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Added an agent to select the appropriate data sources for any prompt (#284)
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Thorsten Sommer authored and 
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@@ -1,5 +1,7 @@
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using System.Text.Json.Serialization;
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using AIStudio.Agents;
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using AIStudio.Components;
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using AIStudio.Provider;
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using AIStudio.Settings;
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using AIStudio.Tools.Services;
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@@ -41,11 +43,19 @@ public sealed class ContentText : IContent
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if(chatThread is null)
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return;
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var logger = Program.SERVICE_PROVIDER.GetService<ILogger<ContentText>>()!;
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//
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// Check if the user wants to bind any data sources to the chat:
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// 1. Check if the user wants to bind any data sources to the chat:
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//
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if (chatThread.DataSourceOptions.IsEnabled())
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if (chatThread.DataSourceOptions.IsEnabled() && lastPrompt is not null)
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{
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logger.LogInformation("Data sources are enabled for this chat.");
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// Across the different code-branches, we keep track of whether it
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// makes sense to proceed with the RAG process:
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var proceedWithRAG = true;
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//
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// When the user wants to bind data sources to the chat, we
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// have to check if the data sources are available for the
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@@ -61,18 +71,146 @@ public sealed class ContentText : IContent
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//
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if (chatThread.DataSourceOptions.AutomaticDataSourceSelection)
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{
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// TODO: Start agent based on allowed data sources.
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// Get the agent for the data source selection:
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var selectionAgent = Program.SERVICE_PROVIDER.GetService<AgentDataSourceSelection>()!;
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// Let the AI agent do its work:
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IReadOnlyList<DataSourceAgentSelected> finalAISelection = [];
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var aiSelectedDataSources = await selectionAgent.PerformSelectionAsync(provider, lastPrompt, chatThread, dataSources, token);
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// Check if the AI selected any data sources:
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if(aiSelectedDataSources.Count is 0)
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{
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logger.LogWarning("The AI did not select any data sources. The RAG process is skipped.");
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proceedWithRAG = false;
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// Send the selected data sources to the data source selection component.
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// Then, the user can see which data sources were selected by the AI.
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await MessageBus.INSTANCE.SendMessage(null, Event.RAG_AUTO_DATA_SOURCES_SELECTED, finalAISelection);
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chatThread.AISelectedDataSources = finalAISelection;
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}
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else
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{
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// Log the selected data sources:
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var selectedDataSourceInfo = aiSelectedDataSources.Select(ds => $"[Id={ds.Id}, reason={ds.Reason}, confidence={ds.Confidence}]").Aggregate((a, b) => $"'{a}', '{b}'");
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logger.LogInformation($"The AI selected the data sources automatically. {aiSelectedDataSources.Count} data source(s) are selected: {selectedDataSourceInfo}.");
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//
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// Check how many data sources were hallucinated by the AI:
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//
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var totalAISelectedDataSources = aiSelectedDataSources.Count;
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// Filter out the data sources that are not available:
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aiSelectedDataSources = aiSelectedDataSources.Where(x => settings.ConfigurationData.DataSources.FirstOrDefault(ds => ds.Id == x.Id) is not null).ToList();
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// Store the real AI-selected data sources:
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finalAISelection = aiSelectedDataSources.Select(x => new DataSourceAgentSelected { DataSource = settings.ConfigurationData.DataSources.First(ds => ds.Id == x.Id), AIDecision = x, Selected = false }).ToList();
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var numHallucinatedSources = totalAISelectedDataSources - aiSelectedDataSources.Count;
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if(numHallucinatedSources > 0)
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logger.LogWarning($"The AI hallucinated {numHallucinatedSources} data source(s). We ignore them.");
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if (aiSelectedDataSources.Count > 3)
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{
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//
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// We have more than 3 data sources. Let's filter by confidence.
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// In order to do that, we must identify the lower and upper
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// bounds of the confidence interval:
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//
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var confidenceValues = aiSelectedDataSources.Select(x => x.Confidence).ToList();
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var lowerBound = confidenceValues.Min();
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var upperBound = confidenceValues.Max();
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//
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// Next, we search for a threshold so that we have between 2 and 3
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// data sources. When not possible, we take all data sources.
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//
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var threshold = 0.0f;
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// Check the case where the confidence values are too close:
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if (upperBound - lowerBound >= 0.01)
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{
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var previousThreshold = 0.0f;
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for (var i = 0; i < 10; i++)
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{
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threshold = lowerBound + (upperBound - lowerBound) * i / 10;
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var numMatches = aiSelectedDataSources.Count(x => x.Confidence >= threshold);
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if (numMatches <= 1)
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{
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threshold = previousThreshold;
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break;
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}
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if (numMatches is <= 3 and >= 2)
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break;
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previousThreshold = threshold;
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}
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}
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//
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// Filter the data sources by the threshold:
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//
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aiSelectedDataSources = aiSelectedDataSources.Where(x => x.Confidence >= threshold).ToList();
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foreach (var dataSource in finalAISelection)
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if(aiSelectedDataSources.Any(x => x.Id == dataSource.DataSource.Id))
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dataSource.Selected = true;
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logger.LogInformation($"The AI selected {aiSelectedDataSources.Count} data source(s) with a confidence of at least {threshold}.");
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// Transform the final data sources to the actual data sources:
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selectedDataSources = aiSelectedDataSources.Select(x => settings.ConfigurationData.DataSources.FirstOrDefault(ds => ds.Id == x.Id)).Where(ds => ds is not null).ToList()!;
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}
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// We have max. 3 data sources. We take all of them:
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else
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{
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// Transform the selected data sources to the actual data sources:
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selectedDataSources = aiSelectedDataSources.Select(x => settings.ConfigurationData.DataSources.FirstOrDefault(ds => ds.Id == x.Id)).Where(ds => ds is not null).ToList()!;
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// Mark the data sources as selected:
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foreach (var dataSource in finalAISelection)
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dataSource.Selected = true;
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}
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// Send the selected data sources to the data source selection component.
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// Then, the user can see which data sources were selected by the AI.
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await MessageBus.INSTANCE.SendMessage(null, Event.RAG_AUTO_DATA_SOURCES_SELECTED, finalAISelection);
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chatThread.AISelectedDataSources = finalAISelection;
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}
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}
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else
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{
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//
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// No, the user made the choice manually:
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//
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var selectedDataSourceInfo = selectedDataSources.Select(ds => ds.Name).Aggregate((a, b) => $"'{a}', '{b}'");
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logger.LogInformation($"The user selected the data sources manually. {selectedDataSources.Count} data source(s) are selected: {selectedDataSourceInfo}.");
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}
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if(selectedDataSources.Count == 0)
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{
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logger.LogWarning("No data sources are selected. The RAG process is skipped.");
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proceedWithRAG = false;
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}
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//
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// Trigger the retrieval part of the (R)AG process:
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//
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if (proceedWithRAG)
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{
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}
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//
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// Perform the augmentation of the R(A)G process:
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//
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if (proceedWithRAG)
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{
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}
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}
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// Store the last time we got a response. We use this later
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// to determine whether we should notify the UI about the
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// new content or not. Depends on the energy saving mode
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