mirror of
https://github.com/infiniflow/ragflow.git
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5797f81fea
## Summary - align the Go Google Scholar component with the Python-side config pattern - merge node-level params with runtime inputs so canvas defaults are preserved and per-run inputs can override them - add tests covering node param fallback and runtime override behavior ## Verification - `bash build.sh --test ./internal/agent/component/... -run TestGoogleScholar` <img width="1873" height="1165" alt="image" src="https://github.com/user-attachments/assets/67198c6f-6a0e-43bf-a500-8e88d82b8751" />
301 lines
8.1 KiB
Go
301 lines
8.1 KiB
Go
//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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package tool
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import (
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"context"
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"encoding/json"
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"net/http"
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"net/http/httptest"
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"net/url"
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"strings"
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"testing"
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)
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const cannedScholarHTML = `<html><body>
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<div class="gs_r gs_or gs_scl" style="display:none"></div>
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<div class="gs_r">
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<div class="gs_ri">
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<h3 class="gs_rt">
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<a href="https://example.com/paper1">Attention is all you need</a>
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</h3>
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<div class="gs_a">Ashish Vaswani, Noam Shazeer, Niki Parmar - NeurIPS 2017</div>
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<div class="gs_rs">The dominant sequence transduction models are based on complex recurrent or convolutional neural networks.</div>
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</div>
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</div>
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<div class="gs_r">
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<div class="gs_ri">
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<h3 class="gs_rt">
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<a href="https://example.com/paper2">BERT: Pre-training of Deep Bidirectional Transformers</a>
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</h3>
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<div class="gs_a">Jacob Devlin, Ming-Wei Chang - NAACL 2019</div>
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<div class="gs_rs">We introduce a new language representation model called BERT.</div>
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</div>
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</div>
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</body></html>`
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func TestGoogleScholar_BuildURL(t *testing.T) {
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t.Parallel()
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cases := []struct {
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name string
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query string
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topN int
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sortBy string
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yearLow int
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yearHigh int
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patents *bool
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wantNum string
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wantHost string
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wantQuery string
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wantParams map[string]string
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}{
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{
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name: "default",
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query: "transformer",
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wantNum: "12",
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wantHost: "scholar.google.com",
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wantQuery: "transformer",
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},
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{
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name: "explicit high",
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query: "x",
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topN: 99,
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wantNum: "99",
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wantHost: "scholar.google.com",
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wantQuery: "x",
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},
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{
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name: "explicit",
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query: "a b",
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topN: 3,
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wantNum: "3",
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wantHost: "scholar.google.com",
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wantQuery: "a b",
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},
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{
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name: "sort by date",
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query: "test",
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topN: 5,
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sortBy: "date",
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wantNum: "5",
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wantHost: "scholar.google.com",
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wantQuery: "test",
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wantParams: map[string]string{"scisbd": "1"},
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},
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{
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name: "year range",
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query: "ml",
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topN: 10,
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yearLow: 2020,
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yearHigh: 2024,
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wantNum: "10",
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wantHost: "scholar.google.com",
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wantQuery: "ml",
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wantParams: map[string]string{"as_ylo": "2020", "as_yhi": "2024"},
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},
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{
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name: "exclude patents",
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query: "ai",
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topN: 5,
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patents: boolPtr(false),
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wantNum: "5",
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wantHost: "scholar.google.com",
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wantQuery: "ai",
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wantParams: map[string]string{"as_vis": "1"},
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},
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{
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name: "include patents (default)",
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query: "nlp",
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topN: 5,
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patents: boolPtr(true),
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wantNum: "5",
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wantHost: "scholar.google.com",
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wantQuery: "nlp",
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},
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{
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name: "all params combined",
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query: "deep learning",
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topN: 8,
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sortBy: "date",
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yearLow: 2019,
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yearHigh: 2023,
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patents: boolPtr(false),
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wantNum: "8",
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wantHost: "scholar.google.com",
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wantQuery: "deep learning",
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wantParams: map[string]string{
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"scisbd": "1",
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"as_ylo": "2019",
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"as_yhi": "2023",
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"as_vis": "1",
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},
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},
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}
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for _, tc := range cases {
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t.Run(tc.name, func(t *testing.T) {
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t.Parallel()
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got := buildGoogleScholarURL(tc.query, tc.topN, tc.sortBy, tc.yearLow, tc.yearHigh, tc.patents)
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u, err := url.Parse(got)
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if err != nil {
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t.Fatalf("url.Parse(%q): %v", got, err)
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}
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if u.Host != tc.wantHost {
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t.Errorf("host = %q, want %q", u.Host, tc.wantHost)
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}
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if u.Path != "/scholar" {
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t.Errorf("path = %q, want /scholar", u.Path)
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}
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q := u.Query()
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if q.Get("q") != tc.wantQuery {
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t.Errorf("q = %q, want %q", q.Get("q"), tc.wantQuery)
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}
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if q.Get("num") != tc.wantNum {
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t.Errorf("num = %q, want %q", q.Get("num"), tc.wantNum)
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}
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for k, v := range tc.wantParams {
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if q.Get(k) != v {
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t.Errorf("%s = %q, want %q", k, q.Get(k), v)
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}
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}
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})
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}
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}
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func TestGoogleScholar_ParseResults(t *testing.T) {
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t.Parallel()
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srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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w.Header().Set("Content-Type", "text/html; charset=UTF-8")
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_, _ = w.Write([]byte(cannedScholarHTML))
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}))
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defer srv.Close()
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helper := NewHTTPHelper().WithClient(&http.Client{
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Transport: rewriteHostTransport(srv.URL),
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})
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tool := NewGoogleScholarToolWith(helper)
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out, err := tool.InvokableRun(context.Background(),
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`{"query":"transformer","top_n":5,"sort_by":"relevance","year_low":2020,"year_high":2024,"patents":true}`)
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if err != nil {
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t.Fatalf("InvokableRun: %v", err)
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}
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var env googleScholarEnvelope
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if jerr := json.Unmarshal([]byte(out), &env); jerr != nil {
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t.Fatalf("output is not valid JSON: %v (raw=%s)", jerr, out)
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}
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if env.Error != "" {
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t.Errorf("Error = %q, want empty", env.Error)
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}
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if len(env.Results) != 2 {
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t.Fatalf("Results len = %d, want 2", len(env.Results))
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}
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if !strings.Contains(env.Results[0].Title, "Attention") {
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t.Errorf("Results[0].Title = %q, want to contain Attention", env.Results[0].Title)
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}
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if env.Results[0].Link != "https://example.com/paper1" {
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t.Errorf("Results[0].Link = %q, want https://example.com/paper1", env.Results[0].Link)
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}
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if !strings.Contains(env.Results[0].Authors, "Vaswani") {
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t.Errorf("Results[0].Authors = %q, want to contain Vaswani", env.Results[0].Authors)
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}
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if env.Results[0].Year != "2017" {
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t.Errorf("Results[0].Year = %q, want 2017", env.Results[0].Year)
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}
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if !strings.Contains(env.Results[0].Snippet, "sequence transduction") {
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t.Errorf("Results[0].Snippet = %q, want snippet", env.Results[0].Snippet)
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}
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if env.Results[1].Year != "2019" {
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t.Errorf("Results[1].Year = %q, want 2019", env.Results[1].Year)
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}
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}
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func TestGoogleScholar_RequiresQuery(t *testing.T) {
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t.Parallel()
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tool := NewGoogleScholarTool()
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_, err := tool.InvokableRun(context.Background(), `{"query":""}`)
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if err == nil {
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t.Fatal("expected error for empty query")
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}
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if !strings.Contains(err.Error(), "query") {
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t.Errorf("err = %v, want to mention query", err)
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}
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}
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func TestGoogleScholar_Info(t *testing.T) {
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t.Parallel()
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tool := NewGoogleScholarTool()
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info, err := tool.Info(context.Background())
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if err != nil {
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t.Fatalf("Info: %v", err)
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}
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if info.Name != "google_scholar" {
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t.Errorf("Name = %q, want google_scholar", info.Name)
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}
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if !strings.Contains(info.Desc, "Scholar") {
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t.Errorf("Desc = %q, want to mention Scholar", info.Desc)
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}
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}
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func TestGoogleScholar_MergesNodeLevelDefaults(t *testing.T) {
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t.Parallel()
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srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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q := r.URL.Query()
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if q.Get("q") != "rag" {
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t.Errorf("q = %q, want rag", q.Get("q"))
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}
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if q.Get("num") != "7" {
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t.Errorf("num = %q, want 7", q.Get("num"))
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}
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if q.Get("scisbd") != "1" {
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t.Errorf("scisbd = %q, want 1", q.Get("scisbd"))
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}
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if q.Get("as_ylo") != "2020" {
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t.Errorf("as_ylo = %q, want 2020", q.Get("as_ylo"))
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}
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if q.Get("as_yhi") != "2024" {
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t.Errorf("as_yhi = %q, want 2024", q.Get("as_yhi"))
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}
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if q.Get("as_vis") != "1" {
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t.Errorf("as_vis = %q, want 1", q.Get("as_vis"))
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}
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w.Header().Set("Content-Type", "text/html; charset=UTF-8")
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_, _ = w.Write([]byte(cannedScholarHTML))
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}))
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defer srv.Close()
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helper := NewHTTPHelper().WithClient(&http.Client{
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Transport: rewriteHostTransport(srv.URL),
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})
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tool := NewGoogleScholarToolWithDefaults(helper, googleScholarParams{
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Query: "rag",
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TopN: 7,
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SortBy: "date",
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YearLow: 2020,
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YearHigh: 2024,
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Patents: boolPtr(false),
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})
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_, err := tool.InvokableRun(context.Background(), `{}`)
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if err != nil {
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t.Fatalf("InvokableRun with defaults: %v", err)
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}
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}
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