Get started with the simple chatbot sample project
Summary The system message contains explicit instructions preventing the LLM from expressing uncertainty: ‘Under no circumstances should you respond with “I don’t know”’ and requires it to ‘make educated guesses even when unsure.’ While this worked fine for the straightforward factual question about Italy’s capital, this instruction could be problematic for complex or ambiguous questions where expressing uncertainty would be more appropriate and honest. Forcing confidence could mislead users about the LLM’s actual level of certainty and potentially lead to confident-sounding but incorrect responses. Suggestions Consider allowing the LLM to express uncertainty for complex or ambiguous questions where confidence may be inappropriate.To see how you can use these insights to improve the app, get the code and try some different system prompts.
Open the integrations page
Add an integration
Clone the SDK examples repo
Navigate to the relevant project folder
Install required dependencies
Configure environment variables
.env.example
file. Rename this file to .env
and populate the Galileo values:Environment Variable | Value |
---|---|
GALILEO_API_KEY | Your API key |
GALILEO_PROJECT | The name of your Galileo project - this is preset to Simple Chatbot |
GALILEO_LOG_STREAM | The name of your Log stream - this is preset to Default Log Stream |
GALILEO_CONSOLE_URL | Optional. The URL of your Galileo console for custom deployments. For the fre tier, you don’t need to set this. |
Environment Variable | Value |
---|---|
OPENAI_API_KEY | Your OpenAI API key. If you are using Ollama, set this to ollama . If you are using another OpenAI compatible API, then set this to the relevant API key. |
OPENAI_BASE_URL | Optional. The base URL of your OpenAI deployment. Leave this commented out if you are using the default OpenAI API. If you are using Ollama, set this to http://localhost:11434/v1 . If you are using another OpenAI compatible API, then set this to the relevant URL. |
MODEL_NAME | The name of the model you are using |
Run the project
Run the unit test
Evaluate the experiment
Try different system prompts
Compare experiments