b1724fe7ca
Chat with any SQLite database using natural language. Built on AnyLanguageModel (HuggingFace) for LLM-agnostic provider support and GRDB for SQLite access. Core features: - Auto schema introspection from sqlite_master (zero config) - NL → SQL generation via any AnyLanguageModel provider - Three rendering modes: text summary, data table, Swift Charts - Drop-in DataChatView (SwiftUI) and headless ChatEngine - Operation allowlist with read-only default - Mutation policy with per-table control - ToolExecutionDelegate for destructive operation confirmation - Multi-turn conversation context - 352 tests across 24 suites, all passing Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
50 lines
1.6 KiB
Swift
50 lines
1.6 KiB
Swift
// MockLanguageModel.swift
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// SwiftDBAI Tests
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//
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// A mock LanguageModel for unit tests that returns canned responses.
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import AnyLanguageModel
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import Foundation
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/// A mock language model that returns a configurable canned response.
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///
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/// Used in tests to avoid hitting a real LLM provider.
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struct MockLanguageModel: LanguageModel {
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typealias UnavailableReason = Never
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/// The text the mock will return from `respond(...)`.
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let responseText: String
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init(responseText: String = "Mock summary response.") {
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self.responseText = responseText
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}
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func respond<Content>(
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within session: LanguageModelSession,
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to prompt: Prompt,
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generating type: Content.Type,
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includeSchemaInPrompt: Bool,
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options: GenerationOptions
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) async throws -> LanguageModelSession.Response<Content> where Content: Generable {
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let rawContent = GeneratedContent(kind: .string(responseText))
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let content = try Content(rawContent)
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return LanguageModelSession.Response(
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content: content,
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rawContent: rawContent,
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transcriptEntries: [][...]
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)
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}
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func streamResponse<Content>(
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within session: LanguageModelSession,
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to prompt: Prompt,
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generating type: Content.Type,
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includeSchemaInPrompt: Bool,
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options: GenerationOptions
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) -> sending LanguageModelSession.ResponseStream<Content> where Content: Generable {
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let rawContent = GeneratedContent(kind: .string(responseText))
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let content = try! Content(rawContent)
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return LanguageModelSession.ResponseStream(content: content, rawContent: rawContent)
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}
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}
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