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[PR #2581] Fix/hit test tsne issue #23720

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opened 2026-02-21 20:21:38 -05:00 by yindo · 0 comments
yindo commented 2026-02-21 20:21:38 -05:00
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Original Pull Request: https://github.com/langgenius/dify/pull/2581

State: closed
Merged: Yes

Description

for below code :

    def get_tsne_positions_from_embeddings(cls, embeddings: list):
        embedding_length = len(embeddings)
        if embedding_length <= 1:
            return [{'x': 0, 'y': 0}]

        noise = np.random.normal(0, 1e-4, np.array(embeddings).shape)
        concatenate_data = np.array(embeddings) + noise
        concatenate_data = concatenate_data.reshape(embedding_length, -1)

        perplexity = embedding_length / 2 + 1
        if perplexity >= embedding_length:
            perplexity = max(embedding_length - 1, 1)

        tsne = TSNE(n_components=2, perplexity=perplexity, early_exaggeration=12.0)
        data_tsne = tsne.fit_transform(concatenate_data)

        tsne_position_data = []
        for i in range(len(data_tsne)):
            tsne_position_data.append({'x': float(data_tsne[i][0]), 'y': float(data_tsne[i][1])})

        return tsne_position_data

when embeddings are the same, the tsne.fit_transform will cause error

Fixes # (issue)

Type of Change

Please delete options that are not relevant.

  • Bug fix (non-breaking change which fixes an issue)

Suggested Checklist:

  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas
  • My changes generate no new warnings
  • I ran dev/reformat(backend) and cd web && npx lint-staged(frontend) to appease the lint gods
  • optional I have made corresponding changes to the documentation
  • optional I have added tests that prove my fix is effective or that my feature works
  • optional New and existing unit tests pass locally with my changes
**Original Pull Request:** https://github.com/langgenius/dify/pull/2581 **State:** closed **Merged:** Yes --- # Description for below code : ``` def get_tsne_positions_from_embeddings(cls, embeddings: list): embedding_length = len(embeddings) if embedding_length <= 1: return [{'x': 0, 'y': 0}] noise = np.random.normal(0, 1e-4, np.array(embeddings).shape) concatenate_data = np.array(embeddings) + noise concatenate_data = concatenate_data.reshape(embedding_length, -1) perplexity = embedding_length / 2 + 1 if perplexity >= embedding_length: perplexity = max(embedding_length - 1, 1) tsne = TSNE(n_components=2, perplexity=perplexity, early_exaggeration=12.0) data_tsne = tsne.fit_transform(concatenate_data) tsne_position_data = [] for i in range(len(data_tsne)): tsne_position_data.append({'x': float(data_tsne[i][0]), 'y': float(data_tsne[i][1])}) return tsne_position_data ``` when embeddings are the same, the `tsne.fit_transform` will cause error Fixes # (issue) ## Type of Change Please delete options that are not relevant. - [ ] Bug fix (non-breaking change which fixes an issue) # Suggested Checklist: - [x] I have performed a self-review of my own code - [x] I have commented my code, particularly in hard-to-understand areas - [x] My changes generate no new warnings - [x] I ran `dev/reformat`(backend) and `cd web && npx lint-staged`(frontend) to appease the lint gods - [ ] `optional` I have made corresponding changes to the documentation - [ ] `optional` I have added tests that prove my fix is effective or that my feature works - [ ] `optional` New and existing unit tests pass locally with my changes
yindo added the pull-request label 2026-02-21 20:21:38 -05:00
yindo closed this issue 2026-02-21 20:21:38 -05:00
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Reference: langgenius/dify#23720
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