The LLM-based topic recognition model is complete and adapted to quickly updating Weibo topics.
This commit is contained in:
戒酒的李白
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"""
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This class tests the init and fit functions of the TopicGPT module.
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"""
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import os
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import sys
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import inspect
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import openai
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import pickle
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import unittest
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from topicgpt.TopicRepresentation import Topic
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from topicgpt.Clustering import Clustering_and_DimRed
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from topicgpt.TopwordEnhancement import TopwordEnhancement
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from topicgpt.TopicPrompting import TopicPrompting
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from topicgpt.TopicGPT import TopicGPT
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class TestTopicGPT_init_and_fit(unittest.TestCase):
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"""
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Test the init and fit functions of the TopicGPT class
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"""
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@classmethod
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def setUpClass(cls, sample_size = 0.5):
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"""
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load the necessary data and only keep a sample of it
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"""
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print("Setting up class...")
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cls.api_key_openai = os.environ.get('api_key')
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# TODO: The 'openai.organization' option isn't read in the client API. You will need to pass it when you instantiate the client, e.g. 'OpenAI(organization=os.environ.get('OPENAI_ORG'))'
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# openai.organization = os.environ.get('OPENAI_ORG')
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with open("../../Data/Emebeddings/embeddings_20ng_raw.pkl", "rb") as f:
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data_raw = pickle.load(f)
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corpus = data_raw["corpus"]
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doc_embeddings = data_raw["embeddings"]
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n_docs = int(len(corpus) * sample_size)
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cls.corpus = corpus[:n_docs]
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cls.doc_embeddings = doc_embeddings[:n_docs]
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print("Using {} out of {} documents".format(n_docs, len(data_raw["corpus"])))
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with open("../../Data/Emebeddings/embeddings_20ng_vocab.pkl", "rb") as f:
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cls.embeddings_vocab = pickle.load(f)
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def test_init(self):
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"""
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test the init function of the TopicGPT class
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"""
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print("Testing init...")
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topicgpt = TopicGPT(api_key = self.api_key_openai)
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self.assertTrue(isinstance(topicgpt, TopicGPT))
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topicgpt = TopicGPT(api_key = self.api_key_openai,
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n_topics= 20)
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self.assertTrue(isinstance(topicgpt, TopicGPT))
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topicgpt = TopicGPT(api_key = self.api_key_openai,
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n_topics= 20,
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corpus_instruction="This is a corpus instruction",
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document_embeddings = self.doc_embeddings,
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vocab_embeddings= self.embeddings_vocab)
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self.assertTrue(isinstance(topicgpt, TopicGPT))
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# check if assertions are triggered
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with self.assertRaises(AssertionError):
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topicgpt = TopicGPT(api_key = None,
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n_topics= 32,
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openai_prompting_model="gpt-4",
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max_number_of_tokens=8000,
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corpus_instruction="This is a corpus instruction")
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with self.assertRaises(AssertionError):
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topicgpt = TopicGPT(api_key = self.api_key_openai,
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n_topics= 0,
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max_number_of_tokens=8000,
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corpus_instruction="This is a corpus instruction")
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with self.assertRaises(AssertionError):
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topicgpt = TopicGPT(api_key = self.api_key_openai,
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n_topics= 20,
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max_number_of_tokens=0,
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corpus_instruction="This is a corpus instruction")
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def test_fit(self):
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"""
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test the fit function of the TopicGPT class
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"""
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print("Testing fit...")
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def instance_test(topicgpt):
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topicgpt.fit(self.corpus)
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self.assertTrue(hasattr(topicgpt, "vocab"))
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self.assertTrue(hasattr(topicgpt, "topic_lis"))
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self.assertTrue(isinstance(topicgpt.vocab, list))
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self.assertTrue(isinstance(topicgpt.vocab[0], str))
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self.assertTrue(isinstance(topicgpt.topic_lis, list))
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self.assertTrue(type(topicgpt.topic_lis[0]) == Topic)
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if topicgpt.n_topics is not None:
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self.assertTrue(len(topicgpt.topic_lis) == topicgpt.n_topics)
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self.assertTrue(topicgpt.topic_lis == topicgpt.topic_prompting.topic_lis)
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self.assertTrue(topicgpt.vocab == topicgpt.topic_prompting.vocab)
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self.assertTrue(topicgpt.vocab_embeddings == topicgpt.topic_prompting.vocab_embeddings)
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topicgpt1 = TopicGPT(api_key = self.api_key_openai,
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n_topics= 20,
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document_embeddings = self.doc_embeddings,
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vocab_embeddings = self.embeddings_vocab)
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topicgpt2 = TopicGPT(api_key = self.api_key_openai,
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n_topics= None,
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document_embeddings = self.doc_embeddings,
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vocab_embeddings = self.embeddings_vocab)
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topicgpt3 = TopicGPT(api_key=self.api_key_openai,
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n_topics = 1,
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document_embeddings = self.doc_embeddings,
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vocab_embeddings = self.embeddings_vocab,
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n_topwords=10,
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n_topwords_description=10,
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topword_extraction_methods=["cosine_similarity"])
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clusterer4 = Clustering_and_DimRed(
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n_dims_umap = 10,
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n_neighbors_umap = 20,
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min_cluster_size_hdbscan = 10,
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number_clusters_hdbscan= 10 # use only 10 clusters
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)
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topword_enhancement4 = TopwordEnhancement(api_key = self.api_key_openai)
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topic_prompting4 = TopicPrompting(
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api_key = self.api_key_openai,
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enhancer = topword_enhancement4,
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topic_lis = None
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)
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topicgpt4 = TopicGPT(api_key=self.api_key_openai,
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n_topics= None,
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document_embeddings = self.doc_embeddings,
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vocab_embeddings = self.embeddings_vocab,
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topic_prompting = topic_prompting4,
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clusterer = clusterer4,
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topword_extraction_methods=["tfidf"])
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topic_gpt_list = [topicgpt1, topicgpt2, topicgpt3, topicgpt4]
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for topic_gpt in topic_gpt_list:
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instance_test(topic_gpt)
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if __name__ == "__main__":
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unittest.main()
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@@ -0,0 +1,469 @@
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"""
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This class is used to mainly test the prompting functionality of the TopicGPT package.
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"""
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import os
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import sys
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import inspect
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import openai
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import pickle
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import unittest
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from topicgpt.TopicGPT import TopicGPT
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from topicgpt.TopicRepresentation import Topic
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from topicgpt.Clustering import Clustering_and_DimRed
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from topicgpt.TopwordEnhancement import TopwordEnhancement
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from topicgpt.TopicPrompting import TopicPrompting
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# TODO: The 'openai.organization' option isn't read in the client API. You will need to pass it when you instantiate the client, e.g. 'OpenAI(organization=os.environ.get('OPENAI_ORG'))'
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# openai.organization = os.environ.get('OPENAI_ORG')
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class TestTopicGPT_prompting(unittest.TestCase):
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"""
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This class is used to mainly test the prompting functionality of the TopicGPT class.
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"""
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@classmethod
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def setUp(self):
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"""
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load the necessary topic prompting object
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"""
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print("Setting up class...")
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try:
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with open("Data/SavedTopicRepresentations/TopicGpt_20ng.pkl", "rb") as f:
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self.topicgpt = pickle.load(f)
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except FileNotFoundError:
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with open("../../Data/SavedTopicRepresentations/TopicGpt_20ng.pkl", "rb") as f:
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self.topicgpt = pickle.load(f)
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print(f"The topic list of this object is: \n {self.topicgpt.topic_lis} \n\n")
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def test_visualize_clusters(self):
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"""
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test the visualize_clusters function of the TopicGPT class
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"""
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print("Testing visualize_clusters...")
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self.topicgpt.visualize_clusters()
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def test_repr_topics(self):
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"""
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test the repr_topics function of the TopicGPT class
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"""
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print("Testing repr_topics...")
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self.assertTrue(type(self.topicgpt.repr_topics()) == str)
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def test_promt_knn_search(self):
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"""
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test the ppromt function that calls knn_search of the TopicPrompting class
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"""
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print("Testing ppromt_knn_search...")
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prompt_lis = ["Is topic 0 about Bananas? Use knn Search",
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"Is topic 0 about Space? Use knn Search",
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"Is topic 13 about Space exploration? Use knn Search"]
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for prompt in prompt_lis:
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result[0]) == list)
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self.assertTrue(type(function_result[1]) == list)
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self.assertTrue(type(function_result[0][0]) == str)
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self.assertTrue(type(function_result[1][0]) == int)
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def test_promt_identify_topic_idx(self):
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"""
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test the ppromt function that calls identify_topic_idx of the TopicPrompting class
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"""
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print("Testing ppromt_identify_topic_idx...")
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prompt_lis = ["What is the index of the topic about Space?",
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"What is the index of the topic about cars?",
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"What is the index of the topic about gun control?"]
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correct_indices = [13, 9, 2]
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for prompt, correct_idx in zip(prompt_lis, correct_indices):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == int)
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self.assertTrue(function_result == correct_idx) # topic 14 is about space
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def test_prompt_identify_topc_idx_no_index_prompt(self):
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"""
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test the ppromt function that calls identify_topic_idx of the TopicPrompting class
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"""
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print("Testing ppromt_identify_topic_idx...")
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no_index_prompt = "What is the index of the topic about bananas?"
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answer, function_result = self.topicgpt.prompt(no_index_prompt)
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print(f"Answer to the prompt '{no_index_prompt}' \n is \n '{answer}'")
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self.assertTrue(type(answer) == str)
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self.assertTrue(function_result == None)
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def test_prompt_split_topic_kmeans(self):
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"""
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test the ppromt function that calls split_topic_kmeans of the TopicPrompting class
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"""
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print("Testing ppromt_split_topic_kmeans...")
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prompt_lis = ["Split topic 0 into 2 subtopics using kmeans",
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"Split topic 1 into 3 subtopics using kmeans",
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"Split topic 2 into 4 subtopics using kmeans"]
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added_topic_lis_len = [2, 3, 4]
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for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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self.assertTrue(type(function_result[0]) == Topic)
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self.assertTrue(len(function_result) == added_topic_len + len(self.topicgpt.topic_lis) -1 )
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def test_prompt_split_topic_kmeans_inplace(self):
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"""
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test the ppromt function that calls split_topic_kmeans of the TopicPrompting class
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"""
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print("Testing ppromt_split_topic_kmeans...")
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prompt_lis = ["Split topic 0 into 2 subtopics using kmeans. Do this inplace"]
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added_topic_lis_len = [2]
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old_number_of_topics = len(self.topicgpt.topic_lis)
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for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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self.assertTrue(type(function_result[0]) == Topic)
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self.assertTrue(len(self.topicgpt.topic_lis) == old_number_of_topics + added_topic_len -1 )
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self.assertTrue(self.topicgpt.topic_lis == function_result)
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def test_prompt_split_topic_hdbscan(self):
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"""
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test the ppromt function that calls split_topic_hdbscan of the TopicPrompting class
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"""
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print("Testing ppromt_split_topic_hdbscan...")
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prompt_lis = ["Split topic 0 into subtopics using hdbscan",
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"Split topic 1 into subtopics using hdbscan",
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"Split topic 2 into subtopics using hdbscan"]
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for prompt in prompt_lis:
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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self.assertTrue(type(function_result[0]) == Topic)
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def test_prompt_split_topic_hdbscan_inplace(self):
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"""
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test the ppromt function that calls split_topic_hdbscan of the TopicPrompting class
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"""
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print("Testing ppromt_split_topic_hdbscan...")
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prompt_lis = ["Split topic 4 into subtopics using hdbscan. Do this inplace"]
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for prompt in prompt_lis:
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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self.assertTrue(type(function_result[0]) == Topic)
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print("topic_gpt_topic_list: ", self.topicgpt.topic_lis)
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print("function_result: ", function_result)
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self.assertTrue(self.topicgpt.topic_lis == function_result)
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def test_prompt_split_topic_keywords(self):
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"""
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test the prompt function that calls split_topic_keywords of the TopicPrompting class. This test works almost the same as the test_prompt_split_topic_kmeans
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"""
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print("Testing ppromt_split_topic_keywords...")
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prompt_lis = ["Split topic 0 into 2 subtopics based on the keywords Technology and Computers",
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"Split topic 14 into two subbtopics based on the keywords Space and Exploration"]
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added_topic_lis_len = [2, 2]
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for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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print(type(function_result[0]))
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self.assertTrue(type(function_result[0]) == Topic)
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self.assertTrue(len(function_result) == added_topic_len + len(self.topicgpt.topic_lis) -1 )
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def test_prompt_split_topic_keywords_inplace(self):
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"""
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test the prompt function that calls split_topic_keywords of the TopicPrompting class. This test works almost the same as the test_prompt_split_topic_kmeans
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"""
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print("Testing ppromt_split_topic_keywords...")
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prompt_lis = ["Split topic 13 into 2 subtopics based on the keywords 'Rocket and 'Milky Way'. Do this inplace"]
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added_topic_lis_len = [2]
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old_number_of_topics = len(self.topicgpt.topic_lis)
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for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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self.assertTrue(type(answer) == str)
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self.assertTrue(type(function_result) == list)
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self.assertTrue(type(function_result[0]) == Topic)
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self.assertTrue(len(self.topicgpt.topic_lis) == old_number_of_topics + added_topic_len - 1)
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self.assertTrue(self.topicgpt.topic_lis == function_result)
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def test_prompt_split_topic_single_keyword(self):
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"""
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test the prompt function that calls split_topic_keywords of the TopicPrompting class. This test works almost the same as the test_prompt_split_topic_kmeans
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"""
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print("Testing ppromt_split_topic_keywords...")
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prompt_lis = ["Split topic into two topics using the additional keyword 'Technology'",
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"Split topic into two topics using the additional keyword 'Space'"]
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added_topic_lis_len = [2, 2]
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for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
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answer, function_result = self.topicgpt.prompt(prompt)
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print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
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print("function_result: ", function_result)
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||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(len(function_result) == added_topic_len + len(self.topicgpt.topic_lis) -1 )
|
||||
|
||||
def test_prompt_split_topic_single_keyword_inplace(self):
|
||||
"""
|
||||
test the prompt function that calls split_topic_keywords of the TopicPrompting class. This test works almost the same as the test_prompt_split_topic_kmeans
|
||||
"""
|
||||
|
||||
print("Testing ppromt_split_topic_keywords...")
|
||||
|
||||
prompt_lis = ["Split topic 0 into 2 subtopics based on the keywords Technology and Computers. Do this inplace"]
|
||||
|
||||
added_topic_lis_len = [2]
|
||||
old_number_of_topics = len(self.topicgpt.topic_lis)
|
||||
for prompt, added_topic_len in zip(prompt_lis, added_topic_lis_len):
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
|
||||
self.assertTrue(len(self.topicgpt.topic_lis) == old_number_of_topics + added_topic_len -1 )
|
||||
self.assertTrue(self.topicgpt.topic_lis == function_result)
|
||||
|
||||
def test_prompt_combine_topics(self):
|
||||
"""
|
||||
test the prompt function that calls combine_topics of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_combine_topics...")
|
||||
|
||||
prompt_lis = ["Combine topic 0 and topic 1 into one topic",
|
||||
"Combine topic 1 and topic 2 into one topic",
|
||||
"Combine topic 2 and topic 3 into one topic"]
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(len(function_result) == len(self.topicgpt.topic_lis) -1)
|
||||
|
||||
def test_prompt_combine_topics_inplace(self):
|
||||
"""
|
||||
test the prompt function that calls combine_topics of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_combine_topics...")
|
||||
|
||||
prompt_lis = ["Combine topic 0 and topic 1 into one topic. Do this inplace"]
|
||||
old_number_topics = len(self.topicgpt.topic_lis)
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
print("topic_gpt_topic_list: ", self.topicgpt.topic_lis)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(self.topicgpt.topic_lis == function_result)
|
||||
self.assertTrue(len(self.topicgpt.topic_lis) == old_number_topics -1)
|
||||
|
||||
def test_prompt_add_new_topic_keyword(self):
|
||||
"""
|
||||
test the prompt function that calls add_new_topic_keyword of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_add_new_topic_keyword...")
|
||||
|
||||
prompt_lis = ["Add a new topic with the keyword 'Politics'",
|
||||
"Add a new topic with the keyword 'Climate Change'",
|
||||
"Add a new topic with the keyword 'Computers'"]
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
print(type(function_result[0]))
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(len(function_result) == len(self.topicgpt.topic_lis) +1)
|
||||
|
||||
def test_prompt_add_new_topic_keyword_inplace(self):
|
||||
"""
|
||||
test the prompt function that calls add_new_topic_keyword of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_add_new_topic_keyword...")
|
||||
|
||||
prompt_lis = ["Add a new topic with the keyword 'Politics'. Do this inplace"]
|
||||
old_number_topics = len(self.topicgpt.topic_lis)
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(self.topicgpt.topic_lis == function_result)
|
||||
self.assertTrue(len(self.topicgpt.topic_lis) == old_number_topics +1)
|
||||
|
||||
def test_prompt_delete_topic(self):
|
||||
"""
|
||||
test the prompt function that calls delete_topic of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_delete_topic...")
|
||||
|
||||
prompt_lis = ["Delete topic 0",
|
||||
"Delete topic 1",
|
||||
"Delete topic 2"]
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(len(function_result) == len(self.topicgpt.topic_lis) -1)
|
||||
|
||||
def test_prompt_delete_topic_inplace(self):
|
||||
"""
|
||||
test the prompt function that calls delete_topic of the TopicPrompting class
|
||||
"""
|
||||
|
||||
print("Testing ppromt_delete_topic...")
|
||||
|
||||
prompt_lis = ["Delete topic 0. Do this inplace"]
|
||||
old_number_topics = len(self.topicgpt.topic_lis)
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == list)
|
||||
self.assertTrue(type(function_result[0]) == Topic)
|
||||
self.assertTrue(self.topicgpt.topic_lis == function_result)
|
||||
self.assertTrue(len(self.topicgpt.topic_lis) == old_number_topics -1)
|
||||
|
||||
def test_prompt_get_topic_information(self):
|
||||
"""
|
||||
test the get_topic_information function of the TopicGPT class
|
||||
"""
|
||||
|
||||
print("Testing get_topic_information...")
|
||||
|
||||
prompt_lis = ["Please compare topic 0 and topic 1",
|
||||
"Please compare topic 3,4,5"]
|
||||
|
||||
for prompt in prompt_lis:
|
||||
|
||||
answer, function_result = self.topicgpt.prompt(prompt)
|
||||
|
||||
print(f"Answer to the prompt '{prompt}' \n is \n '{answer}'")
|
||||
print("function_result: ", function_result)
|
||||
|
||||
self.assertTrue(type(answer) == str)
|
||||
self.assertTrue(type(function_result) == dict)
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
Reference in New Issue
Block a user