Build Your Own Private Knowledge Base with Cloud Studio DeepSeek R1 in Minutes

What is a Knowledge Base?

A knowledge base is a system for storing structured and unstructured information—documents, FAQs, rules, case studies—so that users or applications can quickly retrieve relevant content.

Why Build a Personal Knowledge Base?

Systematic organization : Centralizes scattered knowledge and enables classification and tagging.

Efficiency boost : Fast search reduces time spent locating information and avoids duplicated effort.

Continuous learning : Records solutions and experiences, allowing the base to evolve with new insights.

Team collaboration : Shares knowledge across members, lowering communication overhead.

Retrieval‑Augmented Generation (RAG)

RAG enhances large language models (LLMs) by providing an external knowledge base that the model can consult when answering questions, resulting in more accurate and relevant responses.

Why Use RAG Even With a Powerful LLM?

The model’s training data is limited and may lack proprietary or domain‑specific information.

Fine‑tuning on specialized data is costly and may not yield optimal results.

Without external grounding, LLMs can generate hallucinated answers, which is unacceptable for enterprise use.

Typical RAG Workflow

Step‑by‑Step Setup in Cloud Studio DeepSeek‑R1 Template

Step 1 – Open the DeepSeek CPU Template

Visit https://ide.cloud.tencent.com/dashboard/ and select any DeepSeek CPU template. The workspace automatically launches either AnythingLLM (default on port 4001) or Open‑WebUI, giving you an instant personal knowledge base.

Step 2 – Build the Knowledge Base

2.1 Using AnythingLLM

Create a new workspace.

Upload local documents or provide web links.

Close the settings panel to start chatting.

2.2 Using Open‑WebUI

Configure the model engine:

Open Settings → Admin Settings → Documents → Model Engine.

Set the semantic vector model engine to Ollama and choose the deepseek‑r1 model.

Save the configuration.

Then create a knowledge base:

Navigate to the workspace, click Knowledge Base , and press the “+” button.

Upload files or drag‑and‑drop documents.

Return to the chat window, type “#”, select the newly created knowledge base, and start querying.

Result Example

Using a sample “Micro‑Drama Industry Deep Analysis Report” as the source document, both AnythingLLM and Open‑WebUI return precise answers that cite the document content.

Conclusion

The DeepSeek‑R1 CPU template in Cloud Studio includes built‑in RAG components, allowing users to create a private knowledge base without manual infrastructure setup, thereby lowering the entry barrier for AI‑augmented information retrieval.