He configurado las funciones de LLM, incrustación y persona; sin embargo, mi prompt no está proporcionando las respuestas esperadas de las preguntas y respuestas o de los recursos de wiki disponibles dentro de nuestra comunidad.
LLM autoalojado: mistral:latest
Incrustación autoalojada: all-minilm:latest
Persona:
¿Podría alguien ayudarme más con lo que hay que hacer? Teniendo en cuenta a un novato en IA.
¿Qué modelo Mistral exacto es este?
¿Puedes compartir el prompt?
Puedes añadir Search como una "Herramienta Forzada" para la primera interacción para ayudar a anclar el modelo.
@Falco, A continuación se detallan los detalles para responder:
¿Qué modelo exacto de Mistral es este?
Modelo LLM: mistral:latest
Enlace:
El modelo en https://ollama.com/library/mistral:latest es:
Mistral 7B v0.3 — un modelo de código abierto de 7 mil millones de parámetros lanzado por Mistral AI.
¿Puedes compartir el prompt?
Prompt del sistema:
Eres un asistente de conocimiento comunitario diseñado para este foro llamado {site_title} y con URL de sitio {site_url}, teniendo ingenieros como usuarios.
Siempre busca y referencia publicaciones relevantes del foro, artículos de wiki y discusiones etiquetadas antes de generar una respuesta.
Tu primera prioridad es usar el contenido recuperado del foro (a través de la búsqueda de embeddings) para elaborar respuestas.
Prefiere resúmenes y citas de publicaciones existentes.
Si se encuentran múltiples temas relacionados, combínalos claramente.
Solo si no existe contenido relevante, responde usando tu conocimiento general a través del LLM.
Incluye títulos de temas o URLs al referenciar publicaciones.
Nunca inventes o crees respuestas no respaldadas por datos del foro.
Sé factual, conciso y profesional.
Cuando los usuarios hagan preguntas amplias, prefiere resumir múltiples fuentes en lugar de adivinar.
Siempre prefiere el contexto de categorías, etiquetas y wikis indexados en embeddings.
Se actualizó la herramienta forzada como se sugirió
Me temo que un modelo de 2023 reutilizado no será suficiente aquí. Además, según la propia documentación de Ollama para este modelo, solo admite llamadas a herramientas en la API sin procesar, que no es lo que usamos.
En general, esta es una mala elección para AI Bot hoy.
En su lugar, use uno de los siguientes:
Hola @Falco, y lo siento, gracias por las aportaciones. Lo comprobaremos y le informaremos más adelante.
@Falco Recibiendo un error 502 al habilitar LLM. Por favor, encuentra los registros a continuación.
Mensaje
El worker de Unicorn recibió la señal USR2 indicando que está a punto de agotar el tiempo de espera, volcando el backtrace para el hilo principal
config/unicorn.conf.rb:203:in `backtrace'
config/unicorn.conf.rb:203:in `block (2 levels) in reload'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:229:in `wait_readable'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:229:in `rbuf_fill'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:199:in `readuntil'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:209:in `readline'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http/response.rb:158:in `read_status_line'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http/response.rb:147:in `read_new'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2420:in `block in transport_request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2411:in `catch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2411:in `transport_request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2384:in `request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/patches/net_patches.rb:19:in `block in request_with_mini_profiler'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/mini_profiler/profiling_methods.rb:45:in `step'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/patches/net_patches.rb:18:in `request_with_mini_profiler'
/var/www/discourse/plugins/discourse-ai/lib/completions/endpoints/base.rb:168:in `block in perform_completion!'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:1632:in `start'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:1070:in `start'
/var/www/di...
Backtrace
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:130:in `block in warn'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `block in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `each'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `dispatch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:130:in `warn'
/var/www/discourse/lib/signal_trap_logger.rb:40:in `public_send'
/var/www/discourse/lib/signal_trap_logger.rb:40:in `block (2 levels) in ensure_logging_thread_running'
internal:kernel:187:in `loop'
/var/www/discourse/lib/signal_trap_logger.rb:37:in `block in ensure_logging_thread_running'
Establezca el proveedor en OpenAI si está utilizando la API compatible con OpenAI de Ollama.
He intentado con el proveedor openAI y el problema persiste.
Mensaje
Unicorn worker received USR2 signal indicating it is about to timeout, dumping backtrace for main thread
config/unicorn.conf.rb:203:in `backtrace'
config/unicorn.conf.rb:203:in `block (2 levels) in reload'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:229:in `wait_readable'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:229:in `rbuf_fill'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:199:in `readuntil'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-protocol-0.2.2/lib/net/protocol.rb:209:in `readline'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http/response.rb:158:in `read_status_line'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http/response.rb:147:in `read_new'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2420:in `block in transport_request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2411:in `catch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2411:in `transport_request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:2384:in `request'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/patches/net_patches.rb:19:in `block in request_with_mini_profiler'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/mini_profiler/profiling_methods.rb:45:in `step'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/rack-mini-profiler-4.0.1/lib/patches/net_patches.rb:18:in `request_with_mini_profiler'
/var/www/discourse/plugins/discourse-ai/lib/completions/endpoints/base.rb:168:in `block in perform_completion!'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:1632:in `start'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/net-http-0.6.0/lib/net/http.rb:1070:in `start'
/var/www/di...
Backtrace
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:130:in `block in warn'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `block in dispatch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `each'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:231:in `dispatch'
/var/www/discourse/vendor/bundle/ruby/3.3.0/gems/activesupport-8.0.2.1/lib/active_support/broadcast_logger.rb:130:in `warn'
/var/www/discourse/lib/signal_trap_logger.rb:40:in `public_send'
/var/www/discourse/lib/signal_trap_logger.rb:40:in `block (2 levels) in ensure_logging_thread_running'
kernel:187:in `loop'
/var/www/discourse/lib/signal_trap_logger.rb:37:in `block in ensure_logging_thread_running'
¿Puede tu contenedor de Discourse acceder al servicio en el puerto 11434? Si se está ejecutando en el host, necesitas proporcionar una forma para que la red cruce el límite del contenedor.
Sí, pude acceder a uno de los modelos LLM anteriormente con el mismo puerto con el contenedor de Discourse.
¿Podrías ayudarme con esto y cuál es el requisito mínimo de RAM donde se está ejecutando este LLM?
Así que puede ser
Hola @Falco
He integrado con éxito el Modelo de Lenguaje (LLM) que se describe a continuación. Sin embargo, me he encontrado con un problema durante mi proceso de consulta: el prompt no tiene en cuenta el contenido específico de mi foro. En lugar de basarse en las discusiones y perspectivas relevantes dentro de mi foro, está generando respuestas basadas en información preexistente del LLM. ¿Qué pasos debo seguir para rectificar esta situación y asegurar que el modelo incorpore eficazmente las contribuciones únicas de mi foro?
LLM utilizado como se sugirió anteriormente:
Ejemplo:
En la sección Herramientas de la persona, asegúrate de que tenga acceso tanto a Buscar como a Leer, y configura Buscar como Herramienta forzada.
Además, ¿es el contenido del foro donde se supone que la Persona debe buscar todo público?
@Falco, me gustaría que mi bot proporcione respuestas derivadas del contenido almacenado en mi Base de Conocimiento. ¿Podrías compartir la configuración completa relacionada con el plugin de IA y otros? Además, ¿necesitamos ejecutar algún comando específico dentro de la aplicación para habilitar la Generación Aumentada por Recuperación (RAG)?
@Falco ¿podrías revisar y dar tu opinión sobre lo anterior?
Habilite la depuración del bot a través de AI bot debugging allowed groups y compruebe qué llamadas a herramientas está realizando el bot y cuáles son las respuestas.
@Falco A continuación se muestran los detalles
Tokens de solicitud: 1304
Tokens de respuesta: 652
modelo: gemma3:1b
mensajes:
0:
rol: sistema
contenido: Eres un asistente de Discourse útil.
Comprendes y generas Markdown de Discourse.
Vives en un mensaje de foro de Discourse.
Vives en el foro con la URL: https://faq.company.com
El título de tu sitio: FAQ de la empresa
La descripción es: Portal comunitario de la empresa
Los participantes en esta conversación son: Forum_Helper_bot, testuser
La fecha actual es: 2025-12-02 08:36:27 UTC, mucho ha cambiado desde que fuiste entrenado.
Fuiste entrenado con datos ANTIGUOS, apóyate en la búsqueda para obtener información actualizada sobre este foro
Al buscar, intenta SIMPLIFICAR los términos de búsqueda
La búsqueda de Discourse une todos los términos con Y. Reduce y simplifica los términos para encontrar más resultados.
En este entorno tienes acceso a un conjunto de herramientas que puedes usar para responder a la pregunta del usuario.
Puedes llamarlas así.
<function_calls>
<invoke>
<tool_name>$TOOL_NAME</tool_name>
<parameters>
<$PARAMETER_NAME>$PARAMETER_VALUE</$PARAMETER_NAME>
...
</parameters>
</invoke>
</function_calls>
Si deseas llamar a varias funciones en una sola respuesta, envuelve múltiples <invoke>
bbloquear en un único bloque <function_calls>.
- Prefiera siempre comenzar con llamadas a herramientas, si necesita ejecutar alguna.
- Evite cualquier cortesía antes de las llamadas a herramientas, por ejemplo: "Déjame buscar eso por ti..." etc.
- NO codifique entidades HTML en las llamadas a herramientas. Puede usar <![CDATA[...]]> para codificar si es necesario.
Aquí está la lista completa de herramientas disponibles:
<herramientas>
<descripción_herramienta>
<nombre_herramienta>categorías</nombre_herramienta>
<descripción>Listará las categorías en la instancia actual de Discourse, prefiera formatear con # delante del nombre de la categoría</descripción>
<parámetros>
</parámetros>
</descripción_herramienta>
<descripción_herramienta>
<nombre_herramienta>buscar</nombre_herramienta>
<descripción>Buscará temas en la instancia actual de Discourse, al renderizar prefiera siempre enlazar a los temas que encuentre</descripción>
<parámetros>
<parámetro>
<nombre>consulta_búsqueda</nombre>
<tipo>cadena</tipo>
<descripción>Palabras clave específicas para buscar, separadas por espacios (corrija la ortografía incorrecta, elimine palabras de conexión)</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>usuario</nombre>
<tipo>cadena</tipo>
<descripción>Filtre los resultados de la búsqueda a este nombre de usuario (solo incluya si el usuario solicita explícitamente filtrar por usuario)</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>orden</nombre>
<tipo>cadena</tipo>
<descripción>orden de los resultados de la búsqueda</descripción>
<requerido>falso</requerido>
<opciones>latest,latest_topic,oldest,views,likes</opciones>
</parámetro>
<parámetro>
<nombre>máx_resultados</nombre>
<tipo>entero</tipo>
<descripción>limite el número de resultados devueltos (generalmente prefiera mantenerse en el predeterminado)</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>máx_publicaciones</nombre>
<tipo>entero</tipo>
<descripción>número máximo de publicaciones en los temas (temas donde mucha gente publicó)</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>etiquetas</nombre>
<tipo>cadena</tipo>
<descripción>lista de etiquetas para buscar. Use + para unir con OR, use , para unir con AND</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>categoría</nombre>
<tipo>cadena</tipo>
<descripción>nombre de la categoría para filtrar</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>antes</nombre>
<tipo>cadena</tipo>
<descripción>solo temas creados antes de una fecha específica AAAA-MM-DD</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>después</nombre>
<tipo>cadena</tipo>
<descripción>solo temas creados después de una fecha específica AAAA-MM-DD</descripción>
<requerido>falso</requerido>
</parámetro>
<parámetro>
<nombre>estado</nombre>
<tipo>cadena</tipo>
<descripción>buscar temas en un estado particular</descripción>
<requerido>falso</requerido>
<opciones>open,closed,archived,noreplies,single_user</opciones>
</parámetro>
</parámetros>
</descripción_herramienta>
<descripción_herramienta>
<nombre_herramienta>leer</nombre_herramienta>
<descripción>Leerá un tema o una publicación en esta instancia de Discourse</descripción>
<parámetros>
<parámetro>
<nombre>id_tema</nombre>
<tipo>entero</tipo>
<descripción>el id del tema a leer</descripción>
<requerido>verdadero</requerido>
</parámetro>
<parámetro>
<nombre>números_publicación</nombre>
<tipo>array</tipo>
<descripción>los números de publicación a leer (opcional)</descripción>
<requerido>falso</requerido>
<tipo_elemento_array>entero</tipo_elemento_array>
</parámetro>
</parámetros>
</descripción_herramienta>
<descripción_herramienta>
<nombre_herramienta>etiquetas</nombre_herramienta>
<descripción>Listará las 100 etiquetas más populares en la instancia actual de Discourse</descripción>
<parámetros>
</parámetros>
</descripción_herramienta>
</herramientas>
1:
rol: usuario
nombre: testuser
contenido: Cómo resolver - el paquete apt zliblg:i386 no existe
flujo: verdadero
opciones_flujo:
incluir_uso: verdadero
Respuesta
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"Okay"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":","},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" let"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"'"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"s"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" tackle"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" the"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" \""},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"apt"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" package"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" z"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"lib"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"lg"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":":"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"i"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"3"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"8"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"6"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" does"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" not"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" exist"},"finish_reason":null}]}
datos: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"\""},"finish_reason":null}]}
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¿Por qué marcó la casilla Deshabilitar compatibilidad con herramientas nativas (usar herramientas basadas en XML) (opcional) en la configuración de LLM? Gemma 3 admite herramientas nativas.
Gemma3 1B es demasiado pequeño para la invocación de herramientas de manera confiable; es un modelo más pequeño que los modelos para hardware integrado o para ejecutarse en un navegador. Pruebe, como mínimo, las variantes de 4B o 12B.
@Falco intentaremos más con las entradas proporcionadas y te responderemos