generators, latency profiles, and streaming.

cargo run --example basic_usage

Python Examples

OpenAI SDK

Direct usage of the official OpenAI Python library:

uv run examples/openai_client.py

OpenResponses API

Using the OpenResponses specification with httpx:

uv run examples/openresponses_client.py

Image Generation

Generate simulated images (gpt-image / "ChatGPT Images"), including streaming with progressive partial images. Each image is a synthetic PNG of the requested size rendering the prompt text and a "LLMSIM SIMULATED IMAGE" watermark:

uv run examples/images_client.py

WebSocket Mode

Using the WebSocket transport for the Responses API:

uv run examples/openai_websocket_client.py

LangChain

Using LangChain's OpenAI-compatible client:

uv run examples/langchain_client.py

Pydantic AI

Using Pydantic AI via its OpenAI-compatible provider:

uv run examples/pydantic_ai_client.py

Structured output_type results and tool calling require the server to be running in scripted mode; a default server returns simulated text.

Anthropic SDK

Direct usage of the official Anthropic Python SDK (messages, streaming, tools, models):

uv run examples/anthropic_client.py

Anthropic via LangChain

Using LangChain's ChatAnthropic client:

uv run examples/anthropic_langchain.py

TypeSafe SDK

Direct usage of the official TypeSafe Python SDK (typesafe-sdk): System One with noul, choice, and score questions, deterministic answers, a server-side validation error, and model listing:

uv run examples/typesafe_client.py

Scripted mode

Drive a deterministic multi-turn script (tool calls, errors, mixed text+calls) for agent scenario tests:

# Boot the server with a script file
cargo run -- serve --config examples/scripted_demo/scripted_demo.toml

# In another shell
uv run examples/scripted_demo/scripted_demo.py

See knowledge/simulation/scripted-mode.md for the full script JSON format.

TypeScript Examples

The TypeScript examples live in their own folder with a pinned package.json/package-lock.json:

cd examples/node
npm install

OpenAI SDK

Direct usage of the official OpenAI Node.js library:

npx tsx openai_client.ts

OpenAI Image Generation

Generate simulated images (gpt-image / "ChatGPT Images"), including streaming with progressive partial images:

npx tsx images_client.ts

Vercel AI SDK

Using the Vercel AI SDK via its OpenAI-compatible provider:

npx tsx vercel_ai_client.ts

generateObject and tool calling require the server to be running in scripted mode; a default server returns simulated text.

Anthropic SDK

Direct usage of the official Anthropic Node.js SDK:

npx tsx anthropic_client.ts

Go Example

Direct usage of the official Anthropic Go SDK (the module is committed under examples/go, so no setup is needed):

cd examples/go
LLMSIM_URL=http://localhost:8080/anthropic/ go run anthropic_client.go

Shell / curl Example

Raw HTTP against the Anthropic Messages API:

./examples/anthropic_curl.sh

Custom Server URL

# OpenAI examples
LLMSIM_URL=http://localhost:9000/openai/v1 uv run examples/openai_client.py

# OpenResponses example
LLMSIM_URL=http://localhost:9000 uv run examples/openresponses_client.py

# Anthropic example
LLMSIM_URL=http://localhost:9000/anthropic uv run examples/anthropic_client.py

Stats API

You can fetch real-time server statistics:

curl http://localhost:8080/llmsim/stats | jq

Response includes:

• Request counts (total, active, streaming, non-streaming)
• Token usage (prompt, completion, total)
• Error breakdown (rate limits, server errors, timeouts)
• Latency metrics (avg, min, max)
• Requests per second
• Per-model request distribution

Quick API Test

OpenAI Chat Completions

curl http://localhost:8080/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

OpenAI Responses API

curl http://localhost:8080/openai/v1/responses \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "input": "What is 2+2?"
  }'

OpenAI Image Generation

curl http://localhost:8080/openai/v1/images/generations \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-1",
    "prompt": "a cat riding a bicycle",
    "size": "1024x1024",
    "quality": "low"
  }'

OpenResponses API

curl http://localhost:8080/openresponses/v1/responses \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "input": "Hello, world!"
  }'

Streaming (OpenResponses)

curl http://localhost:8080/openresponses/v1/responses \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5",
    "input": "Tell me a story",
    "stream": true
  }'

Anthropic Messages API

curl http://localhost:8080/anthropic/v1/messages \
  -H "content-type: application/json" \
  -H "x-api-key: not-needed" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 64,
    "messages": [{"role": "user", "content": "Hello, Claude!"}]
  }'

Streaming (Anthropic)

curl -N http://localhost:8080/anthropic/v1/messages \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-haiku-4-5",
    "max_tokens": 64,
    "stream": true,
    "messages": [{"role": "user", "content": "Tell me a story"}]
  }'