fix(sdk): removing deprecating param from our sdk and docs changes with it (#4740)

docs/integrations/google-ai-adk.mdx

@@ -268,7 +268,7 @@ memories = mem0.search(
             {"categories": {"contains": "travel"}}
         ]
     },
-    limit=5
+    top_k=5
 )
 
 # Configure agent with custom model settings

docs/integrations/keywords.mdx

@@ -16,7 +16,7 @@ Combining Mem0 with Keywords AI allows you to:
 4. Optimize token usage and reduce costs
 
 <Note>
-You can get your Mem0 API key, user_id, and org_id from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a>. These are required for proper integration.
+You can get your Mem0 API key from the <a href="https://app.mem0.ai/" rel="nofollow">Mem0 dashboard</a>.
 </Note>
 
 ## Setup and Configuration
@@ -107,7 +107,6 @@ response = client.chat.completions.create(
     extra_body={
         "mem0_params": {
             "user_id": "test_user",
-            "org_id": "org_1",
             "api_key": os.environ.get("MEM0_API_KEY"),
             "add_memories": {
                 "messages": messages,

docs/integrations/langchain-tools.mdx

@@ -29,10 +29,7 @@ import os
 
 os.environ["MEM0_API_KEY"] = "your-api-key"
 
-client = MemoryClient(
-    org_id=your_org_id,
-    project_id=your_project_id
-)
+client = MemoryClient()
 ```
 
 ## Available Tools

docs/integrations/openai-agents-sdk.mdx

@@ -45,7 +45,7 @@ mem0 = MemoryClient()
 @function_tool
 def search_memory(query: str, user_id: str) -> str:
     """Search through past conversations and memories"""
-    memories = mem0.search(query, user_id=user_id, limit=3)
+    memories = mem0.search(query, user_id=user_id, top_k=3)
     if memories and memories.get('results'):
         return "\n".join([f"- {mem['memory']}" for mem in memories['results']])
     return "No relevant memories found."
@@ -215,7 +215,7 @@ Customize memory behavior:
 memories = mem0.search(
     query="travel preferences",
     user_id="alex",
-    limit=5  # Number of memories to retrieve
+    top_k=5  # Number of memories to retrieve
 )
 
 # Add metadata to memories

docs/integrations/openclaw.mdx

@@ -155,7 +155,7 @@ openclaw mem0 stats
 
 | Key | Type | Default | Description |
 |-----|------|---------|-------------|
-| `customPrompt` | `string` | *(built-in)* | Extraction prompt for memory processing |
+| `customInstructions` | `string` | *(built-in)* | Extraction prompt for memory processing |
 | `oss.embedder.provider` | `string` | `"openai"` | Embedding provider (`"openai"`, `"ollama"`, etc.) |
 | `oss.embedder.config` | `object` | — | Provider config: `apiKey`, `model`, `baseURL` |
 | `oss.vectorStore.provider` | `string` | `"memory"` | Vector store (`"memory"`, `"qdrant"`, `"chroma"`, etc.) |

docs/integrations/vercel-ai-sdk.mdx

@@ -52,7 +52,7 @@ npm install @mem0/vercel-ai-provider
 
     > **Note**: The `openai` provider is set as default. Consider using `MEM0_API_KEY` and `OPENAI_API_KEY` as environment variables for security.
 
-    > **Note**: The `mem0Config` is optional. It is used to set the global config for the Mem0 Client (eg. `user_id`, `agent_id`, `app_id`, `run_id`, `org_id`, `project_id` etc).
+    > **Note**: The `mem0Config` is optional. It is used to set the global config for the Mem0 Client (eg. `user_id`, `agent_id`, `app_id`, `run_id` etc).
 
 3. Add Memories to Enhance Context: