📦 NEW: add endpoint for memory

examples/memory/memory.add.py

@@ -0,0 +1,76 @@
+"""
+Example: Add text directly to memory
+
+1. Run memory.create.py first to create a memory.
+2. Add your API key to the environment variables or replace it in the code.
+"""
+
+import os
+
+from langbase import Langbase
+
+# Initialize the Langbase client
+langbase = Langbase(api_key=os.getenv("LANGBASE_API_KEY"))
+
+
+def main():
+    try:
+        # Basic text addition
+        print("📝 Adding basic text to memory...")
+        basic_result = langbase.memories.add(
+            memory_name="my-knowledge-base",
+            text="This is important information about machine learning fundamentals. "
+            "It covers supervised learning, unsupervised learning, and reinforcement learning concepts.",
+        )
+        print(f"✅ Basic text added: {basic_result['document_name']}")
+
+        # Text addition with custom name and metadata
+        print("\n📝 Adding detailed text with metadata...")
+        detailed_result = langbase.memories.add(
+            memory_name="my-knowledge-base",
+            text="Deep learning is a subset of machine learning that uses artificial neural networks "
+            "with multiple layers to model and understand complex patterns in data. It has "
+            "revolutionized fields like computer vision, natural language processing, and speech recognition.",
+            document_name="deep-learning-intro",
+            metadata={
+                "category": "machine-learning",
+                "topic": "deep-learning",
+                "difficulty": "intermediate",
+                "source": "manual-entry",
+            },
+        )
+        print(f"✅ Detailed text added: {detailed_result['document_name']}")
+
+        # Multiple text entries
+        texts = [
+            {
+                "text": "Supervised learning uses labeled training data to learn a mapping from inputs to outputs.",
+                "document_name": "supervised-learning",
+                "metadata": {"type": "definition", "category": "ml-concepts"},
+            },
+            {
+                "text": "Unsupervised learning finds hidden patterns in data without using labeled examples.",
+                "document_name": "unsupervised-learning",
+                "metadata": {"type": "definition", "category": "ml-concepts"},
+            },
+            {
+                "text": "Reinforcement learning learns optimal actions through trial and error interactions with an environment.",
+                "document_name": "reinforcement-learning",
+                "metadata": {"type": "definition", "category": "ml-concepts"},
+            },
+        ]
+
+        print("\n📝 Adding multiple texts...")
+        for item in texts:
+            result = langbase.memories.add(memory_name="my-knowledge-base", **item)
+            print(f"✅ Added: {result['document_name']}")
+
+        print("\n🎉 All texts have been added to the memory!")
+        print("You can now query this memory to retrieve relevant information.")
+
+    except Exception as error:
+        print(f"❌ Error: {error}")
+
+
+if __name__ == "__main__":
+    main()

langbase/constants.py

@@ -38,6 +38,7 @@
 MEMORY_DOCUMENTS_ENDPOINT = "/v1/memory/{memory_name}/documents"
 MEMORY_DOCUMENT_DETAIL_ENDPOINT = "/v1/memory/{memory_name}/documents/{document_name}"
 MEMORY_DOCUMENTS_UPLOAD_ENDPOINT = "/v1/memory/documents"
+MEMORY_TEXT_ADD_ENDPOINT = "/v1/memory/text"
 MEMORY_DOCUMENT_EMBEDDINGS_RETRY_ENDPOINT = (
     "/v1/memory/{memory_name}/documents/{document_name}/embeddings/retry"
 )

langbase/primitives/memories.py

@@ -17,11 +17,13 @@
     MEMORY_DOCUMENTS_UPLOAD_ENDPOINT,
     MEMORY_ENDPOINT,
     MEMORY_RETRIEVE_ENDPOINT,
+    MEMORY_TEXT_ADD_ENDPOINT,
 )
 from langbase.errors import APIError, create_api_error
 from langbase.types import (
     ContentType,
     EmbeddingModel,
+    MemoryAddTextResponse,
     MemoryCreateResponse,
     MemoryDeleteDocResponse,
     MemoryDeleteResponse,
@@ -250,3 +252,30 @@ def list(self) -> List[MemoryListResponse]:
             List of memory objects
         """
         return self.request.get(MEMORY_ENDPOINT)
+
+    def add(
+        self,
+        memory_name: str,
+        text: str,
+        document_name: Optional[str] = None,
+        metadata: Optional[Dict[str, str]] = None,
+    ) -> MemoryAddTextResponse:
+        """
+        Add text directly to a memory without file upload.
+
+        Args:
+            memory_name: Name of the memory to add text to
+            text: Text content to add to the memory
+            document_name: Optional custom document name
+            metadata: Optional metadata for the text document
+
+        Returns:
+            Text addition response
+        """
+        options = {
+            "memoryName": memory_name,
+            "text": text,
+            "documentName": document_name,
+            "metadata": metadata,
+        }
+        return self.request.post(MEMORY_TEXT_ADD_ENDPOINT, clean_null_values(options))

langbase/types.py

@@ -371,6 +371,15 @@ class MemoryRetryDocEmbedResponse(BaseDeleteResponse):
     pass
 
 
+class MemoryAddTextResponse(TypedDict):
+    """Response from adding text to memory."""
+
+    document_name: str
+    status: Literal["queued"]
+    memory_name: str
+    url: str
+
+
 class MemoryRetrieveResponse(TypedDict):
     """Response from retrieving from memory."""
 

tests/test_memories.py

@@ -15,8 +15,10 @@
     MEMORY_DOCUMENTS_UPLOAD_ENDPOINT,
     MEMORY_ENDPOINT,
     MEMORY_RETRIEVE_ENDPOINT,
+    MEMORY_TEXT_ADD_ENDPOINT,
 )
 from langbase.types import (
+    MemoryAddTextResponse,
     MemoryCreateResponse,
     MemoryDeleteResponse,
     MemoryListDocResponse,
@@ -265,3 +267,76 @@ def test_documents_embeddings_retry(self, langbase_client, mock_responses):
         assert len(responses.calls) == 1
         request = responses.calls[0].request
         validate_response_headers(request.headers, AUTH_AND_JSON_CONTENT_HEADER)
+
+    @responses.activate
+    def test_memories_add_text_minimal(self, langbase_client):
+        """Test memories.add method with minimal parameters."""
+        memory_name = "test-memory"
+        text = "This is a test text to add to memory."
+
+        expected_response = {
+            "document_name": "text-2024-08-21T10-30-45.txt",
+            "status": "queued",
+            "memory_name": memory_name,
+            "url": f"https://langbase.com/memory/user/{memory_name}",
+        }
+
+        responses.add(
+            responses.POST,
+            f"{BASE_URL}{MEMORY_TEXT_ADD_ENDPOINT}",
+            json=expected_response,
+            status=200,
+        )
+
+        result = langbase_client.memories.add(memory_name=memory_name, text=text)
+
+        assert result == expected_response
+        assert len(responses.calls) == 1
+        request = responses.calls[0].request
+        validate_response_headers(request.headers, AUTH_AND_JSON_CONTENT_HEADER)
+
+        request_json = json.loads(request.body)
+        assert request_json["memoryName"] == memory_name
+        assert request_json["text"] == text
+        assert "documentName" not in request_json
+        assert "metadata" not in request_json
+
+    @responses.activate
+    def test_memories_add_text_full(self, langbase_client):
+        """Test memories.add method with all parameters."""
+        memory_name = "test-memory"
+        text = "This is a comprehensive test text with metadata."
+        document_name = "test-document"
+        metadata = {"category": "test", "source": "unit-test", "difficulty": "easy"}
+
+        expected_response = {
+            "document_name": f"{document_name}.txt",
+            "status": "queued",
+            "memory_name": memory_name,
+            "url": f"https://langbase.com/memory/user/{memory_name}",
+        }
+
+        responses.add(
+            responses.POST,
+            f"{BASE_URL}{MEMORY_TEXT_ADD_ENDPOINT}",
+            json=expected_response,
+            status=200,
+        )
+
+        result = langbase_client.memories.add(
+            memory_name=memory_name,
+            text=text,
+            document_name=document_name,
+            metadata=metadata,
+        )
+
+        assert result == expected_response
+        assert len(responses.calls) == 1
+        request = responses.calls[0].request
+        validate_response_headers(request.headers, AUTH_AND_JSON_CONTENT_HEADER)
+
+        request_json = json.loads(request.body)
+        assert request_json["memoryName"] == memory_name
+        assert request_json["text"] == text
+        assert request_json["documentName"] == document_name
+        assert request_json["metadata"] == metadata