https://github.com/bigsk1/litellm-tests
LiteLLM Test Scripts
https://github.com/bigsk1/litellm-tests
Last synced: 3 days ago
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LiteLLM Test Scripts
- Host: GitHub
- URL: https://github.com/bigsk1/litellm-tests
- Owner: bigsk1
- License: mit
- Created: 2025-03-20T07:26:50.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-03-20T08:18:28.000Z (7 months ago)
- Last Synced: 2025-10-04T04:43:55.532Z (3 days ago)
- Language: Python
- Size: 64.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LiteLLM Test Scripts Setup Instructions
This document provides instructions for setting up and running the LiteLLM test scripts.
## Prerequisites
- Python 3.7 or later
- pip (Python package manager)
## Setup Steps
1. **Create a project directory**
```bash
mkdir litellm-tests
cd litellm-tests
```
2. **Create a virtual environment (recommended)**
```bash
python -m venv venv
# Windows
venv\Scripts\activate
# macOS/Linux
source venv/bin/activate
```
3. **Install required packages**
```bash
pip install litellm python-dotenv
```
4. **Create a `.env` file**
Create a file named `.env` in your project directory and add your API keys, add keys and model providers as needed:
```
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
# GOOGLE_API_KEY=your_google_api_key
```
5. **Create a directory for test files**
```bash
mkdir docs
```
6. **Add test files (optional)**
- For long context tests: Add a long text file (e.g., a transcript) in the `docs` folder
- For image tests: Add an image file (e.g., a JPEG) in the `docs` folder
## Running the Test Scripts
Place each of the test scripts in your project directory and run them individually:
```bash
python basic-completion.py
python system-message-test.py
python long-context-test.py
python streaming-test.py
python tool-calling-test.py
python image-input-test.py
```
## Modifying the Scripts
- To test different models, update the `models` list in each script
- Adjust the parameters (e.g., temperature, max_tokens) according to your requirements
- For the long context test, update the file path in the script to your text file
## Troubleshooting
- If you encounter API key errors, check that your `.env` file is correctly formatted and the keys are valid
- For context length errors, try using a smaller text file or a model with a larger context window
- For image input errors, ensure your image file exists and is in a supported format (JPEG, PNG)
## Additional Features to Test
The scripts cover the main features mentioned in the transcript:
- Basic completion
- System messages
- Long context
- Streaming
- Tool calling
- Image input
If you want to test additional features:
- Modify parameters (temperature, top_p, etc.)
- Test with different prompts
- Try different model versions