297 lines
8.2 KiB
Ruby
297 lines
8.2 KiB
Ruby
# frozen_string_literal: true
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RSpec.describe AiTool do
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fab!(:llm_model) { Fabricate(:llm_model, name: "claude-2") }
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let(:llm) { DiscourseAi::Completions::Llm.proxy("custom:#{llm_model.id}") }
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def create_tool(
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parameters: nil,
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script: nil,
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rag_chunk_tokens: nil,
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rag_chunk_overlap_tokens: nil
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)
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AiTool.create!(
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name: "test",
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description: "test",
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parameters: parameters || [{ name: "query", type: "string", desciption: "perform a search" }],
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script: script || "function invoke(params) { return params; }",
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created_by_id: 1,
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summary: "Test tool summary",
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rag_chunk_tokens: rag_chunk_tokens || 374,
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rag_chunk_overlap_tokens: rag_chunk_overlap_tokens || 10,
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)
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end
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it "it can run a basic tool" do
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tool = create_tool
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expect(tool.signature).to eq(
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{
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name: "test",
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description: "test",
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parameters: [{ name: "query", type: "string", desciption: "perform a search" }],
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},
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)
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runner = tool.runner({ "query" => "test" }, llm: nil, bot_user: nil, context: {})
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expect(runner.invoke).to eq("query" => "test")
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end
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it "can perform HTTP requests with various verbs" do
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%i[post put delete patch].each do |verb|
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script = <<~JS
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function invoke(params) {
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result = http.#{verb}("https://example.com/api",
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{
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headers: { TestHeader: "TestValue" },
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body: JSON.stringify({ data: params.data })
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}
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);
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return result.body;
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({ "data" => "test data" }, llm: nil, bot_user: nil, context: {})
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stub_request(verb, "https://example.com/api").with(
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body: "{\"data\":\"test data\"}",
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headers: {
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"Accept" => "*/*",
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"Testheader" => "TestValue",
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"User-Agent" => "Discourse AI Bot 1.0 (https://www.discourse.org)",
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},
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).to_return(status: 200, body: "Success", headers: {})
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result = runner.invoke
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expect(result).to eq("Success")
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end
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end
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it "can perform GET HTTP requests, with 1 param" do
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script = <<~JS
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function invoke(params) {
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result = http.get("https://example.com/" + params.query);
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return result.body;
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({ "query" => "test" }, llm: nil, bot_user: nil, context: {})
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stub_request(:get, "https://example.com/test").with(
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headers: {
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"Accept" => "*/*",
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"User-Agent" => "Discourse AI Bot 1.0 (https://www.discourse.org)",
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},
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).to_return(status: 200, body: "Hello World", headers: {})
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result = runner.invoke
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expect(result).to eq("Hello World")
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end
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it "is limited to MAX http requests" do
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script = <<~JS
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function invoke(params) {
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let i = 0;
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while (i < 21) {
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http.get("https://example.com/");
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i += 1;
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}
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return "will not happen";
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({}, llm: nil, bot_user: nil, context: {})
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stub_request(:get, "https://example.com/").to_return(
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status: 200,
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body: "Hello World",
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headers: {
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},
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)
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expect { runner.invoke }.to raise_error(DiscourseAi::AiBot::ToolRunner::TooManyRequestsError)
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end
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it "can perform GET HTTP requests" do
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script = <<~JS
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function invoke(params) {
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result = http.get("https://example.com/" + params.query,
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{ headers: { TestHeader: "TestValue" } }
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);
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return result.body;
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({ "query" => "test" }, llm: nil, bot_user: nil, context: {})
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stub_request(:get, "https://example.com/test").with(
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headers: {
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"Accept" => "*/*",
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"Testheader" => "TestValue",
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"User-Agent" => "Discourse AI Bot 1.0 (https://www.discourse.org)",
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},
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).to_return(status: 200, body: "Hello World", headers: {})
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result = runner.invoke
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expect(result).to eq("Hello World")
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end
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it "will not timeout on slow HTTP reqs" do
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script = <<~JS
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function invoke(params) {
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result = http.get("https://example.com/" + params.query,
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{ headers: { TestHeader: "TestValue" } }
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);
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return result.body;
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({ "query" => "test" }, llm: nil, bot_user: nil, context: {})
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stub_request(:get, "https://example.com/test").to_return do
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sleep 0.01
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{ status: 200, body: "Hello World", headers: {} }
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end
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runner.timeout = 5
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result = runner.invoke
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expect(result).to eq("Hello World")
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end
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it "has access to llm truncation tools" do
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script = <<~JS
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function invoke(params) {
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return llm.truncate("Hello World", 1);
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({}, llm: llm, bot_user: nil, context: {})
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result = runner.invoke
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expect(result).to eq("Hello")
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end
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it "can timeout slow JS" do
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script = <<~JS
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function invoke(params) {
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while (true) {}
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}
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JS
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tool = create_tool(script: script)
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runner = tool.runner({ "query" => "test" }, llm: nil, bot_user: nil, context: {})
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runner.timeout = 5
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result = runner.invoke
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expect(result[:error]).to eq("Script terminated due to timeout")
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end
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context "when defining RAG fragments" do
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before do
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SiteSetting.authorized_extensions = "txt"
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SiteSetting.ai_embeddings_enabled = true
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SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
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SiteSetting.ai_embeddings_model = "bge-large-en"
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Jobs.run_immediately!
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end
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def create_upload(content, filename)
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upload = nil
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Tempfile.create(filename) do |file|
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file.write(content)
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file.rewind
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upload = UploadCreator.new(file, filename).create_for(Discourse.system_user.id)
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end
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upload
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end
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def stub_embeddings
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# this is a trick, we get ever increasing embeddings, this gives us in turn
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# 100% consistent search results
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@counter = 0
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stub_request(:post, "http://test.com/api/v1/classify").to_return(
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status: 200,
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body: lambda { |req| ([@counter += 1] * 1024).to_json },
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headers: {
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},
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)
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end
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it "allows search within uploads" do
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stub_embeddings
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upload1 = create_upload(<<~TXT, "test.txt")
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
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TXT
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upload2 = create_upload(<<~TXT, "test.txt")
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30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
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TXT
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tool = create_tool(rag_chunk_tokens: 10, rag_chunk_overlap_tokens: 4, script: <<~JS)
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function invoke(params) {
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let result1 = index.search("testing a search", { limit: 1 });
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let result2 = index.search("testing another search", { limit: 3, filenames: ["test.txt"] });
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return [result1, result2];
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}
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JS
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RagDocumentFragment.link_target_and_uploads(tool, [upload1.id, upload2.id])
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result = tool.runner({}, llm: nil, bot_user: nil, context: {}).invoke
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expected = [
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[{ "fragment" => "44 45 46 47 48 49 50", "metadata" => nil }],
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[
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{ "fragment" => "44 45 46 47 48 49 50", "metadata" => nil },
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{ "fragment" => "36 37 38 39 40 41 42 43 44 45", "metadata" => nil },
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{ "fragment" => "30 31 32 33 34 35 36 37", "metadata" => nil },
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],
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]
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expect(result).to eq(expected)
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# will force a reindex
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tool.rag_chunk_tokens = 5
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tool.rag_chunk_overlap_tokens = 2
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tool.save!
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# this part of the API is a bit awkward, maybe we should do it
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# automatically
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RagDocumentFragment.update_target_uploads(tool, [upload1.id, upload2.id])
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result = tool.runner({}, llm: nil, bot_user: nil, context: {}).invoke
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expected = [
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[{ "fragment" => "48 49 50", "metadata" => nil }],
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[
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{ "fragment" => "48 49 50", "metadata" => nil },
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{ "fragment" => "45 46 47", "metadata" => nil },
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{ "fragment" => "42 43 44", "metadata" => nil },
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],
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]
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expect(result).to eq(expected)
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end
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end
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end
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