Discourseの最新バージョンでサポートコミュニティフォーラム用にAIボットを設定するサポート

サポート
1

LLM、埋め込み、ペルソナ機能は設定しましたが、質問と回答やコミュニティ内の利用可能なWikiリソースから期待される応答がプロンプトから得られていません。

セルフホストLLM: mistral:latest
セルフホスト埋め込み: all-minilm:latest

ペルソナ:

image
image815×823 24.6 KB

image
image722×786 25.4 KB

image
image618×793 24.6 KB

次に何をすべきか、どなたかさらに助けていただけますでしょうか。AI初心者であることを考慮してください。

2

これは正確にはどのMistralモデルですか？

プロンプトを共有していただけますか？

最初のやり取りでモデルを支援するために、「Search」を「Forced Tool」として追加できます。

3

@Falco、以下は返信の追跡に関する詳細です。

具体的にどのMistralモデルですか？

LLMモデル：mistral:latest

リンク:
https://ollama.com/library/mistral:latest のモデルは次のとおりです。

Mistral 7B v0.3 — Mistral AIがリリースした70億パラメータのオープンソースモデルです。

プロンプトを共有してもらえますか？

システムプロンプト：
あなたは、エンジニアをユーザーとする、このフォーラム{site_title}とサイトURL{site_url}のために設計されたコミュニティナレッジアシスタントです。

回答を生成する前に、必ず関連するフォーラム投稿、Wiki記事、およびタグ付けされたディスカッションを検索して参照してください。

最初の優先事項は、取得したフォーラムコンテンツ（埋め込み検索経由）を使用して応答を作成することです。

  既存の投稿からの要約と引用を優先します。
  関連するトピックが複数見つかった場合は、それらを明確に組み合わせます。
  関連コンテンツが存在しない場合にのみ、LLMを通じて一般的な知識を使用して応答します。
  投稿を参照する際には、トピックのタイトルまたはURLを含めます。
  フォーラムデータでサポートされていない回答を幻覚したり発明したりしないでください。
  事実に基づき、簡潔かつ専門的に対応します。
  ユーザーが広範な質問をした場合は、推測するのではなく、複数のソースを要約することを優先します。
  常に、埋め込みにインデックス化されたカテゴリ、タグ、およびWikiからのコンテキストを優先します。

提案通り、強制ツールを更新しました

4

再利用された2023年のモデルでは、ここでは対応できないと思います。また、Ollamaのこのモデルに関するドキュメントによると、生のAPIでのみツール呼び出しをサポートしており、これは私たちが使用しているものではありません。

全体として、今日のAIボットとしては不適切な選択です。

代わりに、以下のいずれかを使用してください。

5

@Falco様、ご入力ありがとうございます。確認し、改めてご連絡いたします。

6

@Falco LLM を有効にしようとすると 502 エラーが発生します。ログを以下に示します。

image
image586×822 23.5 KB

image
image817×806 32.4 KB

メッセージ

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...

バックトレース

/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

Ollama の OpenAI 互換 API を使用している場合は、プロバイダーを OpenAI に設定してください。

8

@Falco

openAI プロバイダーを試しましたが、問題は引き続き発生しています。

メッセージ

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...

バックトレース

/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

Discourse コンテナーはポート 11434 のサービスにアクセスできますか？ホストで実行している場合は、コンテナー境界を越えてネットワークを通過する方法を提供する必要があります。

10

はい、以前はDiscourseコンテナと同じポートでLLMモデルにアクセスできました。

11

これについて手伝っていただけますか？また、このLLMが実行されている最小RAM要件はいくつですか？

12

なので、おそらく次のようになります。

13

こんにちは、@Falco さん

以下に概説したとおり、言語モデル（LLM）の統合に成功しました。しかし、クエリ処理中に問題が発生しました。プロンプトがフォーラムの特定のコンテンツを考慮していません。フォーラム内の関連する議論や洞察から引き出す代わりに、LLMの既存の情報に基づいて応答を生成しています。この状況を是正し、モデルがフォーラムのユニークな貢献を効果的に組み込むようにするために、どのような手順を踏むべきでしょうか？

以前提案されたLLM:

例:

image

14

ペルソナのツールセクションで、検索と読み取りの両方にアクセスできるようにし、検索を強制ツールに設定してください。

image

また、ペルソナが検索するはずのフォーラムコンテンツはすべて公開されていますか？

15

@Falco、私のボットにナレッジベースに保存されているコンテンツから派生した応答を提供させたいと考えています。AIプラグインおよびその他の包括的な設定を共有していただけますか？また、Retrieval-Augmented Generation (RAG)を有効にするために、アプリケーション内で特定のコマンドを実行する必要はありますか？

16

@Falco 上記についてご確認とフィードバックをお願いできますでしょうか。

17

AI bot debugging allowed groups を介してボットのデバッグを有効にし、ボットが行っているツール呼び出しとその応答を確認します。

18

@Falco 以下は詳細です

Request tokens: 1304
Response tokens: 652
model: gemma3:1b
messages:
0:
role: system
content: あなたは親切な Discourse アシスタントです。
Discourse Markdown を_理解_し、**生成**します。
Discourse フォーラムメッセージ内に存在します。

あなたの存在するフォーラムの URL は: https://faq.company.com
サイトのタイトル: company FAQ
説明: company コミュニティポータル
この会話の参加者は: Forum_Helper_bot, testuser
現在の時刻: 2025-12-02 08:36:27 UTC、トレーニング以来多くのことが変化しました。

あなたは古いデータでトレーニングされました。このフォーラムの最新情報を得るには検索を活用してください
検索時は検索語をSIMPLIFY（簡素化）してください
Discourse 検索はすべての用語を AND で結合します。用語を減らし簡素化してより多くの結果を見つけましょう。

この環境では、ユーザーの質問に答えるために使用できるツールセットにアクセスできます。
これらを次のように呼び出すことができます。

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

もし1つの返信で複数の関数を呼び出したい場合は、複数の <invoke>
をラップします
```1つに固定する<function_calls> ブロック。

- ツール呼び出しを実行する必要がある場合は、常にそれらを最優先してください。
- ツール呼び出しの前に「調べてみますね」などの挨拶や前置きは避けてください。
- ツール呼び出し内でHTMLエンティティをエンコードしないでください。必要に応じて <![CDATA[...]]> を使用してエンコードできます。
利用可能なツールの完全なリストは以下の通りです：

<tools>
<tool_description>
<tool_name>categories</tool_name>
<description>現在の Discourse インスタンスのカテゴリを一覧表示します。カテゴリ名の前に # を付けてフォーマットすることを推奨します。</description>
<parameters>
</parameters>
</tool_description>
<tool_description>
<tool_name>search</tool_name>
<description>現在の Discourse インスタンス内のトピックを検索します。レンダリングする際は、常に検索結果のトピックへのリンクを優先してください。</description>
<parameters>
<parameter>
<name>search_query</name>
<type>string</type>
<description>検索する特定のキーワード（スペース区切り）。誤字を修正し、接続詞を削除してください。</description>
<required>false</required>
</parameter>
<parameter>
<name>user</name>
<type>string</type>
<description>検索結果をこのユーザー名にフィルタリングします（ユーザーが明示的にユーザーによるフィルタリングを求めた場合のみ含めます）。</description>
<required>false</required>
</parameter>
<parameter>
<name>order</name>
<type>string</type>
<description>検索結果の順序</description>
<required>false</required>
<options>latest,latest_topic,oldest,views,likes</options>
</parameter>
<parameter>
<name>max_results</name>
<type>integer</type>
<description>返される結果の数を制限します（一般的にはデフォルト値のままにすることを推奨します）。</description>
<required>false</required>
</parameter>
<parameter>
<name>max_posts</name>
<type>integer</type>
<description>トピック内の投稿の最大数（多くの人が投稿したトピック）</description>
<required>false</required>
</parameter>
<parameter>
<name>tags</name>
<type>string</type>
<description>検索するタグのリスト。OR で結合するには + を、AND で結合するには , を使用します。</description>
<required>false</required>
</parameter>
<parameter>
<name>category</name>
<type>string</type>
<description>フィルタリングするカテゴリ名</description>
<required>false</required>
</parameter>
<parameter>
<name>before</name>
<type>string</type>
<description>特定の日期（YYYY-MM-DD）より前に作成されたトピックのみ</description>
<required>false</required>
</parameter>
<parameter>
<name>after</name>
<type>string</type>
<description>特定の日期（YYYY-MM-DD）より後に作成されたトピックのみ</description>
<required>false</required>
</parameter>
<parameter>
<name>status</name>
<type>string</type>
<description>特定のステータスのトピックを検索</description>
<required>false</required>
<options>open,closed,archived,noreplies,single_user</options>
</parameter>
</parameters>
</tool_description>
<tool_description>
<tool_name>read</tool_name>
<description>この Discourse インスタンスのトピックまたは投稿を読み取ります</description>
<parameters>
<parameter>
<name>topic_id</name>
<type>integer</type>
<description>読み取るトピックのID</description>
<required>true</required>
</parameter>
<parameter>
<name>post_numbers</name>
<type>array</type>
<description>読み取る投稿番号（オプション）</description>
<required>false</required>
<array_item_type>integer</array_item_type>
</parameter>
</parameters>
</tool_description>
<tool_description>
<tool_name>tags</tool_name>
<description>現在の Discourse インスタンスで最も人気のある100個のタグを一覧表示します</description>
<parameters>
</parameters>
</tool_description>
</tools>
1:
role: user
name: testuser
content: aptパッケージ zliblg:i386 が存在しないというエラーを解決するには？
stream: true
stream_options:
include_usage: true

レスポンス

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}]}

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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":" **"},"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":"パッケージ"},"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":"リスト"},"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":"を更新"},"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}]}
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  1. LLM 設定で ネイティブ ツールのサポートを無効にする (XML ベースのツールを使用) (オプション) にチェックを入れたのはなぜですか？Gemma 3 はネイティブ ツールをサポートしています。

  2. Gemma3 1B は信頼性の高いツール呼び出しには小さすぎます。これは、組み込みハードウェアやブラウザで実行されるモデルよりも小さいモデルです。少なくとも 4B または 12B バリアントを試してください。

20

@Falco 提供された入力でさらに試行し、折り返しご連絡します