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Refactor code formatting in lightrag_api_openai_compatible_demo.py
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@ -85,9 +85,7 @@ class LightRAG:
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# LLM
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llm_model_func: callable = gpt_4o_mini_complete # hf_model_complete#
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llm_model_name: str = (
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"meta-llama/Llama-3.2-1B-Instruct" #'meta-llama/Llama-3.2-1B'#'google/gemma-2-2b-it'
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)
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llm_model_name: str = "meta-llama/Llama-3.2-1B-Instruct" #'meta-llama/Llama-3.2-1B'#'google/gemma-2-2b-it'
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llm_model_max_token_size: int = 32768
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llm_model_max_async: int = 16
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@ -286,7 +286,9 @@ async def hf_model_if_cache(
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output = hf_model.generate(
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**input_ids, max_new_tokens=512, num_return_sequences=1, early_stopping=True
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)
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response_text = hf_tokenizer.decode(output[0][len(inputs["input_ids"][0]):], skip_special_tokens=True)
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response_text = hf_tokenizer.decode(
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output[0][len(inputs["input_ids"][0]) :], skip_special_tokens=True
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)
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if hashing_kv is not None:
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await hashing_kv.upsert({args_hash: {"return": response_text, "model": model}})
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return response_text
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31
setup.py
31
setup.py
@ -1,6 +1,7 @@
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import setuptools
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from pathlib import Path
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# Reading the long description from README.md
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def read_long_description():
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try:
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@ -8,6 +9,7 @@ def read_long_description():
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except FileNotFoundError:
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return "A description of LightRAG is currently unavailable."
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# Retrieving metadata from __init__.py
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def retrieve_metadata():
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vars2find = ["__author__", "__version__", "__url__"]
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@ -17,18 +19,26 @@ def retrieve_metadata():
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for line in f.readlines():
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for v in vars2find:
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if line.startswith(v):
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line = line.replace(" ", "").replace('"', "").replace("'", "").strip()
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line = (
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line.replace(" ", "")
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.replace('"', "")
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.replace("'", "")
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.strip()
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)
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vars2readme[v] = line.split("=")[1]
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except FileNotFoundError:
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raise FileNotFoundError("Metadata file './lightrag/__init__.py' not found.")
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# Checking if all required variables are found
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missing_vars = [v for v in vars2find if v not in vars2readme]
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if missing_vars:
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raise ValueError(f"Missing required metadata variables in __init__.py: {missing_vars}")
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raise ValueError(
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f"Missing required metadata variables in __init__.py: {missing_vars}"
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)
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return vars2readme
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# Reading dependencies from requirements.txt
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def read_requirements():
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deps = []
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@ -36,9 +46,12 @@ def read_requirements():
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with open("./requirements.txt") as f:
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deps = [line.strip() for line in f if line.strip()]
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except FileNotFoundError:
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print("Warning: 'requirements.txt' not found. No dependencies will be installed.")
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print(
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"Warning: 'requirements.txt' not found. No dependencies will be installed."
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)
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return deps
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metadata = retrieve_metadata()
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long_description = read_long_description()
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requirements = read_requirements()
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@ -51,7 +64,9 @@ setuptools.setup(
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description="LightRAG: Simple and Fast Retrieval-Augmented Generation",
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long_description=long_description,
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long_description_content_type="text/markdown",
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packages=setuptools.find_packages(exclude=("tests*", "docs*")), # Automatically find packages
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packages=setuptools.find_packages(
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exclude=("tests*", "docs*")
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), # Automatically find packages
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classifiers=[
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"Development Status :: 4 - Beta",
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"Programming Language :: Python :: 3",
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@ -66,6 +81,8 @@ setuptools.setup(
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project_urls={ # Additional project metadata
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"Documentation": metadata.get("__url__", ""),
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"Source": metadata.get("__url__", ""),
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"Tracker": f"{metadata.get('__url__', '')}/issues" if metadata.get("__url__") else ""
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"Tracker": f"{metadata.get('__url__', '')}/issues"
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if metadata.get("__url__")
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else "",
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},
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)
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