diff --git a/docs/components/embedders/models/aws_bedrock.mdx b/docs/components/embedders/models/aws_bedrock.mdx
index e5430e03d..d474f9655 100644
--- a/docs/components/embedders/models/aws_bedrock.mdx
+++ b/docs/components/embedders/models/aws_bedrock.mdx
@@ -59,5 +59,9 @@ Here are the parameters available for configuring AWS Bedrock embedder:
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the embedding model to use | `amazon.titan-embed-text-v1` |
+| `aws_region` | AWS region for the Bedrock client | `us-west-2` |
+| `aws_access_key_id` | AWS access key ID for authentication | `None` |
+| `aws_secret_access_key` | AWS secret access key for authentication | `None` |
+| `aws_session_token` | AWS session token for temporary credentials | `None` |
 </Tab>
 </Tabs>
diff --git a/docs/components/embedders/models/google_AI.mdx b/docs/components/embedders/models/google_AI.mdx
index 7c9db18c1..8dccf45e5 100644
--- a/docs/components/embedders/models/google_AI.mdx
+++ b/docs/components/embedders/models/google_AI.mdx
@@ -67,14 +67,15 @@ Here are the parameters available for configuring Gemini embedder:
 | Parameter        | Description                          | Default Value           |
 | ---------------- | ------------------------------------ | ----------------------- |
 | `model`          | The name of the embedding model to use| `models/gemini-embedding-001` |
-| `embedding_dims` | Dimensions of the embedding model     | `1536`                  |
+| `embedding_dims` | Dimensions of the embedding model     | `768`                   |
 | `api_key`        | The Google API key                   | `None`                  |
+| `output_dimensionality` | Output dimensionality for the embedding model (Gemini-specific; used when `embedding_dims` is not set) | `None` |
 </Tab>
 <Tab title="TypeScript">
 | Parameter         | Description                                   | Default Value              |
 | ----------------- | --------------------------------------------- | -------------------------- |
 | `model`           | The name of the embedding model to use        | `gemini-embedding-001`     |
-| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `embeddingDims`   | Dimensions of the embedding model. When not set, uses the model's native output dimensionality (3072 for `gemini-embedding-001`; MRL truncation to 768, 1536, or 3072 is supported) | `None`                     |
 | `apiKey`          | Google API key                                | `None`                     |
 </Tab>
 </Tabs>
diff --git a/docs/components/embedders/models/lmstudio.mdx b/docs/components/embedders/models/lmstudio.mdx
index 4b8d2212c..66234d8cc 100644
--- a/docs/components/embedders/models/lmstudio.mdx
+++ b/docs/components/embedders/models/lmstudio.mdx
@@ -16,7 +16,7 @@ config = {
     "embedder": {
         "provider": "lmstudio",
         "config": {
-            "model": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf"
+            "model": "nomic-ai/nomic-embed-text-v1.5-GGUF"
         }
     }
 }
@@ -37,6 +37,6 @@ Here are the parameters available for configuring LM Studio embedder:
 
 | Parameter | Description | Default Value |
 | --- | --- | --- |
-| `model` | The name of the LM Studio model to use | `nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf` |
+| `model` | The name of the LM Studio model to use | `nomic-ai/nomic-embed-text-v1.5-GGUF` |
 | `embedding_dims` | Dimensions of the embedding model | `1536` |
 | `lmstudio_base_url` | Base URL for LM Studio connection | `http://localhost:1234/v1` |
\ No newline at end of file
diff --git a/docs/components/embedders/overview.mdx b/docs/components/embedders/overview.mdx
index 45f23d8a5..08921e2b2 100644
--- a/docs/components/embedders/overview.mdx
+++ b/docs/components/embedders/overview.mdx
@@ -10,7 +10,7 @@ Mem0 offers support for various embedding models, allowing users to choose the o
 See the list of supported embedders below.
 
 <Note>
-  The following embedders are supported in the Python implementation. The TypeScript implementation currently only supports OpenAI.
+  All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **Google AI**, **Langchain**, **LM Studio**, and **Ollama**.
 </Note>
 
 <CardGroup cols={4}>
@@ -24,6 +24,7 @@ See the list of supported embedders below.
   <Card title="LM Studio" href="/components/embedders/models/lmstudio"></Card>
   <Card title="Langchain" href="/components/embedders/models/langchain"></Card>
   <Card title="AWS Bedrock" href="/components/embedders/models/aws_bedrock"></Card>
+  <Card title="FastEmbed" href="/components/embedders/models/fastembed"></Card>
 </CardGroup>
 
 ## Usage
diff --git a/docs/components/llms/config.mdx b/docs/components/llms/config.mdx
index 1be19b78a..f493d9fc7 100644
--- a/docs/components/llms/config.mdx
+++ b/docs/components/llms/config.mdx
@@ -98,7 +98,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `max_tokens`         | Tokens to generate                            | All               |
     | `top_p`              | Probability threshold for nucleus sampling    | All               |
     | `top_k`              | Number of highest probability tokens to keep  | All               |
-    | `http_client_proxies`| Allow proxy server settings                   | AzureOpenAI       |
+    | `http_client_proxies`| Allow proxy server settings                   | All               |
     | `models`             | List of models                                | Openrouter        |
     | `route`              | Routing strategy                              | Openrouter        |
     | `openrouter_base_url`| Base URL for Openrouter API                   | Openrouter        |
@@ -110,7 +110,7 @@ Here's a comprehensive list of all parameters that can be used across different
     | `deepseek_base_url`  | Base URL for DeepSeek API                     | DeepSeek          |
     | `xai_base_url`       | Base URL for XAI API                          | XAI               |
     | `sarvam_base_url`    | Base URL for Sarvam API                       | Sarvam            |
-    | `reasoning_effort`   | Reasoning level (low, medium, high)           | Sarvam            |
+    | `reasoning_effort`   | Reasoning level (low, medium, high)           | All               |
     | `frequency_penalty`  | Penalize frequent tokens (-2.0 to 2.0)        | Sarvam            |
     | `presence_penalty`   | Penalize existing tokens (-2.0 to 2.0)        | Sarvam            |
     | `seed`               | Seed for deterministic sampling               | Sarvam            |
diff --git a/docs/components/llms/models/anthropic.mdx b/docs/components/llms/models/anthropic.mdx
index 488a06e4a..8305609aa 100644
--- a/docs/components/llms/models/anthropic.mdx
+++ b/docs/components/llms/models/anthropic.mdx
@@ -20,7 +20,7 @@ config = {
     "llm": {
         "provider": "anthropic",
         "config": {
-            "model": "claude-sonnet-4-20250514",
+            "model": "claude-sonnet-4-6",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -45,7 +45,7 @@ const config = {
     provider: 'anthropic',
     config: {
       apiKey: process.env.ANTHROPIC_API_KEY || '',
-      model: 'claude-sonnet-4-20250514',
+      model: 'claude-sonnet-4-6',
       temperature: 0.1,
       maxTokens: 2000,
     },
diff --git a/docs/components/llms/models/aws_bedrock.mdx b/docs/components/llms/models/aws_bedrock.mdx
index 76b0efedd..3d3de2d29 100644
--- a/docs/components/llms/models/aws_bedrock.mdx
+++ b/docs/components/llms/models/aws_bedrock.mdx
@@ -6,7 +6,7 @@ description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authenti
 ### Setup
 - Before using the AWS Bedrock LLM, make sure you have the appropriate model access from [Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess).
 - You will also need to authenticate the `boto3` client by using a method in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials)
-- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
+- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY_ID`, and `AWS_SECRET_ACCESS_KEY` to set environment variables.
 
 ### Usage
 
diff --git a/docs/components/llms/models/groq.mdx b/docs/components/llms/models/groq.mdx
index d6a82743e..e3c802729 100644
--- a/docs/components/llms/models/groq.mdx
+++ b/docs/components/llms/models/groq.mdx
@@ -21,7 +21,7 @@ config = {
     "llm": {
         "provider": "groq",
         "config": {
-            "model": "mixtral-8x7b-32768",
+            "model": "llama-3.3-70b-versatile",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
@@ -46,7 +46,7 @@ const config = {
     provider: 'groq',
     config: {
       apiKey: process.env.GROQ_API_KEY || '',
-      model: 'mixtral-8x7b-32768',
+      model: 'llama3-70b-8192',
       temperature: 0.1,
       maxTokens: 1000,
     },
diff --git a/docs/components/llms/models/xAI.mdx b/docs/components/llms/models/xAI.mdx
index fb6d930fa..b75b4530c 100644
--- a/docs/components/llms/models/xAI.mdx
+++ b/docs/components/llms/models/xAI.mdx
@@ -20,7 +20,7 @@ config = {
     "llm": {
         "provider": "xai",
         "config": {
-            "model": "grok-3-beta",
+            "model": "grok-4.3",
             "temperature": 0.1,
             "max_tokens": 2000,
         }
diff --git a/docs/components/llms/overview.mdx b/docs/components/llms/overview.mdx
index 94a5cc160..c207e5e06 100644
--- a/docs/components/llms/overview.mdx
+++ b/docs/components/llms/overview.mdx
@@ -16,7 +16,7 @@ For a comprehensive list of available parameters for llm configuration, please r
 See the list of supported LLMs below.
 
 <Note>
-  All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, and **Groq**.
+  All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, **Groq**, **Azure OpenAI**, **DeepSeek**, **Google AI**, **Langchain**, **LM Studio**, **Mistral AI**, and **Ollama**.
 </Note>
 
 <CardGroup cols={4}>