Fix: Handle empty API key in LiteLLMEmbeddingEngine (#1959)

fix(embeddings): handle empty API key in LiteLLMEmbeddingEngine

- Add conditional check for empty API key to prevent authentication
errors- Set default API key to "EMPTY" when no valid key is provided-
This ensures proper fallback behavior when API key is not configured
```

<!-- .github/pull_request_template.md -->

## Description
This PR fixes an issue where the `LiteLLMEmbeddingEngine` throws an authentication error when the `EMBEDDING_API_KEY` environment variable is empty or not set. The error message indicated `"api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable"`.

Log Error: 2025-12-23T11:36:58.220908 [error    ] Error embedding text: litellm.AuthenticationError: AuthenticationError: OpenAIException - The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable [LiteLLMEmbeddingEngine]

**Root Cause**: When initializing the embedding engine, if the `api_key` parameter is an empty string, the underlying LiteLLM client doesn't treat it as "no key provided" but instead uses this empty string to make API requests, triggering authentication failure.

**Solution**: Added a conditional check in the code that creates the `LiteLLMEmbeddingEngine` instance. If the `EMBEDDING_API_KEY` read from configuration is empty (`None` or empty string), we explicitly set the `api_key` parameter passed to the engine constructor to a non-empty placeholder string `"EMPTY"`. This aligns with LiteLLM's handling of optional authentication and prevents exceptions in scenarios where keys are not required or need to be obtained from other sources

**How to Reproduce**:
   Configure the application with the following settings (as shown in the error log):
   EMBEDDING_PROVIDER="custom"
   EMBEDDING_MODEL="openai/Qwen/Qwen3-Embedding-xxx"
   EMBEDDING_ENDPOINT="xxxxx"  
   EMBEDDING_API_VERSION=""
   EMBEDDING_DIMENSIONS=1024
   EMBEDDING_MAX_TOKENS=16384
   EMBEDDING_BATCH_SIZE=10
   # If embedding key is not provided same key set for LLM_API_KEY will be used
   EMBEDDING_API_KEY=""


## Acceptance Criteria
<!--
* Key requirements to the new feature or modification;
* Proof that the changes work and meet the requirements;
* Include instructions on how to verify the changes. Describe how to test it locally;
* Proof that it's sufficiently tested.
-->

## Type of Change
<!-- Please check the relevant option -->
- [x] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to change)
- [ ] Documentation update
- [ ] Code refactoring
- [ ] Performance improvement
- [ ] Other (please specify):

## Screenshots/Videos (if applicable)
<!-- Add screenshots or videos to help explain your changes -->

## Pre-submission Checklist
<!-- Please check all boxes that apply before submitting your PR -->
- [x] I have tested my changes thoroughly before submitting this PR
- [x] This PR contains minimal changes necessary to address the issue/feature
- [ ] My code follows the project's coding standards and style guidelines
- [ ] I have added tests that prove my fix is effective or that my feature works
- [ ] I have added necessary documentation (if applicable)
- [ ] All new and existing tests pass
- [x] I have searched existing PRs to ensure this change hasn't been submitted already
- [ ] I have linked any relevant issues in the description
- [ ] My commits have clear and descriptive messages

## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.


<!-- This is an auto-generated comment: release notes by coderabbit.ai -->
## Summary by CodeRabbit

* **Bug Fixes**
  * Improved API key validation for the embedding service to properly handle blank or missing API keys, ensuring more reliable embedding generation and preventing potential service errors.

<sub>✏️ Tip: You can customize this high-level summary in your review settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py

@@ -134,7 +134,7 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
                         litellm.aembedding(
                             model=self.model,
                             input=text,
-                            api_key=self.api_key,
+                            api_key=self.api_key if self.api_key and self.api_key.strip() != "" else "EMPTY",
                             api_base=self.endpoint,
                             api_version=self.api_version,
                         ),