feat(api): api update

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 8
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/supermemory--inc%2Fsupermemory-9d4f071b79b2524fee219bcfb0eafb1070969bb809e2f3dbee89392bfb3eac53.yml
-openapi_spec_hash: 089ce871ebc7bda9d2974706373a989e
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/supermemory--inc%2Fsupermemory-783134192ebb9f62b9a25815c143704ccec4466fb4c5ba611d60d854db976970.yml
+openapi_spec_hash: 2d0e081f9844f31ae00f95cff68ec29d
 config_hash: eb32087403f958eead829e810f5a71b8

src/supermemory/resources/memory.py

@@ -66,11 +66,24 @@ def create(
         metadata
 
         Args:
-          content: Content of the memory
+          content: The content to extract and process into a memory. This can be a URL to a
+              website, a PDF, an image, or a video.
 
-          metadata: Optional metadata for the memory
+              Plaintext: Any plaintext format
 
-          user_id: Optional end user ID this memory belongs to
+              URL: A URL to a website, PDF, image, or video
+
+              We automatically detect the content type from the url's response format.
+
+          metadata: Optional metadata for the memory. This is used to store additional information
+              about the memory. You can use this to store any additional information you need
+              about the memory. Metadata can be filtered through. Keys must be strings and are
+              case sensitive. Values can be strings, numbers, or booleans. You cannot nest
+              objects.
+
+          user_id: Optional end user ID this memory belongs to. This is used to group memories by
+              user. You should use the same ID stored in your external system where the user
+              is stored
 
           extra_headers: Send extra headers
 
@@ -261,11 +274,24 @@ async def create(
         metadata
 
         Args:
-          content: Content of the memory
+          content: The content to extract and process into a memory. This can be a URL to a
+              website, a PDF, an image, or a video.
+
+              Plaintext: Any plaintext format
+
+              URL: A URL to a website, PDF, image, or video
+
+              We automatically detect the content type from the url's response format.
 
-          metadata: Optional metadata for the memory
+          metadata: Optional metadata for the memory. This is used to store additional information
+              about the memory. You can use this to store any additional information you need
+              about the memory. Metadata can be filtered through. Keys must be strings and are
+              case sensitive. Values can be strings, numbers, or booleans. You cannot nest
+              objects.
 
-          user_id: Optional end user ID this memory belongs to
+          user_id: Optional end user ID this memory belongs to. This is used to group memories by
+              user. You should use the same ID stored in your external system where the user
+              is stored
 
           extra_headers: Send extra headers
 

src/supermemory/resources/search.py

@@ -66,32 +66,40 @@ def execute(
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
     ) -> SearchExecuteResponse:
         """
-        Search through documents with metadata filtering
+        Search through documents with filtering
 
         Args:
           q: Search query string
 
           categories_filter: Optional category filters
 
-          chunk_threshold: Maximum number of chunks to return
+          chunk_threshold: Threshold / sensitivity for chunk selection. 0 is least sensitive (returns most
+              chunks, more results), 1 is most sensitive (returns lesser chunks, accurate
+              results)
 
-          doc_id: Optional document ID to search within
+          doc_id: Optional document ID to search within. You can use this to find chunks in a very
+              large document.
 
-          document_threshold: Maximum number of documents to return
+          document_threshold: Threshold / sensitivity for document selection. 0 is least sensitive (returns
+              most documents, more results), 1 is most sensitive (returns lesser documents,
+              accurate results)
 
           filters: Optional filters to apply to the search
 
           include_summary: If true, include document summary in the response. This is helpful if you want a
-              chatbot to know the context of the document.
+              chatbot to know the full context of the document.
 
           limit: Maximum number of results to return
 
-          only_matching_chunks: If true, only return matching chunks without context
+          only_matching_chunks: If true, only return matching chunks without context. Normally, we send the
+              previous and next chunk to provide more context for LLMs. If you only want the
+              matching chunk, set this to true.
 
           rewrite_query: If true, rewrites the query to make it easier to find documents. This increases
               the latency by about 400ms
 
-          user_id: End user ID this search is associated with
+          user_id: End user ID this search is associated with. NOTE: This also acts as a filter for
+              the search.
 
           extra_headers: Send extra headers
 
@@ -168,32 +176,40 @@ async def execute(
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
     ) -> SearchExecuteResponse:
         """
-        Search through documents with metadata filtering
+        Search through documents with filtering
 
         Args:
           q: Search query string
 
           categories_filter: Optional category filters
 
-          chunk_threshold: Maximum number of chunks to return
+          chunk_threshold: Threshold / sensitivity for chunk selection. 0 is least sensitive (returns most
+              chunks, more results), 1 is most sensitive (returns lesser chunks, accurate
+              results)
 
-          doc_id: Optional document ID to search within
+          doc_id: Optional document ID to search within. You can use this to find chunks in a very
+              large document.
 
-          document_threshold: Maximum number of documents to return
+          document_threshold: Threshold / sensitivity for document selection. 0 is least sensitive (returns
+              most documents, more results), 1 is most sensitive (returns lesser documents,
+              accurate results)
 
           filters: Optional filters to apply to the search
 
           include_summary: If true, include document summary in the response. This is helpful if you want a
-              chatbot to know the context of the document.
+              chatbot to know the full context of the document.
 
           limit: Maximum number of results to return
 
-          only_matching_chunks: If true, only return matching chunks without context
+          only_matching_chunks: If true, only return matching chunks without context. Normally, we send the
+              previous and next chunk to provide more context for LLMs. If you only want the
+              matching chunk, set this to true.
 
           rewrite_query: If true, rewrites the query to make it easier to find documents. This increases
               the latency by about 400ms
 
-          user_id: End user ID this search is associated with
+          user_id: End user ID this search is associated with. NOTE: This also acts as a filter for
+              the search.
 
           extra_headers: Send extra headers
 

src/supermemory/types/memory_create_params.py

@@ -12,12 +12,31 @@
 
 class MemoryCreateParams(TypedDict, total=False):
     content: Required[str]
-    """Content of the memory"""
+    """The content to extract and process into a memory.
+
+    This can be a URL to a website, a PDF, an image, or a video.
+
+    Plaintext: Any plaintext format
+
+    URL: A URL to a website, PDF, image, or video
+
+    We automatically detect the content type from the url's response format.
+    """
 
     id: str
 
     metadata: Dict[str, Union[str, float, bool]]
-    """Optional metadata for the memory"""
+    """Optional metadata for the memory.
+
+    This is used to store additional information about the memory. You can use this
+    to store any additional information you need about the memory. Metadata can be
+    filtered through. Keys must be strings and are case sensitive. Values can be
+    strings, numbers, or booleans. You cannot nest objects.
+    """
 
     user_id: Annotated[str, PropertyInfo(alias="userId")]
-    """Optional end user ID this memory belongs to"""
+    """Optional end user ID this memory belongs to.
+
+    This is used to group memories by user. You should use the same ID stored in
+    your external system where the user is stored
+    """

src/supermemory/types/memory_get_response.py

@@ -1,6 +1,8 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 from typing import Dict, Optional
+from datetime import datetime
+from typing_extensions import Literal
 
 from pydantic import Field as FieldInfo
 
@@ -10,18 +12,25 @@
 
 
 class Doc(BaseModel):
-    created_at: str = FieldInfo(alias="createdAt")
+    created_at: datetime = FieldInfo(alias="createdAt")
+    """Timestamp when the memory was created"""
 
-    updated_at: str = FieldInfo(alias="updatedAt")
+    updated_at: datetime = FieldInfo(alias="updatedAt")
+    """Timestamp when the memory was last updated"""
 
     metadata: Optional[Dict[str, object]] = None
+    """Custom metadata associated with the memory"""
 
     summary: Optional[str] = None
+    """Summary of the memory content"""
 
     title: Optional[str] = None
+    """Title of the memory"""
 
 
 class MemoryGetResponse(BaseModel):
     doc: Doc
+    """Memory document details"""
 
-    status: Optional[str] = None
+    status: Optional[Literal["queued", "extracting", "chunking", "embedding", "indexing", "done", "failed"]] = None
+    """Current processing status of the memory"""

src/supermemory/types/search_execute_params.py

@@ -20,28 +20,43 @@ class SearchExecuteParams(TypedDict, total=False):
     """Optional category filters"""
 
     chunk_threshold: Annotated[float, PropertyInfo(alias="chunkThreshold")]
-    """Maximum number of chunks to return"""
+    """Threshold / sensitivity for chunk selection.
+
+    0 is least sensitive (returns most chunks, more results), 1 is most sensitive
+    (returns lesser chunks, accurate results)
+    """
 
     doc_id: Annotated[str, PropertyInfo(alias="docId")]
-    """Optional document ID to search within"""
+    """Optional document ID to search within.
+
+    You can use this to find chunks in a very large document.
+    """
 
     document_threshold: Annotated[float, PropertyInfo(alias="documentThreshold")]
-    """Maximum number of documents to return"""
+    """Threshold / sensitivity for document selection.
+
+    0 is least sensitive (returns most documents, more results), 1 is most sensitive
+    (returns lesser documents, accurate results)
+    """
 
     filters: Filters
     """Optional filters to apply to the search"""
 
     include_summary: Annotated[bool, PropertyInfo(alias="includeSummary")]
     """If true, include document summary in the response.
 
-    This is helpful if you want a chatbot to know the context of the document.
+    This is helpful if you want a chatbot to know the full context of the document.
     """
 
     limit: int
     """Maximum number of results to return"""
 
     only_matching_chunks: Annotated[bool, PropertyInfo(alias="onlyMatchingChunks")]
-    """If true, only return matching chunks without context"""
+    """If true, only return matching chunks without context.
+
+    Normally, we send the previous and next chunk to provide more context for LLMs.
+    If you only want the matching chunk, set this to true.
+    """
 
     rewrite_query: Annotated[bool, PropertyInfo(alias="rewriteQuery")]
     """If true, rewrites the query to make it easier to find documents.
@@ -50,7 +65,10 @@ class SearchExecuteParams(TypedDict, total=False):
     """
 
     user_id: Annotated[str, PropertyInfo(alias="userId")]
-    """End user ID this search is associated with"""
+    """End user ID this search is associated with.
+
+    NOTE: This also acts as a filter for the search.
+    """
 
 
 class FiltersUnionMember0(TypedDict, total=False):