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fix(anthropic): address gaps found in deep-dive audit

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After studying clawdbot (OpenClaw) and OpenCode implementations:

## Beta headers
- Add interleaved-thinking-2025-05-14 and fine-grained-tool-streaming-2025-05-14
  as common betas (sent with ALL auth types, not just OAuth)
- OAuth tokens additionally get oauth-2025-04-20
- API keys now also get the common betas (previously got none)

## Vision/image support
- Add _convert_vision_content() to convert OpenAI multimodal format
  (image_url blocks) to Anthropic format (image blocks with base64/url source)
- Handles both data: URIs (base64) and regular URLs

## Role alternation enforcement
- Anthropic strictly rejects consecutive same-role messages (400 error)
- Add post-processing step that merges consecutive user/assistant messages
- Handles string, list, and mixed content types during merge

## Tool choice support
- Add tool_choice parameter to build_anthropic_kwargs()
- Maps OpenAI values: auto→auto, required→any, none→omit, name→tool

## Cache metrics tracking
- Anthropic uses cache_read_input_tokens / cache_creation_input_tokens
  (different from OpenRouter's prompt_tokens_details.cached_tokens)
- Add api_mode-aware branch in run_agent.py cache stats logging

## Credential refresh on 401
- On 401 error during anthropic_messages mode, re-read credentials
  via resolve_anthropic_token() (picks up refreshed Claude Code tokens)
- Rebuild client if new token differs from current one
- Follows same pattern as Codex/Nous 401 refresh handlers

## Tests
- 44 adapter tests (8 new: vision conversion, role alternation, tool choice)
- Updated beta header tests to verify new structure
- Full suite: 3198 passed, 0 regressions
This commit is contained in:
teknium1
2026-03-12 16:00:46 -07:00
parent 5e12442b4b
commit d7adfe8f61
3 changed files with 262 additions and 11 deletions
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123
agent/anthropic_adapter.py
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@@ -26,8 +26,16 @@ logger = logging.getLogger(__name__)
THINKING_BUDGET = {"xhigh": 32000, "high": 16000, "medium": 8000, "low": 4000}
# Beta headers required for OAuth/subscription auth
_OAUTH_BETAS = ["oauth-2025-04-20"]
# Beta headers for enhanced features (sent with ALL auth types)
_COMMON_BETAS = [
"interleaved-thinking-2025-05-14",
"fine-grained-tool-streaming-2025-05-14",
]
# Additional beta headers required for OAuth/subscription auth
_OAUTH_ONLY_BETAS = [
"oauth-2025-04-20",
]
def _is_oauth_token(key: str) -> bool:
@@ -54,12 +62,15 @@ def build_anthropic_client(api_key: str, base_url: str = None):
kwargs["base_url"] = base_url
if _is_oauth_token(api_key):
# OAuth access token / setup-token → Bearer auth + beta header
# OAuth access token / setup-token → Bearer auth + beta headers
all_betas = _COMMON_BETAS + _OAUTH_ONLY_BETAS
kwargs["auth_token"] = api_key
kwargs["default_headers"] = {"anthropic-beta": ",".join(_OAUTH_BETAS)}
kwargs["default_headers"] = {"anthropic-beta": ",".join(all_betas)}
else:
# Regular API key → x-api-key header
# Regular API key → x-api-key header + common betas
kwargs["api_key"] = api_key
if _COMMON_BETAS:
kwargs["default_headers"] = {"anthropic-beta": ",".join(_COMMON_BETAS)}
return _anthropic_sdk.Anthropic(**kwargs)
@@ -173,6 +184,58 @@ def convert_tools_to_anthropic(tools: List[Dict]) -> List[Dict]:
return result
def _convert_vision_content(content: Any) -> Any:
"""Convert OpenAI multimodal content blocks to Anthropic format.
OpenAI format: [{"type": "image_url", "image_url": {"url": "data:...;base64,..."}}]
Anthropic format: [{"type": "image", "source": {"type": "base64", ...}}]
"""
if not isinstance(content, list):
return content
result = []
for block in content:
if not isinstance(block, dict):
result.append(block)
continue
if block.get("type") == "image_url":
image_url = block.get("image_url", {})
url = image_url.get("url", "") if isinstance(image_url, dict) else ""
if url.startswith("data:"):
# data:image/png;base64,iVBOR...
try:
header, b64_data = url.split(",", 1)
media_type = header.split(":")[1].split(";")[0]
result.append({
"type": "image",
"source": {
"type": "base64",
"media_type": media_type,
"data": b64_data,
},
})
except (ValueError, IndexError):
logger.warning("Could not parse data URL for image, skipping")
else:
# Regular URL — Anthropic supports url source type
result.append({
"type": "image",
"source": {
"type": "url",
"url": url,
},
})
elif block.get("type") == "text":
result.append({"type": "text", "text": block.get("text", "")})
else:
# Pass through unknown block types
result.append(block)
return result
def convert_messages_to_anthropic(
messages: List[Dict],
) -> Tuple[Optional[Any], List[Dict]]:
@@ -241,8 +304,9 @@ def convert_messages_to_anthropic(
result.append({"role": "user", "content": [tool_result]})
continue
# Regular user message
result.append({"role": "user", "content": content})
# Regular user message — convert vision content if multimodal
converted = _convert_vision_content(content) if isinstance(content, list) else content
result.append({"role": "user", "content": converted})
# Strip orphaned tool_use blocks (no matching tool_result follows)
tool_result_ids = set()
@@ -261,6 +325,40 @@ def convert_messages_to_anthropic(
if not m["content"]:
m["content"] = [{"type": "text", "text": "(tool call removed)"}]
# Enforce strict role alternation (Anthropic rejects consecutive same-role messages)
fixed = []
for m in result:
if fixed and fixed[-1]["role"] == m["role"]:
if m["role"] == "user":
# Merge consecutive user messages
prev_content = fixed[-1]["content"]
curr_content = m["content"]
if isinstance(prev_content, str) and isinstance(curr_content, str):
fixed[-1]["content"] = prev_content + "\n" + curr_content
elif isinstance(prev_content, list) and isinstance(curr_content, list):
fixed[-1]["content"] = prev_content + curr_content
else:
# Mixed types — wrap string in list
if isinstance(prev_content, str):
prev_content = [{"type": "text", "text": prev_content}]
if isinstance(curr_content, str):
curr_content = [{"type": "text", "text": curr_content}]
fixed[-1]["content"] = prev_content + curr_content
else:
# Consecutive assistant messages — merge text content
prev_blocks = fixed[-1]["content"]
curr_blocks = m["content"]
if isinstance(prev_blocks, list) and isinstance(curr_blocks, list):
fixed[-1]["content"] = prev_blocks + curr_blocks
elif isinstance(prev_blocks, str) and isinstance(curr_blocks, str):
fixed[-1]["content"] = prev_blocks + "\n" + curr_blocks
else:
# Keep the later message
fixed[-1] = m
else:
fixed.append(m)
result = fixed
return system, result
@@ -270,6 +368,7 @@ def build_anthropic_kwargs(
tools: Optional[List[Dict]],
max_tokens: Optional[int],
reasoning_config: Optional[Dict[str, Any]],
tool_choice: Optional[str] = None,
) -> Dict[str, Any]:
"""Build kwargs for anthropic.messages.create()."""
system, anthropic_messages = convert_messages_to_anthropic(messages)
@@ -289,6 +388,16 @@ def build_anthropic_kwargs(
if anthropic_tools:
kwargs["tools"] = anthropic_tools
# Map OpenAI tool_choice to Anthropic format
if tool_choice == "auto" or tool_choice is None:
kwargs["tool_choice"] = {"type": "auto"}
elif tool_choice == "required":
kwargs["tool_choice"] = {"type": "any"}
elif tool_choice == "none":
pass # Don't send tool_choice — Anthropic will use tools if needed
elif isinstance(tool_choice, str):
# Specific tool name
kwargs["tool_choice"] = {"type": "tool", "name": tool_choice}
# Map reasoning_config to Anthropic's thinking parameter
if reasoning_config and isinstance(reasoning_config, dict):