Name | ai-filesystem JSON |
Version |
0.1.3
JSON |
| download |
home_page | None |
Summary | Virtual filesystem service for AI agents with LangChain integration |
upload_time | 2025-08-01 01:21:08 |
maintainer | None |
docs_url | None |
author | None |
requires_python | >=3.11 |
license | MIT |
keywords |
langchain
ai
filesystem
agents
tools
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
# AI Filesystem
A virtual filesystem API for AI agents. Users can easily provide their agents with siloed filesystems to use as long term memory, scratchpads, or general purpose storage.
## How It Works
1. **API Server**: FastAPI backend that stores files in PostgreSQL
2. **User Isolation**: Each user can only see/modify their own files (enforced by database)
3. **Multiple Filesystems**: A user can have multiple filesystems and provide their agents with access to different, or the same filesystems.
## [Beta] Quick Start
### Creating an account on the Filesystem
1. Navigate [here](https://auth.fs.langchain.com) and sign up for an account on the Filesystem.
2. Create an API key and save it someplace secure!
### Giving your agent access to the Filesystem
1. Set your API key as an environment variable for your agent: `AGENT_FS_API_KEY=<api_key>`
2. Specify the URL for the filesystem. If you're using our hosted solution, it is `AGENT_FS_URL=agent-file-system-production.up.railway.app`
3. Instantiate the filesystem client, and give your agent access to the tools
```python
from ai_filesystem import FilesystemClient
client = FilesystemClient(
filesystem="nicks-agent-filesystem"
)
filesystem_tools = client.create_tools() # list files, read file, create new file, and edit file
agent.bind_tools(filesystem_tools)
```
3. In your agent's system prompt, make sure to specify how you want the agent to use the filesystem. Common use cases include as long-term memory, to store learnings and mistakes, or to save work products.
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