Update app.py
Browse files
app.py
CHANGED
@@ -17,6 +17,7 @@ from langchain.docstore.document import Document
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from langchain.schema import Document
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from chunk_python_code import chunk_python_code_with_metadata
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from vectorstore import get_chroma_vectorstore
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# Load environment variables from .env file
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load_dotenv()
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@@ -53,55 +54,6 @@ def load_project_id(json_file):
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return data['project_id']
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def download_gitlab_project_by_version():
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try:
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# Load the configuration from config.json
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# Extract GitLab project information from the config
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api_url = config2['gitlab']['api_url']
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project_id = urllib.parse.quote(config2['gitlab']['project']['id'], safe="")
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version = config2['gitlab']['project']['version']
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# Construct the URL for the release's zip file
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url = f"{api_url}/projects/{project_id}/repository/archive.zip?sha={version}"
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# Send GET request to download the zip file
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response = requests.get(url, stream=True)
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archive_bytes = io.BytesIO(response.content)
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if response.status_code == 200:
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# Extract filename from content-disposition header
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content_disposition = response.headers.get("content-disposition")
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if content_disposition and "filename=" in content_disposition:
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filename = content_disposition.split("filename=")[-1].strip('"')
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# test
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# target_path = f"{DATA_DIR}/{filename}"
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# Check if the request was successful
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if response.status_code == 200:
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api.upload_file(
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path_or_fileobj= archive_bytes,
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path_in_repo= f"{DATA_DIR}/{filename}",
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repo_id=HF_SPACE_NAME,
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repo_type='space'
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)
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print(f"Release {version} downloaded successfully as {file_path}.")
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else:
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print(f"Failed to download the release: {response.status_code} - {response.reason}")
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print(response.text)
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except FileNotFoundError:
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print("The config.json file was not found. Please ensure it exists in the project directory.")
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except json.JSONDecodeError:
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print("Failed to parse the config.json file. Please ensure it contains valid JSON.")
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except Exception as e:
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print(f"An error occurred: {e}")
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def download_gitlab_repo():
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print("Start the upload_gitRepository function")
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project_id = load_project_id('repository_ids.json')
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@@ -329,16 +281,14 @@ def get_chroma_vectorstore2(embedding_model):
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def initialize():
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global vector_store, chunks, llm
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code_folder_paths = ['kadi_apy']
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doc_folder_paths = ['docs/source/']
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code_texts, code_references = process_directory(DATA_DIR, code_folder_paths, [])
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print("LEEEEEEEEEEEENGTH of code_texts: ", len(code_texts))
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doc_texts, kadiAPY_doc_references = process_directory(DATA_DIR, doc_folder_paths, [])
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print("LEEEEEEEEEEEENGTH of doc_files: ", len(doc_texts))
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from langchain.schema import Document
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from chunk_python_code import chunk_python_code_with_metadata
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from vectorstore import get_chroma_vectorstore
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from download_gitlab_repo import download_and_upload_kadiAPY_repo_to_huggingfacespace
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# Load environment variables from .env file
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load_dotenv()
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return data['project_id']
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def download_gitlab_repo():
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print("Start the upload_gitRepository function")
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project_id = load_project_id('repository_ids.json')
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def initialize():
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global vector_store, chunks, llm
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download_and_upload_kadiAPY_repo_to_huggingfacespace()
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code_folder_paths = ['kadi_apy']
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doc_folder_paths = ['docs/source/']
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code_texts, code_references = process_directory(DATA_DIR, code_folder_paths, [])
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print("LEEEEEEEEEEEENGTH of code_texts: ", len(code_texts))
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doc_texts, kadiAPY_doc_references = process_directory(DATA_DIR, doc_folder_paths, [])
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print("LEEEEEEEEEEEENGTH of doc_files: ", len(doc_texts))
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