Rename embedchain to mem0 and open sourcing code for long term memory (#1474)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

mem0/vector_stores/configs.py

@@ -0,0 +1,45 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field, field_validator, model_validator
+
+
+class QdrantConfig(BaseModel):
+    host: Optional[str] = Field(None, description="Host address for Qdrant server")
+    port: Optional[int] = Field(None, description="Port for Qdrant server")
+    path: Optional[str] = Field(None, description="Path for local Qdrant database")
+    url: Optional[str] = Field(None, description="Full URL for Qdrant server")
+    api_key: Optional[str] = Field(None, description="API key for Qdrant server")
+
+    @model_validator(mode="before")
+    def check_host_port_or_path(cls, values):
+        host, port, path, url, api_key = (
+            values.get("host"),
+            values.get("port"),
+            values.get("path"),
+            values.get("url"),
+            values.get("api_key"),
+        )
+        if not path and not (host and port) and not (url and api_key):
+            raise ValueError(
+                "Either 'host' and 'port' or 'url' and 'api_key' or 'path' must be provided."
+            )
+        return values
+
+
+class VectorStoreConfig(BaseModel):
+    provider: str = Field(
+        description="Provider of the vector store (e.g., 'qdrant', 'chromadb', 'elasticsearch')",
+        default="qdrant",
+    )
+    config: QdrantConfig = Field(
+        description="Configuration for the specific vector store",
+        default=QdrantConfig(path="/tmp/qdrant"),
+    )
+
+    @field_validator("config")
+    def validate_config(cls, v, values):
+        provider = values.data.get("provider")
+        if provider == "qdrant":
+            return QdrantConfig(**v.model_dump())
+        else:
+            raise ValueError(f"Unsupported vector store provider: {provider}")