These params were silently dropped for Chat Completions because they
were missing from the supported params whitelist. Also adds
prompt_cache_retention to the Responses API TypedDict and fixes
misleading cache_control comments in OpenAI prompt caching docs.
* Add Ask AI chat component to Usage page
- Create UsageAIChatModal component with streaming chat interface
- Integrate with existing model hub for model selection
- Pass usage data context (spend, models, providers, keys) to AI
- Add Ask AI button next to Export Data button in global view
- Add tests for the new component and integration
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Convert Ask AI from modal to right-side sliding panel
- Replace UsageAIChatModal with UsageAIChatPanel
- Panel slides in from right side, usage page stays visible
- Full-height panel with header, model selector, chat area, and input
- Smooth CSS transition for open/close animation
- Update tests for new panel component (34 tests passing)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Remove build output directory from tracking
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Add backend AI usage chat endpoint with tool calling
Backend:
- New /usage/ai/chat SSE streaming endpoint
- AI agent has get_usage_data tool that queries /user/daily/activity/aggregated
- Follows same architecture as policy AI suggest (litellm.acompletion + tools)
- Non-admin users are restricted to their own data
- 12 backend unit tests
Frontend:
- Panel now calls /usage/ai/chat backend endpoint via SSE
- Removed direct OpenAI client calls from frontend
- Added usageAiChatStream networking function following enrichPolicyTemplateStream pattern
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Make model selection optional, default to gpt-4o-mini on backend
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Add team/tag tools, status indicators, and improved AI agent
- AI agent now has 3 tools: get_usage_data, get_team_usage_data, get_tag_usage_data
- Stream status events (Thinking... Fetching... Analyzing...) to UI
- Frontend shows spinner + status text during tool execution
- Better system prompt guiding tool selection
- Entity summariser for team/tag data with ranked breakdowns
- 13 backend tests, 34 frontend tests passing
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Fix: inject today's date into system prompt so AI resolves relative dates correctly
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Show tool calls as distinct steps + render markdown in responses
- Backend emits tool_call events with tool_name, label, args, and status
- Frontend shows each tool call as a step with ✓/spinner/✗ indicator
- Tool call steps show icon, label, date range, and filters
- AI responses rendered with ReactMarkdown (bold, lists, tables, code)
- Cursor-like UX: Thinking → tool calls → Analyzing → streamed answer
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Refactor backend for code quality: proper types, constants, all functions ≤50 LOC
- TypedDict for SSE events (SSEStatusEvent, SSEToolCallEvent, etc.) and ToolHandler
- Constants for table names, entity fields, temperature, page sizes, top-N limits
- Shared _query_activity() eliminates duplicated fetch logic
- _accumulate_breakdown() + _ranked_lines() replace inline aggregation loops
- Extracted _process_tool_call() and _stream_final_response() from main stream fn
- Black + Ruff clean, all 15 functions verified ≤50 LOC
- Replaced Tremor Button with Antd Button in panel (Tremor deprecated per AGENTS.md)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Address greptile review: security fixes and input validation
- Restrict team/tag tools to admin-only users (non-admins only get get_usage_data)
- Constrain ChatMessage.role to Literal['user', 'assistant'] to prevent system prompt injection
- Add test for base tools restriction (non-admin gets 1 tool, admin gets 3)
- Issues 3 (unused imports) and 4 (inline datetime) were already fixed in prior commit
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Address greptile round 2: sanitize errors, defense-in-depth allowlist, revert tsconfig
- Sanitize error messages: generic 'An internal error occurred' sent to client,
full exception logged server-side via verbose_proxy_logger
- Defense-in-depth: _process_tool_call validates fn_name against role-based
allowlist before dispatch (even though LLM only receives allowed tools)
- Revert tsconfig.json jsx back to 'preserve' (Next.js recommended default)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Role-scoped system prompt + additional test coverage
- System prompt is now role-aware: admin sees all 3 tool descriptions,
non-admin only sees get_usage_data (consistent with tool filtering)
- Added tests: non-admin prompt excludes team/tag tools, date injection
- 15 backend tests, 34 frontend tests passing
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* Fix LLM arg validation + cap conversation size at 20 messages
- _resolve_fetch_kwargs uses .get() with ValueError for missing dates
(handles malformed LLM tool arguments gracefully)
- MAX_CHAT_MESSAGES = 20 constant; backend truncates to last 20
- Frontend also sends only last 20 messages per request
- Prevents excessive token usage and context-length errors
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* feat(proxy): tool policies - auto-discover tools, manage policies, guardrail enforcement
- New LiteLLM_ToolTable in schema.prisma to store discovered tools
- Auto-discovery: tools seen in LLM responses get upserted via ToolDiscoveryQueue
(hooks into DBSpendUpdateWriter, same pipeline as spend tracking)
- Management endpoints: GET /v1/tool/list, GET /v1/tool/{name}, POST /v1/tool/policy
- ToolPolicyGuardrail: blocks tool_calls in responses based on policy setting
- UI: Tool Policies page under Guardrails section with policy selector,
filters by policy/team/key, live tail, sortable table
- Unit tests for queue, writer, endpoints, guardrail
* feat(tool-policies): track call_count + discover tools from request body and /messages API
- Add call_count column to LiteLLM_ToolTable; incremented on every flush
- Extract tools from request body too (not just response tool_calls):
- OpenAI /chat/completions: tools[].function.name
- Anthropic /messages pass-through: request_body.tools[].name
- Show call_count column in UI table (sortable)
- UI: drop dual_llm option, keep only trusted/blocked
* fix: address greptile review feedback
- Remove redundant @@index([tool_name]) from schema.prisma (tool_name has @unique which already creates an index)
- Replace gen_random_uuid()::text with str(uuid.uuid4()) for portability
- Rewrite test_tool_registry_writer.py to mock execute_raw/query_raw (actual implementation) instead of Prisma model methods
- Fix test patches in test_tool_management_endpoints.py to target source modules since imports are inside function bodies
- Add "Tool Policies" page title to ToolPolicies.tsx
* fix: address greptile review round 2
- Replace NOW() with Python datetime parameter in tool_registry_writer (SQLite portability)
- Fix cache key collision in tool_policy_guardrail: use null-byte separator instead of colon
- Remove type==function filter from request-side tool extraction to match response-side behavior
- Clear seen_tool_names on flush so call_count increments per batch cycle not per pod lifetime
* fix: address greptile review round 3
- Fix test_seen_names_persist_across_flushes to match actual per-flush-cycle behavior
- Update module docstring in tool_discovery_queue.py to accurately describe flush behavior
- Add created_at/updated_at to raw SQL INSERT in batch_upsert_tools and update_tool_policy
* fix: cache tool policies per tool name not per combination
Previously the cache key was built from the full set of tool names in a
request, so each unique combination of tools got its own cold cache entry
and triggered a separate DB query. With N distinct tools across requests
this was effectively a DB hit on every request.
Now each tool name is cached individually. Cache hits are checked per
tool, only missing tools are fetched from DB in a single batch query,
and each result is cached separately. Once a tool's policy is warm,
any subsequent request using that tool benefits from the cache regardless
of what other tools are in the request.
* Update ui/litellm-dashboard/src/components/ToolPolicies.tsx
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
- Wait for strategy select (API data loaded) before clicking Save
- Assert specific payload content in setCallbacksCall
- Move NotificationsManager import to top of file
- Resolve merge conflict in pass_through_endpoints.py
- Add .copy() to proxy_server_request headers to prevent cache corruption
- Add test for request.state unavailable fallback path
- Remove re-raise in _store_transactions_in_redis so one Redis
push failure doesn't drop remaining transaction types
- Downgrade per-push success log from info to debug to reduce noise
- Fix misleading error message in update_database — entity spend
updates run as independent tasks and are not affected by this catch
* fix(router): preserve _hidden_params in FallbackStreamWrapper so x-litellm-overhead-duration-ms is emitted for streaming requests
* test(router): add regression test for FallbackStreamWrapper _hidden_params preservation
Set prometheus_emit_stream_label: true in litellm_settings to emit a
stream label (True/False/None) on litellm_proxy_total_requests_metric.
Opt-in to avoid breaking cardinality on existing deployments.
Elevate silent debug-level and bare except:pass error paths to
warning/error so spend tracking failures are visible in production logs.
All new log messages are prefixed with "Spend tracking -" for easy
filtering. Changes cover the full request-to-DB lifecycle:
enqueue, in-memory flush, Redis buffer push/pop, DB commit,
cache updates, spend log writes, and pod lock management.
Also fixes a copy-paste bug in _update_team_cache that logged
"end user" instead of "team".
* staged first pass
* black
* Update litellm/proxy/health_check.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* simpler
* restore cached logo
* fix tests for perform_health_check max_concurrency arg
* implement pr suggestion
* and the helm chart
* add configureable resources and probes to the deployment in the helm chart
* more helm chart unittests
* move some background healthcheck loggin to debug
---------
Co-authored-by: Sean Glover <sglover@athenahealth.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
# Please enter a commit message to explain why this merge is necessary,
# especially if it merges an updated upstream into a topic branch.
#
# Lines starting with '#' will be ignored, and an empty message aborts
# the commit.
