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Running
on
Zero
Running
on
Zero
from colpali_manager import ColpaliManager | |
from milvus_manager import MilvusManager | |
from pdf_manager import PdfManager | |
import hashlib | |
pdf_manager = PdfManager() | |
colpali_manager = ColpaliManager() | |
class Middleware: | |
def __init__(self, id:str, create_collection=True): | |
#hashed_id = hashlib.md5(id.encode()).hexdigest()[:8] | |
hashed_id = 0 #switched to persistent db, shld use diff id for diff accs | |
milvus_db_name = f"milvus_{hashed_id}.db" | |
self.milvus_manager = MilvusManager(milvus_db_name, id, create_collection) #create collections based on id rather than colpali | |
def index(self, pdf_path: str, id:str, max_pages: int, pages: list[int] = None): | |
if type(pdf_path) == None: #for direct query without any upload to db | |
print("no docs") | |
return | |
print(f"Indexing {pdf_path}, id: {id}, max_pages: {max_pages}") | |
image_paths = pdf_manager.save_images(id, pdf_path, max_pages) | |
print(f"Saved {len(image_paths)} images") | |
colbert_vecs = colpali_manager.process_images(image_paths) | |
images_data = [{ | |
"colbert_vecs": colbert_vecs[i], | |
"filepath": image_paths[i] | |
} for i in range(len(image_paths))] | |
print(f"Inserting {len(images_data)} images data to Milvus") | |
self.milvus_manager.insert_images_data(images_data) | |
print("Indexing completed") | |
return image_paths | |
def drop_collection(self): | |
"""Drop the current collection from Milvus""" | |
return self.milvus_manager.drop_collection() | |
def search(self, search_queries: list[str], topk: int = 10): | |
print(f"\nπ MIDDLEWARE SEARCH INITIATED") | |
print(f"π Queries to process: {len(search_queries)}") | |
print(f"π― Top-k requested: {topk}") | |
print("-" * 60) | |
final_res = [] | |
for i, query in enumerate(search_queries, 1): | |
print(f"\nπ Processing Query {i}/{len(search_queries)}: '{query}'") | |
print(f"π Converting query to vector representation...") | |
query_vec = colpali_manager.process_text([query])[0] | |
print(f"β Query vector generated (dimension: {len(query_vec)})") | |
print(f"π Executing vector search in Milvus...") | |
search_res = self.milvus_manager.search(query_vec, topk=topk) | |
print(f"β Search completed: {len(search_res)} results retrieved") | |
if search_res: | |
print(f"π Score range: {search_res[0][0]:.4f} (highest) to {search_res[-1][0]:.4f} (lowest)") | |
final_res.append(search_res) | |
print(f"\nπ MIDDLEWARE SEARCH COMPLETED") | |
print(f"π Total queries processed: {len(search_queries)}") | |
print(f"π Total results across all queries: {sum(len(res) for res in final_res)}") | |
print("=" * 60) | |
return final_res | |