Add OpenAI proxy (#1503)

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

mem0/vector_stores/chroma.py

@@ -21,20 +21,20 @@ class OutputData(BaseModel):
 class ChromaDB(VectorStoreBase):
     def __init__(
         self,
-        collection_name="mem0",
-        client=None,
-        host=None,
-        port=None,
-        path=None
+        collection_name,
+        client,
+        host,
+        port,
+        path
     ):
         """
         Initialize the Qdrant vector store.
 
         Args:
-            client (QdrantClient, optional): Existing Qdrant client instance. Defaults to None.
-            host (str, optional): Host address for Qdrant server. Defaults to None.
-            port (int, optional): Port for Qdrant server. Defaults to None.
-            path (str, optional): Path for local Qdrant database. Defaults to None.
+            client (QdrantClient, optional): Existing Qdrant client instance.
+            host (str, optional): Host address for Qdrant server.
+            port (int, optional): Port for Qdrant server.
+            path (str, optional): Path for local Qdrant database.
         """
         if client:
             self.client = client
@@ -95,7 +95,7 @@ class ChromaDB(VectorStoreBase):
 
         Args:
             name (str): Name of the collection.
-            embedding_fn (function): Embedding function to use.
+            embedding_fn (function): Embedding function to use. Defaults to None.
         """
         # Skip creating collection if already exists
         collections = self.list_cols()
@@ -213,7 +213,7 @@ class ChromaDB(VectorStoreBase):
 
         Args:
             name (str): Name of the collection.
-            filters (dict, optional): Filters to apply to the list. Defaults to None.
+            filters (dict, optional): Filters to apply to the list.
             limit (int, optional): Number of vectors to return. Defaults to 100.
 
         Returns:

mem0/vector_stores/configs.py

@@ -3,14 +3,23 @@ from typing import Optional
 from pydantic import BaseModel, Field, field_validator, model_validator
 
 
+def create_default_config(provider: str):
+    """Create a default configuration based on the provider."""
+    if provider == "qdrant":
+        return QdrantConfig(path="/tmp/qdrant")
+    elif provider == "chromadb":
+        return ChromaDbConfig(path="/tmp/chromadb")
+    else:
+        raise ValueError(f"Unsupported vector store provider: {provider}")
+
+
 class QdrantConfig(BaseModel):
-    collection_name: str = Field(default="mem0", description="Name of the collection")
-    embedding_model_dims: Optional[int] = Field(
-        default=1536, description="Dimensions of the embedding model"
-    )
+    collection_name: str = Field("mem0", description="Name of the collection")
+    embedding_model_dims: Optional[int] = Field(1536, description="Dimensions of the embedding model")
+    client: Optional[str] = Field(None, description="Existing Qdrant client instance")
     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")
+    path: Optional[str] = Field("/tmp/qdrant", 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")
 
@@ -31,18 +40,11 @@ class QdrantConfig(BaseModel):
 
 
 class ChromaDbConfig(BaseModel):
-    collection_name: str = Field(
-        default="mem0", description="Default name for the collection"
-    )
-    path: Optional[str] = Field(
-        default=None, description="Path to the database directory"
-    )
-    host: Optional[str] = Field(
-        default=None, description="Database connection remote host"
-    )
-    port: Optional[str] = Field(
-        default=None, description="Database connection remote port"
-    )
+    collection_name: str = Field("mem0", description="Default name for the collection")
+    client: Optional[str] = Field(None, description="Existing ChromaDB client instance")
+    path: Optional[str] = Field(None, description="Path to the database directory")
+    host: Optional[str] = Field(None, description="Database connection remote host")
+    port: Optional[str] = Field(None, description="Database connection remote port")
 
     @model_validator(mode="before")
     def check_host_port_or_path(cls, values):
@@ -59,15 +61,37 @@ class VectorStoreConfig(BaseModel):
     )
     config: Optional[dict] = Field(
         description="Configuration for the specific vector store",
-        default={},
+        default=None
     )
 
     @field_validator("config")
     def validate_config(cls, v, values):
         provider = values.data.get("provider")
-        if provider == "qdrant":
-            return QdrantConfig(**v.model_dump())
-        elif provider == "chromadb":
-            return ChromaDbConfig(**v.model_dump())
-        else:
-            raise ValueError(f"Unsupported vector store provider: {provider}")
+        
+        if v is None:
+            return create_default_config(provider)
+        
+        if isinstance(v, dict):
+            if provider == "qdrant":
+                return QdrantConfig(**v)
+            elif provider == "chromadb":
+                return ChromaDbConfig(**v)
+        
+        return v
+
+    @model_validator(mode="after")
+    def ensure_config_type(cls, values):
+        provider = values.provider
+        config = values.config
+        
+        if config is None:
+            values.config = create_default_config(provider)
+        elif isinstance(config, dict):
+            if provider == "qdrant":
+                values.config = QdrantConfig(**config)
+            elif provider == "chromadb":
+                values.config = ChromaDbConfig(**config)
+        elif not isinstance(config, (QdrantConfig, ChromaDbConfig)):
+            raise ValueError(f"Invalid config type for provider {provider}")
+        
+        return values

mem0/vector_stores/qdrant.py

@@ -20,25 +20,25 @@ from mem0.vector_stores.base import VectorStoreBase
 class Qdrant(VectorStoreBase):
     def __init__(
         self,
-        collection_name="mem0",
-        embedding_model_dims=1536,
-        client=None,
-        host="localhost",
-        port=6333,
-        path=None,
-        url=None,
-        api_key=None,
+        collection_name,
+        embedding_model_dims,
+        client,
+        host,
+        port,
+        path,
+        url,
+        api_key,
     ):
         """
         Initialize the Qdrant vector store.
 
         Args:
-            client (QdrantClient, optional): Existing Qdrant client instance. Defaults to None.
-            host (str, optional): Host address for Qdrant server. Defaults to "localhost".
-            port (int, optional): Port for Qdrant server. Defaults to 6333.
-            path (str, optional): Path for local Qdrant database. Defaults to None.
-            url (str, optional): Full URL for Qdrant server. Defaults to None.
-            api_key (str, optional): API key for Qdrant server. Defaults to None.
+            client (QdrantClient, optional): Existing Qdrant client instance.
+            host (str, optional): Host address for Qdrant server.
+            port (int, optional): Port for Qdrant server.
+            path (str, optional): Path for local Qdrant database.
+            url (str, optional): Full URL for Qdrant server.
+            api_key (str, optional): API key for Qdrant server.
         """
         if client:
             self.client = client