Rename embedchain to mem0 and open sourcing code for long term memory (#1474)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

embedchain/tests/chunkers/test_text.py

@@ -0,0 +1,86 @@
+# ruff: noqa: E501
+
+from embedchain.chunkers.text import TextChunker
+from embedchain.config import ChunkerConfig
+from embedchain.models.data_type import DataType
+
+
+class TestTextChunker:
+    def test_chunks_without_app_id(self):
+        """
+        Test the chunks generated by TextChunker.
+        """
+        chunker_config = ChunkerConfig(chunk_size=10, chunk_overlap=0, length_function=len, min_chunk_size=0)
+        chunker = TextChunker(config=chunker_config)
+        text = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
+        # Data type must be set manually in the test
+        chunker.set_data_type(DataType.TEXT)
+        result = chunker.create_chunks(MockLoader(), text, chunker_config)
+        documents = result["documents"]
+        assert len(documents) > 5
+
+    def test_chunks_with_app_id(self):
+        """
+        Test the chunks generated by TextChunker with app_id
+        """
+        chunker_config = ChunkerConfig(chunk_size=10, chunk_overlap=0, length_function=len, min_chunk_size=0)
+        chunker = TextChunker(config=chunker_config)
+        text = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
+        chunker.set_data_type(DataType.TEXT)
+        result = chunker.create_chunks(MockLoader(), text, chunker_config)
+        documents = result["documents"]
+        assert len(documents) > 5
+
+    def test_big_chunksize(self):
+        """
+        Test that if an infinitely high chunk size is used, only one chunk is returned.
+        """
+        chunker_config = ChunkerConfig(chunk_size=9999999999, chunk_overlap=0, length_function=len, min_chunk_size=0)
+        chunker = TextChunker(config=chunker_config)
+        text = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
+        # Data type must be set manually in the test
+        chunker.set_data_type(DataType.TEXT)
+        result = chunker.create_chunks(MockLoader(), text, chunker_config)
+        documents = result["documents"]
+        assert len(documents) == 1
+
+    def test_small_chunksize(self):
+        """
+        Test that if a chunk size of one is used, every character is a chunk.
+        """
+        chunker_config = ChunkerConfig(chunk_size=1, chunk_overlap=0, length_function=len, min_chunk_size=0)
+        chunker = TextChunker(config=chunker_config)
+        # We can't test with lorem ipsum because chunks are deduped, so would be recurring characters.
+        text = """0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~ \t\n\r\x0b\x0c"""
+        # Data type must be set manually in the test
+        chunker.set_data_type(DataType.TEXT)
+        result = chunker.create_chunks(MockLoader(), text, chunker_config)
+        documents = result["documents"]
+        assert len(documents) == len(text)
+
+    def test_word_count(self):
+        chunker_config = ChunkerConfig(chunk_size=1, chunk_overlap=0, length_function=len, min_chunk_size=0)
+        chunker = TextChunker(config=chunker_config)
+        chunker.set_data_type(DataType.TEXT)
+
+        document = ["ab cd", "ef gh"]
+        result = chunker.get_word_count(document)
+        assert result == 4
+
+
+class MockLoader:
+    @staticmethod
+    def load_data(src) -> dict:
+        """
+        Mock loader that returns a list of data dictionaries.
+        Adjust this method to return different data for testing.
+        """
+        return {
+            "doc_id": "123",
+            "data": [
+                {
+                    "content": src,
+                    "meta_data": {"url": "none"},
+                }
+            ],
+        }