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Copy pathutils.py
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243 lines (180 loc) · 7.12 KB
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import json
import os
import pickle
import shutil
import time
import uuid
from datetime import datetime, timedelta
from config import (
USER_DOCUMENTS_DIR,
METADATA_FILE,
CHUNK_METADATA_FILE,
EMBEDDING_METADATA_FILE,
DOCUMENT_TTL_SECONDS
)
# =====================================================
# SESSION FUNCTIONS
# =====================================================
def create_user_session():
"""
Creates a unique user session directory.
"""
session_id = str(uuid.uuid4())
session_path = os.path.join(USER_DOCUMENTS_DIR, session_id)
os.makedirs(session_path, exist_ok=True)
return session_id
def get_session_path(session_id):
return os.path.join(USER_DOCUMENTS_DIR, session_id)
# =====================================================
# METADATA HELPERS
# =====================================================
def load_json(file_path):
if not os.path.exists(file_path):
return {}
with open(file_path, "r", encoding="utf-8") as file:
return json.load(file)
def save_json(data, file_path):
with open(file_path, "w", encoding="utf-8") as file:
json.dump(data, file, indent=4)
def load_pickle(file_path):
if not os.path.exists(file_path):
return []
with open(file_path, "rb") as file:
return pickle.load(file)
# =====================================================
# DOCUMENT HELPERS
# =====================================================
def get_uploaded_documents(session_id):
"""
Returns all uploaded documents
for a particular session.
"""
metadata_path = os.path.join(get_session_path(session_id), METADATA_FILE)
metadata = load_json(metadata_path)
return metadata.get("documents", [])
def get_document_statistics(session_id, document_id):
metadata_path = os.path.join(get_session_path(session_id), METADATA_FILE)
metadata = load_json(metadata_path)
for document in metadata.get("documents", []):
if document["id"] == document_id:
return {
"document_size": document["document_size"],
"total_characters": document["total_characters"],
"total_words": document["total_words"],
"total_chunks": document["total_chunks"],
"total_embeddings": document["total_embeddings"],
"embedding_dimension": document["embedding_dimension"],
"uploaded_at": document["uploaded_at"],
"expires_at": document["expires_at"]
}
return {}
# =====================================================
# CHUNK DETAILS
# =====================================================
def get_chunk_details(session_id, document_id, chunk_number):
chunk_file = os.path.join(get_session_path(session_id), CHUNK_METADATA_FILE)
chunks = load_pickle(chunk_file)
for chunk in chunks:
if (chunk["document_id"] == document_id and chunk["chunk_number"] == chunk_number):
return {
"characters": chunk["character_count"],
"words": chunk["word_count"],
"text": chunk["chunk_text"]
}
return {}
# =====================================================
# EMBEDDING DETAILS
# =====================================================
def get_embedding_details(session_id, document_id, embedding_number):
embedding_file = os.path.join(get_session_path(session_id), EMBEDDING_METADATA_FILE)
embeddings = load_pickle(embedding_file)
for embedding in embeddings:
if (embedding["document_id"] == document_id and embedding["embedding_number"] == embedding_number):
return {
"dimension": embedding["embedding_dimension"],
"vector": embedding["embedding_vector"]
}
return {}
# =====================================================
# SESSION STATISTICS
# =====================================================
def get_session_statistics(session_id):
metadata_path = os.path.join(get_session_path(session_id), METADATA_FILE)
metadata = load_json(metadata_path)
documents = metadata.get("documents", [])
total_chunks = 0
total_embeddings = 0
total_characters = 0
total_words = 0
for document in documents:
total_chunks += (document["total_chunks"])
total_embeddings += (document["total_embeddings"])
total_characters += (document["total_characters"])
total_words += (document["total_words"])
return {
"session_id": session_id,
"active_documents": len(documents),
"active_chunks": total_chunks,
"active_embeddings": total_embeddings,
"total_characters": total_characters,
"total_words": total_words
}
# =====================================================
# DOCUMENT EXPIRY
# =====================================================
def get_remaining_time(document):
"""
Returns remaining expiry time.
"""
expiry_time = datetime.strptime(document["expires_at"], "%Y-%m-%d %H:%M:%S")
remaining = (expiry_time - datetime.now())
seconds = int(remaining.total_seconds())
if seconds <= 0:
return "Expired"
minutes = seconds // 60
return f"{minutes} Minutes"
def calculate_expiry_time():
expiry = datetime.now() + timedelta(seconds=DOCUMENT_TTL_SECONDS)
return expiry.strftime("%Y-%m-%d %H:%M:%S")
def get_current_time():
return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
# =====================================================
# DELETE DOCUMENT
# =====================================================
def delete_document(session_id, document_id):
"""
Deletes a document's metadata.
NOTE:
The FAISS index will be rebuilt
in rag.py after deletion.
"""
metadata_path = os.path.join(get_session_path(session_id), METADATA_FILE)
metadata = load_json(metadata_path)
documents = metadata.get("documents", [])
updated_documents = []
for document in documents:
if document["id"] != document_id:
updated_documents.append(document)
metadata["documents"] = (updated_documents)
save_json(metadata, metadata_path)
# =====================================================
# DOCUMENT EXISTS
# =====================================================
def document_exists(session_id, document_name):
documents = get_uploaded_documents(session_id)
for document in documents:
if (document["name"] == document_name):
return True
return False
# =====================================================
# DELETE ENTIRE SESSION
# =====================================================
def delete_session(session_id):
session_path = get_session_path(session_id)
if os.path.exists(session_path):
shutil.rmtree(session_path)
def download_sample_document(file_name):
path = os.path.join("sample_documents", file_name)
with open(path, "r", encoding="utf-8") as f:
data = f.read()
return data