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Helpful Link

https://blog.logrocket.com/building-ai-agent-frontend-project/?ref=dailydev

https://baseai.dev/docs/guides/using-ollama-models

https://langbase.com/settings/keys

https://langbase.com/luisvalgoi/faqs-generator

Explaining BaseAi Commands

  • npx baseai@latest auth: Authenticate using BaseAI.

  • npx baseai@latest init: Initializing a BaseAI project.

  • npx baseai@latest pipe: Creating a Pipeline for the project using BaseAI.

  • npx baseai@latest memory: Creating a Memory for the project using BaseAI.

  • npx baseai@latest embed -m <memory_name>: Creating a Memory Embedding

  • npx baseai@latest dev: Running the Server Agents.

  • npx baseai@latest deploy: Deplying into BaseAI Studio.

Running the Server

  • npx tsx index.ts: Running the Server Agents with a minimal example.

  • npx tsx index-rag.ts: Running the Server Agents with a minimal RAG example.

Running Models Locally with Ollama

  • ollama run deepseek-r1:7b: Running DeepSeekR1 Model

  • http://localhost:11434: Any model once is ran with Ollama, will be pushed into this port

Configuring Model

  • /set temperature: Defining the model's criativity level (0 = factual. 1 = creative)

  • /set system: Defining the base instructions.

Running App Flow

  • npx baseai@latest dev: Spinning up the Server Agents.

  • npx tsx index-rag.ts: Running the Server Agents with a minimal RAG example.

  • npm run dev: Running the client pointing to the deployed langbase pipe.

  • ollama run deepseek-r1:7b: Run Ollama Model: If you want to bind the Server Agents with a local model.

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Repo for playing with custom AI Agents deployed to Langbase with a client consuming it

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