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https://github.com/Azure-Samples/graphrag-accelerator.git
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Upgrade python package (#42)
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This graphrag wheel file was built from the following repo
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https://github.com/microsoft/graphrag
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on commit hash b860d08a907e834166edf03e617d9cfeac946a64
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@ -272,8 +272,6 @@ async def generate_prompts(storage_name: str, limit: int = 5):
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this_directory = os.path.dirname(
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this_directory = os.path.dirname(
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os.path.abspath(inspect.getfile(inspect.currentframe()))
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os.path.abspath(inspect.getfile(inspect.currentframe()))
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)
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)
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print("THIS DIRECTORY: ", this_directory)
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print("CWD: ", os.getcwd())
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# write custom settings.yaml to a file and store in a temporary directory
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# write custom settings.yaml to a file and store in a temporary directory
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data = yaml.safe_load(open(f"{this_directory}/pipeline-settings.yaml"))
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data = yaml.safe_load(open(f"{this_directory}/pipeline-settings.yaml"))
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@ -281,7 +279,6 @@ async def generate_prompts(storage_name: str, limit: int = 5):
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temp_dir = f"/tmp/{sanitized_storage_name}_prompt_tuning"
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temp_dir = f"/tmp/{sanitized_storage_name}_prompt_tuning"
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shutil.rmtree(temp_dir, ignore_errors=True)
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shutil.rmtree(temp_dir, ignore_errors=True)
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os.makedirs(temp_dir, exist_ok=True)
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os.makedirs(temp_dir, exist_ok=True)
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print(f"TEMP SETTINGS DIR: {temp_dir}")
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with open(f"{temp_dir}/settings.yaml", "w") as f:
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with open(f"{temp_dir}/settings.yaml", "w") as f:
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yaml.dump(data, f, default_flow_style=False)
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yaml.dump(data, f, default_flow_style=False)
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@ -306,9 +303,6 @@ async def generate_prompts(storage_name: str, limit: int = 5):
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f"{temp_dir}/prompts" # will become a zip file with the name prompts.zip
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f"{temp_dir}/prompts" # will become a zip file with the name prompts.zip
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)
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)
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shutil.make_archive(temp_archive, "zip", root_dir=temp_dir, base_dir="prompts")
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shutil.make_archive(temp_archive, "zip", root_dir=temp_dir, base_dir="prompts")
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print(f"ARCHIVE: {temp_archive}.zip")
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for f in os.listdir(temp_dir):
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print(f"FILE: {f}")
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def iterfile(file_path: str):
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def iterfile(file_path: str):
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with open(file_path, mode="rb") as file_like:
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with open(file_path, mode="rb") as file_like:
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@ -176,7 +176,7 @@ class CommunitySearchHelpers:
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relationships=relationships, entities=entities, ranking_attribute="rank"
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relationships=relationships, entities=entities, ranking_attribute="rank"
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)
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)
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if covariate_df:
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if covariate_df is not None:
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claims = read_covariates(
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claims = read_covariates(
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df=covariate_df,
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df=covariate_df,
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id_col="id",
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id_col="id",
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@ -529,7 +529,7 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"generate_prompts(storage_name=storage_name, limit=5, zip_file_name=\"prompts.zip\")\n",
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"generate_prompts(storage_name=storage_name, limit=1, zip_file_name=\"prompts.zip\")\n",
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"with ZipFile(\"prompts.zip\", \"r\") as zip_ref:\n",
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"with ZipFile(\"prompts.zip\", \"r\") as zip_ref:\n",
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" zip_ref.extractall()"
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" zip_ref.extractall()"
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]
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]
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792
poetry.lock
generated
792
poetry.lock
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Load Diff
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[tool.poetry]
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[tool.poetry]
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name = "graphrag-solution-accelerator"
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name = "graphrag-solution-accelerator"
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version = "0.0.1"
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version = "0.1.1"
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description = ""
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description = ""
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authors = [
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authors = [
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"Josh Bradley <joshbradley@microsoft.com>",
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"Josh Bradley <joshbradley@microsoft.com>",
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@ -46,7 +46,7 @@ environs = ">=9.5.0"
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fastapi = ">=0.110.0"
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fastapi = ">=0.110.0"
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fastparquet = ">=2023.10.1"
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fastparquet = ">=2023.10.1"
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fsspec = ">=2024.2.0"
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fsspec = ">=2024.2.0"
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graphrag = {path = "backend/graphrag-wheel/graphrag-0.0.1-py3-none-any.whl"}
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graphrag = "==0.1.1"
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graspologic = ">=3.3.0"
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graspologic = ">=3.3.0"
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httpx = ">=0.25.2"
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httpx = ">=0.25.2"
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kubernetes = ">=29.0.0"
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kubernetes = ">=29.0.0"
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