GopherDigest FAQs

Question 1

What is GopherDigest?

Accepted Answer

GopherDigest is an MCP server tool that uses a local Ollama LLM to extract key facts from conversation transcripts and seamlessly merge them into a GopherCache `context.json` file, enriching your knowledge base.

Question 2

How does GopherDigest utilize LLMs?

Accepted Answer

It integrates with a local Ollama instance (e.g., using the `llama3.2` model) to process conversation transcripts, ensuring fact extraction is performed privately on your own infrastructure.

Question 3

Can I review extracted facts before saving them?

Accepted Answer

Yes, GopherDigest offers a `summarize_only` tool that allows you to preview the extracted facts as raw JSON text without modifying any persistent storage, providing a safe way to verify results.

Question 4

What are the core requirements to run GopherDigest?

Accepted Answer

To run GopherDigest, you need Python 3.10+, a local Ollama instance running on `http://localhost:11434`, and the `llama3.2` model pulled and available in Ollama.

Question 5

What is the primary benefit of using GopherDigest?

Accepted Answer

The main benefit is automated, private knowledge management. It streamlines the process of extracting critical information from conversations and integrating it into your GopherCache, making your knowledge base more dynamic and intelligent.

GopherDigest

주요 기능

사용 사례

GopherDigest

주요 기능

사용 사례