FEATURE: Add Question Consolidator for robust Upload support in Personas (#596)
This commit introduces a new feature for AI Personas called the "Question Consolidator LLM". The purpose of the Question Consolidator is to consolidate a user's latest question into a self-contained, context-rich question before querying the vector database for relevant fragments. This helps improve the quality and relevance of the retrieved fragments. Previous to this change we used the last 10 interactions, this is not ideal cause the RAG would "lock on" to an answer. EG: - User: how many cars are there in europe - Model: detailed answer about cars in europe including the term car and vehicle many times - User: Nice, what about trains are there in the US In the above example "trains" and "US" becomes very low signal given there are pages and pages talking about cars and europe. This mean retrieval is sub optimal. Instead, we pass the history to the "question consolidator", it would simply consolidate the question to "How many trains are there in the United States", which would make it fare easier for the vector db to find relevant content. The llm used for question consolidator can often be less powerful than the model you are talking to, we recommend using lighter weight and fast models cause the task is very simple. This is configurable from the persona ui. This PR also removes support for {uploads} placeholder, this is too complicated to get right and we want freedom to shift RAG implementation. Key changes: 1. Added a new `question_consolidator_llm` column to the `ai_personas` table to store the LLM model used for question consolidation. 2. Implemented the `QuestionConsolidator` module which handles the logic for consolidating the user's latest question. It extracts the relevant user and model messages from the conversation history, truncates them if needed to fit within the token limit, and generates a consolidated question prompt. 3. Updated the `Persona` class to use the Question Consolidator LLM (if configured) when crafting the RAG fragments prompt. It passes the conversation context to the consolidator to generate a self-contained question. 4. Added UI elements in the AI Persona editor to allow selecting the Question Consolidator LLM. Also made some UI tweaks to conditionally show/hide certain options based on persona configuration. 5. Wrote unit tests for the QuestionConsolidator module and updated existing persona tests to cover the new functionality. This feature enables AI Personas to better understand the context and intent behind a user's question by consolidating the conversation history into a single, focused question. This can lead to more relevant and accurate responses from the AI assistant.
This commit is contained in:
parent
85734fef52
commit
32b3004ce9
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@ -124,6 +124,7 @@ module DiscourseAi
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:rag_chunk_tokens,
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:rag_chunk_overlap_tokens,
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:rag_conversation_chunks,
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:question_consolidator_llm,
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allowed_group_ids: [],
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rag_uploads: [:id],
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)
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@ -113,6 +113,7 @@ class AiPersona < ActiveRecord::Base
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vision_enabled = self.vision_enabled
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vision_max_pixels = self.vision_max_pixels
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rag_conversation_chunks = self.rag_conversation_chunks
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question_consolidator_llm = self.question_consolidator_llm
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persona_class = DiscourseAi::AiBot::Personas::Persona.system_personas_by_id[self.id]
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if persona_class
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@ -152,6 +153,10 @@ class AiPersona < ActiveRecord::Base
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vision_max_pixels
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end
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persona_class.define_singleton_method :question_consolidator_llm do
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question_consolidator_llm
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end
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persona_class.define_singleton_method :rag_conversation_chunks do
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rag_conversation_chunks
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end
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@ -243,6 +248,10 @@ class AiPersona < ActiveRecord::Base
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rag_conversation_chunks
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end
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define_singleton_method :question_consolidator_llm do
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question_consolidator_llm
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end
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define_singleton_method :to_s do
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"#<DiscourseAi::AiBot::Personas::Persona::Custom @name=#{self.name} @allowed_group_ids=#{self.allowed_group_ids.join(",")}>"
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end
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@ -377,6 +386,7 @@ end
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# rag_chunk_tokens :integer default(374), not null
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# rag_chunk_overlap_tokens :integer default(10), not null
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# rag_conversation_chunks :integer default(10), not null
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# question_consolidator_llm :text
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#
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# Indexes
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#
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@ -22,7 +22,8 @@ class LocalizedAiPersonaSerializer < ApplicationSerializer
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:vision_max_pixels,
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:rag_chunk_tokens,
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:rag_chunk_overlap_tokens,
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:rag_conversation_chunks
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:rag_conversation_chunks,
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:question_consolidator_llm
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has_one :user, serializer: BasicUserSerializer, embed: :object
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has_many :rag_uploads, serializer: UploadSerializer, embed: :object
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@ -25,6 +25,7 @@ const CREATE_ATTRIBUTES = [
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"rag_chunk_tokens",
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"rag_chunk_overlap_tokens",
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"rag_conversation_chunks",
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"question_consolidator_llm",
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];
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const SYSTEM_ATTRIBUTES = [
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@ -44,6 +45,7 @@ const SYSTEM_ATTRIBUTES = [
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"rag_chunk_tokens",
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"rag_chunk_overlap_tokens",
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"rag_conversation_chunks",
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"question_consolidator_llm",
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];
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class CommandOption {
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@ -133,6 +133,18 @@ export default class PersonaEditor extends Component {
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return AdminUser.create(this.editingModel?.user);
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}
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get mappedQuestionConsolidatorLlm() {
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return this.editingModel?.question_consolidator_llm || "blank";
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}
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set mappedQuestionConsolidatorLlm(value) {
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if (value === "blank") {
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this.editingModel.question_consolidator_llm = null;
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} else {
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this.editingModel.question_consolidator_llm = value;
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}
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}
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get mappedDefaultLlm() {
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return this.editingModel?.default_llm || "blank";
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}
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@ -460,11 +472,13 @@ export default class PersonaEditor extends Component {
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@updateUploads={{this.updateUploads}}
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@onRemove={{this.removeUpload}}
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/>
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{{#if this.editingModel.rag_uploads}}
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<a
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href="#"
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class="ai-persona-editor__indexing-options"
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{{on "click" this.toggleIndexingOptions}}
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>{{this.indexingOptionsText}}</a>
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{{/if}}
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</div>
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{{#if this.showIndexingOptions}}
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<div class="control-group">
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@ -519,6 +533,24 @@ export default class PersonaEditor extends Component {
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}}
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/>
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</div>
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<div class="control-group">
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<label>{{I18n.t
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"discourse_ai.ai_persona.question_consolidator_llm"
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}}</label>
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<AiLlmSelector
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class="ai-persona-editor__llms"
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@value={{this.mappedQuestionConsolidatorLlm}}
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@llms={{@personas.resultSetMeta.llms}}
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/>
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<DTooltip
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@icon="question-circle"
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@content={{I18n.t
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"discourse_ai.ai_persona.question_consolidator_llm_help"
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}}
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/>
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</div>
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{{/if}}
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{{/if}}
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<div class="control-group ai-persona-editor__action_panel">
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@ -111,8 +111,8 @@ export default class PersonaRagUploader extends Component.extend(
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<div class="persona-rag-uploader" {{willDestroy this.removeListener}}>
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<h3>{{I18n.t "discourse_ai.ai_persona.uploads.title"}}</h3>
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<p>{{I18n.t "discourse_ai.ai_persona.uploads.description"}}</p>
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<p>{{I18n.t "discourse_ai.ai_persona.uploads.hint"}}</p>
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{{#if this.ragUploads}}
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<div class="persona-rag-uploader__search-input-container">
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<div class="persona-rag-uploader__search-input">
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{{icon
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@ -127,6 +127,7 @@ export default class PersonaRagUploader extends Component.extend(
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/>
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</div>
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</div>
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{{/if}}
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<table class="persona-rag-uploader__uploads-list">
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<tbody>
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@ -141,9 +141,11 @@ en:
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create_user_help: You can optionally attach a user to this persona. If you do, the AI will use this user to respond to requests.
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default_llm: Default Language Model
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default_llm_help: The default language model to use for this persona. Required if you wish to mention persona on public posts.
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question_consolidator_llm: Language Model for Question Consolidator
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question_consolidator_llm_help: The language model to use for the question consolidator, you may choose a less powerful model to save costs.
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system_prompt: System Prompt
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show_indexing_options: "Show Indexing Options"
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hide_indexing_options: "Hide Indexing Options"
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show_indexing_options: "Show Upload Options"
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hide_indexing_options: "Hide Upload Options"
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save: Save
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saved: AI Persona Saved
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enabled: "Enabled?"
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@ -181,8 +183,7 @@ en:
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uploads:
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title: "Uploads"
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description: "Your AI persona will be able to search and reference the content of included files. Uploaded files must be formatted as plaintext (.txt)"
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hint: "To control where the file's content gets placed within the system prompt, include the {uploads} placeholder in the system prompt above."
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description: "Your AI persona will be able to search and reference the content of included files. Uploaded files should be formatted as plaintext (.txt) or markdown (.md)."
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button: "Add Files"
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filter: "Filter uploads"
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indexed: "Indexed"
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@ -0,0 +1,7 @@
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# frozen_string_literal: true
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class AddConsolidatedQuestionLlmToAiPersona < ActiveRecord::Migration[7.0]
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def change
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add_column :ai_personas, :question_consolidator_llm, :text, max_length: 2000
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end
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end
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@ -50,7 +50,8 @@ module DiscourseAi
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end
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def reply(context, &update_blk)
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prompt = persona.craft_prompt(context)
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llm = DiscourseAi::Completions::Llm.proxy(model)
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prompt = persona.craft_prompt(context, llm: llm)
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total_completions = 0
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ongoing_chain = true
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@ -63,8 +64,6 @@ module DiscourseAi
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llm_kwargs[:top_p] = persona.top_p if persona.top_p
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while total_completions <= MAX_COMPLETIONS && ongoing_chain
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current_model = model
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llm = DiscourseAi::Completions::Llm.proxy(current_model)
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tool_found = false
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result =
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@ -17,6 +17,10 @@ module DiscourseAi
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1_048_576
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end
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def question_consolidator_llm
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nil
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end
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def system_personas
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@system_personas ||= {
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Personas::General => -1,
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@ -125,7 +129,7 @@ module DiscourseAi
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self.class.all_available_tools.filter { |tool| tools.include?(tool) }
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end
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def craft_prompt(context)
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def craft_prompt(context, llm: nil)
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system_insts =
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system_prompt.gsub(/\{(\w+)\}/) do |match|
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found = context[match[1..-2].to_sym]
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@ -137,15 +141,20 @@ module DiscourseAi
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#{available_tools.map(&:custom_system_message).compact_blank.join("\n")}
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TEXT
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fragments_guidance = rag_fragments_prompt(context[:conversation_context].to_a)&.strip
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question_consolidator_llm = llm
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if self.class.question_consolidator_llm.present?
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question_consolidator_llm =
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DiscourseAi::Completions::Llm.proxy(self.class.question_consolidator_llm)
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end
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if fragments_guidance.present?
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if system_insts.include?("{uploads}")
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prompt_insts = prompt_insts.gsub("{uploads}", fragments_guidance)
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else
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prompt_insts << fragments_guidance
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end
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end
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fragments_guidance =
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rag_fragments_prompt(
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context[:conversation_context].to_a,
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llm: question_consolidator_llm,
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user: context[:user],
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)&.strip
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prompt_insts << fragments_guidance if fragments_guidance.present?
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prompt =
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DiscourseAi::Completions::Prompt.new(
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@ -202,7 +211,7 @@ module DiscourseAi
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)
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end
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def rag_fragments_prompt(conversation_context)
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def rag_fragments_prompt(conversation_context, llm:, user:)
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upload_refs =
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UploadReference.where(target_id: id, target_type: "AiPersona").pluck(:upload_id)
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@ -210,18 +219,30 @@ module DiscourseAi
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return nil if conversation_context.blank? || upload_refs.blank?
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latest_interactions =
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conversation_context
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.select { |ctx| %i[model user].include?(ctx[:type]) }
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.map { |ctx| ctx[:content] }
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.last(10)
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.join("\n")
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conversation_context.select { |ctx| %i[model user].include?(ctx[:type]) }.last(10)
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return nil if latest_interactions.empty?
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# first response
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if latest_interactions.length == 1
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consolidated_question = latest_interactions[0][:content]
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else
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consolidated_question =
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DiscourseAi::AiBot::QuestionConsolidator.consolidate_question(
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llm,
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latest_interactions,
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user,
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)
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end
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return nil if !consolidated_question
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strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
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vector_rep =
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DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
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reranker = DiscourseAi::Inference::HuggingFaceTextEmbeddings
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interactions_vector = vector_rep.vector_from(latest_interactions)
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interactions_vector = vector_rep.vector_from(consolidated_question)
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rag_conversation_chunks = self.class.rag_conversation_chunks
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@ -0,0 +1,93 @@
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# frozen_string_literal: true
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module DiscourseAi
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module AiBot
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class QuestionConsolidator
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attr_reader :llm, :messages, :user, :max_tokens
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def self.consolidate_question(llm, messages, user)
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new(llm, messages, user).consolidate_question
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end
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def initialize(llm, messages, user)
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@llm = llm
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@messages = messages
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@user = user
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@max_tokens = 2048
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end
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def consolidate_question
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@llm.generate(revised_prompt, user: @user)
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end
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def revised_prompt
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max_tokens_per_model = @max_tokens / 5
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conversation_snippet = []
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tokens = 0
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messages.reverse_each do |message|
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# skip tool calls
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next if message[:type] != :user && message[:type] != :model
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row = +""
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row << ((message[:type] == :user) ? "user" : "model")
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content = message[:content]
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current_tokens = @llm.tokenizer.tokenize(content).length
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allowed_tokens = @max_tokens - tokens
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allowed_tokens = [allowed_tokens, max_tokens_per_model].min if message[:type] == :model
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truncated_content = content
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if current_tokens > allowed_tokens
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truncated_content = @llm.tokenizer.truncate(content, allowed_tokens)
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current_tokens = allowed_tokens
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end
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row << ": #{truncated_content}"
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tokens += current_tokens
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conversation_snippet << row
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break if tokens >= @max_tokens
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end
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history = conversation_snippet.reverse.join("\n")
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system_message = <<~TEXT
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You are Question Consolidation Bot: an AI assistant tasked with consolidating a user's latest question into a self-contained, context-rich question.
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- Your output will be used to query a vector database. DO NOT include superflous text such as "here is your consolidated question:".
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- You interact with an API endpoint, not a user, you must never produce denials, nor conversations directed towards a non-existent user.
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- You only produce automated responses to input, where a response is a consolidated question without further discussion.
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- You only ever reply with consolidated questions. You never try to answer user queries.
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If for any reason there is no discernable question (Eg: thank you, or good job) reply with the text NO_QUESTION.
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TEXT
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message = <<~TEXT
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Given the following conversation snippet, craft a self-contained context-rich question (if there is no question reply with NO_QUESTION):
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{{{
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#{history}
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}}}
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Only ever reply with a consolidated question. Do not try to answer user queries.
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TEXT
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response =
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DiscourseAi::Completions::Prompt.new(
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system_message,
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messages: [{ type: :user, content: message }],
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)
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if response == "NO_QUESTION"
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nil
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else
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response
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end
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end
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end
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end
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end
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@ -75,6 +75,13 @@ module DiscourseAi
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Congratulations, you've now seen a small sample of what Discourse's Markdown can do! For more intricate formatting, consider exploring the advanced styling options. Remember that the key to great formatting is not just the available tools, but also the **clarity** and **readability** it brings to your readers.
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TEXT
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def self.with_fake_content(content)
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@fake_content = content
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yield
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ensure
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@fake_content = nil
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end
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def self.fake_content
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@fake_content || STOCK_CONTENT
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end
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|
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@ -47,6 +47,7 @@ RSpec.describe DiscourseAi::AiBot::Personas::Persona do
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end
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fab!(:user)
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fab!(:upload)
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it "renders the system prompt" do
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freeze_time
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|
@ -221,9 +222,56 @@ RSpec.describe DiscourseAi::AiBot::Personas::Persona do
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end
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end
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context "when a persona has RAG uploads" do
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fab!(:upload)
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context "when RAG is running with a question consolidator" do
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let(:consolidated_question) { "what is the time in france?" }
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it "will run the question consolidator" do
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context_embedding = [0.049382, 0.9999]
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EmbeddingsGenerationStubs.discourse_service(
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SiteSetting.ai_embeddings_model,
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consolidated_question,
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context_embedding,
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)
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custom_ai_persona =
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Fabricate(
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:ai_persona,
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name: "custom",
|
||||
rag_conversation_chunks: 3,
|
||||
allowed_group_ids: [Group::AUTO_GROUPS[:trust_level_0]],
|
||||
question_consolidator_llm: "fake:fake",
|
||||
)
|
||||
|
||||
UploadReference.ensure_exist!(target: custom_ai_persona, upload_ids: [upload.id])
|
||||
|
||||
custom_persona =
|
||||
DiscourseAi::AiBot::Personas::Persona.find_by(id: custom_ai_persona.id, user: user).new
|
||||
|
||||
# this means that we will consolidate
|
||||
ctx =
|
||||
with_cc.merge(
|
||||
conversation_context: [
|
||||
{ content: "Tell me the time", type: :user },
|
||||
{ content: "the time is 1", type: :model },
|
||||
{ content: "in france?", type: :user },
|
||||
],
|
||||
)
|
||||
|
||||
DiscourseAi::Completions::Endpoints::Fake.with_fake_content(consolidated_question) do
|
||||
custom_persona.craft_prompt(ctx).messages.first[:content]
|
||||
end
|
||||
|
||||
message =
|
||||
DiscourseAi::Completions::Endpoints::Fake.last_call[:dialect].prompt.messages.last[
|
||||
:content
|
||||
]
|
||||
expect(message).to include("Tell me the time")
|
||||
expect(message).to include("the time is 1")
|
||||
expect(message).to include("in france?")
|
||||
end
|
||||
end
|
||||
|
||||
context "when a persona has RAG uploads" do
|
||||
def stub_fragments(limit, expected_limit: nil)
|
||||
candidate_ids = []
|
||||
|
||||
|
@ -255,32 +303,6 @@ RSpec.describe DiscourseAi::AiBot::Personas::Persona do
|
|||
)
|
||||
end
|
||||
|
||||
context "when the system prompt has an uploads placeholder" do
|
||||
before { stub_fragments(10) }
|
||||
|
||||
it "replaces the placeholder with the fragments" do
|
||||
custom_persona_record =
|
||||
AiPersona.create!(
|
||||
name: "custom",
|
||||
description: "description",
|
||||
system_prompt: "instructions\n{uploads}\nmore instructions",
|
||||
allowed_group_ids: [Group::AUTO_GROUPS[:trust_level_0]],
|
||||
)
|
||||
UploadReference.ensure_exist!(target: custom_persona_record, upload_ids: [upload.id])
|
||||
custom_persona =
|
||||
DiscourseAi::AiBot::Personas::Persona.find_by(
|
||||
id: custom_persona_record.id,
|
||||
user: user,
|
||||
).new
|
||||
|
||||
crafted_system_prompt = custom_persona.craft_prompt(with_cc).messages.first[:content]
|
||||
|
||||
expect(crafted_system_prompt).to include("fragment-n0")
|
||||
|
||||
expect(crafted_system_prompt.ends_with?("</guidance>")).to eq(false)
|
||||
end
|
||||
end
|
||||
|
||||
context "when persona allows for less fragments" do
|
||||
before { stub_fragments(3) }
|
||||
|
||||
|
|
|
@ -0,0 +1,33 @@
|
|||
# frozen_string_literal: true
|
||||
|
||||
RSpec.describe DiscourseAi::AiBot::QuestionConsolidator do
|
||||
let(:llm) { DiscourseAi::Completions::Llm.proxy("fake:fake") }
|
||||
let(:fake_endpoint) { DiscourseAi::Completions::Endpoints::Fake }
|
||||
|
||||
fab!(:user)
|
||||
|
||||
describe ".consolidate_question" do
|
||||
it "properly picks all the right messages and consolidates" do
|
||||
messages = [
|
||||
{ type: :user, content: "What is the capital of France?" },
|
||||
{ type: :tool_call, content: "search:google", id: "123" },
|
||||
{ type: :tool, content: "some results from google", id: "123" },
|
||||
{ type: :model, content: "Paris" },
|
||||
{ type: :user, content: "What about Germany?" },
|
||||
]
|
||||
|
||||
result = described_class.consolidate_question(llm, messages, user)
|
||||
expect(result).to eq(fake_endpoint.fake_content)
|
||||
|
||||
call = fake_endpoint.last_call
|
||||
|
||||
prompt = call[:dialect].prompt
|
||||
expect(prompt.messages.length).to eq(2)
|
||||
content = prompt.messages[1][:content]
|
||||
expect(content).to include("Germany")
|
||||
expect(content).to include("France")
|
||||
expect(content).to include("Paris")
|
||||
expect(content).not_to include("google")
|
||||
end
|
||||
end
|
||||
end
|
|
@ -52,6 +52,7 @@ module("Discourse AI | Unit | Model | ai-persona", function () {
|
|||
rag_chunk_tokens: 374,
|
||||
rag_chunk_overlap_tokens: 10,
|
||||
rag_conversation_chunks: 10,
|
||||
question_consolidator_llm: "Question Consolidator LLM",
|
||||
};
|
||||
|
||||
const aiPersona = AiPersona.create({ ...properties });
|
||||
|
@ -90,6 +91,7 @@ module("Discourse AI | Unit | Model | ai-persona", function () {
|
|||
rag_chunk_tokens: 374,
|
||||
rag_chunk_overlap_tokens: 10,
|
||||
rag_conversation_chunks: 10,
|
||||
question_consolidator_llm: "Question Consolidator LLM",
|
||||
};
|
||||
|
||||
const aiPersona = AiPersona.create({ ...properties });
|
||||
|
|
Loading…
Reference in New Issue