feat(Vector): support pgvector (#1624)

private_gpt/components/vector_store/vector_store_component.py

@@ -40,6 +40,21 @@ class VectorStoreComponent:
     @inject
     def __init__(self, settings: Settings) -> None:
         match settings.vectorstore.database:
+            case "pgvector":
+                from llama_index.vector_stores import PGVectorStore
+
+                if settings.pgvector is None:
+                    raise ValueError(
+                        "PGVectorStore settings not found. Please provide settings."
+                    )
+
+                self.vector_store = typing.cast(
+                    VectorStore,
+                    PGVectorStore.from_params(
+                        **settings.pgvector.model_dump(exclude_none=True)
+                    ),
+                )
+
             case "chroma":
                 try:
                     import chromadb  # type: ignore

private_gpt/settings/settings.py

@@ -101,7 +101,7 @@ class LLMSettings(BaseModel):
 
 
 class VectorstoreSettings(BaseModel):
-    database: Literal["chroma", "qdrant"]
+    database: Literal["chroma", "qdrant", "pgvector"]
 
 
 class LocalSettings(BaseModel):
@@ -197,6 +197,41 @@ class UISettings(BaseModel):
     )
 
 
+class PGVectorSettings(BaseModel):
+    host: str = Field(
+        "localhost",
+        description="The server hosting the Postgres database",
+    )
+    port: int = Field(
+        5432,
+        description="The port on which the Postgres database is accessible",
+    )
+    user: str = Field(
+        "postgres",
+        description="The user to use to connect to the Postgres database",
+    )
+    password: str = Field(
+        "postgres",
+        description="The password to use to connect to the Postgres database",
+    )
+    database: str = Field(
+        "postgres",
+        description="The database to use to connect to the Postgres database",
+    )
+    embed_dim: int = Field(
+        384,
+        description="The dimension of the embeddings stored in the Postgres database",
+    )
+    schema_name: str = Field(
+        "public",
+        description="The name of the schema in the Postgres database where the embeddings are stored",
+    )
+    table_name: str = Field(
+        "embeddings",
+        description="The name of the table in the Postgres database where the embeddings are stored",
+    )
+
+
 class QdrantSettings(BaseModel):
     location: str | None = Field(
         None,
@@ -263,6 +298,7 @@ class Settings(BaseModel):
     ollama: OllamaSettings
     vectorstore: VectorstoreSettings
     qdrant: QdrantSettings | None = None
+    pgvector: PGVectorSettings | None = None
 
 
 """