Feature/remove version from ingestion end pt (#936)

* sync model

* remove ability to set version

* tweak versions impl

* fix version bug

py/cli/commands/ingestion.py

@@ -21,21 +21,15 @@
 @click.option(
     "--metadatas", type=JSON, help="Metadatas for ingestion as a JSON string"
 )
-@click.option(
-    "--versions",
-    multiple=True,
-    help="Starting version for ingested files (e.g. `v1`)",
-)
 @click.pass_obj
-def ingest_files(client, file_paths, document_ids, metadatas, versions):
+def ingest_files(client, file_paths, document_ids, metadatas):
     """Ingest files into R2R."""
     with timer():
         file_paths = list(file_paths)
         document_ids = list(document_ids) if document_ids else None
-        versions = list(versions) if versions else None
 
         response = client.ingest_files(
-            file_paths, metadatas, document_ids, versions
+            file_paths, metadatas, document_ids
         )
     click.echo(json.dumps(response, indent=2))
 

py/core/main/api/routes/ingestion/base.py

@@ -34,7 +34,7 @@ def load_openapi_extras(self):
 
     def setup_routes(self):
         # Note, we use the following verbose input parameters because FastAPI struggles to handle `File` input and `Body` inputs
-        # at the same time. Therefore, we must ues `Form` inputs for the metadata, document_ids, and versions inputs.
+        # at the same time. Therefore, we must ues `Form` inputs for the metadata, document_ids
         ingest_files_extras = self.openapi_extras.get("ingest_files", {})
         ingest_files_descriptions = ingest_files_extras.get(
             "input_descriptions", {}
@@ -53,9 +53,6 @@ async def ingest_files_app(
                 None,
                 description=ingest_files_descriptions.get("document_ids"),
             ),
-            versions: Optional[Json[list[str]]] = Form(
-                None, description=ingest_files_descriptions.get("versions")
-            ),
             metadatas: Optional[Json[list[dict]]] = Form(
                 None, description=ingest_files_descriptions.get("metadatas")
             ),
@@ -107,7 +104,6 @@ async def ingest_files_app(
                 files=files,
                 metadatas=metadatas,
                 document_ids=document_ids,
-                versions=versions,
                 user=auth_user,
                 chunking_provider=chunking_provider,
             )

py/core/main/services/ingestion_service.py

@@ -28,7 +28,7 @@
 
 logger = logging.getLogger(__name__)
 MB_CONVERSION_FACTOR = 1024 * 1024
-
+STARTING_VERSION = "v0"
 
 class IngestionService(Service):
     def __init__(
@@ -56,7 +56,6 @@ async def ingest_files(
         user: UserResponse,
         metadatas: Optional[list[dict]] = None,
         document_ids: Optional[list[UUID]] = None,
-        versions: Optional[list[str]] = None,
         chunking_provider: Optional[ChunkingProvider] = None,
         *args: Any,
         **kwargs: Any,
@@ -89,7 +88,6 @@ async def ingest_files(
             # ingests all documents in parallel
             return await self.ingest_documents(
                 documents,
-                versions,
                 chunking_provider=chunking_provider,
                 *args,
                 **kwargs,
@@ -178,10 +176,11 @@ async def update_files(
                 )
                 documents.append(document)
 
+
             ingestion_results = await self.ingest_documents(
                 documents,
-                versions=new_versions,
                 chunking_provider=chunking_provider,
+                versions=new_versions,
                 *args,
                 **kwargs,
             )
@@ -252,7 +251,7 @@ async def ingest_documents(
         }
 
         for iteration, document in enumerate(documents):
-            version = versions[iteration] if versions else "v0"
+            version = versions[iteration] if versions else STARTING_VERSION
 
             # Check for duplicates within the current batch
             if document.id in processed_documents:
@@ -263,7 +262,8 @@ async def ingest_documents(
 
             if (
                 document.id in existing_document_info
-                and existing_document_info[document.id].version == version
+                # apply `geq` check to prevent re-ingestion of updated documents
+                and (existing_document_info[document.id].version >= version)
                 and existing_document_info[document.id].status == "success"
             ):
                 logger.error(
@@ -305,6 +305,9 @@ async def ingest_documents(
             processed_documents[document.id] = document.metadata.get(
                 "title", str(document.id)
             )
+            # Add version to metadata to propagate through pipeline
+            document.metadata["version"] = version
+
 
         if duplicate_documents:
             duplicate_details = [
@@ -336,7 +339,6 @@ async def ingest_documents(
                     not in [skipped["id"] for skipped in skipped_documents]
                 ],
             ),
-            versions=[info.version for info in document_infos],
             run_manager=self.run_manager,
             *args,
             **kwargs,

py/core/pipes/ingestion/parsing_pipe.py

@@ -72,11 +72,9 @@ async def _run_logic(
         input: Input,
         state: AsyncState,
         run_id: UUID,
-        versions: Optional[list[str]] = None,
         *args,
         **kwargs,
     ) -> AsyncGenerator[DocumentExtraction, None]:
         async for document in input.message:
-            version = versions[0] if versions else "v0"
-            async for result in self._parse(document, run_id, version):
-                yield result
+            async for result in self._parse(document, run_id, document.metadata.get("version", "1.0")):
+                yield result

py/sdk/ingestion.py

@@ -15,7 +15,6 @@ async def ingest_files(
         file_paths: list[str],
         document_ids: Optional[list[Union[str, UUID]]] = None,
         metadatas: Optional[list[dict]] = None,
-        versions: Optional[list[str]] = None,
         chunking_settings: Optional[Union[dict, ChunkingConfig]] = None,
     ) -> dict:
         """
@@ -25,7 +24,6 @@ async def ingest_files(
             file_paths (List[str]): List of file paths to ingest.
             document_ids (Optional[List[str]]): List of document IDs.
             metadatas (Optional[List[dict]]): List of metadata dictionaries for each file.
-            versions (Optional[List[str]]): List of version strings for each file.
             chunking_settings (Optional[Union[dict, ChunkingConfig]]): Custom chunking configuration.
 
         Returns:
@@ -39,10 +37,6 @@ async def ingest_files(
             raise ValueError(
                 "Number of metadatas must match number of document IDs."
             )
-        if versions is not None and len(file_paths) != len(versions):
-            raise ValueError(
-                "Number of versions must match number of document IDs."
-            )
         if (
             chunking_settings is not None
             and chunking_settings is not ChunkingConfig
@@ -80,7 +74,6 @@ async def ingest_files(
                     if document_ids
                     else None
                 ),
-                "versions": json.dumps(versions) if versions else None,
                 "chunking_settings": (
                     json.dumps(
                         chunking_settings.model_dump()

py/sdk/models.py

@@ -205,6 +205,37 @@ class Token(BaseModel):
     token_type: str
 
 
+class IndexMeasure(str, Enum):
+    """
+    An enum representing the types of distance measures available for indexing.
+
+    Attributes:
+        cosine_distance (str): The cosine distance measure for indexing.
+        l2_distance (str): The Euclidean (L2) distance measure for indexing.
+        max_inner_product (str): The maximum inner product measure for indexing.
+    """
+
+    cosine_distance = "cosine_distance"
+    l2_distance = "l2_distance"
+    max_inner_product = "max_inner_product"
+
+
+
+class HybridSearchSettings(BaseModel):
+    full_text_weight: float = Field(
+        default=1.0, description="Weight to apply to full text search"
+    )
+    semantic_weight: float = Field(
+        default=5.0, description="Weight to apply to semantic search"
+    )
+    full_text_limit: int = Field(
+        default=200,
+        description="Maximum number of results to return from full text search",
+    )
+    rrf_k: int = Field(
+        default=50, description="K-value for RRF (Rank Reciprocal Fusion)"
+    )
+
 class VectorSearchSettings(BaseModel):
     use_vector_search: bool = Field(
         default=True, description="Whether to use vector search"