Codex Responses Lite clients routed to a chat-native OpenAI-compatible
provider lost tool use in three places: non-streaming Chat responses
leaked the raw chat.completion envelope instead of Responses output
items, internal reasoning continuity fields leaked into the outbound
Chat body causing some upstreams to reject the request, and the
Responses to Chat request translator ignored additional_tools,
custom_tool_call, and custom_tool_call_output items entirely.
Also fixes apiType (chat vs responses) for openai-compatible nodes
being resolved from the immutable provider ID instead of the stored
node config, so editing a node's API Type had no runtime effect.
handleForcedSSEToJson dropped cached prompt tokens in two ways: the
Responses branch summed only input_tokens, which excludes cache_read
and cache_creation on cache-capable upstreams (measured 2012 reported
vs ~5344 actual, 5332 from cache); and the Chat Completions branch
computed usage correctly but it didn't always reach the client (an
Anthropic response with cache_read_input_tokens: 11022 arrived with no
usage field at all). Now folds cache counters into prompt_tokens,
surfaces them via prompt_tokens_details, and re-attaches usage before
serialisation.
Validate AWS EventStream framing, header bounds, CRCs, error frames,
and terminal stop metadata before exposing Kiro output. Classify stop
reasons into dispositions (complete / retryable / terminal_incomplete /
refusal) and retry once when the stream ends with a malformed tool call,
ellipsis-only output, or a short future-action sentence.
Fail closed: propagate streaming failures as error SSE (502) instead of
collapsing them into a successful stop, so incomplete responses no longer
leak as final answers.
Detect the observed evidence-prefixed trailing progress final without
broadening the Chinese heuristic to completed findings.
sseToJsonHandler.js unconditionally deleted reasoning_content from all
non-streaming responses (added for Firecrawl SDK compatibility). This
breaks thinking models (Qwen3.5, Claude extended thinking, etc.) where
the model may use all tokens for reasoning, leaving content empty.
When reasoning_content is stripped in that case, the response appears
completely empty to the client.
Fix: only strip reasoning_content when the response also has non-empty
content, so that reasoning output is preserved when it is the only
useful output.
Co-authored-by: Agent Zero <agent@agent-zero.local>
Some upstream providers (e.g. Antigravity) return non-standard finish_reason
values like 'other' instead of the OpenAI-standard 'tool_calls' when the
model invokes tools. This causes downstream consumers (e.g. OpenClaw) to
fail to execute tool calls, breaking agentic sub-agent workflows.
Changes:
- nonStreamingHandler: post-translation guard that normalizes finish_reason
to 'tool_calls' when message.tool_calls is present
- sseToJsonHandler: accumulate tool_calls from streaming deltas in
parseSSEToOpenAIResponse; extract function_call items from Responses API
output in handleForcedSSEToJson
- openai-responses translator: use toolCallIndex to choose between
'tool_calls' and 'stop' in flush and response.completed events
Tested: 7 scenarios (non-stream text, single/multiple tool calls, stream
text/tool calls, multi-turn tool conversation, tools present but unused)
Root cause: Codex/OpenAI Responses streams multiple alternating reasoning and
message output items. The first message block often has empty output_text; the
visible answer lives in a later message. Previous code used output.find() which
always picked the first (empty) message block.
Fix: walk message items from end and use the last message whose extracted text
is non-empty; fall back to final message if all are empty.
Note: Removed debug logging code from original PR #383 to keep implementation clean.
Co-authored-by: lokinh <locnh@uniultra.xyz>
Made-with: Cursor
