¿Configuraciones para las embeddings bge-large-en de Hugging Face? - ¡Los bots RAG no responden!

Soporte
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Por favor, asesora… ¿cuáles son la mejor configuración para permitir que el modelo de incrustación bge-large-en funcione como el servicio de vectores predeterminado de Discourse AI?

Tengo una instancia de bge-large-en en ejecución en AWS y sé que mi Discourse AI se está comunicando con ella (ver prueba a continuación), pero la incrustación no funciona en general (la incrustación de OpenAI funciona bien).

RESUMEN DEL PROBLEMA: Los bots RAG no responden cuando la incrustación se establece en HF bge-large-en.

aquí está el modelo de incrustación de AWS:

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aquí están la configuración de Discourse AI:

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aquí hay una prueba de ‘Ejecutar prueba’ de un LLM personalizado de Discourse solo para verificar la conectividad…

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aquí están los registros de bge-large-en en el lado de AWS:

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¡¡Muchas gracias!!

Aquí está el registro de errores…

Job exception: can't quote Array

hostname ai-qa-ubuntu-s-1vcpu-2gb-amd-sfo3-01-app
process_id 1165935
application_version f9192835a7e4d2067c3d1844f43f9e7b69de39e7
current_db default
current_hostname ai-qa.net
job Jobs::CreateAiReply
problem_db default
time 7:22 pm
opts post_id 618
--- --- --- ---
--- ---
bot_user_id -1208
persona_id 5
current_site_id default


Backtrace

/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/connection_adapters/abstract/quoting.rb:25:in `quote'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/connection_adapters/postgresql/quoting.rb:69:in `quote'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/connection_adapters/abstract/quoting.rb:51:in `quote_bound_value'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:193:in `block in quote_bound_value'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:193:in `map!'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:193:in `quote_bound_value'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:171:in `replace_bind_variable'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:180:in `block in replace_named_bind_variables'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:176:in `gsub'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:176:in `replace_named_bind_variables'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activerecord-7.0.8.1/lib/active_record/sanitization.rb:128:in `sanitize_sql_array'
/var/www/discourse/lib/mini_sql_multisite_connection.rb:21:in `public_send'
/var/www/discourse/lib/mini_sql_multisite_connection.rb:21:in `encode'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/connection.rb:64:in `to_sql'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/postgres/connection.rb:202:in `run'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/active_record_postgres/connection.rb:38:in `block in run'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/active_record_postgres/connection.rb:34:in `block in with_lock'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activesupport-7.0.8.1/lib/active_support/concurrency/load_interlock_aware_monitor.rb:25:in `handle_interrupt'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activesupport-7.0.8.1/lib/active_support/concurrency/load_interlock_aware_monitor.rb:25:in `block in synchronize'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activesupport-7.0.8.1/lib/active_support/concurrency/load_interlock_aware_monitor.rb:21:in `handle_interrupt'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/activesupport-7.0.8.1/lib/active_support/concurrency/load_interlock_aware_monitor.rb:21:in `synchronize'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/active_record_postgres/connection.rb:34:in `with_lock'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/active_record_postgres/connection.rb:38:in `run'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/mini_sql-1.5.0/lib/mini_sql/postgres/connection.rb:99:in `query'
/var/www/discourse/plugins/discourse-ai/lib/embeddings/vector_representations/base.rb:272:in `asymmetric_rag_fragment_similarity_search'
/var/www/discourse/plugins/discourse-ai/lib/ai_bot/personas/persona.rb:286:in `rag_fragments_prompt'
/var/www/discourse/plugins/discourse-ai/lib/ai_bot/personas/persona.rb:156:in `craft_prompt'
/var/www/discourse/plugins/discourse-ai/lib/ai_bot/bot.rb:54:in `reply'
/var/www/discourse/plugins/discourse-ai/lib/ai_bot/playground.rb:424:in `reply_to'
/var/www/discourse/plugins/discourse-ai/app/jobs/regular/create_ai_reply.rb:18:in `execute'
/var/www/discourse/app/jobs/base.rb:305:in `block (2 levels) in perform'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/rails_multisite-6.0.0/lib/rails_multisite/connection_management/null_instance.rb:49:in `with_connection'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/rails_multisite-6.0.0/lib/rails_multisite/connection_management.rb:21:in `with_connection'
/var/www/discourse/app/jobs/base.rb:292:in `block in perform'
/var/www/discourse/app/jobs/base.rb:288:in `each'
/var/www/discourse/app/jobs/base.rb:288:in `perform'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:202:in `execute_job'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:170:in `block (2 levels) in process'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/middleware/chain.rb:177:in `block in invoke'
/var/www/discourse/lib/sidekiq/pausable.rb:132:in `call'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/middleware/chain.rb:179:in `block in invoke'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/middleware/chain.rb:182:in `invoke'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:169:in `block in process'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:136:in `block (6 levels) in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/job_retry.rb:113:in `local'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:135:in `block (5 levels) in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq.rb:44:in `block in <module:Sidekiq>'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:131:in `block (4 levels) in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:263:in `stats'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:126:in `block (3 levels) in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/job_logger.rb:13:in `call'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:125:in `block (2 levels) in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/job_retry.rb:80:in `global'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:124:in `block in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/job_logger.rb:39:in `prepare'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:123:in `dispatch'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:168:in `process'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:78:in `process_one'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/processor.rb:68:in `run'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/component.rb:8:in `watchdog'
/var/www/discourse/vendor/bundle/ruby/3.2.0/gems/sidekiq-6.5.12/lib/sidekiq/component.rb:17:in `block in safe_thread'
2 Me gusta
3

¡Gracias por informarnos, le echaremos un vistazo!

2 Me gusta
4

¿Cuál es la salida de ejecutar los siguientes comandos en una consola de Rails?

strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
vector_rep = DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
vector_rep.vector_from("test")

Además, nuestra API está diseñada para funcionar contra alguien que ejecuta GitHub - huggingface/text-embeddings-inference: A blazing fast inference solution for text embeddings models por sí mismo según la documentación, por lo que es posible que no funcione contra la versión alojada.

Si proporciona el backtrace, podemos investigar para que funcione.

2 Me gusta
5

@Falco

aquí está lo que sucedió cuando ejecuté el código de prueba (con bge-large-en ejecutándose en una instancia de punto final dedicado de AWS configurada como modelo de incrustación)

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root@studyqa-ubuntu-s-1vcpu-2gb-amd-sfo3-01-app:/var/www/discourse# rails c

[1] pry(main)> strategy = DiscourseAi::Embeddings::Strategies::Truncation.new

puts "Strategy initialized"

vector_rep = DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)

puts "Vector representation obtained"

vector = vector_rep.vector_from("test")

[1] pry(main)> strategy = DiscourseAi::Embeddings::Strategies::Truncation.new

puts "Strategy initialized"

vector_rep = DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)

puts "Vector representation obtained"

vector = vector_rep.vector_from("test")

puts "Vector generated"

puts vector.inspect

Strategy initialized

Vector representation obtained

Vector generated

[:embeddings, [-0.0020444912370294333, 0.008787356317043304, -0.010865539312362671, 0.01865551434457302, -0.02099628746509552, -0.009864491410553455, -0.0011329081607982516, 0.02949545904994011, 0.027839021757245064, 0.043966952711343765, 0.0406080037355423, 0.0016647017328068614, 0.007204003632068634, -0.03770752251148224, -0.025242917239665985, -0.0015279072104021907, -0.02805529721081257, -0.020901955664157867, -0.029206447303295135, -0.006209365092217922, -0.02105099707841873,

etc.

parece que está alcanzando bge-large-en en aws:

- 2024-05-29T13:57:34.609+00:00 Batches: 0%| | 0/1 [00:00<?, ?it/s] Batches: 100%|██████████| 1/1 [00:00<00:00, 4.80it/s] Batches: 100%|██████████| 1/1 [00:00<00:00, 4.79it/s]

• 2024/05/29 09:57:34
INFO | POST / | Duration: 212.84 ms


- 2024-05-29T13:57:53.806+00:00 Batches: 0%| | 0/1 [00:00<?, ?it/s] Batches: 100%|██████████| 1/1 [00:01<00:00, 1.97s/it] Batches: 100%|██████████| 1/1 [00:01<00:00, 1.97s/it]

• 2024/05/29 09:57:53
INFO | POST / | Duration: 1978.36 ms
1 me gusta
6

¿Así que parece que está funcionando bien?

¿Quizás el problema sea el reordenador? ¿Puedes anular la configuración de ai_hugging_face_tei_reranker_endpoint y probar si RAG funciona?

7

desactivado el reranker.. todavía no hay embedding.. recibo este mensaje en ambos extremos:

Prueba de ejecución de Discourse LLM:

Intentar contactar con el modelo devolvió este error: {“error”:“Body needs to provide a inputs key, recieved: b’{"model":"bge-large-en","temperature":0.7,"messages":[{"role":"system","content":"You are a helpful bot"},{"role":"user","content":"How much is 1 + 1?"}],"max_tokens":1009}'”}

log de bge-large-en

• 2024/05/29 13:40:03

ERROR | Body needs to provide a inputs key, recieved: b’{"model":"bge-large-en","temperature":0.7,"messages":[{"role":"system","content":"You are a helpful bot"},{"role":"user","content":"How much is 1 + 1?"}],"max_tokens":1009}’

discourse b1b218aa99
discourse-ai d812ecf5

8

Así no es como deberíamos probar los embeddings :slight_smile: esa es una prueba de LLM, no una prueba de modelo de embeddings que esperaría números como respuesta. La interfaz de usuario de LLM no es donde añadirías esto, necesitaríamos una interfaz de usuario de Embeddings para ello, la cual aún no tenemos. Los modelos de embeddings solo se configuran en la configuración del sitio.

9

Sí. Tiene sentido.

(Intenté señalar que solo estaba usando la prueba de ejecución del LLM para confirmar la “conectividad” (ver abajo). Debería haberlo dejado más claro.)

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1 me gusta