Feat/add python version test envs (#2774)

CONTRIBUTING.md

@@ -16,18 +16,19 @@ To make a contribution, follow these steps:
 For more details about pull requests, please read [GitHub's guides](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request).
 
 
-### 📦 Package manager
+### 📦 Development Environment
 
-We use `poetry` as our package manager. You can install poetry by following the instructions [here](https://python-poetry.org/docs/#installation).
+We use `hatch` for managing development environments. To set up:
-
-Please DO NOT use pip or conda to install the dependencies. Instead, use poetry:
 
 ```bash
-make install_all
+# Activate environment for specific Python version:
+hatch shell dev_py_3_9   # Python 3.9
+hatch shell dev_py_3_10  # Python 3.10  
+hatch shell dev_py_3_11  # Python 3.11
 
-#activate
+# The environment will automatically install all dev dependencies
-
+# Run tests within the activated shell:
-poetry shell
+make test
 ```
 
 ### 📌 Pre-commit
@@ -40,16 +41,21 @@ pre-commit install
 
 ### 🧪 Testing
 
-We use `pytest` to test our code. You can run the tests by running the following command:
+We use `pytest` to test our code across multiple Python versions. You can run tests using:
 
 ```bash
-poetry run pytest tests
+# Run tests with default Python version
-
-# or
-
 make test
+
+# Test specific Python versions:
+make test-py-3.9   # Python 3.9 environment
+make test-py-3.10  # Python 3.10 environment
+make test-py-3.11  # Python 3.11 environment
+
+# When using hatch shells, run tests with:
+make test  # After activating a shell with hatch shell test_XX
 ```
 
-Several packages have been removed from Poetry to make the package lighter. Therefore, it is recommended to run `make install_all` to install the remaining packages and ensure all tests pass. Make sure that all tests pass before submitting a pull request.
+Make sure that all tests pass across all supported Python versions before submitting a pull request.
 
-We look forward to your pull requests and can't wait to see your contributions!
+We look forward to your pull requests and can't wait to see your contributions!

Makefile

@@ -41,3 +41,12 @@ clean:
 
 test:
 	hatch run test
+
+test-py-3.9:
+	hatch run dev_py_3_9:test
+
+test-py-3.10:
+	hatch run dev_py_3_10:test
+
+test-py-3.11:
+	hatch run dev_py_3_11:test

mem0/memory/main.py

@@ -28,8 +28,8 @@ from mem0.memory.utils import (
     get_fact_retrieval_messages,
     parse_messages,
     parse_vision_messages,
-    remove_code_blocks,
     process_telemetry_filters,
+    remove_code_blocks,
 )
 from mem0.utils.factory import EmbedderFactory, LlmFactory, VectorStoreFactory
 
@@ -338,10 +338,9 @@ class Memory(MemoryBase):
         except Exception as e:
             logging.error(f"Error in new_retrieved_facts: {e}")
             new_retrieved_facts = []
-
+        
         if not new_retrieved_facts:
             logger.debug("No new facts retrieved from input. Skipping memory update LLM call.")
-            return []
 
         retrieved_old_memory = []
         new_message_embeddings = {}
@@ -369,24 +368,27 @@ class Memory(MemoryBase):
             temp_uuid_mapping[str(idx)] = item["id"]
             retrieved_old_memory[idx]["id"] = str(idx)
 
-        function_calling_prompt = get_update_memory_messages(
+        if new_retrieved_facts:
-            retrieved_old_memory, new_retrieved_facts, self.config.custom_update_memory_prompt
+            function_calling_prompt = get_update_memory_messages(
-        )
+                retrieved_old_memory, new_retrieved_facts, self.config.custom_update_memory_prompt
-
-        try:
-            response: str = self.llm.generate_response(
-                messages=[{"role": "user", "content": function_calling_prompt}],
-                response_format={"type": "json_object"},
             )
-        except Exception as e:
-            logging.error(f"Error in new memory actions response: {e}")
-            response = ""
 
-        try:
+            try:
-            response = remove_code_blocks(response)
+                response: str = self.llm.generate_response(
-            new_memories_with_actions = json.loads(response)
+                    messages=[{"role": "user", "content": function_calling_prompt}],
-        except Exception as e:
+                    response_format={"type": "json_object"},
-            logging.error(f"Invalid JSON response: {e}")
+                )
+            except Exception as e:
+                logging.error(f"Error in new memory actions response: {e}")
+                response = ""
+
+            try:
+                response = remove_code_blocks(response)
+                new_memories_with_actions = json.loads(response)
+            except Exception as e:
+                logging.error(f"Invalid JSON response: {e}")
+                new_memories_with_actions = {}
+        else:
             new_memories_with_actions = {}
 
         returned_memories = []
@@ -1162,13 +1164,11 @@ class AsyncMemory(MemoryBase):
             response = remove_code_blocks(response)
             new_retrieved_facts = json.loads(response)["facts"]
         except Exception as e:
-            new_retrieved_facts = []
-
-        if not new_retrieved_facts:
-            logger.info("No new facts retrieved from input. Skipping memory update LLM call.")
-            return []
             logging.error(f"Error in new_retrieved_facts: {e}")
             new_retrieved_facts = []
+        
+        if not new_retrieved_facts:
+            logger.debug("No new facts retrieved from input. Skipping memory update LLM call.")
 
         retrieved_old_memory = []
         new_message_embeddings = {}
@@ -1200,31 +1200,25 @@ class AsyncMemory(MemoryBase):
             temp_uuid_mapping[str(idx)] = item["id"]
             retrieved_old_memory[idx]["id"] = str(idx)
 
-        function_calling_prompt = get_update_memory_messages(
+        if new_retrieved_facts:
-            retrieved_old_memory, new_retrieved_facts, self.config.custom_update_memory_prompt
+            function_calling_prompt = get_update_memory_messages(
-        )
+                retrieved_old_memory, new_retrieved_facts, self.config.custom_update_memory_prompt
-        try:
-            response = await asyncio.to_thread(
-                self.llm.generate_response,
-                messages=[{"role": "user", "content": function_calling_prompt}],
-                response_format={"type": "json_object"},
             )
-        except Exception as e:
+            try:
-            response = ""
+                response = await asyncio.to_thread(
-            logging.error(f"Error in new memory actions response: {e}")
+                    self.llm.generate_response,
-            response = ""
+                    messages=[{"role": "user", "content": function_calling_prompt}],
-        try:
+                    response_format={"type": "json_object"},
-            response = remove_code_blocks(response)
+                )
-            new_memories_with_actions = json.loads(response)
+            except Exception as e:
-        except Exception as e:
+                logging.error(f"Error in new memory actions response: {e}")
-            new_memories_with_actions = {}
+                response = ""
-
+            try:
-        if not new_memories_with_actions:
+                response = remove_code_blocks(response)
-            logger.info("No new facts retrieved from input (async). Skipping memory update LLM call.")
+                new_memories_with_actions = json.loads(response)
-            return []
+            except Exception as e:
-
+                logging.error(f"Invalid JSON response: {e}")
-            logging.error(f"Invalid JSON response: {e}")
+                new_memories_with_actions = {}
-            new_memories_with_actions = {}
 
         returned_memories = []
         try:

pyproject.toml

@@ -26,6 +26,32 @@ graph = [
     "neo4j>=5.23.1",
     "rank-bm25>=0.2.2",
 ]
+vector_stores = [
+    "vecs>=0.4.0",
+    "chromadb>=0.4.24",
+    "weaviate-client>=4.4.0",
+    "pinecone<7.0.0",
+    "pinecone-text>=0.1.1",
+    "faiss-cpu>=1.7.4",
+    "upstash-vector>=0.1.0",
+    "azure-search-documents>=11.4.0b8",
+]
+llms = [
+    "groq>=0.3.0",
+    "together>=0.2.10",
+    "litellm>=0.1.0",
+    "ollama>=0.1.0",
+    "vertexai>=0.1.0",
+    "google-generativeai>=0.3.0",
+]
+extras = [
+    "boto3>=1.34.0",
+    "langchain-community>=0.0.0",
+    "sentence-transformers>=2.2.2",
+    "elasticsearch>=8.0.0",
+    "opensearch-py>=2.0.0",
+    "langchain-memgraph>=0.1.0",
+]
 test = [
     "pytest>=8.2.2",
     "pytest-mock>=3.14.0",
@@ -53,6 +79,36 @@ only-include = ["mem0"]
 [tool.hatch.build.targets.wheel.shared-data]
 "README.md" = "README.md"
 
+[tool.hatch.envs.dev_py_3_9]
+python = "3.9"
+features = [
+  "test",
+  "graph",
+  "vector_stores",
+  "llms",
+  "extras",
+]
+
+[tool.hatch.envs.dev_py_3_10]
+python = "3.10"
+features = [
+  "test",
+  "graph",
+  "vector_stores",
+  "llms",
+  "extras",
+]
+
+[tool.hatch.envs.dev_py_3_11]
+python = "3.11"
+features = [
+  "test",
+  "graph",
+  "vector_stores",
+  "llms",
+  "extras",
+]
+
 [tool.hatch.envs.default.scripts]
 format = [
     "ruff format",

tests/memory/test_main.py

@@ -40,10 +40,12 @@ class TestAddToVectorStoreErrors:
 
         return memory
 
-    def test_empty_llm_response_fact_extraction(self, mock_memory, caplog):
+    def test_empty_llm_response_fact_extraction(self, mocker, mock_memory, caplog):
         """Test empty response from LLM during fact extraction"""
         # Setup
         mock_memory.llm.generate_response.return_value = ""
+        mock_capture_event = mocker.MagicMock()
+        mocker.patch("mem0.memory.main.capture_event", mock_capture_event)
 
         # Execute
         with caplog.at_level(logging.ERROR):
@@ -52,9 +54,10 @@ class TestAddToVectorStoreErrors:
             )
 
         # Verify
-        assert mock_memory.llm.generate_response.call_count == 2
+        assert mock_memory.llm.generate_response.call_count == 1
         assert result == []  # Should return empty list when no memories processed
         assert "Error in new_retrieved_facts" in caplog.text
+        assert mock_capture_event.call_count == 1
 
     def test_empty_llm_response_memory_actions(self, mock_memory, caplog):
         """Test empty response from LLM during memory actions"""
@@ -94,25 +97,31 @@ class TestAsyncAddToVectorStoreErrors:
         """Test empty response in AsyncMemory._add_to_vector_store"""
         mocker.patch("mem0.utils.factory.EmbedderFactory.create", return_value=MagicMock())
         mock_async_memory.llm.generate_response.return_value = ""
+        mock_capture_event = mocker.MagicMock()
+        mocker.patch("mem0.memory.main.capture_event", mock_capture_event)
 
         with caplog.at_level(logging.ERROR):
             result = await mock_async_memory._add_to_vector_store(
-                messages=[{"role": "user", "content": "test"}], metadata={}, filters={}, infer=True
+                messages=[{"role": "user", "content": "test"}], metadata={}, effective_filters={}, infer=True
             )
-
+        assert mock_async_memory.llm.generate_response.call_count == 1
         assert result == []
         assert "Error in new_retrieved_facts" in caplog.text
+        assert mock_capture_event.call_count == 1
 
     @pytest.mark.asyncio
     async def test_async_empty_llm_response_memory_actions(self, mock_async_memory, caplog, mocker):
         """Test empty response in AsyncMemory._add_to_vector_store"""
         mocker.patch("mem0.utils.factory.EmbedderFactory.create", return_value=MagicMock())
         mock_async_memory.llm.generate_response.side_effect = ['{"facts": ["test fact"]}', ""]
+        mock_capture_event = mocker.MagicMock()
+        mocker.patch("mem0.memory.main.capture_event", mock_capture_event)
 
         with caplog.at_level(logging.ERROR):
             result = await mock_async_memory._add_to_vector_store(
-                messages=[{"role": "user", "content": "test"}], metadata={}, filters={}, infer=True
+                messages=[{"role": "user", "content": "test"}], metadata={}, effective_filters={}, infer=True
             )
 
         assert result == []
         assert "Invalid JSON response" in caplog.text
+        assert mock_capture_event.call_count == 1

tests/test_main.py

@@ -19,13 +19,14 @@ def mock_openai():
 def memory_instance():
     with (
         patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
-        patch("mem0.utils.factory.VectorStoreFactory") as mock_vector_store,
+        patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
         patch("mem0.utils.factory.LlmFactory") as mock_llm,
         patch("mem0.memory.telemetry.capture_event"),
         patch("mem0.memory.graph_memory.MemoryGraph"),
     ):
         mock_embedder.create.return_value = Mock()
         mock_vector_store.create.return_value = Mock()
+        mock_vector_store.create.return_value.search.return_value = []
         mock_llm.create.return_value = Mock()
 
         config = MemoryConfig(version="v1.1")
@@ -37,13 +38,14 @@ def memory_instance():
 def memory_custom_instance():
     with (
         patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
-        patch("mem0.utils.factory.VectorStoreFactory") as mock_vector_store,
+        patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
         patch("mem0.utils.factory.LlmFactory") as mock_llm,
         patch("mem0.memory.telemetry.capture_event"),
         patch("mem0.memory.graph_memory.MemoryGraph"),
     ):
         mock_embedder.create.return_value = Mock()
         mock_vector_store.create.return_value = Mock()
+        mock_vector_store.create.return_value.search.return_value = []
         mock_llm.create.return_value = Mock()
 
         config = MemoryConfig(
@@ -250,7 +252,11 @@ def test_get_all(memory_instance, version, enable_graph, expected_result):
 
 def test_custom_prompts(memory_custom_instance):
     messages = [{"role": "user", "content": "Test message"}]
+    from mem0.embeddings.mock import MockEmbeddings
     memory_custom_instance.llm.generate_response = Mock()
+    memory_custom_instance.llm.generate_response.return_value = '{"facts": ["fact1", "fact2"]}'
+    memory_custom_instance.embedding_model = MockEmbeddings()
+    
 
     with patch("mem0.memory.main.parse_messages", return_value="Test message") as mock_parse_messages:
         with patch(
@@ -273,7 +279,7 @@ def test_custom_prompts(memory_custom_instance):
             ## custom update memory prompt
             ##
             mock_get_update_memory_messages.assert_called_once_with(
-                [], [], memory_custom_instance.config.custom_update_memory_prompt
+                [], ["fact1", "fact2"], memory_custom_instance.config.custom_update_memory_prompt
             )
 
             memory_custom_instance.llm.generate_response.assert_any_call(