Is Archive Agent a chatbot?
No. Archive Agent is a file indexer and RAG engine that provides answers through a CLI, GUI, or MCP interface — it does not offer a conversational chatbot interface.
@shredEngineer
基本信息
Find your files with natural language and ask questions.
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Archive Agent is an intelligent file indexer that brings RAG (Retrieval Augmented Generation) to your command line. It indexes local documents (PDFs, images, Markdown, plaintext, and more) using automatic OCR, semantic chunking, and a local Qdrant vector database, then lets you search or query those files with natural language. It integrates with AI tools via a built-in MCP server — it is not a chatbot.
First, install Docker and Python ≥3.10, then run git clone, cd Archive-Agent, chmod +x install.sh, ./install.sh. The script sets up a Python environment, installs dependencies, and deploys a Qdrant Docker container. After installation, configure an AI provider (OpenAI, OpenRouter, Ollama, or LM Studio) and run archive-agent to use the CLI (track, commit, search, query, GUI) or start the MCP server (archive-agent mcp).
No. Archive Agent is a file indexer and RAG engine that provides answers through a CLI, GUI, or MCP interface — it does not offer a conversational chatbot interface.
OpenAI (or any OpenAI‑compatible API), OpenRouter (access to 400+ models), Ollama, and LM Studio. Local providers (Ollama/LM Studio) offer best privacy; remote APIs often give higher performance.
No. The embeddings generated by one provider are incompatible with another. To switch providers, you must create a new profile.
Not for core indexing and querying if you use a local LLM (Ollama/LM Studio) and the local Qdrant database. However, installation and initial setup (e.g., downloading models) typically require internet.
Archive Agent natively ingests PDFs, images (with automatic OCR), Markdown, plaintext, and several other formats. Files are selected for tracking using pattern‑based inclusion/exclusion rules.

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