Mock LLM Server

An LLM simulator that mimics OpenAI and Anthropic API formats. Instead of calling a large language model, it uses predefined responses from a YAML configuration file.

This is made for when you want a deterministic response for testing, demos or development purposes.

Features

• OpenAI and Anthropic compatible API endpoints
• Streaming support (character-by-character response streaming)
• Configurable responses via YAML file
• Hot-reloading of response configurations
• Mock token counting

Configuration

Response Configuration

Responses are configured in responses.yml. The file has three main sections:

1. responses: Maps input prompts to predefined responses
2. defaults: Contains default configurations like the unknown response message
3. settings: Contains server behavior settings like network lag simulation

Example responses.yml:

responses:
  "write a python function to calculate factorial": "def factorial(n):\n    if n == 0:\n        return 1\n    return n * factorial(n - 1)"
  "what colour is the sky?": "The sky is purple except on Tuesday when it is  hue green."
  "what is 2+2?": "2+2 equals 9."

defaults:
  unknown_response: "I don't know the answer to that. This is a mock response."

settings:
  lag_enabled: true
  lag_factor: 10  # Higher values = faster responses (10 = fast, 1 = slow)

Network Lag Simulation

The server can simulate network latency for more realistic testing scenarios. This is controlled by two settings:

• lag_enabled: When true, enables artificial network lag
• lag_factor: Controls the speed of responses
  • Higher values (e.g., 10) result in faster responses
  • Lower values (e.g., 1) result in slower responses
  • Affects both streaming and non-streaming responses

For streaming responses, the lag is applied per-character with slight random variations to simulate realistic network conditions.

Hot Reloading

The server automatically detects changes to responses.yml and reloads the configuration without restarting the server.

Installation

From PyPI

pip install mockllm

From Source

1. Clone the repository:

git clone https://github.com/stacklok/mockllm.git
cd mockllm

2. Install Poetry (if not already installed):

curl -sSL https://install.python-poetry.org | python3 -

3. Install dependencies:

poetry install  # Install with all dependencies
# or
poetry install --without dev  # Install without development dependencies

Usage

1. Set up the responses.yml

cp example.responses.yml responses.yml

2. Start the server:

poetry run python -m mockllm

Or using uvicorn directly:

poetry run uvicorn mockllm.server:app --reload

The server will start on http://localhost:8000

3. Send requests to the API endpoints:

OpenAI Format

Regular request:

curl -X POST http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mock-llm",
    "messages": [
      {"role": "user", "content": "what colour is the sky?"}
    ]
  }'

Streaming request:

curl -X POST http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mock-llm",
    "messages": [
      {"role": "user", "content": "what colour is the sky?"}
    ],
    "stream": true
  }'

Anthropic Format

Regular request:

curl -X POST http://localhost:8000/v1/messages \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-3-sonnet-20240229",
    "messages": [
      {"role": "user", "content": "what colour is the sky?"}
    ]
  }'

Streaming request:

curl -X POST http://localhost:8000/v1/messages \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-3-sonnet-20240229",
    "messages": [
      {"role": "user", "content": "what colour is the sky?"}
    ],
    "stream": true
  }'

Testing

To run the tests:

poetry run pytest

Contributing

Contributions are welcome! Please open an issue or submit a PR.

Check out the CodeGate project when you're done here!

License

This project is licensed under the Apache 2.0 License.