AttributeError: module 'keras._tf_keras.keras' has no attribute '__internal__'

[AbdulmohsenA]

!pip install top2vec[sentence_encoders]
!pip install tensorflow-probability

---

from top2vec import Top2Vec
import pandas as pd
import numpy as np

df = pd.read_csv("/content/drive/My Drive/_csvfile")
documents = df['summary'].to_list()
model = Top2Vec(documents)

i get the error:
AttributeError: module keras._tf_keras.keras has no attribute __internal__

Google Colab shows the error is in the from top2vec import Top2Vec line

[IsrarAwan]

Install the packages in the following order:

!pip install -q tensorflow==2.15.1
!pip install -q tensorflow_hub==0.12.0
!pip install -q tensorflow_text==2.15.0
!pip install -q top2vec[sentence_transformers]

Keras 3 is incompatible with tensorflow-probability, which is why it's not working. Using the aforementioned versions, top2vec will work and you will not get the AttributeError.

PS. Make sure to delete runtime of Colab before running the cell containing the dependencies above.

[DLesmes]

Install the packages in the following order:

!pip install -q tensorflow==2.15.1
!pip install -q tensorflow_hub==0.12.0
!pip install -q tensorflow_text==2.15.0
!pip install -q top2vec[sentence_transformers]

Keras 3 is incompatible with tensorflow-probability, which is why it's not working. Using the aforementioned versions, top2vec will work and you will not get the AttributeError.

PS. Make sure to delete runtime of Colab before running the cell containing the dependencies above.

✅ this works for my use case despite of this error pip message! 🐛

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
tensorflow-text 2.15.0 requires tensorflow-hub>=0.13.0, but you have tensorflow-hub 0.12.0 which is incompatible.