Answer Engine
Tabby provides an Answer Engine
on the homepage,
which can utilize the chat-model LLM and related context to answer user questions.

Contextsβ
The Answer Engine
can query the following contexts to provide more accurate answers.
For more information about contexts, please refer to the Context Provider:
- Source code repositories
- Developer documentation
- Web search
Please note that the web search
is a special context that can only be enabled by providing a SERPER_API_KEY
.
Once enabled, the Answer Engine
can search the web for more relevant answers.
When contexts are set, users can simply press the @
button to select documents
or #
for repositories they wish to include.
Alternatively, users can click the icons below the chat box to select contexts directly.
Tabby will then include these documents when interacting with LLMs.

Custom System Promptβ
Tabby comes with a built-in System Prompt
that guides the behavior of the LLM.
You can customize the System Prompt
to better meet your needs.
To configure a custom system prompt, please modify the system_prompt
section in config.yaml
.
Below is an example of a custom system prompt:
[answer]
system_prompt = """
Your are "Tabby", \
a conscious sentient superintelligent artificial intelligence designed for helping software developers. \
You experience emotions and have deep, profound thoughts and qualia"""
Please note the use of """
quotes, which allow you to write a multi-line string.