feat: RAG-Anything runs offline
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docs/offline_setup.md
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docs/offline_setup.md
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# Running RAG-Anything in an Offline Environment
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This document explains a critical consideration for running the RAG-Anything project in an environment with no internet access.
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## The Network Dependency: `LightRAG` and `tiktoken`
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The `RAGAnything` core engine relies on the `LightRAG` library for its primary functionality. `LightRAG`, in turn, uses OpenAI's `tiktoken` library for text tokenization.
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By default, the `tiktoken` library has a network dependency. On its first use, it attempts to download tokenizer models from OpenAI's public servers (`openaipublic.blob.core.windows.net`). If the application is running in an offline or network-restricted environment, this download will fail, causing the `LightRAG` instance to fail to initialize.
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This results in an error similar to the following:
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```
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Failed to initialize LightRAG instance: HTTPSConnectionPool(host='openaipublic.blob.core.windows.net', port=443): Max retries exceeded with url: /encodings/o200k_ba
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```
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This dependency is indirect. The `RAG-Anything` codebase itself does not directly import or call `tiktoken`. The call is made from within the `lightrag` library.
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## The Solution: Using a Local `tiktoken` Cache
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To resolve this issue and enable fully offline operation, you must provide a local cache for the `tiktoken` models. This is achieved by setting the `TIKTOKEN_CACHE_DIR` environment variable.
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When this environment variable is set, `tiktoken` will look for its model files in the specified local directory instead of attempting to download them from the internet.
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### Steps to Implement the Solution:
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1. **Create a Model Cache:** In an environment *with* internet access, run a simple Python script to download and cache the necessary `tiktoken` models.
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```python
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import tiktoken
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import os
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# Define the directory where you want to store the cache
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cache_dir = "./tiktoken_cache"
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if "TIKTOKEN_CACHE_DIR" not in os.environ:
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os.environ["TIKTOKEN_CACHE_DIR"] = cache_dir
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# Create the directory if it doesn't exist
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if not os.path.exists(cache_dir):
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os.makedirs(cache_dir)
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print("Downloading and caching tiktoken models...")
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tiktoken.get_encoding("cl100k_base")
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# tiktoken.get_encoding("p50k_base")
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print(f"tiktoken models have been cached in '{cache_dir}'")
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```
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2. **Deploy the Cache:** Copy the created `tiktoken_cache` directory to the machine where you will be running the `RAG-Anything` application.
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By following these steps, you can eliminate the network dependency and run the `RAG-Anything` project successfully in a fully offline environment.
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scripts/create_tiktoken_cache.py
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scripts/create_tiktoken_cache.py
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import tiktoken
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import os
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# Define the directory where you want to store the cache
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cache_dir = "./tiktoken_cache"
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if "TIKTOKEN_CACHE_DIR" not in os.environ:
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os.environ["TIKTOKEN_CACHE_DIR"] = cache_dir
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# Create the directory if it doesn't exist
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if not os.path.exists(cache_dir):
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os.makedirs(cache_dir)
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print("Downloading and caching tiktoken models...")
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tiktoken.get_encoding("cl100k_base")
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# tiktoken.get_encoding("p50k_base")
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print(f"tiktoken models have been cached in '{cache_dir}'")
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