Add configs to Embedding docs (#1702)

docs/components/embedders.mdx

@@ -1,64 +0,0 @@
----
-title: Embedding models
----
-
-## Overview
-
-Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.
-
-<CardGroup cols={3}>
-    <Card title="OpenAI" href="#openai"></Card>
-    <Card title="Ollama" href="#ollama"></Card>
-</CardGroup>
-
-> When using `Qdrant` as a vector database, ensure you update the `embedding_model_dims` to match the dimensions of the embedding model you are using.
-
-## OpenAI
-
-To use OpenAI embedding models, set the `OPENAI_API_KEY` environment variable. You can obtain the OpenAI API key from the [OpenAI Platform](https://platform.openai.com/account/api-keys).
-
-Example of how to select the desired embedding model:
-
-```python
-import os
-from mem0 import Memory
-
-os.environ["OPENAI_API_KEY"] = "your_api_key"
-
-config = {
-    "embedder": {
-        "provider": "openai",
-        "config": {
-            "model": "text-embedding-3-large"
-        }
-    }
-}
-
-m = Memory.from_config(config)
-m.add("I'm visiting Paris", user_id="john")
-```
-
-## Ollama
-
-You can use embedding models from Ollama to run Mem0 locally.
-
-Here's how to select it:
-
-```python
-import os
-from mem0 import Memory
-
-os.environ["OPENAI_API_KEY"] = "your_api_key"
-
-config = {
-    "embedder": {
-        "provider": "ollama",
-        "config": {
-            "model": "mxbai-embed-large"
-        }
-    }
-}
-
-m = Memory.from_config(config)
-m.add("I'm visiting Paris", user_id="john")
-```

docs/components/embedders/config.mdx

@@ -0,0 +1,57 @@
+## What is Config?
+
+Config in mem0 is a dictionary that specifies the settings for your embedding models. It allows you to customize the behavior and connection details of your chosen embedder.
+
+## How to Define Config
+
+The config is defined as a Python dictionary with two main keys:
+- `embedder`: Specifies the embedder provider and its configuration
+  - `provider`: The name of the embedder (e.g., "openai", "ollama")
+  - `config`: A nested dictionary containing provider-specific settings
+
+## How to Use Config
+
+Here's a general example of how to use the config with mem0:
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "sk-xx"
+
+config = {
+    "embedder": {
+        "provider": "your_chosen_provider",
+        "config": {
+            # Provider-specific settings go here
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("Your text here", user_id="user", metadata={"category": "example"})
+```
+
+## Why is Config Needed?
+
+Config is essential for:
+1. Specifying which embedding model to use.
+2. Providing necessary connection details (e.g., model, api_key, embedding_dims).
+3. Ensuring proper initialization and connection to your chosen embedder.
+
+## Master List of All Params in Config
+
+Here's a comprehensive list of all parameters that can be used across different embedders:
+
+| Parameter | Description |
+|-----------|-------------|
+| `model` | Embedding model to use |
+| `api_key` | API key of the provider |
+| `embedding_dims` | Dimensions of the embedding model |
+| `ollama_base_url` | Base URL for the Ollama embedding model |
+| `model_kwargs` | Key-Value arguments for the Huggingface embedding model |
+
+
+## Supported Embedding Models
+
+For detailed information on configuring specific embedders, please visit the [Embedding Models](./models) section. There you'll find information for each supported embedder with provider-specific usage examples and configuration details.

docs/components/embedders/models/azure_openai.mdx

@@ -0,0 +1,34 @@
+To use Azure OpenAI embedding models, set the `AZURE_OPENAI_API_KEY` environment variable. You can obtain the Azure OpenAI API key from the Azure.
+
+### Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your_api_key"
+os.environ["AZURE_OPENAI_API_KEY"] = "your_api_key"
+
+
+config = {
+    "embedder": {
+        "provider": "azure_openai",
+        "config": {
+            "model": "text-embedding-3-large"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("I'm visiting Paris", user_id="john")
+```
+
+### Config
+
+Here are the parameters available for configuring Azure OpenAI embedder:
+
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the embedding model to use | `text-embedding-3-small` |
+| `embedding_dims` | Dimensions of the embedding model | `1536` |
+| `api_key` | The Azure OpenAI API key | `None` |

docs/components/embedders/models/huggingface.mdx

@@ -0,0 +1,32 @@
+You can use embedding models from Huggingface to run Mem0 locally.
+
+### Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your_api_key"
+
+config = {
+    "embedder": {
+        "provider": "huggingface",
+        "config": {
+            "model": "multi-qa-MiniLM-L6-cos-v1"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("I'm visiting Paris", user_id="john")
+```
+
+### Config
+
+Here are the parameters available for configuring Huggingface embedder:
+
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the model to use | `multi-qa-MiniLM-L6-cos-v1` |
+| `embedding_dims` | Dimensions of the embedding model | `selected_model_dimensions` |
+| `model_kwargs` | Additional arguments for the model | `None` |

docs/components/embedders/models/ollama.mdx

@@ -0,0 +1,32 @@
+You can use embedding models from Ollama to run Mem0 locally.
+
+### Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your_api_key"
+
+config = {
+    "embedder": {
+        "provider": "ollama",
+        "config": {
+            "model": "mxbai-embed-large"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("I'm visiting Paris", user_id="john")
+```
+
+### Config
+
+Here are the parameters available for configuring Ollama embedder:
+
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the OpenAI model to use | `nomic-embed-text` |
+| `embedding_dims` | Dimensions of the embedding model | `512` |
+| `ollama_base_url` | Base URL for ollama connection | `None` |

docs/components/embedders/models/openai.mdx

@@ -0,0 +1,32 @@
+To use OpenAI embedding models, set the `OPENAI_API_KEY` environment variable. You can obtain the OpenAI API key from the [OpenAI Platform](https://platform.openai.com/account/api-keys).
+
+### Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["OPENAI_API_KEY"] = "your_api_key"
+
+config = {
+    "embedder": {
+        "provider": "openai",
+        "config": {
+            "model": "text-embedding-3-large"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("I'm visiting Paris", user_id="john")
+```
+
+### Config
+
+Here are the parameters available for configuring OpenAI embedder:
+
+| Parameter | Description | Default Value |
+| --- | --- | --- |
+| `model` | The name of the embedding model to use | `text-embedding-3-small` |
+| `embedding_dims` | Dimensions of the embedding model | `1536` |
+| `api_key` | The OpenAI API key | `None` |

docs/components/embedders/overview.mdx

@@ -0,0 +1,15 @@
+---
+title: Overview
+---
+
+Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.
+
+## Usage
+
+To utilize a embedder, you must provide a configuration to customize its usage. If no configuration is supplied, a default configuration will be applied, and `OpenAI` will be used as the embedder.
+
+For a comprehensive list of available parameters for embedder configuration, please refer to [Config](./config).
+
+To view all supported embedders, visit the [Supported embedders](./models).
+
+

docs/mint.json

@@ -82,7 +82,19 @@
         },
         {
           "group": "Embedding Models",
-          "pages": ["components/embedders"]
+          "pages": [
+            "components/embedders/overview",
+            "components/embedders/config",
+            {
+              "group": "Supported Embedding Models",
+              "pages": [
+                "components/embedders/models/openai",
+                "components/embedders/models/azure_openai",
+                "components/embedders/models/ollama",
+                "components/embedders/models/huggingface"
+              ]
+            }
+          ]
         },
         {
           "group": "Features",

mem0/embeddings/azure_openai.py

@@ -1,3 +1,4 @@
+import os
 from typing import Optional
 
 from openai import AzureOpenAI
@@ -13,7 +14,9 @@ class AzureOpenAIEmbedding(EmbeddingBase):
             self.config.model = "text-embedding-3-small"
         if self.config.embedding_dims is None:
             self.config.embedding_dims = 1536
-        self.client = AzureOpenAI()
+        
+        api_key = os.getenv("AZURE_OPENAI_API_KEY") or self.config.api_key
+        self.client = AzureOpenAI(api_key=api_key) 
 
     def embed(self, text):
         """