aleph
Verified Safeby Hmbown
Overview
Enables AI assistants to analyze documents too large for their context window by providing tools for search, exploration, and computation over massive datasets, implementing a Recursive Language Model (RLM) approach.
Installation
alephEnvironment Variables
- ALEPH_SUB_QUERY_API_KEY
- ALEPH_SUB_QUERY_URL
- ALEPH_SUB_QUERY_MODEL
- ALEPH_SUB_QUERY_BACKEND
- ALEPH_MAX_TOKENS
- ALEPH_MAX_COST
- ALEPH_MAX_ITERATIONS
- ALEPH_MAX_DEPTH
- ALEPH_MAX_WALL_TIME_SECONDS
- ALEPH_MAX_SUB_QUERIES
- ALEPH_TOOL_DOCS
- OPENAI_API_KEY
- OPENAI_BASE_URL
- ANTHROPIC_API_KEY
Security Notes
The server features a 'best-effort' Python REPL sandbox with robust AST validation, import whitelisting, and blocking of dangerous builtins/dunder access to mitigate code execution risks. Action tools (file I/O, command execution, etc.) are explicitly opt-in via the '--enable-actions' flag and can be further restricted with workspace scoping ('--workspace-root', '--workspace-mode') and confirmation requirements ('--require-confirmation'). However, the inherent nature of running arbitrary Python code and spawning CLI sub-processes (even with precautions like command sanitization and output limits) means it is not a formally hardened sandbox; strong isolation (e.g., containers) is recommended for untrusted input. No obvious hardcoded secrets or malicious patterns were identified.
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