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from ragflow_sdk import RAGFlow
from common import HOST_ADDRESS
from time import sleep
def test_parse_document_with_txt(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_parse_document")
name = 'ragflow_test.txt'
with open("test_data/ragflow_test.txt", "rb") as file :
blob = file.read()
docs = ds.upload_documents([{"displayed_name": name, "blob": blob}])
doc = docs[0]
ds.async_parse_documents(document_ids=[doc.id])
'''
for n in range(100):
if doc.progress == 1:
break
sleep(1)
else:
raise Exception("Run time ERROR: Document parsing did not complete in time.")
'''
def test_parse_and_cancel_document(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_parse_and_cancel_document")
name = 'ragflow_test.txt'
with open("test_data/ragflow_test.txt", "rb") as file :
blob = file.read()
docs=ds.upload_documents([{"displayed_name": name, "blob": blob}])
doc = docs[0]
ds.async_parse_documents(document_ids=[doc.id])
sleep(1)
if 0 < doc.progress < 1:
ds.async_cancel_parse_documents(document_ids=[doc.id])
def test_bulk_parse_documents(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_bulk_parse_and_cancel_documents")
with open("test_data/ragflow.txt", "rb") as file:
blob = file.read()
documents = [
{'displayed_name': 'test1.txt', 'blob': blob},
{'displayed_name': 'test2.txt', 'blob': blob},
{'displayed_name': 'test3.txt', 'blob': blob}
]
docs = ds.upload_documents(documents)
ids = [doc.id for doc in docs]
ds.async_parse_documents(ids)
'''
for n in range(100):
all_completed = all(doc.progress == 1 for doc in docs)
if all_completed:
break
sleep(1)
else:
raise Exception("Run time ERROR: Bulk document parsing did not complete in time.")
'''
def test_list_chunks_with_success(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_list_chunks_with_success")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_list_chunks_with_success.txt","blob":blob}]
docs = ds.upload_documents(documents)
ids = [doc.id for doc in docs]
ds.async_parse_documents(ids)
'''
for n in range(100):
all_completed = all(doc.progress == 1 for doc in docs)
if all_completed:
break
sleep(1)
else:
raise Exception("Run time ERROR: Chunk document parsing did not complete in time.")
'''
doc = docs[0]
doc.list_chunks()
def test_add_chunk_with_success(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_add_chunk_with_success")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_list_chunks_with_success.txt","blob":blob}]
docs = ds.upload_documents(documents)
doc = docs[0]
doc.add_chunk(content="This is a chunk addition test")
def test_delete_chunk_with_success(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_delete_chunk_with_success")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_delete_chunk_with_success.txt","blob":blob}]
docs = ds.upload_documents(documents)
doc = docs[0]
chunk = doc.add_chunk(content="This is a chunk addition test")
sleep(5)
doc.delete_chunks([chunk.id])
def test_update_chunk_content(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_update_chunk_content_with_success")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_update_chunk_content_with_success.txt","blob":blob}]
docs = ds.upload_documents(documents)
doc = docs[0]
chunk = doc.add_chunk(content="This is a chunk addition test")
# For Elasticsearch, the chunk is not searchable in shot time (~2s).
sleep(3)
chunk.update({"content":"This is a updated content"})
def test_update_chunk_available(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="test_update_chunk_available_with_success")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_update_chunk_available_with_success.txt","blob":blob}]
docs = ds.upload_documents(documents)
doc = docs[0]
chunk = doc.add_chunk(content="This is a chunk addition test")
# For Elasticsearch, the chunk is not searchable in shot time (~2s).
sleep(3)
chunk.update({"available":0})
def test_retrieve_chunks(get_api_key_fixture):
API_KEY = get_api_key_fixture
rag = RAGFlow(API_KEY, HOST_ADDRESS)
ds = rag.create_dataset(name="retrieval")
with open("test_data/ragflow_test.txt", "rb") as file:
blob = file.read()
'''
# chunk_size = 1024 * 1024
# chunks = [blob[i:i + chunk_size] for i in range(0, len(blob), chunk_size)]
documents = [
{'displayed_name': f'chunk_{i}.txt', 'blob': chunk} for i, chunk in enumerate(chunks)
]
'''
documents =[{"displayed_name":"test_retrieve_chunks.txt","blob":blob}]
docs = ds.upload_documents(documents)
doc = docs[0]
doc.add_chunk(content="This is a chunk addition test")
rag.retrieve(dataset_ids=[ds.id],document_ids=[doc.id])
rag.delete_datasets(ids=[ds.id])
# test different parameters for the retrieval
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