fix: gracefully skip assistant messages with empty content in LLM format conversion
**Problem:**
Context window calculation crashed with AssertionError when converting messages
to Google/Anthropic/OpenAI format:
```
AssertionError at line 2047: assert self.tool_calls is not None or
text_content is not None or len(self.content) > 1
```
This happened when loading agents with old/malformed messages that had
`content=None` or `content=[]` in the database.
**Root Cause:**
The Message ORM model allows `content: Optional[List[...]] = None` (line 252),
but format conversion methods assumed content would always have extractable text
or tool calls.
Scenarios that triggered crashes:
1. Assistant message with `content=None` (old migrations/edge cases)
2. Assistant message with `content=[]` (message creation bugs)
3. Assistant message with single non-text content that doesn't match extraction logic
**Fix:**
Replaced assertions with defensive checks in 3 conversion methods:
1. `to_google_dict()` (line 2054) - Return None to skip unconvertible messages
2. `to_openai_responses_api_dicts()` (line 1476) - Return early to skip
3. `to_anthropic_dict()` (line 1794) - Return None to skip
Pattern: Check for empty content, return None/early to skip gracefully.
**Result:**
- Context window calculation no longer crashes on malformed/old messages
- Messages with no convertible content are silently skipped
- Consistent with existing Anthropic reasoning-only message handling (line 1308)
👾 Generated with [Letta Code](https://letta.com)
Co-authored-by: Letta <noreply@letta.com>
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