docs(integrations): fix retired model IDs, v3 response shapes & vercel deps (#5842)
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@@ -73,7 +73,7 @@ client = MemoryClient()
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# Define the agent
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# Define the agent
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agent = Agent(
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agent = Agent(
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name="Personal Agent",
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name="Personal Agent",
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model=OpenAIChat(id="gpt-4"),
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model=OpenAIChat(id="gpt-5-mini"),
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description="You are a helpful personal agent that helps me with day to day activities."
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description="You are a helpful personal agent that helps me with day to day activities."
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"You can process both text and images.",
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"You can process both text and images.",
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markdown=True
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markdown=True
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@@ -43,7 +43,7 @@ OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY')
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memory_client = MemoryClient()
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memory_client = MemoryClient()
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agent = ConversableAgent(
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agent = ConversableAgent(
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"chatbot",
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"chatbot",
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llm_config={"config_list": [{"model": "gpt-4", "api_key": OPENAI_API_KEY}]},
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llm_config={"config_list": [{"model": "gpt-5-mini", "api_key": OPENAI_API_KEY}]},
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code_execution_config=False,
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code_execution_config=False,
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human_input_mode="NEVER",
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human_input_mode="NEVER",
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)
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)
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@@ -99,7 +99,7 @@ For more complex scenarios, you can create multiple agents:
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manager = ConversableAgent(
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manager = ConversableAgent(
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"manager",
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"manager",
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system_message="You are a manager who helps in resolving complex customer issues.",
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system_message="You are a manager who helps in resolving complex customer issues.",
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llm_config={"config_list": [{"model": "gpt-4", "api_key": OPENAI_API_KEY}]},
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llm_config={"config_list": [{"model": "gpt-5-mini", "api_key": OPENAI_API_KEY}]},
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human_input_mode="NEVER"
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human_input_mode="NEVER"
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)
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)
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@@ -98,20 +98,9 @@ add_result = add_tool.invoke(add_input)
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```json Output
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```json Output
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{
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{
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"results": [
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"message": "Memory processing has been queued for background execution",
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{
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"status": "PENDING",
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"memory": "Name is Alex",
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"event_id": "3a1b2c3d-4e5f-6789-abcd-ef0123456789"
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"event": "ADD"
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},
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{
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"memory": "Is a vegetarian",
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"event": "ADD"
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},
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{
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"memory": "Is allergic to nuts",
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"event": "ADD"
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}
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]
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}
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}
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```
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```
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</CodeGroup>
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</CodeGroup>
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@@ -173,23 +162,25 @@ result = search_tool.invoke(search_input)
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```
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```
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```json Output
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```json Output
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[
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{
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{
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"results": [
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"id": "1a75e827-7eca-45ea-8c5c-cfd43299f061",
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{
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"memory": "Name is Alex",
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"id": "1a75e827-7eca-45ea-8c5c-cfd43299f061",
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"user_id": "alex",
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"memory": "Name is Alex",
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"hash": "d0fccc8fa47f7a149ee95750c37bb0ca",
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"user_id": "alex",
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"metadata": {
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"hash": "d0fccc8fa47f7a149ee95750c37bb0ca",
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"food": "vegan"
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"metadata": {
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},
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"food": "vegan"
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"categories": [
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},
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"personal_details"
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"categories": [
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],
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"personal_details"
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"created_at": "2024-11-27T16:53:43.276872-08:00",
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],
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"updated_at": "2024-11-27T16:53:43.276885-08:00",
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"created_at": "2024-11-27T16:53:43.276872-08:00",
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"score": 0.3810526501504994
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"updated_at": "2024-11-27T16:53:43.276885-08:00",
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}
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"score": 0.3810526501504994
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]
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}
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]
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}
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```
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```
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</CodeGroup>
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</CodeGroup>
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@@ -41,7 +41,7 @@ load_dotenv()
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# MEM0_API_KEY = 'your-mem0-key' # Replace with your actual Mem0 API key
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# MEM0_API_KEY = 'your-mem0-key' # Replace with your actual Mem0 API key
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# Initialize LangChain and Mem0
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# Initialize LangChain and Mem0
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llm = ChatOpenAI(model="gpt-4")
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llm = ChatOpenAI(model="gpt-5-mini")
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mem0 = MemoryClient()
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mem0 = MemoryClient()
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```
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```
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@@ -121,7 +121,7 @@ async def websocket_endpoint(websocket: WebSocket):
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# LLM for response generation
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# LLM for response generation
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llm = OpenAILLMService(
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llm = OpenAILLMService(
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api_key=os.getenv("OPENAI_API_KEY"),
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api_key=os.getenv("OPENAI_API_KEY"),
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model="gpt-3.5-turbo",
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model="gpt-5-mini",
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system_prompt="You are a helpful assistant that remembers past conversations."
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system_prompt="You are a helpful assistant that remembers past conversations."
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)
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)
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@@ -26,12 +26,12 @@ Install the SDK provider and AI SDK:
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npm install @mem0/vercel-ai-provider ai@^6
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npm install @mem0/vercel-ai-provider ai@^6
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```
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```
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### Peer Dependencies
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### Dependencies
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`@mem0/vercel-ai-provider` v3.0.0 requires:
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`@mem0/vercel-ai-provider` bundles `ai`, all `@ai-sdk/*` provider packages, and `@ai-sdk/provider` as regular dependencies — you do **not** need to install them separately. The install command above (`npm install @mem0/vercel-ai-provider ai@^6`) is sufficient.
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- `ai` v6+ (`^6.0.199`)
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- `@ai-sdk/provider` v3+ (`^3.0.10`)
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The only true peer dependency is `zod` (optional):
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- Provider packages at v3+: `@ai-sdk/openai@^3`, `@ai-sdk/anthropic@^3`, `@ai-sdk/google@^3`, `@ai-sdk/groq@^3`, `@ai-sdk/cohere@^3`
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- `zod` v3+ (`^3.0.0`) — required only if you use Zod schemas in tool definitions
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## Getting Started
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## Getting Started
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@@ -305,6 +305,8 @@ These options can be passed per-request when creating a model instance:
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| `rerank` | `boolean` | Enable reranking of results |
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| `rerank` | `boolean` | Enable reranking of results |
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| `page` | `number` | Page number for pagination |
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| `page` | `number` | Page number for pagination |
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| `page_size` | `number` | Results per page |
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| `page_size` | `number` | Results per page |
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| `mem0ApiKey` | `string` | Mem0 API key; overrides the `MEM0_API_KEY` env var |
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| `host` | `string` | Custom Mem0 API base URL for self-hosted deployments |
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## Key Features
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## Key Features
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@@ -312,6 +314,7 @@ These options can be passed per-request when creating a model instance:
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- `retrieveMemories()`: Retrieves memory context for prompts as a formatted system prompt string.
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- `retrieveMemories()`: Retrieves memory context for prompts as a formatted system prompt string.
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- `getMemories()`: Get memories from your profile in array format.
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- `getMemories()`: Get memories from your profile in array format.
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- `addMemories()`: Adds user memories to enhance contextual responses.
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- `addMemories()`: Adds user memories to enhance contextual responses.
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- `searchMemories()`: Searches memories and returns the raw results array (semantic search rather than the full retrieval pipeline).
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## Migrating from v2.x
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## Migrating from v2.x
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