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Update Docs: Added Mem0 integration with Short Term and Entity Memory (#3293)
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* Added Mem0 integration with Short Term and Entity Memory

* Flaky test case of telemetry
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Vidit Ostwal
2025-08-15 08:20:24 +05:30
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commit 992e093610
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docs/en/concepts/memory.mdx
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@@ -539,16 +539,71 @@ crew = Crew(
)
```
### Mem0 Provider
Short-Term Memory and Entity Memory both supports a tight integration with both Mem0 OSS and Mem0 Client as a provider. Here is how you can use Mem0 as a provider.
```python
from crewai.memory.short_term.short_term_memory import ShortTermMemory
from crewai.memory.entity_entity_memory import EntityMemory
mem0_oss_embedder_config = {
"provider": "mem0",
"config": {
"user_id": "john",
"local_mem0_config": {
"vector_store": {"provider": "qdrant","config": {"host": "localhost", "port": 6333}},
"llm": {"provider": "openai","config": {"api_key": "your-api-key", "model": "gpt-4"}},
"embedder": {"provider": "openai","config": {"api_key": "your-api-key", "model": "text-embedding-3-small"}}
},
"infer": True # Optional defaults to True
},
}
mem0_client_embedder_config = {
"provider": "mem0",
"config": {
"user_id": "john",
"org_id": "my_org_id", # Optional
"project_id": "my_project_id", # Optional
"api_key": "custom-api-key" # Optional - overrides env var
"run_id": "my_run_id", # Optional - for short-term memory
"includes": "include1", # Optional
"excludes": "exclude1", # Optional
"infer": True # Optional defaults to True
"custom_categories": new_categories # Optional - custom categories for user memory
},
}
short_term_memory_mem0_oss = ShortTermMemory(embedder_config=mem0_oss_embedder_config) # Short Term Memory with Mem0 OSS
short_term_memory_mem0_client = ShortTermMemory(embedder_config=mem0_client_embedder_config) # Short Term Memory with Mem0 Client
entity_memory_mem0_oss = EntityMemory(embedder_config=mem0_oss_embedder_config) # Entity Memory with Mem0 OSS
entity_memory_mem0_client = EntityMemory(embedder_config=mem0_client_embedder_config) # Short Term Memory with Mem0 Client
crew = Crew(
memory=True,
short_term_memory=short_term_memory_mem0_oss, # or short_term_memory_mem0_client
entity_memory=entity_memory_mem0_oss # or entity_memory_mem0_client
)
```
### Choosing the Right Embedding Provider
| Provider | Best For | Pros | Cons |
|:---------|:----------|:------|:------|
| **OpenAI** | General use, reliability | High quality, well-tested | Cost, requires API key |
| **Ollama** | Privacy, cost savings | Free, local, private | Requires local setup |
| **Google AI** | Google ecosystem | Good performance | Requires Google account |
| **Azure OpenAI** | Enterprise, compliance | Enterprise features | Complex setup |
| **Cohere** | Multilingual content | Great language support | Specialized use case |
| **VoyageAI** | Retrieval tasks | Optimized for search | Newer provider |
When selecting an embedding provider, consider factors like performance, privacy, cost, and integration needs.
Below is a comparison to help you decide:
| Provider | Best For | Pros | Cons |
| -------------- | ------------------------------ | --------------------------------- | ------------------------- |
| **OpenAI** | General use, high reliability | High quality, widely tested | Paid service, API key required |
| **Ollama** | Privacy-focused, cost savings | Free, runs locally, fully private | Requires local installation/setup |
| **Google AI** | Integration in Google ecosystem| Strong performance, good support | Google account required |
| **Azure OpenAI** | Enterprise & compliance needs| Enterprise-grade features, security | More complex setup process |
| **Cohere** | Multilingual content handling | Excellent language support | More niche use cases |
| **VoyageAI** | Information retrieval & search | Optimized for retrieval tasks | Relatively new provider |
| **Mem0** | Per-user personalization | Search-optimized embeddings | Paid service, API key required |
### Environment Variable Configuration