# CrewAI memory=True: "Please provide an OpenAI API key" when you're not using OpenAI (embedder fix)

*Disclosure: I work on MemorySync (I'm Mohammed, the founder). I drafted this page with AI assistance and checked it against the source thread and the official docs listed under Sources on Oct 28, 2026. I read the issue, the CrewAI memory docs and the crewAI 1.15.32 source; I didn't run a crew for this page.*

Founding offer: use code FOUNDING30 for 30% off Starter for your first 3 months (Settings → Billing).

## The question

In crewAI GitHub issue [#2943](https://github.com/crewAIInc/crewAI/issues/2943) (Jun 3, 2025), a developer's crew worked with `cache=True` but failed as soon as they added `memory=True`:

```text
pydantic_core._pydantic_core.ValidationError: 1 validation error for Crew
  Value error, Please provide an OpenAI API key. You can get one at https://platform.openai.com/account/api-keys [type=value_error, input_value={'agents': [Agent(role=Ho...': True, 'memory': True}, input_type=dict]
```

Their crew (crewAI 0.121.0, Python 3.10):

```python
synergistic_crew = Crew(
    agents=[holiday_agent, macro_agent, news_summarizer_agent, analysis_forecast_agent, user_query_agent],
    tasks=[holiday_task, macro_task, news_summarizer_task, analysis_forecast_task, user_query_task],
    process=Process.sequential,
    verbose=True,
    cache=True,
    memory=True,
)
```

**Status (checked Oct 28, 2026):** closed as completed on Jun 4, 2025. The maintainer's answer: "memory use Embedding features that by default use OpenAI as provider", so either define `OPENAI_API_KEY` or "use another provider for embeddings".

> **Skip the memory plumbing around this fix.** Once the fix below is in, the [MemorySync CrewAI guide](https://docs.memorysync.io/guides/crewai?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key) shows how to add per-user memory with MemorySync. MemorySync doesn't fix this error itself. When you're ready, [see MemorySync](https://memorysync.io/?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key). Founding offer: use code FOUNDING30 for 30% off Starter for your first 3 months (Settings → Billing).

## Why it happens

Your agents' LLM and crew memory's embedder are separate settings. Memory turns text into vectors for search, and the [CrewAI memory docs](https://docs.crewai.com/en/concepts/memory) say that "Without a custom `embedder`, memory uses OpenAI `text-embedding-3-large` embeddings." So a crew whose agents run on Gemini, Claude or a local model still asks for an OpenAI key the moment memory is on.

On crewAI 0.121 the check fired while the `Crew` was being validated, hence the pydantic `ValidationError`. In crewAI 1.x the default embedder is created lazily, so the error shows up when memory is first used, not when you build the crew. In the 1.15.32 source ([`unified_memory.py`](https://github.com/crewAIInc/crewAI/blob/1.15.32/lib/crewai/src/crewai/memory/unified_memory.py)) the message starts with `Memory requires an embedder for vector search but initialization failed` and lists the fixes: set `OPENAI_API_KEY`, pass a different embedder, or pass a callable. The docs also note that memory saves run in a background thread, and save errors are emitted as `MemorySaveFailedEvent` instead of crashing the agent, so check your logs too.

## Fix 1: set an embedder for your provider

If you want memory without OpenAI, give the crew an `embedder`. With `memory=True`, the docs say "the crew's `embedder` config is passed through". Here's a local embedder through Ollama (config from the docs' provider examples):

```python
from crewai import Crew, Process

crew = Crew(
    agents=[...],
    tasks=[...],
    process=Process.sequential,
    memory=True,
    embedder={
        "provider": "ollama",
        "config": {
            "model_name": "mxbai-embed-large",
            "url": "http://localhost:11434/api/embeddings",
        },
    },
)
```

The docs' provider reference table lists the other keys, including `google-generativeai` (set `GOOGLE_API_KEY`), `azure` (needs `deployment_id`), `cohere`, `voyageai`, `amazon-bedrock` (uses boto3 credentials), `huggingface`, `jina`, `watsonx`, `sentence-transformer` and `custom`. The table marks Ollama and Sentence Transformer as needing no API key.

## Fix 2: build Memory yourself and set its LLM too

Memory also uses an LLM to analyze what it saves and recalls (scope, categories, importance). In the 1.15.32 source ([`crew.py`](https://github.com/crewAIInc/crewAI/blob/1.15.32/lib/crewai/src/crewai/crew.py)), `memory=True` reuses the crew's `chat_llm` or the first agent's `llm` for that. When you create `Memory()` yourself, nothing is reused: its `llm` defaults to an OpenAI model. So pass both. The docs show this for fully local operation:

```python
from crewai import Crew, Memory

memory = Memory(
    llm="ollama/llama3.2",
    embedder={"provider": "ollama", "config": {"model_name": "mxbai-embed-large"}},
)

crew = Crew(agents=[...], tasks=[...], memory=memory)
```

If you're happy to use OpenAI for embeddings only, the simplest fix is the one the maintainer gave: set `OPENAI_API_KEY` and leave the defaults alone.

## Checklist

1. Decide which provider embeds memory. It doesn't have to match your agents' LLM.
2. `memory=True`: set `embedder=` on the `Crew`. Your own `Memory(...)`: set `embedder=` and `llm=` on it.
3. Provide that provider's credentials, or use Ollama or Sentence Transformer, which need none.
4. Changed embedders on an existing local store? The docs warn about dimension mismatches; for local testing run `crewai reset-memories -m` or delete the local memory directory.
5. Watch the logs for `MemorySaveFailedEvent` errors, since background save failures don't crash the agent.

## Common questions

**My agents use Gemini. Why does CrewAI want an OpenAI key at all?** Because the embedder defaults to OpenAI whatever your agents' `llm` is. Setting `llm` on the agents doesn't change the embedder.

**Does** `cache=True` **need an embedder?** No. In the issue, the crew ran with `cache=True` and only failed once `memory=True` was added. Tool caching and memory are separate features.

**Where does crew memory get stored?** By default in LanceDB under `./.crewai/memory` (or `$CREWAI_STORAGE_DIR/memory`), per the docs' Storage Backend section. You can pass your own `StorageBackend` with `Memory(storage=...)`.

## Skip the plumbing with MemorySync

Changing where memory is stored doesn't remove the embedder requirement. The [MemorySync CrewAI guide](https://docs.memorysync.io/guides/crewai?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key) says CrewAI "embeds with its own embedder" before calling storage, so you still need Fix 1 or Fix 2 when you use `Memory(storage=MemorySyncStorage(user_id=...))`. What it adds is a managed `StorageBackend`, so records outlive the container and can be scoped per `user_id`. The guide's agent tools (`create_memorysync_tools`) work differently: they send text to MemorySync and don't call CrewAI's embedder (checked in the `crewai-memorysync` 1.1.0 source). Read the [guide](https://docs.memorysync.io/guides/crewai?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key) first. For an overview of MemorySync, see [the MemorySync homepage](https://memorysync.io/?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key).

From the guide:

```bash
pip install crewai-memorysync
```

```python
from crewai import Agent, Crew, Task
from crewai.memory import Memory
from crewai_memorysync import MemorySyncStorage

crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, write_task],
    memory=Memory(
        storage=MemorySyncStorage(user_id="support-crew"),
    ),
)

crew.kickoff()
# Every record the crew saved is now stored on MemorySync: it survives
# redeploys and is shared by every service using this user_id. The
# facts in those records show up in Memory Explorer and in recall.
```

*Snippet adapted from the* [*MemorySync CrewAI guide*](https://docs.memorysync.io/guides/crewai?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key)*; I haven't run it for this page.*

Starter template: [memorysyncio/memorysync-first-memory](https://github.com/memorysyncio/memorysync-first-memory?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key).

## Sources

- [github.com/crewAIInc/crewAI/issues/2943](http://github.com/crewAIInc/crewAI/issues/2943) (closed as completed Jun 4, 2025, 2 comments; read 2026-10-28)
- [docs.crewai.com/en/concepts/memory](http://docs.crewai.com/en/concepts/memory) (default embedder, crew embedder pass-through, provider reference, LLM configuration, storage backend, troubleshooting; read 2026-10-28)
- crewAI 1.15.32 source: lib/crewai/src/crewai/crew.py (`create_crew_memory`, `_memory_llm`) and lib/crewai/src/crewai/memory/unified_memory.py (lazy embedder and LLM errors; read 2026-10-28)
- MemorySync docs: [docs.memorysync.io/guides/crewai](http://docs.memorysync.io/guides/crewai); crewai-memorysync 1.1.0 (PyPI)

**Next step:** read the [MemorySync CrewAI guide](https://docs.memorysync.io/guides/crewai?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key), then [see MemorySync](https://memorysync.io/?utm_source=hashnode&utm_medium=organic_page&utm_campaign=v5_oct25&utm_content=pseo_crewai-memory-true-please-provide-an-openai-api-key). Founding offer: use code FOUNDING30 for 30% off Starter for your first 3 months (Settings → Billing).