Start log tracing to log business events. Storage in both database and logging-backend.
This commit is contained in:
Josako
@@ -24,6 +24,9 @@ from eveai_workers.Processors.html_processor import HTMLProcessor
|
||||
from eveai_workers.Processors.pdf_processor import PDFProcessor
|
||||
from eveai_workers.Processors.srt_processor import SRTProcessor
|
||||
|
||||
from common.utils.business_event import BusinessEvent
|
||||
from common.utils.business_event_context import current_event
|
||||
|
||||
|
||||
# Healthcheck task
|
||||
@current_celery.task(name='ping', queue='embeddings')
|
||||
@@ -33,76 +36,80 @@ def ping():
|
||||
|
||||
@current_celery.task(name='create_embeddings', queue='embeddings')
|
||||
def create_embeddings(tenant_id, document_version_id):
|
||||
current_app.logger.info(f'Creating embeddings for tenant {tenant_id} on document version {document_version_id}.')
|
||||
# BusinessEvent creates a context, which is why we need to use it with a with block
|
||||
with BusinessEvent('Create Embeddings', tenant_id, document_version_id=document_version_id):
|
||||
current_app.logger.info(f'Creating embeddings for tenant {tenant_id} on document version {document_version_id}')
|
||||
current_event.log("Starting Embedding Creation Task")
|
||||
|
||||
try:
|
||||
# Retrieve Tenant for which we are processing
|
||||
tenant = Tenant.query.get(tenant_id)
|
||||
if tenant is None:
|
||||
raise Exception(f'Tenant {tenant_id} not found')
|
||||
try:
|
||||
# Retrieve Tenant for which we are processing
|
||||
tenant = Tenant.query.get(tenant_id)
|
||||
if tenant is None:
|
||||
raise Exception(f'Tenant {tenant_id} not found')
|
||||
|
||||
# Ensure we are working in the correct database schema
|
||||
Database(tenant_id).switch_schema()
|
||||
# Ensure we are working in the correct database schema
|
||||
Database(tenant_id).switch_schema()
|
||||
|
||||
# Select variables to work with depending on tenant and model
|
||||
model_variables = select_model_variables(tenant)
|
||||
current_app.logger.debug(f'Model variables: {model_variables}')
|
||||
# Select variables to work with depending on tenant and model
|
||||
model_variables = select_model_variables(tenant)
|
||||
current_app.logger.debug(f'Model variables: {model_variables}')
|
||||
|
||||
# Retrieve document version to process
|
||||
document_version = DocumentVersion.query.get(document_version_id)
|
||||
if document_version is None:
|
||||
raise Exception(f'Document version {document_version_id} not found')
|
||||
# Retrieve document version to process
|
||||
document_version = DocumentVersion.query.get(document_version_id)
|
||||
if document_version is None:
|
||||
raise Exception(f'Document version {document_version_id} not found')
|
||||
|
||||
except Exception as e:
|
||||
current_app.logger.error(f'Create Embeddings request received '
|
||||
f'for non existing document version {document_version_id} '
|
||||
f'for tenant {tenant_id}, '
|
||||
f'error: {e}')
|
||||
raise
|
||||
except Exception as e:
|
||||
current_app.logger.error(f'Create Embeddings request received '
|
||||
f'for non existing document version {document_version_id} '
|
||||
f'for tenant {tenant_id}, '
|
||||
f'error: {e}')
|
||||
raise
|
||||
|
||||
try:
|
||||
db.session.add(document_version)
|
||||
try:
|
||||
db.session.add(document_version)
|
||||
|
||||
# start processing
|
||||
document_version.processing = True
|
||||
document_version.processing_started_at = dt.now(tz.utc)
|
||||
document_version.processing_finished_at = None
|
||||
document_version.processing_error = None
|
||||
# start processing
|
||||
document_version.processing = True
|
||||
document_version.processing_started_at = dt.now(tz.utc)
|
||||
document_version.processing_finished_at = None
|
||||
document_version.processing_error = None
|
||||
|
||||
db.session.commit()
|
||||
except SQLAlchemyError as e:
|
||||
current_app.logger.error(f'Unable to save Embedding status information '
|
||||
f'in document version {document_version_id} '
|
||||
f'for tenant {tenant_id}')
|
||||
raise
|
||||
db.session.commit()
|
||||
except SQLAlchemyError as e:
|
||||
current_app.logger.error(f'Unable to save Embedding status information '
|
||||
f'in document version {document_version_id} '
|
||||
f'for tenant {tenant_id}')
|
||||
raise
|
||||
|
||||
delete_embeddings_for_document_version(document_version)
|
||||
delete_embeddings_for_document_version(document_version)
|
||||
|
||||
try:
|
||||
match document_version.file_type:
|
||||
case 'pdf':
|
||||
process_pdf(tenant, model_variables, document_version)
|
||||
case 'html':
|
||||
process_html(tenant, model_variables, document_version)
|
||||
case 'srt':
|
||||
process_srt(tenant, model_variables, document_version)
|
||||
case 'mp4' | 'mp3' | 'ogg':
|
||||
process_audio(tenant, model_variables, document_version)
|
||||
case _:
|
||||
raise Exception(f'No functionality defined for file type {document_version.file_type} '
|
||||
f'for tenant {tenant_id} '
|
||||
f'while creating embeddings for document version {document_version_id}')
|
||||
try:
|
||||
match document_version.file_type:
|
||||
case 'pdf':
|
||||
process_pdf(tenant, model_variables, document_version)
|
||||
case 'html':
|
||||
process_html(tenant, model_variables, document_version)
|
||||
case 'srt':
|
||||
process_srt(tenant, model_variables, document_version)
|
||||
case 'mp4' | 'mp3' | 'ogg':
|
||||
process_audio(tenant, model_variables, document_version)
|
||||
case _:
|
||||
raise Exception(f'No functionality defined for file type {document_version.file_type} '
|
||||
f'for tenant {tenant_id} '
|
||||
f'while creating embeddings for document version {document_version_id}')
|
||||
current_event.log("Finished Embedding Creation Task")
|
||||
|
||||
except Exception as e:
|
||||
current_app.logger.error(f'Error creating embeddings for tenant {tenant_id} '
|
||||
f'on document version {document_version_id} '
|
||||
f'error: {e}')
|
||||
document_version.processing = False
|
||||
document_version.processing_finished_at = dt.now(tz.utc)
|
||||
document_version.processing_error = str(e)[:255]
|
||||
db.session.commit()
|
||||
create_embeddings.update_state(state=states.FAILURE)
|
||||
raise
|
||||
except Exception as e:
|
||||
current_app.logger.error(f'Error creating embeddings for tenant {tenant_id} '
|
||||
f'on document version {document_version_id} '
|
||||
f'error: {e}')
|
||||
document_version.processing = False
|
||||
document_version.processing_finished_at = dt.now(tz.utc)
|
||||
document_version.processing_error = str(e)[:255]
|
||||
db.session.commit()
|
||||
create_embeddings.update_state(state=states.FAILURE)
|
||||
raise
|
||||
|
||||
|
||||
def delete_embeddings_for_document_version(document_version):
|
||||
@@ -118,38 +125,48 @@ def delete_embeddings_for_document_version(document_version):
|
||||
|
||||
|
||||
def process_pdf(tenant, model_variables, document_version):
|
||||
current_event.log("Starting PDF Processing")
|
||||
processor = PDFProcessor(tenant, model_variables, document_version)
|
||||
markdown, title = processor.process()
|
||||
|
||||
# Process markdown and embed
|
||||
embed_markdown(tenant, model_variables, document_version, markdown, title)
|
||||
current_event.log("Finished PDF Processing")
|
||||
|
||||
|
||||
def process_html(tenant, model_variables, document_version):
|
||||
processor = HTMLProcessor(tenant, model_variables, document_version)
|
||||
markdown, title = processor.process()
|
||||
with current_event.create_span("HTML Processing"):
|
||||
processor = HTMLProcessor(tenant, model_variables, document_version)
|
||||
markdown, title = processor.process()
|
||||
|
||||
# Process markdown and embed
|
||||
embed_markdown(tenant, model_variables, document_version, markdown, title)
|
||||
with current_event.create_span("Embedding"):
|
||||
embed_markdown(tenant, model_variables, document_version, markdown, title)
|
||||
|
||||
|
||||
|
||||
def process_audio(tenant, model_variables, document_version):
|
||||
current_event.log("Starting Audio Processing")
|
||||
processor = AudioProcessor(tenant, model_variables, document_version)
|
||||
markdown, title = processor.process()
|
||||
|
||||
# Process markdown and embed
|
||||
embed_markdown(tenant, model_variables, document_version, markdown, title)
|
||||
current_event.log("Finished Audio Processing")
|
||||
|
||||
|
||||
def process_srt(tenant, model_variables, document_version):
|
||||
current_event.log("Starting SRT Processing")
|
||||
processor = SRTProcessor(tenant, model_variables, document_version)
|
||||
markdown, title = processor.process()
|
||||
|
||||
# Process markdown and embed
|
||||
embed_markdown(tenant, model_variables, document_version, markdown, title)
|
||||
current_event.log("Finished SRT Processing")
|
||||
|
||||
|
||||
def embed_markdown(tenant, model_variables, document_version, markdown, title):
|
||||
current_event.log("Starting Embedding Markdown Processing")
|
||||
# Create potential chunks
|
||||
potential_chunks = create_potential_chunks_for_markdown(tenant.id, document_version, f"{document_version.id}.md")
|
||||
|
||||
@@ -178,9 +195,11 @@ def embed_markdown(tenant, model_variables, document_version, markdown, title):
|
||||
|
||||
current_app.logger.info(f'Embeddings created successfully for tenant {tenant.id} '
|
||||
f'on document version {document_version.id} :-)')
|
||||
current_event.log("Finished Embedding Markdown Processing")
|
||||
|
||||
|
||||
def enrich_chunks(tenant, model_variables, document_version, title, chunks):
|
||||
current_event.log("Starting Enriching Chunks Processing")
|
||||
current_app.logger.debug(f'Enriching chunks for tenant {tenant.id} '
|
||||
f'on document version {document_version.id}')
|
||||
|
||||
@@ -213,11 +232,13 @@ def enrich_chunks(tenant, model_variables, document_version, title, chunks):
|
||||
|
||||
current_app.logger.debug(f'Finished enriching chunks for tenant {tenant.id} '
|
||||
f'on document version {document_version.id}')
|
||||
current_event.log("Finished Enriching Chunks Processing")
|
||||
|
||||
return enriched_chunks
|
||||
|
||||
|
||||
def summarize_chunk(tenant, model_variables, document_version, chunk):
|
||||
current_event.log("Starting Summarizing Chunk Processing")
|
||||
current_app.logger.debug(f'Summarizing chunk for tenant {tenant.id} '
|
||||
f'on document version {document_version.id}')
|
||||
llm = model_variables['llm']
|
||||
@@ -235,6 +256,7 @@ def summarize_chunk(tenant, model_variables, document_version, chunk):
|
||||
summary = chain.invoke({"text": chunk})
|
||||
current_app.logger.debug(f'Finished summarizing chunk for tenant {tenant.id} '
|
||||
f'on document version {document_version.id}.')
|
||||
current_event.log("Finished summarizing chunk for tenant ")
|
||||
return summary
|
||||
except LangChainException as e:
|
||||
current_app.logger.error(f'Error creating summary for chunk enrichment for tenant {tenant.id} '
|
||||
@@ -244,6 +266,7 @@ def summarize_chunk(tenant, model_variables, document_version, chunk):
|
||||
|
||||
|
||||
def embed_chunks(tenant, model_variables, document_version, chunks):
|
||||
current_event.log("Starting Embedding Chunks Processing")
|
||||
current_app.logger.debug(f'Embedding chunks for tenant {tenant.id} '
|
||||
f'on document version {document_version.id}')
|
||||
embedding_model = model_variables['embedding_model']
|
||||
@@ -268,6 +291,8 @@ def embed_chunks(tenant, model_variables, document_version, chunks):
|
||||
new_embedding.embedding = embedding
|
||||
new_embeddings.append(new_embedding)
|
||||
|
||||
current_app.logger.debug(f'Finished embedding chunks for tenant {tenant.id} ')
|
||||
|
||||
return new_embeddings
|
||||
|
||||
|
||||
@@ -281,244 +306,6 @@ def log_parsing_info(tenant, tags, included_elements, excluded_elements, exclude
|
||||
current_app.embed_tuning_logger.debug(f'First element to parse: {elements_to_parse[0]}')
|
||||
|
||||
|
||||
# def process_youtube(tenant, model_variables, document_version):
|
||||
# download_file_name = f'{document_version.id}.mp4'
|
||||
# compressed_file_name = f'{document_version.id}.mp3'
|
||||
# transcription_file_name = f'{document_version.id}.txt'
|
||||
# markdown_file_name = f'{document_version.id}.md'
|
||||
#
|
||||
# # Remove existing files (in case of a re-processing of the file
|
||||
# minio_client.delete_document_file(tenant.id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, download_file_name)
|
||||
# minio_client.delete_document_file(tenant.id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, compressed_file_name)
|
||||
# minio_client.delete_document_file(tenant.id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, transcription_file_name)
|
||||
# minio_client.delete_document_file(tenant.id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, markdown_file_name)
|
||||
#
|
||||
# of, title, description, author = download_youtube(document_version.url, tenant.id, document_version,
|
||||
# download_file_name)
|
||||
# document_version.system_context = f'Title: {title}\nDescription: {description}\nAuthor: {author}'
|
||||
# compress_audio(tenant.id, document_version, download_file_name, compressed_file_name)
|
||||
# transcribe_audio(tenant.id, document_version, compressed_file_name, transcription_file_name, model_variables)
|
||||
# annotate_transcription(tenant, document_version, transcription_file_name, markdown_file_name, model_variables)
|
||||
#
|
||||
# potential_chunks = create_potential_chunks_for_markdown(tenant.id, document_version, markdown_file_name)
|
||||
# actual_chunks = combine_chunks_for_markdown(potential_chunks, model_variables['min_chunk_size'],
|
||||
# model_variables['max_chunk_size'])
|
||||
#
|
||||
# enriched_chunks = enrich_chunks(tenant, document_version, actual_chunks)
|
||||
# embeddings = embed_chunks(tenant, model_variables, document_version, enriched_chunks)
|
||||
#
|
||||
# try:
|
||||
# db.session.add(document_version)
|
||||
# document_version.processing_finished_at = dt.now(tz.utc)
|
||||
# document_version.processing = False
|
||||
# db.session.add_all(embeddings)
|
||||
# db.session.commit()
|
||||
# except SQLAlchemyError as e:
|
||||
# current_app.logger.error(f'Error saving embedding information for tenant {tenant.id} '
|
||||
# f'on Youtube document version {document_version.id}'
|
||||
# f'error: {e}')
|
||||
# raise
|
||||
#
|
||||
# current_app.logger.info(f'Embeddings created successfully for tenant {tenant.id} '
|
||||
# f'on Youtube document version {document_version.id} :-)')
|
||||
#
|
||||
#
|
||||
# def download_youtube(url, tenant_id, document_version, file_name):
|
||||
# try:
|
||||
# current_app.logger.info(f'Downloading YouTube video: {url} for tenant: {tenant_id}')
|
||||
# yt = YouTube(url)
|
||||
# stream = yt.streams.get_audio_only()
|
||||
#
|
||||
# with tempfile.NamedTemporaryFile(delete=False) as temp_file:
|
||||
# stream.download(output_path=temp_file.name)
|
||||
# with open(temp_file.name, 'rb') as f:
|
||||
# file_data = f.read()
|
||||
#
|
||||
# minio_client.upload_document_file(tenant_id, document_version.doc_id, document_version.language,
|
||||
# document_version.id,
|
||||
# file_name, file_data)
|
||||
#
|
||||
# current_app.logger.info(f'Downloaded YouTube video: {url} for tenant: {tenant_id}')
|
||||
# return file_name, yt.title, yt.description, yt.author
|
||||
# except Exception as e:
|
||||
# current_app.logger.error(f'Error downloading YouTube video: {url} for tenant: {tenant_id} with error: {e}')
|
||||
# raise
|
||||
#
|
||||
#
|
||||
# def compress_audio(tenant_id, document_version, input_file, output_file):
|
||||
# try:
|
||||
# current_app.logger.info(f'Compressing audio for tenant: {tenant_id}')
|
||||
#
|
||||
# input_data = minio_client.download_document_file(tenant_id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, input_file)
|
||||
#
|
||||
# with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_input:
|
||||
# temp_input.write(input_data)
|
||||
# temp_input.flush()
|
||||
#
|
||||
# with tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') as temp_output:
|
||||
# result = subprocess.run(
|
||||
# ['ffmpeg', '-i', temp_input.name, '-b:a', '64k', '-f', 'mp3', temp_output.name],
|
||||
# capture_output=True,
|
||||
# text=True
|
||||
# )
|
||||
#
|
||||
# if result.returncode != 0:
|
||||
# raise Exception(f"Compression failed: {result.stderr}")
|
||||
#
|
||||
# with open(temp_output.name, 'rb') as f:
|
||||
# compressed_data = f.read()
|
||||
#
|
||||
# minio_client.upload_document_file(tenant_id, document_version.doc_id, document_version.language,
|
||||
# document_version.id,
|
||||
# output_file, compressed_data)
|
||||
#
|
||||
# current_app.logger.info(f'Compressed audio for tenant: {tenant_id}')
|
||||
# except Exception as e:
|
||||
# current_app.logger.error(f'Error compressing audio for tenant: {tenant_id} with error: {e}')
|
||||
# raise
|
||||
#
|
||||
#
|
||||
# def transcribe_audio(tenant_id, document_version, input_file, output_file, model_variables):
|
||||
# try:
|
||||
# current_app.logger.info(f'Transcribing audio for tenant: {tenant_id}')
|
||||
# client = model_variables['transcription_client']
|
||||
# model = model_variables['transcription_model']
|
||||
#
|
||||
# # Download the audio file from MinIO
|
||||
# audio_data = minio_client.download_document_file(tenant_id, document_version.doc_id, document_version.language,
|
||||
# document_version.id, input_file)
|
||||
#
|
||||
# # Load the audio data into pydub
|
||||
# audio = AudioSegment.from_mp3(io.BytesIO(audio_data))
|
||||
#
|
||||
# # Define segment length (e.g., 10 minutes)
|
||||
# segment_length = 10 * 60 * 1000 # 10 minutes in milliseconds
|
||||
#
|
||||
# transcriptions = []
|
||||
#
|
||||
# # Split audio into segments and transcribe each
|
||||
# for i, chunk in enumerate(audio[::segment_length]):
|
||||
# current_app.logger.debug(f'Transcribing chunk {i + 1} of {len(audio) // segment_length + 1}')
|
||||
#
|
||||
# with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as temp_audio:
|
||||
# chunk.export(temp_audio.name, format="mp3")
|
||||
#
|
||||
# with open(temp_audio.name, 'rb') as audio_segment:
|
||||
# transcription = client.audio.transcriptions.create(
|
||||
# file=audio_segment,
|
||||
# model=model,
|
||||
# language=document_version.language,
|
||||
# response_format='verbose_json',
|
||||
# )
|
||||
#
|
||||
# transcriptions.append(transcription.text)
|
||||
#
|
||||
# os.unlink(temp_audio.name) # Delete the temporary file
|
||||
#
|
||||
# # Combine all transcriptions
|
||||
# full_transcription = " ".join(transcriptions)
|
||||
#
|
||||
# # Upload the full transcription to MinIO
|
||||
# minio_client.upload_document_file(
|
||||
# tenant_id,
|
||||
# document_version.doc_id,
|
||||
# document_version.language,
|
||||
# document_version.id,
|
||||
# output_file,
|
||||
# full_transcription.encode('utf-8')
|
||||
# )
|
||||
#
|
||||
# current_app.logger.info(f'Transcribed audio for tenant: {tenant_id}')
|
||||
# except Exception as e:
|
||||
# current_app.logger.error(f'Error transcribing audio for tenant: {tenant_id}, with error: {e}')
|
||||
# raise
|
||||
#
|
||||
#
|
||||
# def annotate_transcription(tenant, document_version, input_file, output_file, model_variables):
|
||||
# try:
|
||||
# current_app.logger.debug(f'Annotating transcription for tenant {tenant.id}')
|
||||
#
|
||||
# char_splitter = CharacterTextSplitter(separator='.',
|
||||
# chunk_size=model_variables['annotation_chunk_length'],
|
||||
# chunk_overlap=0)
|
||||
#
|
||||
# headers_to_split_on = [
|
||||
# ("#", "Header 1"),
|
||||
# ("##", "Header 2"),
|
||||
# ]
|
||||
# markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on, strip_headers=False)
|
||||
#
|
||||
# llm = model_variables['llm']
|
||||
# template = model_variables['transcript_template']
|
||||
# language_template = create_language_template(template, document_version.language)
|
||||
# transcript_prompt = ChatPromptTemplate.from_template(language_template)
|
||||
# setup = RunnablePassthrough()
|
||||
# output_parser = StrOutputParser()
|
||||
#
|
||||
# # Download the transcription file from MinIO
|
||||
# transcript_data = minio_client.download_document_file(tenant.id, document_version.doc_id,
|
||||
# document_version.language, document_version.id,
|
||||
# input_file)
|
||||
# transcript = transcript_data.decode('utf-8')
|
||||
#
|
||||
# chain = setup | transcript_prompt | llm | output_parser
|
||||
#
|
||||
# chunks = char_splitter.split_text(transcript)
|
||||
# all_markdown_chunks = []
|
||||
# last_markdown_chunk = ''
|
||||
# for chunk in chunks:
|
||||
# current_app.logger.debug(f'Annotating next chunk of {len(chunks)} for tenant {tenant.id}')
|
||||
# full_input = last_markdown_chunk + '\n' + chunk
|
||||
# if tenant.embed_tuning:
|
||||
# current_app.embed_tuning_logger.debug(f'Annotating chunk: \n '
|
||||
# f'------------------\n'
|
||||
# f'{full_input}\n'
|
||||
# f'------------------\n')
|
||||
# input_transcript = {'transcript': full_input}
|
||||
# markdown = chain.invoke(input_transcript)
|
||||
# # GPT-4o returns some kind of content description: ```markdown <text> ```
|
||||
# if markdown.startswith("```markdown"):
|
||||
# markdown = "\n".join(markdown.strip().split("\n")[1:-1])
|
||||
# if tenant.embed_tuning:
|
||||
# current_app.embed_tuning_logger.debug(f'Markdown Received: \n '
|
||||
# f'------------------\n'
|
||||
# f'{markdown}\n'
|
||||
# f'------------------\n')
|
||||
# md_header_splits = markdown_splitter.split_text(markdown)
|
||||
# markdown_chunks = [doc.page_content for doc in md_header_splits]
|
||||
# # claude-3.5-sonnet returns introductory text
|
||||
# if not markdown_chunks[0].startswith('#'):
|
||||
# markdown_chunks.pop(0)
|
||||
# last_markdown_chunk = markdown_chunks[-1]
|
||||
# last_markdown_chunk = "\n".join(markdown.strip().split("\n")[1:])
|
||||
# markdown_chunks.pop()
|
||||
# all_markdown_chunks += markdown_chunks
|
||||
#
|
||||
# all_markdown_chunks += [last_markdown_chunk]
|
||||
#
|
||||
# annotated_transcript = '\n'.join(all_markdown_chunks)
|
||||
#
|
||||
# # Upload the annotated transcript to MinIO
|
||||
# minio_client.upload_document_file(
|
||||
# tenant.id,
|
||||
# document_version.doc_id,
|
||||
# document_version.language,
|
||||
# document_version.id,
|
||||
# output_file,
|
||||
# annotated_transcript.encode('utf-8')
|
||||
# )
|
||||
#
|
||||
# current_app.logger.info(f'Annotated transcription for tenant {tenant.id}')
|
||||
# except Exception as e:
|
||||
# current_app.logger.error(f'Error annotating transcription for tenant {tenant.id}, with error: {e}')
|
||||
# raise
|
||||
|
||||
|
||||
def create_potential_chunks_for_markdown(tenant_id, document_version, input_file):
|
||||
try:
|
||||
current_app.logger.info(f'Creating potential chunks for tenant {tenant_id}')
|
||||
|
||||
Reference in New Issue
Block a user