2023-06-06 01:38:15 +03:00
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import os
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import time
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from langchain.document_loaders import GitLoader
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from langchain.schema import Document
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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2023-06-19 23:46:25 +03:00
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from models.settings import CommonsDep
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2023-06-06 01:38:15 +03:00
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from parsers.common import file_already_exists_from_content
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2023-06-17 00:36:53 +03:00
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from utils.file import compute_sha1_from_content
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2023-06-19 22:15:35 +03:00
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from utils.vectors import Neurons
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2023-06-06 01:38:15 +03:00
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2023-06-17 00:36:53 +03:00
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async def process_github(commons: CommonsDep, repo, enable_summarization, user, supabase, user_openai_api_key):
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2023-06-06 01:38:15 +03:00
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random_dir_name = os.urandom(16).hex()
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dateshort = time.strftime("%Y%m%d")
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loader = GitLoader(
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clone_url=repo,
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repo_path="/tmp/" + random_dir_name,
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)
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documents = loader.load()
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os.system("rm -rf /tmp/" + random_dir_name)
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2023-06-19 18:53:07 +03:00
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chunk_size = 500
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2023-06-06 01:38:15 +03:00
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chunk_overlap = 0
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text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
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chunk_size=chunk_size, chunk_overlap=chunk_overlap)
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documents = text_splitter.split_documents(documents)
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print(documents[:1])
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for doc in documents:
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2023-06-19 12:23:58 +03:00
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if doc.metadata["file_type"] in [".pyc",".png",".svg", ".env", ".lock", ".gitignore", ".gitmodules", ".gitattributes", ".gitkeep", ".git", ".json"]:
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2023-06-06 01:38:15 +03:00
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continue
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metadata = {
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"file_sha1": compute_sha1_from_content(doc.page_content.encode("utf-8")),
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"file_size": len(doc.page_content)*8,
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"file_name": doc.metadata["file_name"],
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"chunk_size": chunk_size,
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"chunk_overlap": chunk_overlap,
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"date": dateshort,
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"summarization": "true" if enable_summarization else "false"
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}
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doc_with_metadata = Document(
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page_content=doc.page_content, metadata=metadata)
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exist = await file_already_exists_from_content(supabase, doc.page_content.encode("utf-8"), user)
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if not exist:
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2023-06-19 22:15:35 +03:00
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neurons = Neurons(commons=commons)
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neurons.create_vector(user.email, doc_with_metadata, user_openai_api_key)
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2023-06-06 01:38:15 +03:00
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print("Created vector for ", doc.metadata["file_name"])
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return {"message": f"✅ Github with {len(documents)} files has been uploaded.", "type": "success"}
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