* fix(images): render agent-generated images in chat
When a chat model calls generate_image mid-conversation (agentic flow), the image does
not display — it survives only as a URL the model echoes in prose. generate_image runs
as a text-only MCP server, so result['image_url'] is never populated and the existing
buildImageBubble render path never fires. Promote the image URL out of the tool's stdout
in tool_execution so the agent loop's existing forwarding renders it via buildImageBubble
— deterministically, no dependence on the model echoing the URL. Backend-only; reuses
dev's image bubble, forwarding, and the tool's existing parseable output.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(images): fully-qualified, valid generated-image links
The chat model often mangled the generated-image URL it echoed in prose (relative path,
or copying the 'image_url:' label into the link href). Build a fully-qualified link by
prefixing the existing app_public_url setting (empty default keeps relative paths), and
present it as a clean 'Direct link:' the model can echo verbatim (the frontend auto-links
bare https URLs). One file; independent of how the image is rendered.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(images): cover _promote_image_fields; make exit-code guard self-contained
Adds the unit tests requested in review on #2809: absolute URL, relative URL,
no URL (result unchanged), and non-zero exit_code (not promoted). Moves the
dict/exit_code==0 guard from the call site into _promote_image_fields so the
function is self-contained and the failure case is unit-testable; call-site
behavior is unchanged.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(stream): read 'reasoning' SSE field for vLLM 0.20.2 / NIM
vLLM 0.20.2 / NVIDIA NIM emit reasoning-parser output in the `reasoning` delta field; older builds use `reasoning_content`. stream_llm() read only the latter, so reasoning from models like Nemotron-3-Nano (--reasoning-parser) was silently dropped and never rendered. Accept either field.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(agent): keep reasoning_content only on the latest assistant turn
The agent loop echoed each round's reasoning back as `reasoning_content` on every assistant turn, assuming vendors ignore it. Nemotron's chat template re-injects ALL prior reasoning_content as <think> blocks, and the loop is trimmed only once (before it starts) — so reasoning accumulated unbounded across rounds, bloating context and feeding the model its own prior reasoning, which reinforced repetition/looping. Strip reasoning_content from earlier assistant turns so only the most recent round carries it (still satisfies DeepSeek's thinking-mode follow-up requirement).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(agent-ui): wrap each round's reasoning in its own <think> block
The streamed think-tag wrapper gated on whole-message substring checks (accumulated.includes('<think>')), which only ever wrapped ONE reasoning block per message. A multi-round agent response has a reasoning phase per round, so once round 1 closed its <think>...</think>, rounds 2+ reasoning was emitted unwrapped and leaked into the visible answer. Replace the substring checks with a stateful open/close flag that toggles per think/answer cycle, so each round's reasoning gets its own collapsible block. Single-turn chat is unchanged (one open, one close).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(stream): reasoning/reasoning_content delta surfaces as thinking chunk
Covers @pewdiepie-archdaemon's requested regression: a streamed {reasoning: ...} delta emits a thinking chunk while {content: ...} streams as normal content; plus the older reasoning_content field for backward compat. Mirrors the #591 scenario.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(cost): treat dotless container hostnames as local (free)
getModelCost() substring-matches model names against a cloud price table, so a self-hosted 'nemotron'/'llama' model was billed at cloud rates. isLocalEndpoint() only recognized IPs / localhost / .local, not bare Docker service names (nim-nano, llamaswap), so the local-is-free guard missed them. A single-label hostname (no dot) can never be a public API -> treat as local.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* test(cost): isLocalEndpoint classifies service names local, cloud FQDNs billable
Covers @pewdiepie-archdaemon's requested cases: llamaswap/nim-nano + localhost/private-IPs/.local => local (free); api.openai.com/openrouter.ai/etc => not local. Drives the real function via node --input-type=module (same approach as test_reply_recipients_js.py), skips when node is absent.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
