This avoids emitting the progress indicators to stderr, and the interactive
prompts to the output file or pipe. Running "ollama run model > out.txt"
now exits immediately, and "echo hello | ollama run model > out.txt"
produces zero stderr output and a typical response in out.txt
OrionChat is a free web-based chat interface that simplifies interactions
with multiple AI model providers. It provides a unified platform for chatting
and exploring multiple large language models (LLMs).
Previous versions of the runner would truncate inputs to the context
window before beginning processing. The main processing loop relied
on this behavior if the context needed to be shifted later (due to
token generation). If truncation did not occur then invariants
would be broken, causing crashes or infinite loops.
Later versions attempted to fix these bugs and make the logic less
subtle so that all inputs could be handled. Truncation was removed
to make things consistent.
However, truncation is much faster than processing and shifting, so
removing it caused performance problems when the input vastly exceeded
the context size. This restores the input truncation as a performance
optimization while keeping the more robust processing logic.
Fixes#7762
We need to track which tokens are in the cache ourselves. We currently
add tokens to the cache tracker when we add them to batch but they are
not actually in the cache until we call Decode. This can cause
confusion when we are shifting the cache.
Avoids "could not find a KV slot for the batch" issues.
Bug #7545
We try to recover from errors by dropping the tokens that caused the
problem and re-trying. However, dropping the tokens is not correct
and continuing often leads to infinite loops. To avoid, this we
end the sequence if such a condition is detected, which is also
surprising.
At this point, it is better to just report the error. This will make
it easier to find problems and the alternatives are perhaps even more
surprising to users.
This is not a very satisfactory solution either - we should isolate
the error and return it to the user without killing the whole process.
However, this is an incremental step and consistent with most other
failures (which either manifest as abort() or panic).
Fragmentation of the KV cache can occur due to cache shifting or
different sequences getting processed. Decode uses a heuristic to
decide if it should defrag. However, this heuristic isn't 100%
accurate, so decoding can sometimes fail by surprise.
For these cases, if decode indicates that there is no KV cache space,
we should defrag and then try again.
Many model crashes are masked behind "An existing connection was forcibly closed by the remote host"
This captures that common error message and wires in any detected errors from the log.
This also adds the deepseek context shift error to the known errors we capture.
This change allows for mixed-case model names to be pushed, pulled,
copied, and created, which was previously disallowed because the Ollama
registry was backed by a Docker registry that enforced a naming
convention that disallowed mixed-case names, which is no longer the
case.
This does not break existing, intended, behaviors.
Also, make TestCase test a story of creating, updating, pulling, and
copying a model with case variations, ensuring the model's manifest is
updated correctly, and not duplicated across different files with
different case variations.
