The staleness check compared the local manifest digest (SHA256 of the
file on disk) against the registry's Ollama-Content-Digest header.
These never matched because PullModel re-serializes the manifest JSON
before writing, producing different bytes than the registry's original.
The fallback comparison (local modified_at vs upstream push time) was
also broken: the generated TypeScript Time class discards the actual
timestamp value, so Date parsing always produced NaN.
Fix by moving the staleness comparison server-side where we have
reliable access to both the local manifest file mtime and the upstream
push time. The /api/v1/model/upstream endpoint now returns a simple
`stale` boolean instead of raw digests for the frontend to compare.
Also adds User-Agent to the CORS allowed headers for dev mode.
A stop-gap for now to guide users better. We'll add more in-depth recommendations per integration as well.
---------
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
Add periodic snapshots every 8k tokens and near the end of the prompt
so that long prompts can be partially restored and thinking/generation
can be retried without full reprocessing.
Update LRU last used time just on the nodes that actually used
during processing rather than all snapshots along the path. This
allows eviction to remove nodes more accurately so we can avoid
other heuristics to auto-merge nodes.
mlx.Copy shares the backing buffer with its source (via
copy_shared_buffer) rather than allocating independent storage.
When used to snapshot a slice of the KV cache, the snapshot array
holds the entire original cache buffer alive through the shared
data pointer — even after eval detaches the computation graph.
Replace Copy with Contiguous in Snapshot and Split. Contiguous
allocates a compact buffer when the source buffer is significantly
larger than the logical slice (Contiguous::eval checks
buffer_size > nbytes + 16384), which is always the case for KV
cache slices.
Copilot Chat prefers to use `general.basename` in the built-in Ollama
integration, but this name isn't usually shown directly to users (and
there may be many models that share this name). Instead we pass back
`req.Model`, which for this extension is the value that we return from
`/api/tags`
* integration: improve ability to test individual models
Add OLLAMA_TEST_MODEL env var to run integration tests against a
single model.
Enhance vision tests: multi-turn chat with cached image tokens, object
counting, spatial reasoning, detail recognition, scene understanding, OCR, and
multi-image comparison.
Add tool calling stress tests with complex agent-style prompts, large
system messages, and multi-turn tool response handling.
* review comments
Previously, a partial match within a node's edge would truncate the path
to the parent snapshot - effectively making all cache types behave as
recurrent caches. Caches with only transformer layers can rewind to
arbitrary boundary so this restores this capability to improve cache
hits
* mlx: update to HEAD on 3/23
Also fixes a few misc vendoring bugs uncovered with this first update.
This also renames the version files to make them clearer.
* CUDA Fast Gated Delta kernel
* mlx: detect eval errors and panic
On model errors or missing kernels, don't mask the error, bubble it up.
Receiving from a buffered chan error consumes the value, so only the
first caller (WaitUntilRunning, HasExited, or Close) sees the signal.
Subsequent receivers block or take the wrong branch. Replace with a
closed chan struct{} which can be received from any number of times,
and store the error in a separate field.
The stderr reader used bufio.Scanner which has a 64KB max line size.
If the subprocess wrote a line exceeding this limit, the scanner would
stop reading, the OS pipe buffer would fill, and the subprocess would
deadlock.
Replace the scanner with a statusWriter that wraps io.Copy. The writer
forwards all stderr to os.Stderr while capturing the last short line
(≤256 bytes) for error reporting, avoiding both the deadlock and the
need to buffer arbitrarily long lines.
If `OLLAMA_DEBUG_LOG_REQUESTS` is set, then on server startup a temp
folder will be created. Upon any inference request, the body will be
logged to a file in this folder, as well as a small shell script to
"replay" the request using cURL.
This is just intended for debugging scenarios, not as something to turn
on normally.
Previous xml repair for glm was a good start, but we need to go further and repair any incorrect open or closing tags
Co-authored-by: Dongluo Chen <dongluo.chen@gmail.com>
Enable multiple conversations to reuse cached computations when they
share token prefixes (e.g. the same system prompt). A prefix trie
tracks shared regions so switching between conversations only
recomputes tokens that diverge. Inactive conversation state is paged
from active GPU memory to other memory and restored on demand, with LRU
eviction to keep memory usage bounded.
Slice used cmp.Or to resolve a zero stop value to the dimension size,
intended to support open-ended slices like a[i:]. This made Slice(0, 0)
indistinguishable from Slice(), so any slice with a zero stop would
silently include the entire dimension instead of being empty.
Replace cmp.Or with an explicit End sentinel and resolve negative
indices against the dimension size, matching Python/PyTorch semantics.
Defensively handle environments without a display server to ensure signin remains usable on headless VMs and SSH sessions.
- Skip calling xdg-open when neither DISPLAY nor WAYLAND_DISPLAY is set, preventing silent failures or unexpected browser handlers
- Render the signin URL as plain text instead of wrapping it in OSC 8 hyperlink escape sequences, which can be garbled or hidden by terminals that don't support them
Claude Code sends an x-anthropic-billing-header that changes on every
request. This is embedded in the system prompt and consequently
breaks the KV cache for every request. Given the size of the prompts
that Claude Code usees, this has significant performance impact.
The OpenClaw installer requires git in addition to npm. Update the
dependency check to detect both and provide specific install guidance
for whichever dependencies are missing.
`WebSearchAnthropicWriter` expects a single object per write. The new
transparent proxy will instead send it whatever bytes it sees. This
cloud-model + local-orchestration + cloud-search is a temporary code
path, so instead of making the web search code more robust to this, I
put an adapter in the middle that will flush line-by-line to preserve
the old behavior.
Add QuantizedEmbedding and EmbeddingLayer interface so models can
use quantized embedding weights and expose tied output projections.
This change updates gemma3, glm4_moe_lite, llama, qwen3, and qwen3_5
to use the new interface.
This change adds a tensorImportTransform interface for model-specific
tensor transformations during safetensors import. This allows importing
and modifying the standard HF based weights as well as the mlx-community
derived pre-quantized safetensors repos to be directly
imported into `ollama create`. Right now this only works with Qwen3.5
importing which does tensor renaming, norm weight shifting (it
adds +1 to each value of the norm vectors), conv1d transposition,
and casts to BF16s for F32 based vectors.
MLX runners (image generation and LLM) previously bypassed the
scheduler's standard load path via a separate loadMLX method. This meant
they skipped VRAM fitting checks and couldn't participate in model
eviction.
Now all model types flow through the same load function. Model eviction
for MLX is based on weights as KV cache and compute graph are dynamic.
This means that eviction does not take into account the worst case
memory and models can still compete for memory but it is a significant
improvement.
