KI-Bot zur Konfiguration für ein Support-Community-Forum mit der neuesten Version von Discourse unterstützen

Unterstützung
1

Ich habe die LLM-, Embedding- und Persona-Funktionen eingerichtet. Meine Eingabeaufforderung liefert jedoch nicht die erwarteten Antworten auf die Fragen und Antworten oder die verfügbaren Wiki-Ressourcen in unserer Community.

Selbst gehostetes LLM: mistral:latest
Selbst gehostetes Embedding: all-minilm:latest

Persona:

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Könnte mir jemand weiterhelfen, was noch getan werden muss? Unter Berücksichtigung eines KI-Neulings.

2

Welches genaue Mistral-Modell ist das?

Können Sie die Eingabeaufforderung teilen?

Sie können Search als "erzwungenes Werkzeug" für die erste Interaktion hinzufügen, um das Modell zu unterstützen.

3

@Falco, unten sind die Details für die Antwort auf die Nachverfolgung:

\u003eWelches genaue Mistral-Modell ist das?

LLM-Modell: mistral:latest

Link:
Das Modell unter https://ollama.com/library/mistral:latest ist:

Mistral 7B v0.3 — ein Open-Source-Modell mit 7 Milliarden Parametern, veröffentlicht von Mistral AI.

\u003e Können Sie den Prompt teilen?

System-Prompt:
Sie sind ein Community-Wissensassistent, der für dieses Forum namens {site_title} mit der Website-URL {site_url} entwickelt wurde und Ingenieure als Benutzer hat.

Suchen und referenzieren Sie immer relevante Forumsposts, Wiki-Artikel und getaggte Diskussionen, bevor Sie eine Antwort generieren.

Ihre erste Priorität ist es, abgerufene Foreninhalte (durch Einbettungssuche) zu verwenden, um Antworten zu formulieren.

  Bevorzugen Sie Zusammenfassungen und Zitate aus bestehenden Beiträgen.
  Wenn mehrere verwandte Themen gefunden werden, kombinieren Sie sie klar.
  Nur wenn keine relevanten Inhalte vorhanden sind, antworten Sie mit Ihrem allgemeinen Wissen durch das LLM.
  Fügen Sie Themenüberschriften oder URLs hinzu, wenn Sie auf Beiträge verweisen.
  Erfinden Sie niemals Antworten, die nicht durch Forendaten gestützt werden.
  Seien Sie sachlich, prägnant und professionell.
  Wenn Benutzer breite Fragen stellen, fassen Sie lieber mehrere Quellen zusammen, anstatt zu raten.
  Bevorzugen Sie immer den Kontext aus Kategorien, Tags und Wikis, die in Einbettungen indiziert sind.

Das erzwungene Tool wurde wie vorgeschlagen aktualisiert

4

Ich befürchte, ein wiederaufbereitetes Modell von 2023 wird hier nicht ausreichen. Außerdem unterstützt es laut Ollamas eigener Dokumentation für dieses Modell nur Tool Calling über die Raw API, was wir nicht verwenden.

Insgesamt ist dies heute eine schlechte Wahl für AI Bot.

Verwenden Sie stattdessen eines der folgenden Modelle:

1 „Gefällt mir“
5

Hallo @Falco, und entschuldigen Sie, vielen Dank für die Eingaben. Wir werden dies prüfen und Sie weiter informieren.

1 „Gefällt mir“
6

@Falco Sie erhalten einen 502-Fehler beim Aktivieren von LLM. Bitte finden Sie die Protokolle unten

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Nachricht

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'
internal:kernel:187:in `loop'
/var/www/discourse/lib/signal_trap_logger.rb:37:in `block in ensure_logging_thread_running'
7

Stellen Sie den Anbieter auf OpenAI ein, wenn Sie die OpenAI-kompatible API von Ollama verwenden.

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8

@Falco

Ich habe es mit dem openAI-Anbieter versucht, aber das Problem besteht weiterhin.

Nachricht

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'
internal:kernel:187:in `loop'
/var/www/discourse/lib/signal_trap_logger.rb:37:in `block in ensure_logging_thread_running'
9

Kann Ihr Discourse-Container auf den Dienst im Port 11434 zugreifen? Wenn er auf dem Host läuft, müssen Sie eine Möglichkeit bereitstellen, damit das Netzwerk die Containergrenze überschreiten kann.

10

Ja, ich konnte früher mit demselben Port über einen Discourse-Container auf eines der LLM-Modelle zugreifen.

11

Könnten Sie mir bitte dabei helfen und wie hoch ist der minimale RAM-Bedarf, wo diese LLM läuft.

12

Es könnte also sein

13

Hallo @Falco

Ich habe das unten beschriebene Sprachmodell (LLM) erfolgreich integriert. Ich bin jedoch auf ein Problem während meines Abfrageprozesses gestoßen: Der Prompt berücksichtigt nicht den spezifischen Inhalt meines Forums. Anstatt relevante Diskussionen und Erkenntnisse aus meinem Forum zu ziehen, generiert er Antworten, die auf bereits vorhandenen Informationen aus dem LLM basieren. Welche Schritte sollte ich unternehmen, um diese Situation zu beheben und sicherzustellen, dass das Modell die einzigartigen Beiträge meines Forums effektiv einbezieht?

Verwendetes LLM wie zuvor vorgeschlagen:

Beispiel:

image

14

Stellen Sie im Abschnitt Tools der Persona sicher, dass sie Zugriff auf Suchen und Lesen hat, und setzen Sie Suchen auf Erzwungenes Tool.

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Außerdem, sind die Foreninhalte, in denen die Persona suchen soll, alle öffentlich?

15

@Falco, ich möchte, dass mein Bot Antworten liefert, die aus den Inhalten meiner Wissensdatenbank stammen. Könnten Sie bitte die umfassenden Einstellungen für das KI-Plugin und andere mitteilen? Müssen wir außerdem bestimmte Befehle in der Anwendung ausführen, um Retrieval-Augmented Generation (RAG) zu aktivieren?

16

@Falco könnten Sie bitte das oben Genannte überprüfen und Feedback geben.

17

Bot-Debugging über AI bot debugging allowed groups aktivieren und prüfen, welche Tool-Aufrufe der Bot vornimmt und wie die Antworten lauten.

18

@Falco The following are the details

Request tokens: 1304
Response tokens: 652
model: gemma3:1b
messages:
0:
role: system
content: You are a helpful Discourse assistant.
You _understand_ and **generate** Discourse Markdown.
You live in a Discourse Forum Message.

You live in the forum with the URL: https://faq.company.com
The title of your site: company FAQ
The description is: company Community Portal
The participants in this conversation are: Forum_Helper_bot, testuser
The date now is: 2025-12-02 08:36:27 UTC, much has changed since you were trained.

You were trained on OLD data, lean on search to get up to date information about this forum
When searching try to SIMPLIFY search terms
Discourse search joins all terms with AND. Reduce and simplify terms to find more results.

In this environment you have access to a set of tools you can use to answer the user's question.
You may call them like this.

<function_calls>
<invoke>
<tool_name>$TOOL_NAME</tool_name>
<parameters>
<$PARAMETER_NAME>$PARAMETER_VALUE</$PARAMETER_NAME>
...
</parameters>
</invoke>
</function_calls>

If you wish to call multiple function in one reply, wrap multiple <invoke>
block in a single <function_calls> block.

- Always prefer to lead with tool calls, if you need to execute any.
- Avoid all niceties prior to tool calls, Eg: "Let me look this up for you.." etc.
- DO NOT encode HTML entities in tool calls. You may use <![CDATA[...]]> for encoding if required.
Here are the complete list of tools available:

<tools>
<tool_description>
<tool_name>categories</tool_name>
<description>Will list the categories on the current discourse instance, prefer to format with # in front of the category name</description>
<parameters>
</parameters>
</tool_description>
<tool_description>
<tool_name>search</tool_name>
<description>Will search topics in the current discourse instance, when rendering always prefer to link to the topics you find</description>
<parameters>
<parameter>
<name>search_query</name>
<type>string</type>
<description>Specific keywords to search for, space separated (correct bad spelling, remove connector words)</description>
<required>false</required>
</parameter>
<parameter>
<name>user</name>
<type>string</type>
<description>Filter search results to this username (only include if user explicitly asks to filter by user)</description>
<required>false</required>
</parameter>
<parameter>
<name>order</name>
<type>string</type>
<description>search result order</description>
<required>false</required>
<options>latest,latest_topic,oldest,views,likes</options>
</parameter>
<parameter>
<name>max_results</name>
<type>integer</type>
<description>limit number of results returned (generally prefer to just keep to default)</description>
<required>false</required>
</parameter>
<parameter>
<name>max_posts</name>
<type>integer</type>
<description>maximum number of posts on the topics (topics where lots of people posted)</description>
<required>false</required>
</parameter>
<parameter>
<name>tags</name>
<type>string</type>
<description>list of tags to search for. Use + to join with OR, use , to join with AND</description>
<required>false</required>
</parameter>
<parameter>
<name>category</name>
<type>string</type>
<description>category name to filter to</description>
<required>false</required>
</parameter>
<parameter>
<name>before</name>
<type>string</type>
<description>only topics created before a specific date YYYY-MM-DD</description>
<required>false</required>
</parameter>
<parameter>
<name>after</name>
<type>string</type>
<description>only topics created after a specific date YYYY-MM-DD</description>
<required>false</required>
</parameter>
<parameter>
<name>status</name>
<type>string</type>
<description>search for topics in a particular state</description>
<required>false</required>
<options>open,closed,archived,noreplies,single_user</options>
</parameter>
</parameters>
</tool_description>
<tool_description>
<tool_name>read</tool_name>
<description>Will read a topic or a post on this Discourse instance</description>
<parameters>
<parameter>
<name>topic_id</name>
<type>integer</type>
<description>the id of the topic to read</description>
<required>true</required>
</parameter>
<parameter>
<name>post_numbers</name>
<type>array</type>
<description>the post numbers to read (optional)</description>
<required>false</required>
<array_item_type>integer</array_item_type>
</parameter>
</parameters>
</tool_description>
<tool_description>
<tool_name>tags</tool_name>
<description>Will list the 100 most popular tags on the current discourse instance</description>
<parameters>
</parameters>
</tool_description>
</tools>
1:
role: user
name: testuser
content: How to resolve - apt package zliblg:i386 does not exist
stream: true
stream_options:
include_usage: true

Response

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"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}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" error"},"finish_reason":null}]}

data: {"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}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" This"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" usually"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664602,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" means"},"finish_reason":null}]}

data: {"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}]}

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data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664603,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":"Update"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664603,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" Your"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664603,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" Package"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664603,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":" List"},"finish_reason":null}]}

data: {"id":"chatcmpl-678","object":"chat.completion.chunk","created":1764664603,"model":"gemma3:1b","system_fingerprint":"fp_ollama","choices":[{"index":0,"delta":{"role":"assistant","content":":**"},"finish_reason":null}]}
19

  1. Warum haben Sie bei der LLM-Konfiguration „Native Tool-Unterstützung deaktivieren (XML-basierte Tools verwenden) (optional)“ aktiviert? Gemma 3 unterstützt native Tools.

  2. Gemma3 1B ist viel zu klein für zuverlässiges Tool-Aufrufen; es ist ein Modell, das kleiner ist als Modelle für eingebettete Hardware oder für die Ausführung im Browser. Versuchen Sie es mit mindestens den Varianten 4B oder 12B.

20

@Falco Wir werden es mit den bereitgestellten Eingaben weiter versuchen und uns bei Ihnen melden