removed torch from requirement lightrag server
Browse files- README.md +3 -0
- lightrag/api/requirements.txt +0 -1
- lightrag/llm/hf.py +6 -43
README.md
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@@ -246,6 +246,9 @@ rag = LightRAG(
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<summary> Using Hugging Face Models </summary>
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* If you want to use Hugging Face models, you only need to set LightRAG as follows:
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```python
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from lightrag.llm import hf_model_complete, hf_embed
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from transformers import AutoModel, AutoTokenizer
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<summary> Using Hugging Face Models </summary>
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* If you want to use Hugging Face models, you only need to set LightRAG as follows:
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See lightrag_hf_demo.py
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```python
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from lightrag.llm import hf_model_complete, hf_embed
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from transformers import AutoModel, AutoTokenizer
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lightrag/api/requirements.txt
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python-multipart
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tenacity
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tiktoken
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torch
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uvicorn
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python-multipart
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tenacity
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tiktoken
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uvicorn
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lightrag/llm/hf.py
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"""
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Hugging face LLM Interface Module
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==========================
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This module provides interfaces for interacting with Hugging face's language models,
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including text generation and embedding capabilities.
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Author: Lightrag team
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Created: 2024-01-24
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License: MIT License
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Copyright (c) 2024 Lightrag
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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Version: 1.0.0
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Change Log:
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- 1.0.0 (2024-01-24): Initial release
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* Added async chat completion support
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* Added embedding generation
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* Added stream response capability
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Dependencies:
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- transformers
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- numpy
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- pipmaster
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- Python >= 3.10
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Usage:
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from llm_interfaces.hf import hf_model_complete, hf_embed
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"""
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__version__ = "1.0.0"
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__author__ = "lightrag Team"
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__status__ = "Production"
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import copy
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import os
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import pipmaster as pm # Pipmaster for dynamic library install
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# install specific modules
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pm.install("torch")
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if not pm.is_installed("tenacity"):
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pm.install("tenacity")
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from functools import lru_cache
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from tenacity import (
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retry,
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stop_after_attempt,
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import copy
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import os
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from functools import lru_cache
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import pipmaster as pm # Pipmaster for dynamic library install
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# install specific modules
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pm.install("torch")
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if not pm.is_installed("tenacity"):
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pm.install("tenacity")
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if not pm.is_installed("numpy"):
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pm.install("numpy")
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if not pm.is_installed("tenacity"):
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pm.install("tenacity")
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from tenacity import (
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retry,
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stop_after_attempt,
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