OpenAI rejects any reasoning_effort (even 'none') with tools in
/v1/chat/completions for gpt-5.4. Update the guard to drop reasoning_effort
regardless of value. Add docs explaining the auto-drop behavior.
The existing documentation for the Responses API bridge only showed
examples with models that have `mode: responses` (like o3-deep-research),
which work automatically. This update clarifies that models with
`mode: chat` (like gpt-4o, gpt-5) require the `openai/responses/` prefix
to use built-in tools like web_search_preview.
Changes:
- Explain the `mode` property from model_prices_and_context_window.json
- List models with mode: responses vs mode: chat
- Add example showing the common error and how to fix it
- Add SDK example using the prefix with gpt-4o
- Update proxy example with both automatic and prefix-based configs
- Fix invalid trailing comma in original JSON example
Implement Anthropic Files API (upload, retrieve, list, delete, content)
using the BaseFilesConfig provider pattern. Adds multipart form-data
support to BaseLLMHTTPHandler for file uploads.
Add Claude Opus 4.6, Sonnet 4.6, Opus 4.5, Sonnet 4.5, and Haiku 4.5
to the web fetch supported models documentation. These models were
missing from the list despite supporting the web_fetch tool.
Add usage example with concrete model entry, explanation of load-time
expansion, and cross-reference to model_alias_map to clarify the
difference between the two features.
When a provider's finish_reason is mapped to a different OpenAI-compatible
value (e.g. "MALFORMED_FUNCTION_CALL" → "stop"), the original value is now
preserved in choices[].provider_specific_fields["native_finish_reason"].
This allows agent loops to distinguish between different stop conditions
without breaking the unified OpenAI-compatible finish_reason mapping.
Also returns a defensive copy from get_finish_reason_mapping() to prevent
accidental mutation of the global _FINISH_REASON_MAP.
* docs: add pip/venv upgrade workflow guide
- Add comprehensive guide for upgrading LiteLLM proxy via pip
- Covers Prisma client regeneration and DB migration steps
- Includes verification commands and troubleshooting tips
- Links to existing Prisma migration troubleshooting doc
* docs: clarify Python version in prisma generate command
- Update example to show multiple Python versions (3.11, 3.12, 3.13)
- Make it clear LiteLLM supports multiple Python versions, not just 3.11
* docs: emphasize venv activation before running commands
- Add info box at top reminding users to activate venv
- Include venv activation step before starting proxy (both options)
- Add Windows activation command for cross-platform clarity
- Make it clear all commands assume activated venv
* docs: add pip_venv_upgrade to sidebar navigation
- Add new page to Troubleshooting section in sidebars.js
- Positioned after Performance/Latency category and before rollback
- Makes the upgrade guide discoverable through docs navigation
* docs: show explicit --schema flag in prisma migrate deploy
- Add explicit --schema path to Option B migration command
- Remove ambiguous instruction about running from litellm_proxy_extras
- Include path variable guidance for clarity
- Makes the command immediately runnable without directory navigation
* Update docs/my-website/docs/troubleshoot/pip_venv_upgrade.md
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update docs/my-website/docs/troubleshoot/pip_venv_upgrade.md
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* fix: close code block and add missing section in pip_venv_upgrade.md
* docs: define schema-path placeholder in verification section
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Resolve conflict in perplexity/responses/transformation.py by keeping
the simplified ~50 line version (PR's goal) instead of main's ~410 line
version. Added supports_native_websocket() -> False from main.
Add usage example with concrete model entry, explanation of load-time
expansion, and cross-reference to model_alias_map to clarify the
difference between the two features.
Chesars