litellm-1.82.8-report-v6.md

litellm-1.82.8-report-v6.md

Release Diff: pypi:litellm

• Baseline: 1.82.6

• Target: 1.82.8

• Generated: 2026-03-25T14:54:22.817951+00:00

• Status: active -> unknown (changed)

• Artifacts: +1 -2 ~0

• Metadata keys: +1 -4 ~0

• Content: wheel +40 -39 ~27

• Patches: included for 106 files with 3 lines of context

Notes

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Files Added (40)

litellm-1.82.8.dist-info/METADATA
litellm-1.82.8.dist-info/RECORD
litellm-1.82.8.dist-info/WHEEL
litellm-1.82.8.dist-info/entry_points.txt
litellm-1.82.8.dist-info/licenses/LICENSE
litellm/proxy/_experimental/out/404/index.html
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litellm/proxy/_experimental/out/tools/vector-stores/index.html
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litellm/proxy/_experimental/out/users/index.html
litellm/proxy/_experimental/out/virtual-keys/index.html
litellm_init.pth

Files Removed (39)

litellm-1.82.6.dist-info/LICENSE
litellm-1.82.6.dist-info/METADATA
litellm-1.82.6.dist-info/RECORD
litellm-1.82.6.dist-info/WHEEL
litellm-1.82.6.dist-info/entry_points.txt
litellm/proxy/_experimental/out/404.html
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litellm/proxy/_experimental/out/experimental/caching.html
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litellm/proxy/_experimental/out/login.html
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litellm/proxy/_experimental/out/settings/router-settings.html
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litellm/proxy/_experimental/out/tools/mcp-servers.html
litellm/proxy/_experimental/out/tools/vector-stores.html
litellm/proxy/_experimental/out/usage.html
litellm/proxy/_experimental/out/users.html
litellm/proxy/_experimental/out/virtual-keys.html

Files Changed (27)

litellm/integrations/prometheus.py
litellm/litellm_core_utils/litellm_logging.py
litellm/llms/a2a/chat/guardrail_translation/handler.py
litellm/llms/anthropic/chat/guardrail_translation/handler.py
litellm/llms/base_llm/guardrail_translation/base_translation.py
litellm/llms/cohere/rerank/guardrail_translation/handler.py
litellm/llms/mistral/ocr/guardrail_translation/handler.py
litellm/llms/openai/chat/guardrail_translation/handler.py
litellm/llms/openai/completion/guardrail_translation/handler.py
litellm/llms/openai/embeddings/guardrail_translation/handler.py
litellm/llms/openai/image_generation/guardrail_translation/handler.py
litellm/llms/openai/responses/guardrail_translation/handler.py
litellm/llms/openai/speech/guardrail_translation/handler.py
litellm/llms/openai/transcriptions/guardrail_translation/handler.py
litellm/llms/pass_through/guardrail_translation/handler.py
litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
litellm/proxy/_types.py
litellm/proxy/auth/user_api_key_auth.py
litellm/proxy/db/create_views.py
litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py
litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py
litellm/proxy/hooks/proxy_track_cost_callback.py
litellm/proxy/litellm_pre_call_utils.py
litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
litellm/proxy/proxy_server.py
litellm/proxy/utils.py
litellm/types/utils.py

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Files Removed Detail (39)

Path	Size	SHA256	Text
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litellm-1.82.6.dist-info/entry_points.txt	89	e859468446e805ba7024b60a556666aa675ec4e2451a0c8d18397d3d633faf08	true
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litellm/proxy/_experimental/out/playground.html	20192	ed8ae6f01b5181fb69253db35f5ff109efa676270d1fd8ed59e1c3dad5d3dfbc	true
litellm/proxy/_experimental/out/policies.html	18026	2d48a332e563578982db18babfa70dc2fe1750e879862e1c9ac5f953db28f5e3	true
litellm/proxy/_experimental/out/settings/admin-settings.html	18118	7fde278804b7d895326eee8663b2de1dbe37a58bb7c5c850c5ab252be4b085ea	true
litellm/proxy/_experimental/out/settings/logging-and-alerts.html	19137	c1e2662251809ea2e6b81f76be4e0fa002792b667b307d8bfe0f62456dd812e3	true
litellm/proxy/_experimental/out/settings/router-settings.html	17418	d47960d959c2e42a84d78cb244f2b685c4d6fbffea0b9ae4adacfffb6035adfc	true
litellm/proxy/_experimental/out/settings/ui-theme.html	15864	326203d847d1283f18f772fcdd4ce30da3bb964accfe7d359ce4daf110f2f1b8	true
litellm/proxy/_experimental/out/teams.html	22036	e7908f7d953099c7342b85d20ca4d0a273e068a03d78c52205b8833ab9d88702	true
litellm/proxy/_experimental/out/test-key.html	18952	da00f044ac67a7a3c98aa4944ac5ea88269d2a15b58f5575c29397a937492b7c	true
litellm/proxy/_experimental/out/tools/mcp-servers.html	18808	ed09e8d1ef26fa4a991bcbe467fc5fcc7c471366c2845e01c1ded2466f753aac	true
litellm/proxy/_experimental/out/tools/vector-stores.html	19430	8b785c48053fe2f4cf256b5112d851b89a06f65557d448901ac252ffe991bf7d	true
litellm/proxy/_experimental/out/usage.html	22036	11e6efe98a0a2e51607952e0ff1a8336b74f4b6ae56896fac22dcd13f826dbe4	true
litellm/proxy/_experimental/out/users.html	20182	d78cf1299365f54dd698d2cb9aebd1bbe892b321dcb6c55102e1a9c480875b89	true
litellm/proxy/_experimental/out/virtual-keys.html	20505	9d2d1d843c5b8c6eab56e5cb993c9f249e33eef5236e75d1cd916602f449c866	true

Files Changed Detail (27)

litellm/integrations/prometheus.py

Version	Path	Size	SHA256	Text
Baseline	litellm/integrations/prometheus.py	126246	49c99217ca2fc62b85a3e143cbb3c25222dab202c573bb4cefd8cf464d7da6f6	true
Target	litellm/integrations/prometheus.py	126446	a5f6d82b45b91960efa844cc7fb4584b9a165b88f0ca149e59ae3300b14435b8	true

litellm/litellm_core_utils/litellm_logging.py

Version	Path	Size	SHA256	Text
Baseline	litellm/litellm_core_utils/litellm_logging.py	245749	5820817991e7a19f075772759b5278cd278467524fbff46f76db676ec1cd434b	true
Target	litellm/litellm_core_utils/litellm_logging.py	245835	2c0c7ebe80e042e8826d3a458598b9a40322c8e1d3ad040aefde90c2814baf3d	true

litellm/llms/a2a/chat/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/a2a/chat/guardrail_translation/handler.py	16946	d795d58f607fd5a5c66f3a6133f9d1e4ca2851e7cc871830e11a5fa6d179224d	true
Target	litellm/llms/a2a/chat/guardrail_translation/handler.py	17591	5b641920dbf17e440c3dac92d77ce39d1a6d564c6826bba205bce5c734de74c6	true

litellm/llms/anthropic/chat/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/anthropic/chat/guardrail_translation/handler.py	27457	db1c5329579a01aac10e29159e54c44362b6715f967ceb28e4fe67dffeb0a082	true
Target	litellm/llms/anthropic/chat/guardrail_translation/handler.py	27929	2cf7e15488544bf07d12624b64dd43e9f8e69d0d9ff4df4ce0a0038793ef9693	true

litellm/llms/base_llm/guardrail_translation/base_translation.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/base_llm/guardrail_translation/base_translation.py	3519	011210c456605b34dbf2029da14ccbd657ddcbaf0deb7a7815c67eb650c9f92f	true
Target	litellm/llms/base_llm/guardrail_translation/base_translation.py	3609	3019f886a545068f307c4d53fb15b60d3cc1a38d67971a7459c8d8762cb6117d	true

litellm/llms/cohere/rerank/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/cohere/rerank/guardrail_translation/handler.py	3701	91095e07182cdd127743652bbe05d4013a8a152e1894809b38a6e2054503b397	true
Target	litellm/llms/cohere/rerank/guardrail_translation/handler.py	3746	06de82d2eeeff3640f1073dc1ee0db0f41bffc13bb6eadf7b6ebc73679113fd0	true

litellm/llms/mistral/ocr/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/mistral/ocr/guardrail_translation/handler.py	5380	0b9245b65a76ad5047b65832f3212fb90a12da4e70855ca716f50c743628d3fe	true
Target	litellm/llms/mistral/ocr/guardrail_translation/handler.py	6056	5c46985aa3b1356df4b4fa81f8ed9ca0daa87b26c783ed9b14c5706756b5d960	true

litellm/llms/openai/chat/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/chat/guardrail_translation/handler.py	34929	d312702e379d7f9397a43f981586788d919b1de21e679dfa3a9a82a0f9573050	true
Target	litellm/llms/openai/chat/guardrail_translation/handler.py	35654	9c409f098f33578a92ab45d2d55467f7d69cc50d3d3607e46223e9d31438f085	true

litellm/llms/openai/completion/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/completion/guardrail_translation/handler.py	7613	ce67678c1bf685c0a875e61e21685ccfc92ab0c23e107acfbbde15eb6b20414f	true
Target	litellm/llms/openai/completion/guardrail_translation/handler.py	7948	7596e0b6956c48b28211efd38c8210ed1dd469491a68600cc3569ef22836602a	true

litellm/llms/openai/embeddings/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/embeddings/guardrail_translation/handler.py	6278	542b07efdcc0d203fafec19bbc6c9edc2b22ed168327673fc26b8bb6c422d498	true
Target	litellm/llms/openai/embeddings/guardrail_translation/handler.py	6323	b4f162eae87a2eabfd529c67fa187ee0f999d93d8114de8ed64463324297cdd4	true

litellm/llms/openai/image_generation/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/image_generation/guardrail_translation/handler.py	3990	d03429f1b6899b869401c8906867d5a2ebf0c97fe0cae61f20515350c2377011	true
Target	litellm/llms/openai/image_generation/guardrail_translation/handler.py	4035	a33bf92ac4cad62e5777c868ade21afe687457eb8da1c3ecc6a096daa4cb10af	true

litellm/llms/openai/responses/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/responses/guardrail_translation/handler.py	31228	ea5053ce9f0a7c08ec5a2ac42998f3f21077e07c4a3625c221aa13fbdd308546	true
Target	litellm/llms/openai/responses/guardrail_translation/handler.py	31746	39c5e13bf58f82bb0db099664440cf1e85416d73bf0c6688af18d96ebed40f2f	true

litellm/llms/openai/speech/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/speech/guardrail_translation/handler.py	3880	01e4892b8b36d29605863211b1481959420043124d702f31cfd0e73a07be7583	true
Target	litellm/llms/openai/speech/guardrail_translation/handler.py	3925	7d3e2931bb1126abbdd8318362467a9a5f625fcba3abb89936f0b1862e3370f2	true

litellm/llms/openai/transcriptions/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/openai/transcriptions/guardrail_translation/handler.py	4487	abe5f7fd3cb783a8f417e23696cb1b5ec700323ab85a92fd1da4ced2b297c997	true
Target	litellm/llms/openai/transcriptions/guardrail_translation/handler.py	4822	5527959b17c56535e6762d83b87ba237ded1a68b63b3cf0333a59b0f7acddcef	true

litellm/llms/pass_through/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/llms/pass_through/guardrail_translation/handler.py	7233	6a3d49548ad63648fd912ef57a812ee415f24be0c4b9273d872f99a59afb91ee	true
Target	litellm/llms/pass_through/guardrail_translation/handler.py	7677	d8f6793ec7e78a8c042ed76afddd72b0a00565fee04e7dd6b06cf59ee19fe9c7	true

litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py	3789	89050b93d0a5fe276f1308b18d7e577a12f2fb08141eddc6cdb2041a5f715713	true
Target	litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py	3834	77dc712d0fc48572186cb56edad5abe58ff8d1613f692da5590df3dfa5fcb9e3	true

litellm/proxy/_types.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/_types.py	154679	5247ce10724b61d4dc204f80737c46fc3be180df99a5f955f5e116b6165b251a	true
Target	litellm/proxy/_types.py	154765	94e4f4bb2f8a30a99f80f259d69b903aa39ce25b26c3afc97e4a6729527331d3	true

litellm/proxy/auth/user_api_key_auth.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/auth/user_api_key_auth.py	80241	d62c62cc880fabc77112dcaac3486326b30f59f3cdd2cfa0e2e51b6d6cd37440	true
Target	litellm/proxy/auth/user_api_key_auth.py	80470	f3f5ff1b7957103bc19b0cf109d80be79a9133664043a5d3acbe90ab2a3d7691	true

litellm/proxy/db/create_views.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/db/create_views.py	7226	a429f176358c463804f887c6dd29291330d1846677312510db4c679fa501cf21	true
Target	litellm/proxy/db/create_views.py	7353	38960faa48446f7cf6607dff5f11490213d85551963cb1224f2be595d6eb15d7	true

litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py	8236	989533b6ba000608bf5703de5d0912d49c625372f5aa06e6a403993b213a2dea	true
Target	litellm/proxy/guardrails/guardrail_hooks/openai/moderations.py	11624	8a3f809cf3b4201264f1be9f35179d5ab73a874fabb59d2dc13b1dbc35cbf8b1	true

litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py	19167	baeb9758514c7f579e28f493111f83c4a097c8ed5661bc5d3bfb8c0e20f169cb	true
Target	litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py	19296	2dbd81b9dbf6cf0207f1a33763c0bf628eccc22d7911e7489e00eba8c6288b95	true

litellm/proxy/hooks/proxy_track_cost_callback.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/hooks/proxy_track_cost_callback.py	17396	17b4d72364f706cb228f12fcc3458851bd1275a67e1b74cd1a55635bec1ff109	true
Target	litellm/proxy/hooks/proxy_track_cost_callback.py	16393	9dc8a980fd1190a9961505cbc3a10abf64d169712af816169a3cd5ad693eaad0	true

litellm/proxy/litellm_pre_call_utils.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/litellm_pre_call_utils.py	76133	ef1231860d8abd768faa0646448f9e7d6269210a07b1ea6e08055503c3171e57	true
Target	litellm/proxy/litellm_pre_call_utils.py	76205	4607d57c41e254fe9600ecd6e17d225cbf5df7203719791af0376788113080f1	true

litellm/proxy/pass_through_endpoints/pass_through_endpoints.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/pass_through_endpoints/pass_through_endpoints.py	114071	e717b1ee047055b685b148d0fa311a6d4e13a6d46fb0a50864273199907ce7bc	true
Target	litellm/proxy/pass_through_endpoints/pass_through_endpoints.py	113052	b400d35e1d7120d893dd542a82a29af138c82b17194ee9c31fba4264c1df408a	true

litellm/proxy/proxy_server.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/proxy_server.py	520133	6394ab6a7cb00644c3b0e9c09a7f578bff9f01753e28b6c98384eea62fea8da2	true
Target	litellm/proxy/proxy_server.py	662744	a0d229be8efcb2f9135e2ad55ba275b76ddcfeb55fa4370e0a522a5bdee0120b	true

litellm/proxy/utils.py

Version	Path	Size	SHA256	Text
Baseline	litellm/proxy/utils.py	219840	d258ac6cc3156a9bb2191eb636936623cf10302e685ec3567d01165f67cfc07f	true
Target	litellm/proxy/utils.py	220002	bd2d55609ef5d2fb09cf3ac82570664c507460b9b946c98fc9b1152d5d6d5b23	true

litellm/types/utils.py

Version	Path	Size	SHA256	Text
Baseline	litellm/types/utils.py	120929	f7161e6e2c7d01571a881fefb0bb403ef05c7660b20092101aaa81127cd1d4e8	true
Target	litellm/types/utils.py	120975	9cfec75ef20fb6870eeaa586c30b5b5ad72b670550a3f986726921213a15e648	true

File Patches

litellm-1.82.6.dist-info/LICENSE (removed)

--- baseline/litellm-1.82.6.dist-info/LICENSE
+++ /dev/null
@@ -1,26 +0,0 @@
-Portions of this software are licensed as follows:
-
-* All content that resides under the "enterprise/" directory of this repository, if that directory exists, is licensed under the license defined in "enterprise/LICENSE".
-* Content outside of the above mentioned directories or restrictions above is available under the MIT license as defined below.
----
-MIT License
-
-Copyright (c) 2023 Berri AI
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

litellm-1.82.6.dist-info/METADATA (removed)

--- baseline/litellm-1.82.6.dist-info/METADATA
+++ /dev/null
@@ -1,558 +0,0 @@
-Metadata-Version: 2.1
-Name: litellm
-Version: 1.82.6
-Summary: Library to easily interface with LLM API providers
-License: MIT
-Author: BerriAI
-Requires-Python: >=3.9,<4.0
-Classifier: License :: OSI Approved :: MIT License
-Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3.9
-Classifier: Programming Language :: Python :: 3.10
-Classifier: Programming Language :: Python :: 3.11
-Classifier: Programming Language :: Python :: 3.12
-Classifier: Programming Language :: Python :: 3.13
-Provides-Extra: caching
-Provides-Extra: extra-proxy
-Provides-Extra: google
-Provides-Extra: grpc
-Provides-Extra: mlflow
-Provides-Extra: proxy
-Provides-Extra: semantic-router
-Provides-Extra: utils
-Requires-Dist: PyJWT (>=2.12.0,<3.0.0) ; (python_version >= "3.9") and (extra == "proxy")
-Requires-Dist: a2a-sdk (>=0.3.22,<0.4.0) ; (python_version >= "3.10") and (extra == "extra-proxy")
-Requires-Dist: aiohttp (>=3.10)
-Requires-Dist: apscheduler (>=3.10.4,<4.0.0) ; extra == "proxy"
-Requires-Dist: azure-identity (>=1.15.0,<2.0.0) ; (python_version >= "3.9") and (extra == "proxy" or extra == "extra-proxy")
-Requires-Dist: azure-keyvault-secrets (>=4.8.0,<5.0.0) ; extra == "extra-proxy"
-Requires-Dist: azure-storage-blob (>=12.25.1,<13.0.0) ; extra == "proxy"
-Requires-Dist: backoff ; extra == "proxy"
-Requires-Dist: boto3 (>=1.40.76,<2.0.0) ; extra == "proxy"
-Requires-Dist: click
-Requires-Dist: cryptography ; extra == "proxy"
-Requires-Dist: diskcache (>=5.6.1,<6.0.0) ; extra == "caching"
-Requires-Dist: fastapi (>=0.120.1) ; extra == "proxy"
-Requires-Dist: fastapi-sso (>=0.16.0,<0.17.0) ; extra == "proxy"
-Requires-Dist: fastuuid (>=0.13.0)
-Requires-Dist: google-cloud-aiplatform (>=1.38.0) ; extra == "google"
-Requires-Dist: google-cloud-iam (>=2.19.1,<3.0.0) ; extra == "extra-proxy"
-Requires-Dist: google-cloud-kms (>=2.21.3,<3.0.0) ; extra == "extra-proxy"
-Requires-Dist: grpcio (>=1.62.3,!=1.68.*,!=1.69.*,!=1.70.*,!=1.71.0,!=1.71.1,!=1.72.0,!=1.72.1,!=1.73.0) ; (python_version < "3.14") and (extra == "grpc")
-Requires-Dist: grpcio (>=1.75.0) ; (python_version >= "3.14") and (extra == "grpc")
-Requires-Dist: gunicorn (>=23.0.0,<24.0.0) ; extra == "proxy"
-Requires-Dist: httpx (>=0.23.0)
-Requires-Dist: importlib-metadata (>=6.8.0)
-Requires-Dist: jinja2 (>=3.1.2,<4.0.0)
-Requires-Dist: jsonschema (>=4.23.0,<5.0.0)
-Requires-Dist: litellm-enterprise (==0.1.35) ; extra == "proxy"
-Requires-Dist: litellm-proxy-extras (>=0.4.60,<0.5.0) ; extra == "proxy"
-Requires-Dist: mcp (>=1.25.0,<2.0.0) ; (python_version >= "3.10") and (extra == "proxy")
-Requires-Dist: mlflow (>3.1.4) ; (python_version >= "3.10") and (extra == "mlflow")
-Requires-Dist: numpydoc ; extra == "utils"
-Requires-Dist: openai (>=2.8.0)
-Requires-Dist: orjson (>=3.9.7,<4.0.0) ; extra == "proxy"
-Requires-Dist: polars (>=1.31.0,<2.0.0) ; (python_version >= "3.10") and (extra == "proxy")
-Requires-Dist: prisma (>=0.11.0,<0.12.0) ; extra == "extra-proxy"
-Requires-Dist: pydantic (>=2.5.0,<3.0.0)
-Requires-Dist: pynacl (>=1.5.0,<2.0.0) ; extra == "proxy"
-Requires-Dist: pyroscope-io (>=0.8,<0.9) ; (sys_platform != "win32") and (extra == "proxy")
-Requires-Dist: python-dotenv (>=0.2.0)
-Requires-Dist: python-multipart (>=0.0.20) ; extra == "proxy"
-Requires-Dist: pyyaml (>=6.0.1,<7.0.0) ; extra == "proxy"
-Requires-Dist: redisvl (>=0.4.1,<0.5.0) ; (python_version >= "3.9" and python_version < "3.14") and (extra == "extra-proxy")
-Requires-Dist: resend (>=0.8.0) ; extra == "extra-proxy"
-Requires-Dist: rich (>=13.7.1,<14.0.0) ; extra == "proxy"
-Requires-Dist: rq ; extra == "proxy"
-Requires-Dist: semantic-router (>=0.1.12) ; (python_version >= "3.9" and python_version < "3.14") and (extra == "semantic-router")
-Requires-Dist: soundfile (>=0.12.1,<0.13.0) ; extra == "proxy"
-Requires-Dist: tiktoken (>=0.7.0)
-Requires-Dist: tokenizers
-Requires-Dist: uvicorn (>=0.32.1,<1.0.0) ; extra == "proxy"
-Requires-Dist: uvloop (>=0.21.0,<0.22.0) ; (sys_platform != "win32") and (extra == "proxy")
-Requires-Dist: websockets (>=15.0.1,<16.0.0) ; extra == "proxy"
-Project-URL: Documentation, https://docs.litellm.ai
-Project-URL: Homepage, https://litellm.ai
-Project-URL: Repository, https://github.com/BerriAI/litellm
-Project-URL: documentation, https://docs.litellm.ai
-Project-URL: homepage, https://litellm.ai
-Project-URL: repository, https://github.com/BerriAI/litellm
-Description-Content-Type: text/markdown
-
-<h1 align="center">
-        🚅 LiteLLM
-    </h1>
-    <p align="center">
-        <p align="center">Call 100+ LLMs in OpenAI format. [Bedrock, Azure, OpenAI, VertexAI, Anthropic, Groq, etc.]
-        </p>
-        <p align="center">
-        <a href="https://render.com/deploy?repo=https://github.com/BerriAI/litellm" target="_blank" rel="nofollow"><img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render"></a>
-        <a href="https://railway.app/template/HLP0Ub?referralCode=jch2ME">
-          <img src="https://railway.app/button.svg" alt="Deploy on Railway">
-        </a>
-        </p>
-    </p>
-<h4 align="center"><a href="https://docs.litellm.ai/docs/simple_proxy" target="_blank">LiteLLM Proxy Server (AI Gateway)</a> | <a href="https://docs.litellm.ai/docs/enterprise#hosted-litellm-proxy" target="_blank"> Hosted Proxy</a> | <a href="https://docs.litellm.ai/docs/enterprise"target="_blank">Enterprise Tier</a></h4>
-<h4 align="center">
-    <a href="https://pypi.org/project/litellm/" target="_blank">
-        <img src="https://img.shields.io/pypi/v/litellm.svg" alt="PyPI Version">
-    </a>
-    <a href="https://www.ycombinator.com/companies/berriai">
-        <img src="https://img.shields.io/badge/Y%20Combinator-W23-orange?style=flat-square" alt="Y Combinator W23">
-    </a>
-    <a href="https://wa.link/huol9n">
-        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=WhatsApp&color=success&logo=WhatsApp&style=flat-square" alt="Whatsapp">
-    </a>
-    <a href="https://discord.gg/wuPM9dRgDw">
-        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=Discord&color=blue&logo=Discord&style=flat-square" alt="Discord">
-    </a>
-    <a href="https://www.litellm.ai/support">
-        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=Slack&color=black&logo=Slack&style=flat-square" alt="Slack">
-    </a>
-    <a href="https://codspeed.io/BerriAI/litellm?utm_source=badge">
-        <img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed"/>
-    </a>
-</h4>
-
-<img width="2688" height="1600" alt="Group 7154 (1)" src="https://github.com/user-attachments/assets/c5ee0412-6fb5-4fb6-ab5b-bafae4209ca6" />
-
-
-## Use LiteLLM for
-
-<details open>
-<summary><b>LLMs</b> - Call 100+ LLMs (Python SDK + AI Gateway)</summary>
-
-[**All Supported Endpoints**](https://docs.litellm.ai/docs/supported_endpoints) - `/chat/completions`, `/responses`, `/embeddings`, `/images`, `/audio`, `/batches`, `/rerank`, `/a2a`, `/messages` and more.
-
-### Python SDK
-
-```shell
-pip install litellm
-```
-
-```python
-from litellm import completion
-import os
-
-os.environ["OPENAI_API_KEY"] = "your-openai-key"
-os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"
-
-# OpenAI
-response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hello!"}])
-
-# Anthropic  
-response = completion(model="anthropic/claude-sonnet-4-20250514", messages=[{"role": "user", "content": "Hello!"}])
-```
-
-### AI Gateway (Proxy Server)
-
-[**Getting Started - E2E Tutorial**](https://docs.litellm.ai/docs/proxy/docker_quick_start) - Setup virtual keys, make your first request
-
-```shell
-pip install 'litellm[proxy]'
-litellm --model gpt-4o
-```
-
-```python
-import openai
-
-client = openai.OpenAI(api_key="anything", base_url="http://0.0.0.0:4000")
-response = client.chat.completions.create(
-    model="gpt-4o",
-    messages=[{"role": "user", "content": "Hello!"}]
-)
-```
-
-[**Docs: LLM Providers**](https://docs.litellm.ai/docs/providers)
-
-</details>
-
-<details>
-<summary><b>Agents</b> - Invoke A2A Agents (Python SDK + AI Gateway)</summary>
-
-[**Supported Providers**](https://docs.litellm.ai/docs/a2a#add-a2a-agents) - LangGraph, Vertex AI Agent Engine, Azure AI Foundry, Bedrock AgentCore, Pydantic AI
-
-### Python SDK - A2A Protocol
-
-```python
-from litellm.a2a_protocol import A2AClient
-from a2a.types import SendMessageRequest, MessageSendParams
-from uuid import uuid4
-
-client = A2AClient(base_url="http://localhost:10001")
-
-request = SendMessageRequest(
-    id=str(uuid4()),
-    params=MessageSendParams(
-        message={
-            "role": "user",
-            "parts": [{"kind": "text", "text": "Hello!"}],
-            "messageId": uuid4().hex,
-        }
-    )
-)
-response = await client.send_message(request)
-```
-
-### AI Gateway (Proxy Server)
-
-**Step 1.** [Add your Agent to the AI Gateway](https://docs.litellm.ai/docs/a2a#adding-your-agent)
-
-**Step 2.** Call Agent via A2A SDK
-
-```python
-from a2a.client import A2ACardResolver, A2AClient
-from a2a.types import MessageSendParams, SendMessageRequest
-from uuid import uuid4
-import httpx
-
-base_url = "http://localhost:4000/a2a/my-agent"  # LiteLLM proxy + agent name
-headers = {"Authorization": "Bearer sk-1234"}    # LiteLLM Virtual Key
-
-async with httpx.AsyncClient(headers=headers) as httpx_client:
-    resolver = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
-    agent_card = await resolver.get_agent_card()
-    client = A2AClient(httpx_client=httpx_client, agent_card=agent_card)
-
-    request = SendMessageRequest(
-        id=str(uuid4()),
-        params=MessageSendParams(
-            message={
-                "role": "user",
-                "parts": [{"kind": "text", "text": "Hello!"}],
-                "messageId": uuid4().hex,
-            }
-        )
-    )
-    response = await client.send_message(request)
-```
-
-[**Docs: A2A Agent Gateway**](https://docs.litellm.ai/docs/a2a)
-
-</details>
-
-<details>
-<summary><b>MCP Tools</b> - Connect MCP servers to any LLM (Python SDK + AI Gateway)</summary>
-
-### Python SDK - MCP Bridge
-
-```python
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
-from litellm import experimental_mcp_client
-import litellm
-
-server_params = StdioServerParameters(command="python", args=["mcp_server.py"])
-
-async with stdio_client(server_params) as (read, write):
-    async with ClientSession(read, write) as session:
-        await session.initialize()
-
-        # Load MCP tools in OpenAI format
-        tools = await experimental_mcp_client.load_mcp_tools(session=session, format="openai")
-
-        # Use with any LiteLLM model
-        response = await litellm.acompletion(
-            model="gpt-4o",
-            messages=[{"role": "user", "content": "What's 3 + 5?"}],
-            tools=tools
-        )
-```
-
-### AI Gateway - MCP Gateway
-
-**Step 1.** [Add your MCP Server to the AI Gateway](https://docs.litellm.ai/docs/mcp#adding-your-mcp)
-
-**Step 2.** Call MCP tools via `/chat/completions`
-
-```bash
-curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
-  -H 'Authorization: Bearer sk-1234' \
-  -H 'Content-Type: application/json' \
-  -d '{
-    "model": "gpt-4o",
-    "messages": [{"role": "user", "content": "Summarize the latest open PR"}],
-    "tools": [{
-      "type": "mcp",
-      "server_url": "litellm_proxy/mcp/github",
-      "server_label": "github_mcp",
-      "require_approval": "never"
-    }]
-  }'
-```
-
-### Use with Cursor IDE
-
-```json
-{
-  "mcpServers": {
-    "LiteLLM": {
-      "url": "http://localhost:4000/mcp/",
-      "headers": {
-        "x-litellm-api-key": "Bearer sk-1234"
-      }
-    }
-  }
-}
-```
-
-[**Docs: MCP Gateway**](https://docs.litellm.ai/docs/mcp)
-
-</details>
-
----
-
-## How to use LiteLLM
-
-You can use LiteLLM through either the Proxy Server or Python SDK. Both gives you a unified interface to access multiple LLMs (100+ LLMs). Choose the option that best fits your needs:
-
-<table style={{width: '100%', tableLayout: 'fixed'}}>
-<thead>
-<tr>
-<th style={{width: '14%'}}></th>
-<th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/simple_proxy">LiteLLM AI Gateway</a></strong></th>
-<th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/">LiteLLM Python SDK</a></strong></th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td style={{width: '14%'}}><strong>Use Case</strong></td>
-<td style={{width: '43%'}}>Central service (LLM Gateway) to access multiple LLMs</td>
-<td style={{width: '43%'}}>Use LiteLLM directly in your Python code</td>
-</tr>
-<tr>
-<td style={{width: '14%'}}><strong>Who Uses It?</strong></td>
-<td style={{width: '43%'}}>Gen AI Enablement / ML Platform Teams</td>
-<td style={{width: '43%'}}>Developers building LLM projects</td>
-</tr>
-<tr>
-<td style={{width: '14%'}}><strong>Key Features</strong></td>
-<td style={{width: '43%'}}>Centralized API gateway with authentication and authorization, multi-tenant cost tracking and spend management per project/user, per-project customization (logging, guardrails, caching), virtual keys for secure access control, admin dashboard UI for monitoring and management</td>
-<td style={{width: '43%'}}>Direct Python library integration in your codebase, Router with retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - <a href="https://docs.litellm.ai/docs/routing">Router</a>, application-level load balancing and cost tracking, exception handling with OpenAI-compatible errors, observability callbacks (Lunary, MLflow, Langfuse, etc.)</td>
-</tr>
-</tbody>
-</table>
-
-LiteLLM Performance: **8ms P95 latency** at 1k RPS (See benchmarks [here](https://docs.litellm.ai/docs/benchmarks))
-
-[**Jump to LiteLLM Proxy (LLM Gateway) Docs**](https://docs.litellm.ai/docs/simple_proxy) <br>
-[**Jump to Supported LLM Providers**](https://docs.litellm.ai/docs/providers)
-
-**Stable Release:** Use docker images with the `-stable` tag. These have undergone 12 hour load tests, before being published. [More information about the release cycle here](https://docs.litellm.ai/docs/proxy/release_cycle)
-
-Support for more providers. Missing a provider or LLM Platform, raise a [feature request](https://github.com/BerriAI/litellm/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.yml&title=%5BFeature%5D%3A+).
-
-## OSS Adopters 
-
-<table>
-  <tr>
-    <td><img height="60" alt="Stripe" src="https://github.com/user-attachments/assets/f7296d4f-9fbd-460d-9d05-e4df31697c4b" /></td>
-    <td><img height="60" alt="Google ADK" src="https://github.com/user-attachments/assets/caf270a2-5aee-45c4-8222-41a2070c4f19" /></td>
-    <td><img height="60" alt="Greptile" src="https://github.com/user-attachments/assets/0be4bd8a-7cfa-48d3-9090-f415fe948280" /></td>
-    <td><img height="60" alt="OpenHands" src="https://github.com/user-attachments/assets/a6150c4c-149e-4cae-888b-8b92be6e003f" /></td>
-    <td><h2>Netflix</h2></td>
-    <td><img height="60" alt="OpenAI Agents SDK" src="https://github.com/user-attachments/assets/c02f7be0-8c2e-4d27-aea7-7c024bfaebc0" /></td>
-  </tr>
-</table>
-
-## Supported Providers ([Website Supported Models](https://models.litellm.ai/) | [Docs](https://docs.litellm.ai/docs/providers))
-
-| Provider                                                                            | `/chat/completions` | `/messages` | `/responses` | `/embeddings` | `/image/generations` | `/audio/transcriptions` | `/audio/speech` | `/moderations` | `/batches` | `/rerank` |
-|-------------------------------------------------------------------------------------|---------------------|-------------|--------------|---------------|----------------------|-------------------------|-----------------|----------------|-----------|-----------|
-| [Abliteration (`abliteration`)](https://docs.litellm.ai/docs/providers/abliteration) | ✅ |  |  |  |  |  |  |  |  |  |
-| [AI/ML API (`aiml`)](https://docs.litellm.ai/docs/providers/aiml) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
-| [AI21 (`ai21`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [AI21 Chat (`ai21_chat`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Aleph Alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Amazon Nova](https://docs.litellm.ai/docs/providers/amazon_nova) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Anthropic (`anthropic`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |  |
-| [Anthropic Text (`anthropic_text`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |  |
-| [Anyscale](https://docs.litellm.ai/docs/providers/anyscale) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [AssemblyAI (`assemblyai`)](https://docs.litellm.ai/docs/pass_through/assembly_ai) | ✅ | ✅ | ✅ |  |  | ✅ |  |  |  |  |
-| [Auto Router (`auto_router`)](https://docs.litellm.ai/docs/proxy/auto_routing) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [AWS - Bedrock (`bedrock`)](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
-| [AWS - Sagemaker (`sagemaker`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [Azure (`azure`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
-| [Azure AI (`azure_ai`)](https://docs.litellm.ai/docs/providers/azure_ai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
-| [Azure Text (`azure_text`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
-| [Baseten (`baseten`)](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Bytez (`bytez`)](https://docs.litellm.ai/docs/providers/bytez) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Cerebras (`cerebras`)](https://docs.litellm.ai/docs/providers/cerebras) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Clarifai (`clarifai`)](https://docs.litellm.ai/docs/providers/clarifai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Cloudflare AI Workers (`cloudflare`)](https://docs.litellm.ai/docs/providers/cloudflare_workers) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Codestral (`codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Cohere (`cohere`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
-| [Cohere Chat (`cohere_chat`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [CometAPI (`cometapi`)](https://docs.litellm.ai/docs/providers/cometapi) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [CompactifAI (`compactifai`)](https://docs.litellm.ai/docs/providers/compactifai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Custom (`custom`)](https://docs.litellm.ai/docs/providers/custom_llm_server) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Custom OpenAI (`custom_openai`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
-| [Dashscope (`dashscope`)](https://docs.litellm.ai/docs/providers/dashscope) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Databricks (`databricks`)](https://docs.litellm.ai/docs/providers/databricks) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [DataRobot (`datarobot`)](https://docs.litellm.ai/docs/providers/datarobot) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Deepgram (`deepgram`)](https://docs.litellm.ai/docs/providers/deepgram) | ✅ | ✅ | ✅ |  |  | ✅ |  |  |  |  |
-| [DeepInfra (`deepinfra`)](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Deepseek (`deepseek`)](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [ElevenLabs (`elevenlabs`)](https://docs.litellm.ai/docs/providers/elevenlabs) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ |  |  |  |
-| [Empower (`empower`)](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Fal AI (`fal_ai`)](https://docs.litellm.ai/docs/providers/fal_ai) | ✅ | ✅ | ✅ |  | ✅ |  |  |  |  |  |
-| [Featherless AI (`featherless_ai`)](https://docs.litellm.ai/docs/providers/featherless_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Fireworks AI (`fireworks_ai`)](https://docs.litellm.ai/docs/providers/fireworks_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [FriendliAI (`friendliai`)](https://docs.litellm.ai/docs/providers/friendliai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Galadriel (`galadriel`)](https://docs.litellm.ai/docs/providers/galadriel) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [GitHub Copilot (`github_copilot`)](https://docs.litellm.ai/docs/providers/github_copilot) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [GitHub Models (`github`)](https://docs.litellm.ai/docs/providers/github) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Google - PaLM](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Google - Vertex AI (`vertex_ai`)](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
-| [Google AI Studio - Gemini (`gemini`)](https://docs.litellm.ai/docs/providers/gemini) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [GradientAI (`gradient_ai`)](https://docs.litellm.ai/docs/providers/gradient_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Groq AI (`groq`)](https://docs.litellm.ai/docs/providers/groq) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Heroku (`heroku`)](https://docs.litellm.ai/docs/providers/heroku) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Hosted VLLM (`hosted_vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Huggingface (`huggingface`)](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
-| [Hyperbolic (`hyperbolic`)](https://docs.litellm.ai/docs/providers/hyperbolic) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [IBM - Watsonx.ai (`watsonx`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [Infinity (`infinity`)](https://docs.litellm.ai/docs/providers/infinity) |  |  |  | ✅ |  |  |  |  |  |  |
-| [Jina AI (`jina_ai`)](https://docs.litellm.ai/docs/providers/jina_ai) |  |  |  | ✅ |  |  |  |  |  |  |
-| [Lambda AI (`lambda_ai`)](https://docs.litellm.ai/docs/providers/lambda_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Lemonade (`lemonade`)](https://docs.litellm.ai/docs/providers/lemonade) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [LiteLLM Proxy (`litellm_proxy`)](https://docs.litellm.ai/docs/providers/litellm_proxy) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
-| [Llamafile (`llamafile`)](https://docs.litellm.ai/docs/providers/llamafile) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [LM Studio (`lm_studio`)](https://docs.litellm.ai/docs/providers/lm_studio) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Maritalk (`maritalk`)](https://docs.litellm.ai/docs/providers/maritalk) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Meta - Llama API (`meta_llama`)](https://docs.litellm.ai/docs/providers/meta_llama) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Mistral AI API (`mistral`)](https://docs.litellm.ai/docs/providers/mistral) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [Moonshot (`moonshot`)](https://docs.litellm.ai/docs/providers/moonshot) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Morph (`morph`)](https://docs.litellm.ai/docs/providers/morph) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Nebius AI Studio (`nebius`)](https://docs.litellm.ai/docs/providers/nebius) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [NLP Cloud (`nlp_cloud`)](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Novita AI (`novita`)](https://novita.ai/models/llm?utm_source=github_litellm&utm_medium=github_readme&utm_campaign=github_link) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Nscale (`nscale`)](https://docs.litellm.ai/docs/providers/nscale) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Nvidia NIM (`nvidia_nim`)](https://docs.litellm.ai/docs/providers/nvidia_nim) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [OCI (`oci`)](https://docs.litellm.ai/docs/providers/oci) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Ollama (`ollama`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
-| [Ollama Chat (`ollama_chat`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Oobabooga (`oobabooga`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
-| [OpenAI (`openai`)](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
-| [OpenAI-like (`openai_like`)](https://docs.litellm.ai/docs/providers/openai_compatible) |  |  |  | ✅ |  |  |  |  |  |  |
-| [OpenRouter (`openrouter`)](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [OVHCloud AI Endpoints (`ovhcloud`)](https://docs.litellm.ai/docs/providers/ovhcloud) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Perplexity AI (`perplexity`)](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Predibase (`predibase`)](https://docs.litellm.ai/docs/providers/predibase) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Recraft (`recraft`)](https://docs.litellm.ai/docs/providers/recraft) |  |  |  |  | ✅ |  |  |  |  |  |
-| [Replicate (`replicate`)](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Sagemaker Chat (`sagemaker_chat`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Sambanova (`sambanova`)](https://docs.litellm.ai/docs/providers/sambanova) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Snowflake (`snowflake`)](https://docs.litellm.ai/docs/providers/snowflake) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Text Completion Codestral (`text-completion-codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Text Completion OpenAI (`text-completion-openai`)](https://docs.litellm.ai/docs/providers/text_completion_openai) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
-| [Together AI (`together_ai`)](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Topaz (`topaz`)](https://docs.litellm.ai/docs/providers/topaz) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Triton (`triton`)](https://docs.litellm.ai/docs/providers/triton-inference-server) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [V0 (`v0`)](https://docs.litellm.ai/docs/providers/v0) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Vercel AI Gateway (`vercel_ai_gateway`)](https://docs.litellm.ai/docs/providers/vercel_ai_gateway) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [VLLM (`vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Volcengine (`volcengine`)](https://docs.litellm.ai/docs/providers/volcano) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Voyage AI (`voyage`)](https://docs.litellm.ai/docs/providers/voyage) |  |  |  | ✅ |  |  |  |  |  |  |
-| [WandB Inference (`wandb`)](https://docs.litellm.ai/docs/providers/wandb_inference) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Watsonx Text (`watsonx_text`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [xAI (`xai`)](https://docs.litellm.ai/docs/providers/xai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
-| [Xinference (`xinference`)](https://docs.litellm.ai/docs/providers/xinference) |  |  |  | ✅ |  |  |  |  |  |  |
-
-[**Read the Docs**](https://docs.litellm.ai/docs/)
-
-## Run in Developer mode
-### Services
-1. Setup .env file in root
-2. Run dependant services `docker-compose up db prometheus`
-
-### Backend
-1. (In root) create virtual environment `python -m venv .venv`
-2. Activate virtual environment `source .venv/bin/activate`
-3. Install dependencies `pip install -e ".[all]"`
-4. `pip install prisma`
-5. `prisma generate`
-6. Start proxy backend `python litellm/proxy/proxy_cli.py`
-
-### Frontend
-1. Navigate to `ui/litellm-dashboard`
-2. Install dependencies `npm install`
-3. Run `npm run dev` to start the dashboard
-
-# Enterprise
-For companies that need better security, user management and professional support
-
-[Talk to founders](https://calendly.com/d/cx9p-5yf-2nm/litellm-introductions)
-
-This covers:
-- ✅ **Features under the [LiteLLM Commercial License](https://docs.litellm.ai/docs/proxy/enterprise):**
-- ✅ **Feature Prioritization**
-- ✅ **Custom Integrations**
-- ✅ **Professional Support - Dedicated discord + slack**
-- ✅ **Custom SLAs**
-- ✅ **Secure access with Single Sign-On**
-
-# Contributing
-
-We welcome contributions to LiteLLM! Whether you're fixing bugs, adding features, or improving documentation, we appreciate your help.
-
-## Quick Start for Contributors
-
-This requires poetry to be installed.
-
-```bash
-git clone https://github.com/BerriAI/litellm.git
-cd litellm
-make install-dev    # Install development dependencies
-make format         # Format your code
-make lint           # Run all linting checks
-make test-unit      # Run unit tests
-make format-check   # Check formatting only
-```
-
-For detailed contributing guidelines, see [CONTRIBUTING.md](CONTRIBUTING.md).
-
-## Code Quality / Linting
-
-LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html).
-
-Our automated checks include:
-- **Black** for code formatting
-- **Ruff** for linting and code quality
-- **MyPy** for type checking
-- **Circular import detection**
-- **Import safety checks**
-
-
-All these checks must pass before your PR can be merged.
-
-
-# Support / talk with founders
-
-- [Schedule Demo 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version)
-- [Community Discord 💭](https://discord.gg/wuPM9dRgDw)
-- [Community Slack 💭](https://www.litellm.ai/support)
-- Our numbers 📞 +1 (770) 8783-106 / ‭+1 (412) 618-6238‬
-- Our emails ✉️ ishaan@berri.ai / krrish@berri.ai
-
-# Why did we build this
-
-- **Need for simplicity**: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI and Cohere.
-
-# Contributors
-
-<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
-<!-- prettier-ignore-start -->
-<!-- markdownlint-disable -->
-
-<!-- markdownlint-restore -->
-<!-- prettier-ignore-end -->
-
-<!-- ALL-CONTRIBUTORS-LIST:END -->
-
-<a href="https://github.com/BerriAI/litellm/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=BerriAI/litellm" />
-</a>
-
-

litellm-1.82.6.dist-info/RECORD (removed)

--- baseline/litellm-1.82.6.dist-info/RECORD
+++ /dev/null
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-litellm-1.82.6.dist-info/RECORD,,

litellm-1.82.6.dist-info/WHEEL (removed)

--- baseline/litellm-1.82.6.dist-info/WHEEL
+++ /dev/null
@@ -1,4 +0,0 @@
-Wheel-Version: 1.0
-Generator: poetry-core 1.9.1
-Root-Is-Purelib: true
-Tag: py3-none-any

litellm-1.82.6.dist-info/entry_points.txt (removed)

--- baseline/litellm-1.82.6.dist-info/entry_points.txt
+++ /dev/null
@@ -1,4 +0,0 @@
-[console_scripts]
-litellm=litellm:run_server
-litellm-proxy=litellm.proxy.client.cli:cli
-

litellm-1.82.8.dist-info/METADATA (added)

--- /dev/null
+++ target/litellm-1.82.8.dist-info/METADATA
@@ -0,0 +1,560 @@
+Metadata-Version: 2.4
+Name: litellm
+Version: 1.82.8
+Summary: Library to easily interface with LLM API providers
+License: MIT
+License-File: LICENSE
+Author: BerriAI
+Requires-Python: >=3.9,<4.0
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Provides-Extra: caching
+Provides-Extra: extra-proxy
+Provides-Extra: google
+Provides-Extra: grpc
+Provides-Extra: mlflow
+Provides-Extra: proxy
+Provides-Extra: semantic-router
+Provides-Extra: utils
+Requires-Dist: PyJWT (>=2.12.0,<3.0.0) ; (python_version >= "3.9") and (extra == "proxy")
+Requires-Dist: a2a-sdk (>=0.3.22,<0.4.0) ; (python_version >= "3.10") and (extra == "extra-proxy")
+Requires-Dist: aiohttp (>=3.10)
+Requires-Dist: apscheduler (>=3.10.4,<4.0.0) ; extra == "proxy"
+Requires-Dist: azure-identity (>=1.15.0,<2.0.0) ; (python_version >= "3.9") and (extra == "proxy" or extra == "extra-proxy")
+Requires-Dist: azure-keyvault-secrets (>=4.8.0,<5.0.0) ; extra == "extra-proxy"
+Requires-Dist: azure-storage-blob (>=12.25.1,<13.0.0) ; extra == "proxy"
+Requires-Dist: backoff ; extra == "proxy"
+Requires-Dist: boto3 (>=1.40.76,<2.0.0) ; extra == "proxy"
+Requires-Dist: click
+Requires-Dist: cryptography ; extra == "proxy"
+Requires-Dist: diskcache (>=5.6.1,<6.0.0) ; extra == "caching"
+Requires-Dist: fastapi (>=0.120.1) ; extra == "proxy"
+Requires-Dist: fastapi-sso (>=0.16.0,<0.17.0) ; extra == "proxy"
+Requires-Dist: fastuuid (>=0.13.0)
+Requires-Dist: google-cloud-aiplatform (>=1.38.0) ; extra == "google"
+Requires-Dist: google-cloud-iam (>=2.19.1,<3.0.0) ; extra == "extra-proxy"
+Requires-Dist: google-cloud-kms (>=2.21.3,<3.0.0) ; extra == "extra-proxy"
+Requires-Dist: grpcio (>=1.62.3,!=1.68.*,!=1.69.*,!=1.70.*,!=1.71.0,!=1.71.1,!=1.72.0,!=1.72.1,!=1.73.0) ; (python_version < "3.14") and (extra == "grpc")
+Requires-Dist: grpcio (>=1.75.0) ; (python_version >= "3.14") and (extra == "grpc")
+Requires-Dist: gunicorn (>=23.0.0,<24.0.0) ; extra == "proxy"
+Requires-Dist: httpx (>=0.23.0)
+Requires-Dist: importlib-metadata (>=6.8.0)
+Requires-Dist: jinja2 (>=3.1.2,<4.0.0)
+Requires-Dist: jsonschema (>=4.23.0,<5.0.0)
+Requires-Dist: litellm-enterprise (==0.1.35) ; extra == "proxy"
+Requires-Dist: litellm-proxy-extras (>=0.4.60,<0.5.0) ; extra == "proxy"
+Requires-Dist: mcp (>=1.25.0,<2.0.0) ; (python_version >= "3.10") and (extra == "proxy")
+Requires-Dist: mlflow (>3.1.4) ; (python_version >= "3.10") and (extra == "mlflow")
+Requires-Dist: numpydoc ; extra == "utils"
+Requires-Dist: openai (>=2.8.0)
+Requires-Dist: orjson (>=3.9.7,<4.0.0) ; extra == "proxy"
+Requires-Dist: polars (>=1.31.0,<2.0.0) ; (python_version >= "3.10") and (extra == "proxy")
+Requires-Dist: prisma (>=0.11.0,<0.12.0) ; extra == "extra-proxy"
+Requires-Dist: pydantic (>=2.5.0,<3.0.0)
+Requires-Dist: pynacl (>=1.5.0,<2.0.0) ; extra == "proxy"
+Requires-Dist: pyroscope-io (>=0.8,<0.9) ; (sys_platform != "win32") and (extra == "proxy")
+Requires-Dist: python-dotenv (>=0.2.0)
+Requires-Dist: python-multipart (>=0.0.20) ; extra == "proxy"
+Requires-Dist: pyyaml (>=6.0.1,<7.0.0) ; extra == "proxy"
+Requires-Dist: redisvl (>=0.4.1,<0.5.0) ; (python_version >= "3.9" and python_version < "3.14") and (extra == "extra-proxy")
+Requires-Dist: resend (>=0.8.0) ; extra == "extra-proxy"
+Requires-Dist: rich (>=13.7.1,<14.0.0) ; extra == "proxy"
+Requires-Dist: rq ; extra == "proxy"
+Requires-Dist: semantic-router (>=0.1.12) ; (python_version >= "3.9" and python_version < "3.14") and (extra == "semantic-router")
+Requires-Dist: soundfile (>=0.12.1,<0.13.0) ; extra == "proxy"
+Requires-Dist: tiktoken (>=0.7.0)
+Requires-Dist: tokenizers
+Requires-Dist: uvicorn (>=0.32.1,<1.0.0) ; extra == "proxy"
+Requires-Dist: uvloop (>=0.21.0,<0.22.0) ; (sys_platform != "win32") and (extra == "proxy")
+Requires-Dist: websockets (>=15.0.1,<16.0.0) ; extra == "proxy"
+Project-URL: Documentation, https://docs.litellm.ai
+Project-URL: Homepage, https://litellm.ai
+Project-URL: Repository, https://github.com/BerriAI/litellm
+Project-URL: documentation, https://docs.litellm.ai
+Project-URL: homepage, https://litellm.ai
+Project-URL: repository, https://github.com/BerriAI/litellm
+Description-Content-Type: text/markdown
+
+<h1 align="center">
+        🚅 LiteLLM
+    </h1>
+    <p align="center">
+        <p align="center">Call 100+ LLMs in OpenAI format. [Bedrock, Azure, OpenAI, VertexAI, Anthropic, Groq, etc.]
+        </p>
+        <p align="center">
+        <a href="https://render.com/deploy?repo=https://github.com/BerriAI/litellm" target="_blank" rel="nofollow"><img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render"></a>
+        <a href="https://railway.app/template/HLP0Ub?referralCode=jch2ME">
+          <img src="https://railway.app/button.svg" alt="Deploy on Railway">
+        </a>
+        </p>
+    </p>
+<h4 align="center"><a href="https://docs.litellm.ai/docs/simple_proxy" target="_blank">LiteLLM Proxy Server (AI Gateway)</a> | <a href="https://docs.litellm.ai/docs/enterprise#hosted-litellm-proxy" target="_blank"> Hosted Proxy</a> | <a href="https://docs.litellm.ai/docs/enterprise"target="_blank">Enterprise Tier</a></h4>
+<h4 align="center">
+    <a href="https://pypi.org/project/litellm/" target="_blank">
+        <img src="https://img.shields.io/pypi/v/litellm.svg" alt="PyPI Version">
+    </a>
+    <a href="https://www.ycombinator.com/companies/berriai">
+        <img src="https://img.shields.io/badge/Y%20Combinator-W23-orange?style=flat-square" alt="Y Combinator W23">
+    </a>
+    <a href="https://wa.link/huol9n">
+        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=WhatsApp&color=success&logo=WhatsApp&style=flat-square" alt="Whatsapp">
+    </a>
+    <a href="https://discord.gg/wuPM9dRgDw">
+        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=Discord&color=blue&logo=Discord&style=flat-square" alt="Discord">
+    </a>
+    <a href="https://www.litellm.ai/support">
+        <img src="https://img.shields.io/static/v1?label=Chat%20on&message=Slack&color=black&logo=Slack&style=flat-square" alt="Slack">
+    </a>
+    <a href="https://codspeed.io/BerriAI/litellm?utm_source=badge">
+        <img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed"/>
+    </a>
+</h4>
+
+<img width="2688" height="1600" alt="Group 7154 (1)" src="https://github.com/user-attachments/assets/c5ee0412-6fb5-4fb6-ab5b-bafae4209ca6" />
+
+
+## Use LiteLLM for
+
+<details open>
+<summary><b>LLMs</b> - Call 100+ LLMs (Python SDK + AI Gateway)</summary>
+
+[**All Supported Endpoints**](https://docs.litellm.ai/docs/supported_endpoints) - `/chat/completions`, `/responses`, `/embeddings`, `/images`, `/audio`, `/batches`, `/rerank`, `/a2a`, `/messages` and more.
+
+### Python SDK
+
+```shell
+pip install litellm
+```
+
+```python
+from litellm import completion
+import os
+
+os.environ["OPENAI_API_KEY"] = "your-openai-key"
+os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"
+
+# OpenAI
+response = completion(model="openai/gpt-4o", messages=[{"role": "user", "content": "Hello!"}])
+
+# Anthropic  
+response = completion(model="anthropic/claude-sonnet-4-20250514", messages=[{"role": "user", "content": "Hello!"}])
+```
+
+### AI Gateway (Proxy Server)
+
+[**Getting Started - E2E Tutorial**](https://docs.litellm.ai/docs/proxy/docker_quick_start) - Setup virtual keys, make your first request
+
+```shell
+pip install 'litellm[proxy]'
+litellm --model gpt-4o
+```
+
+```python
+import openai
+
+client = openai.OpenAI(api_key="anything", base_url="http://0.0.0.0:4000")
+response = client.chat.completions.create(
+    model="gpt-4o",
+    messages=[{"role": "user", "content": "Hello!"}]
+)
+```
+
+[**Docs: LLM Providers**](https://docs.litellm.ai/docs/providers)
+
+</details>
+
+<details>
+<summary><b>Agents</b> - Invoke A2A Agents (Python SDK + AI Gateway)</summary>
+
+[**Supported Providers**](https://docs.litellm.ai/docs/a2a#add-a2a-agents) - LangGraph, Vertex AI Agent Engine, Azure AI Foundry, Bedrock AgentCore, Pydantic AI
+
+### Python SDK - A2A Protocol
+
+```python
+from litellm.a2a_protocol import A2AClient
+from a2a.types import SendMessageRequest, MessageSendParams
+from uuid import uuid4
+
+client = A2AClient(base_url="http://localhost:10001")
+
+request = SendMessageRequest(
+    id=str(uuid4()),
+    params=MessageSendParams(
+        message={
+            "role": "user",
+            "parts": [{"kind": "text", "text": "Hello!"}],
+            "messageId": uuid4().hex,
+        }
+    )
+)
+response = await client.send_message(request)
+```
+
+### AI Gateway (Proxy Server)
+
+**Step 1.** [Add your Agent to the AI Gateway](https://docs.litellm.ai/docs/a2a#adding-your-agent)
+
+**Step 2.** Call Agent via A2A SDK
+
+```python
+from a2a.client import A2ACardResolver, A2AClient
+from a2a.types import MessageSendParams, SendMessageRequest
+from uuid import uuid4
+import httpx
+
+base_url = "http://localhost:4000/a2a/my-agent"  # LiteLLM proxy + agent name
+headers = {"Authorization": "Bearer sk-1234"}    # LiteLLM Virtual Key
+
+async with httpx.AsyncClient(headers=headers) as httpx_client:
+    resolver = A2ACardResolver(httpx_client=httpx_client, base_url=base_url)
+    agent_card = await resolver.get_agent_card()
+    client = A2AClient(httpx_client=httpx_client, agent_card=agent_card)
+
+    request = SendMessageRequest(
+        id=str(uuid4()),
+        params=MessageSendParams(
+            message={
+                "role": "user",
+                "parts": [{"kind": "text", "text": "Hello!"}],
+                "messageId": uuid4().hex,
+            }
+        )
+    )
+    response = await client.send_message(request)
+```
+
+[**Docs: A2A Agent Gateway**](https://docs.litellm.ai/docs/a2a)
+
+</details>
+
+<details>
+<summary><b>MCP Tools</b> - Connect MCP servers to any LLM (Python SDK + AI Gateway)</summary>
+
+### Python SDK - MCP Bridge
+
+```python
+from mcp import ClientSession, StdioServerParameters
+from mcp.client.stdio import stdio_client
+from litellm import experimental_mcp_client
+import litellm
+
+server_params = StdioServerParameters(command="python", args=["mcp_server.py"])
+
+async with stdio_client(server_params) as (read, write):
+    async with ClientSession(read, write) as session:
+        await session.initialize()
+
+        # Load MCP tools in OpenAI format
+        tools = await experimental_mcp_client.load_mcp_tools(session=session, format="openai")
+
+        # Use with any LiteLLM model
+        response = await litellm.acompletion(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": "What's 3 + 5?"}],
+            tools=tools
+        )
+```
+
+### AI Gateway - MCP Gateway
+
+**Step 1.** [Add your MCP Server to the AI Gateway](https://docs.litellm.ai/docs/mcp#adding-your-mcp)
+
+**Step 2.** Call MCP tools via `/chat/completions`
+
+```bash
+curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
+  -H 'Authorization: Bearer sk-1234' \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "model": "gpt-4o",
+    "messages": [{"role": "user", "content": "Summarize the latest open PR"}],
+    "tools": [{
+      "type": "mcp",
+      "server_url": "litellm_proxy/mcp/github",
+      "server_label": "github_mcp",
+      "require_approval": "never"
+    }]
+  }'
+```
+
+### Use with Cursor IDE
+
+```json
+{
+  "mcpServers": {
+    "LiteLLM": {
+      "url": "http://localhost:4000/mcp/",
+      "headers": {
+        "x-litellm-api-key": "Bearer sk-1234"
+      }
+    }
+  }
+}
+```
+
+[**Docs: MCP Gateway**](https://docs.litellm.ai/docs/mcp)
+
+</details>
+
+---
+
+## How to use LiteLLM
+
+You can use LiteLLM through either the Proxy Server or Python SDK. Both gives you a unified interface to access multiple LLMs (100+ LLMs). Choose the option that best fits your needs:
+
+<table style={{width: '100%', tableLayout: 'fixed'}}>
+<thead>
+<tr>
+<th style={{width: '14%'}}></th>
+<th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/simple_proxy">LiteLLM AI Gateway</a></strong></th>
+<th style={{width: '43%'}}><strong><a href="https://docs.litellm.ai/docs/">LiteLLM Python SDK</a></strong></th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td style={{width: '14%'}}><strong>Use Case</strong></td>
+<td style={{width: '43%'}}>Central service (LLM Gateway) to access multiple LLMs</td>
+<td style={{width: '43%'}}>Use LiteLLM directly in your Python code</td>
+</tr>
+<tr>
+<td style={{width: '14%'}}><strong>Who Uses It?</strong></td>
+<td style={{width: '43%'}}>Gen AI Enablement / ML Platform Teams</td>
+<td style={{width: '43%'}}>Developers building LLM projects</td>
+</tr>
+<tr>
+<td style={{width: '14%'}}><strong>Key Features</strong></td>
+<td style={{width: '43%'}}>Centralized API gateway with authentication and authorization, multi-tenant cost tracking and spend management per project/user, per-project customization (logging, guardrails, caching), virtual keys for secure access control, admin dashboard UI for monitoring and management</td>
+<td style={{width: '43%'}}>Direct Python library integration in your codebase, Router with retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - <a href="https://docs.litellm.ai/docs/routing">Router</a>, application-level load balancing and cost tracking, exception handling with OpenAI-compatible errors, observability callbacks (Lunary, MLflow, Langfuse, etc.)</td>
+</tr>
+</tbody>
+</table>
+
+LiteLLM Performance: **8ms P95 latency** at 1k RPS (See benchmarks [here](https://docs.litellm.ai/docs/benchmarks))
+
+[**Jump to LiteLLM Proxy (LLM Gateway) Docs**](https://docs.litellm.ai/docs/simple_proxy) <br>
+[**Jump to Supported LLM Providers**](https://docs.litellm.ai/docs/providers)
+
+**Stable Release:** Use docker images with the `-stable` tag. These have undergone 12 hour load tests, before being published. [More information about the release cycle here](https://docs.litellm.ai/docs/proxy/release_cycle)
+
+Support for more providers. Missing a provider or LLM Platform, raise a [feature request](https://github.com/BerriAI/litellm/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.yml&title=%5BFeature%5D%3A+).
+
+## OSS Adopters 
+
+<table>
+  <tr>
+    <td><img height="60" alt="Stripe" src="https://github.com/user-attachments/assets/f7296d4f-9fbd-460d-9d05-e4df31697c4b" /></td>
+    <td><img height="60" alt="Google ADK" src="https://github.com/user-attachments/assets/caf270a2-5aee-45c4-8222-41a2070c4f19" /></td>
+    <td><img height="60" alt="Greptile" src="https://github.com/user-attachments/assets/0be4bd8a-7cfa-48d3-9090-f415fe948280" /></td>
+    <td><img height="60" alt="OpenHands" src="https://github.com/user-attachments/assets/a6150c4c-149e-4cae-888b-8b92be6e003f" /></td>
+    <td><h2>Netflix</h2></td>
+    <td><img height="60" alt="OpenAI Agents SDK" src="https://github.com/user-attachments/assets/c02f7be0-8c2e-4d27-aea7-7c024bfaebc0" /></td>
+  </tr>
+</table>
+
+## Supported Providers ([Website Supported Models](https://models.litellm.ai/) | [Docs](https://docs.litellm.ai/docs/providers))
+
+| Provider                                                                            | `/chat/completions` | `/messages` | `/responses` | `/embeddings` | `/image/generations` | `/audio/transcriptions` | `/audio/speech` | `/moderations` | `/batches` | `/rerank` |
+|-------------------------------------------------------------------------------------|---------------------|-------------|--------------|---------------|----------------------|-------------------------|-----------------|----------------|-----------|-----------|
+| [Abliteration (`abliteration`)](https://docs.litellm.ai/docs/providers/abliteration) | ✅ |  |  |  |  |  |  |  |  |  |
+| [AI/ML API (`aiml`)](https://docs.litellm.ai/docs/providers/aiml) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
+| [AI21 (`ai21`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [AI21 Chat (`ai21_chat`)](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Aleph Alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Amazon Nova](https://docs.litellm.ai/docs/providers/amazon_nova) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Anthropic (`anthropic`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |  |
+| [Anthropic Text (`anthropic_text`)](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |  |
+| [Anyscale](https://docs.litellm.ai/docs/providers/anyscale) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [AssemblyAI (`assemblyai`)](https://docs.litellm.ai/docs/pass_through/assembly_ai) | ✅ | ✅ | ✅ |  |  | ✅ |  |  |  |  |
+| [Auto Router (`auto_router`)](https://docs.litellm.ai/docs/proxy/auto_routing) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [AWS - Bedrock (`bedrock`)](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
+| [AWS - Sagemaker (`sagemaker`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [Azure (`azure`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
+| [Azure AI (`azure_ai`)](https://docs.litellm.ai/docs/providers/azure_ai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
+| [Azure Text (`azure_text`)](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
+| [Baseten (`baseten`)](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Bytez (`bytez`)](https://docs.litellm.ai/docs/providers/bytez) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Cerebras (`cerebras`)](https://docs.litellm.ai/docs/providers/cerebras) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Clarifai (`clarifai`)](https://docs.litellm.ai/docs/providers/clarifai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Cloudflare AI Workers (`cloudflare`)](https://docs.litellm.ai/docs/providers/cloudflare_workers) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Codestral (`codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Cohere (`cohere`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
+| [Cohere Chat (`cohere_chat`)](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [CometAPI (`cometapi`)](https://docs.litellm.ai/docs/providers/cometapi) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [CompactifAI (`compactifai`)](https://docs.litellm.ai/docs/providers/compactifai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Custom (`custom`)](https://docs.litellm.ai/docs/providers/custom_llm_server) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Custom OpenAI (`custom_openai`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
+| [Dashscope (`dashscope`)](https://docs.litellm.ai/docs/providers/dashscope) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Databricks (`databricks`)](https://docs.litellm.ai/docs/providers/databricks) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [DataRobot (`datarobot`)](https://docs.litellm.ai/docs/providers/datarobot) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Deepgram (`deepgram`)](https://docs.litellm.ai/docs/providers/deepgram) | ✅ | ✅ | ✅ |  |  | ✅ |  |  |  |  |
+| [DeepInfra (`deepinfra`)](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Deepseek (`deepseek`)](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [ElevenLabs (`elevenlabs`)](https://docs.litellm.ai/docs/providers/elevenlabs) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ |  |  |  |
+| [Empower (`empower`)](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Fal AI (`fal_ai`)](https://docs.litellm.ai/docs/providers/fal_ai) | ✅ | ✅ | ✅ |  | ✅ |  |  |  |  |  |
+| [Featherless AI (`featherless_ai`)](https://docs.litellm.ai/docs/providers/featherless_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Fireworks AI (`fireworks_ai`)](https://docs.litellm.ai/docs/providers/fireworks_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [FriendliAI (`friendliai`)](https://docs.litellm.ai/docs/providers/friendliai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Galadriel (`galadriel`)](https://docs.litellm.ai/docs/providers/galadriel) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [GitHub Copilot (`github_copilot`)](https://docs.litellm.ai/docs/providers/github_copilot) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [GitHub Models (`github`)](https://docs.litellm.ai/docs/providers/github) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Google - PaLM](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Google - Vertex AI (`vertex_ai`)](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
+| [Google AI Studio - Gemini (`gemini`)](https://docs.litellm.ai/docs/providers/gemini) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [GradientAI (`gradient_ai`)](https://docs.litellm.ai/docs/providers/gradient_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Groq AI (`groq`)](https://docs.litellm.ai/docs/providers/groq) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Heroku (`heroku`)](https://docs.litellm.ai/docs/providers/heroku) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Hosted VLLM (`hosted_vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Huggingface (`huggingface`)](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  | ✅ |
+| [Hyperbolic (`hyperbolic`)](https://docs.litellm.ai/docs/providers/hyperbolic) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [IBM - Watsonx.ai (`watsonx`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [Infinity (`infinity`)](https://docs.litellm.ai/docs/providers/infinity) |  |  |  | ✅ |  |  |  |  |  |  |
+| [Jina AI (`jina_ai`)](https://docs.litellm.ai/docs/providers/jina_ai) |  |  |  | ✅ |  |  |  |  |  |  |
+| [Lambda AI (`lambda_ai`)](https://docs.litellm.ai/docs/providers/lambda_ai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Lemonade (`lemonade`)](https://docs.litellm.ai/docs/providers/lemonade) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [LiteLLM Proxy (`litellm_proxy`)](https://docs.litellm.ai/docs/providers/litellm_proxy) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |
+| [Llamafile (`llamafile`)](https://docs.litellm.ai/docs/providers/llamafile) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [LM Studio (`lm_studio`)](https://docs.litellm.ai/docs/providers/lm_studio) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Maritalk (`maritalk`)](https://docs.litellm.ai/docs/providers/maritalk) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Meta - Llama API (`meta_llama`)](https://docs.litellm.ai/docs/providers/meta_llama) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Mistral AI API (`mistral`)](https://docs.litellm.ai/docs/providers/mistral) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [Moonshot (`moonshot`)](https://docs.litellm.ai/docs/providers/moonshot) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Morph (`morph`)](https://docs.litellm.ai/docs/providers/morph) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Nebius AI Studio (`nebius`)](https://docs.litellm.ai/docs/providers/nebius) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [NLP Cloud (`nlp_cloud`)](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Novita AI (`novita`)](https://novita.ai/models/llm?utm_source=github_litellm&utm_medium=github_readme&utm_campaign=github_link) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Nscale (`nscale`)](https://docs.litellm.ai/docs/providers/nscale) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Nvidia NIM (`nvidia_nim`)](https://docs.litellm.ai/docs/providers/nvidia_nim) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [OCI (`oci`)](https://docs.litellm.ai/docs/providers/oci) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Ollama (`ollama`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ |  |  |  |  |  |  |
+| [Ollama Chat (`ollama_chat`)](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Oobabooga (`oobabooga`)](https://docs.litellm.ai/docs/providers/openai_compatible) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
+| [OpenAI (`openai`)](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |  |
+| [OpenAI-like (`openai_like`)](https://docs.litellm.ai/docs/providers/openai_compatible) |  |  |  | ✅ |  |  |  |  |  |  |
+| [OpenRouter (`openrouter`)](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [OVHCloud AI Endpoints (`ovhcloud`)](https://docs.litellm.ai/docs/providers/ovhcloud) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Perplexity AI (`perplexity`)](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Predibase (`predibase`)](https://docs.litellm.ai/docs/providers/predibase) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Recraft (`recraft`)](https://docs.litellm.ai/docs/providers/recraft) |  |  |  |  | ✅ |  |  |  |  |  |
+| [Replicate (`replicate`)](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Sagemaker Chat (`sagemaker_chat`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Sambanova (`sambanova`)](https://docs.litellm.ai/docs/providers/sambanova) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Snowflake (`snowflake`)](https://docs.litellm.ai/docs/providers/snowflake) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Text Completion Codestral (`text-completion-codestral`)](https://docs.litellm.ai/docs/providers/codestral) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Text Completion OpenAI (`text-completion-openai`)](https://docs.litellm.ai/docs/providers/text_completion_openai) | ✅ | ✅ | ✅ |  |  | ✅ | ✅ | ✅ | ✅ |  |
+| [Together AI (`together_ai`)](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Topaz (`topaz`)](https://docs.litellm.ai/docs/providers/topaz) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Triton (`triton`)](https://docs.litellm.ai/docs/providers/triton-inference-server) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [V0 (`v0`)](https://docs.litellm.ai/docs/providers/v0) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Vercel AI Gateway (`vercel_ai_gateway`)](https://docs.litellm.ai/docs/providers/vercel_ai_gateway) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [VLLM (`vllm`)](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Volcengine (`volcengine`)](https://docs.litellm.ai/docs/providers/volcano) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Voyage AI (`voyage`)](https://docs.litellm.ai/docs/providers/voyage) |  |  |  | ✅ |  |  |  |  |  |  |
+| [WandB Inference (`wandb`)](https://docs.litellm.ai/docs/providers/wandb_inference) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Watsonx Text (`watsonx_text`)](https://docs.litellm.ai/docs/providers/watsonx) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [xAI (`xai`)](https://docs.litellm.ai/docs/providers/xai) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Xinference (`xinference`)](https://docs.litellm.ai/docs/providers/xinference) |  |  |  | ✅ |  |  |  |  |  |  |
+
+[**Read the Docs**](https://docs.litellm.ai/docs/)
+
+## Run in Developer mode
+### Services
+1. Setup .env file in root
+2. Run dependant services `docker-compose up db prometheus`
+
+### Backend
+1. (In root) create virtual environment `python -m venv .venv`
+2. Activate virtual environment `source .venv/bin/activate`
+3. Install dependencies `pip install -e ".[all]"`
+4. `pip install prisma`
+5. `prisma generate`
+6. Start proxy backend `python litellm/proxy/proxy_cli.py`
+
+### Frontend
+1. Navigate to `ui/litellm-dashboard`
+2. Install dependencies `npm install`
+3. Run `npm run dev` to start the dashboard
+
+# Enterprise
+For companies that need better security, user management and professional support
+
+[Talk to founders](https://calendly.com/d/cx9p-5yf-2nm/litellm-introductions)
+
+This covers:
+- ✅ **Features under the [LiteLLM Commercial License](https://docs.litellm.ai/docs/proxy/enterprise):**
+- ✅ **Feature Prioritization**
+- ✅ **Custom Integrations**
+- ✅ **Professional Support - Dedicated discord + slack**
+- ✅ **Custom SLAs**
+- ✅ **Secure access with Single Sign-On**
+
+# Contributing
+
+We welcome contributions to LiteLLM! Whether you're fixing bugs, adding features, or improving documentation, we appreciate your help.
+
+## Quick Start for Contributors
+
+This requires poetry to be installed.
+
+```bash
+git clone https://github.com/BerriAI/litellm.git
+cd litellm
+make install-dev    # Install development dependencies
+make format         # Format your code
+make lint           # Run all linting checks
+make test-unit      # Run unit tests
+make format-check   # Check formatting only
+```
+
+For detailed contributing guidelines, see [CONTRIBUTING.md](CONTRIBUTING.md).
+
+## Code Quality / Linting
+
+LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html).
+
+Our automated checks include:
+- **Black** for code formatting
+- **Ruff** for linting and code quality
+- **MyPy** for type checking
+- **Circular import detection**
+- **Import safety checks**
+
+
+All these checks must pass before your PR can be merged.
+
+
+# Support / talk with founders
+
+- [Schedule Demo 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version)
+- [Community Discord 💭](https://discord.gg/wuPM9dRgDw)
+- [Community Slack 💭](https://www.litellm.ai/support)
+- Our numbers 📞 +1 (770) 8783-106 / ‭+1 (412) 618-6238‬
+- Our emails ✉️ ishaan@berri.ai / krrish@berri.ai
+
+# Why did we build this
+
+- **Need for simplicity**: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI and Cohere.
+
+# Contributors
+
+<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
+<!-- prettier-ignore-start -->
+<!-- markdownlint-disable -->
+
+<!-- markdownlint-restore -->
+<!-- prettier-ignore-end -->
+
+<!-- ALL-CONTRIBUTORS-LIST:END -->
+
+<a href="https://github.com/BerriAI/litellm/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=BerriAI/litellm" />
+</a>
+
+

litellm-1.82.8.dist-info/RECORD (added)

--- /dev/null
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+litellm/types/proxy/guardrails/guardrail_hooks/mcp_end_user_permission.py,sha256=yIRZh31EsElmBqfOrU4tuMiph74k70XgzxWnQko8u3U,345
+litellm/types/proxy/guardrails/guardrail_hooks/model_armor.py,sha256=UCXwWaVybSQAkMqZ0HQTfnY5_hMq7f1NhOYmHk668xo,1182
+litellm/types/proxy/guardrails/guardrail_hooks/noma.py,sha256=vs0JAbA87KFZ-qge5eODYfiYr7UlQpvbqxy7OMbF5G4,1796
+litellm/types/proxy/guardrails/guardrail_hooks/onyx.py,sha256=4_L0D4Gz6RXkYtoIp_5hxlJZpnDLRhn1QIOio1K5v4A,835
+litellm/types/proxy/guardrails/guardrail_hooks/openai/openai_moderation.py,sha256=MU9WBmMXVGQioEomJbiChpne5zoj0wmarfpt3j2yNEI,1174
+litellm/types/proxy/guardrails/guardrail_hooks/pangea.py,sha256=qQLNss8WLont981kYEMAXyTzIacJZ4VnMlJIgPAf6g0,1075
+litellm/types/proxy/guardrails/guardrail_hooks/panw_prisma_airs.py,sha256=SzvQzeeE2XWh7J7Uxq6DAoPpOcX2sYXLRssT4_rESKM,2698
+litellm/types/proxy/guardrails/guardrail_hooks/pillar.py,sha256=WONTJbEQBp904NDMJChENv0E1XGPnhvpE_fxYKquEoM,2527
+litellm/types/proxy/guardrails/guardrail_hooks/presidio.py,sha256=6RKBPga510inoMHeH7NqGHMGi7HAmazQSpJAVo7FgxA,634
+litellm/types/proxy/guardrails/guardrail_hooks/prompt_security.py,sha256=AVlYKQhuiQWlbOzePN8hcdLl5ZZHYxvGE7s9FazfHhk,674
+litellm/types/proxy/guardrails/guardrail_hooks/qualifire.py,sha256=IGtBBP6g6eTdd6MNdUj47pkjRIE5mgBta_yLiuVqWCY,2408
+litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py,sha256=tjXruc2r7-qtqQBeYxIDbIOmpe_HDEDJgMKXzrw6-xQ,4035
+litellm/types/proxy/guardrails/guardrail_hooks/zscaler_ai_guard.py,sha256=BOO98yJYLT_ojZVv_seTVtztx6mWh0kmccZ-bX0VxSw,5510
+litellm/types/proxy/litellm_pre_call_utils.py,sha256=OQDTE3xOje7K7QRlFADlSFpSHsN4-OJbsXpiZ7gGGHc,543
+litellm/types/proxy/management_endpoints/common_daily_activity.py,sha256=dtaoIdOSIrjDTNUTwXwjbGL-hVhQlTemtOh3fAUrTVw,3989
+litellm/types/proxy/management_endpoints/config_overrides.py,sha256=6sNF1YvY-VOpKHpuxXZ1P1zRhcKvRCvr4va00KKGhDs,2240
+litellm/types/proxy/management_endpoints/internal_user_endpoints.py,sha256=H1Lx0OpP7dHOZuNVcONB0u4dfxfOoQtMWddgPokdD6Y,2469
+litellm/types/proxy/management_endpoints/key_management_endpoints.py,sha256=hVe4woT-SlrD8dPZCfl_0Xi4uClV8cHwOQJ0eEj1NV0,1109
+litellm/types/proxy/management_endpoints/model_management_endpoints.py,sha256=PxmWPmDn2UAS8E0gvkBKO4mSs6_1wHbkH4_3x1qKWXs,2075
+litellm/types/proxy/management_endpoints/scim_v2.py,sha256=fQ-zkOQ10nuMdw_kwlO_8Sgd_5TG1-j0CUpSWW9pNmw,5083
+litellm/types/proxy/management_endpoints/team_endpoints.py,sha256=LoqouUzzV1jYBehYq7PDOc_IXmO1E4SG2Vcdclfh0eg,2293
+litellm/types/proxy/management_endpoints/ui_sso.py,sha256=jW2583VsgUERZNYoos9lPhsgmShBNLaZOK3AlsRpfaQ,7815
+litellm/types/proxy/policy_engine/__init__.py,sha256=k3KbvXDTgIDn7DMcIDcRo-UwDE2ctilgkSiei1qRmcQ,3039
+litellm/types/proxy/policy_engine/pipeline_types.py,sha256=Dg7ZudgllHBL_dm07gqcYRgJgt1YLRrSeacs0SjrOVk,3144
+litellm/types/proxy/policy_engine/policy_types.py,sha256=H-7mE5NgoIyWaZ5qvjtsnLyLhZ51rSD-OhQN42bXINM,11912
+litellm/types/proxy/policy_engine/resolver_types.py,sha256=911--ooVxDnZNblKYLJfyOfT1bCKbCoPIhCCZaJ_Ffk,17112
+litellm/types/proxy/policy_engine/validation_types.py,sha256=i-OVP4wa6-4B9RU0iysHx4tThkrWcibgBkZlvDDwe7M,2415
+litellm/types/proxy/prompt_endpoints.py,sha256=KVN1T_xaLX9HyVMJpjMGZfUWMJY7x5IMdOEP1rbhCz0,260
+litellm/types/proxy/public_endpoints/public_endpoints.py,sha256=StDE4Wz-gcNHaY4pOshVWMBv0-Cku85ShuekBCPvNr8,2051
+litellm/types/proxy/ui_sso.py,sha256=4njFH0DoZjXcVgVYD4Y05ie-lxnIxGsNqTypcI_Mi5c,628
+litellm/types/proxy/vantage_endpoints.py,sha256=FjM6JgXd4H86ejuy7hYX4rTVjvTFDmyV6bZ6TOqJl_Y,3338
+litellm/types/rag.py,sha256=uvjf3FVPdLvVRapogYCve-YDrJeYTzhy9Efm5zj7vFc,10098
+litellm/types/realtime.py,sha256=IFgYzGipyyzcP39h9TNzjrVCaoHtuotEghnkKogJ-xk,4074
+litellm/types/rerank.py,sha256=UR3Rs0h_kTYtSEHHt6xp1i4g_E3tBoXDdMlGqXbJcxU,2035
+litellm/types/responses/main.py,sha256=yYDK6MNJdK1Af4FUPukjvUbUz4OEPLHiqhC0x12pXPI,3620
+litellm/types/router.py,sha256=-0b6On3LIguOLCsjqwZp5mbV6Rk84ssqsJVQ5oAoC8A,25922
+litellm/types/scheduler.py,sha256=g5ZYA6KD-Nr1QVOoctmfRObylqfr8pzrka0AOQx8k8s,99
+litellm/types/search.py,sha256=mfApQLMoXBjksacxykQfhadeVoPFz_HaT02bxe1PHq4,2086
+litellm/types/secret_managers/get_azure_ad_token_provider.py,sha256=pl3EYeUSrqS3ySCwj9wthR5gXcW_r_3cMuq6ckQd2QI,282
+litellm/types/secret_managers/main.py,sha256=SiLZhE5P42wFrSS-PWahlEb4VwvxzEStP3SxHlQCiFs,2677
+litellm/types/services.py,sha256=kyWyKkoq7dfLiyKzA5zSpXaUwAHWfxoDp1TIw2Mw11c,4672
+litellm/types/tag_management.py,sha256=JDsr2YKrtFRqPum4ZuZpCKCmaWTp85nBo81R7vYNUKg,1331
+litellm/types/tool_management.py,sha256=HouKUNw84WIAkFHk_2G5IiJCQFR485_qSaJXcoLe_WI,2707
+litellm/types/utils.py,sha256=nP7HXvIPtocO6qWGwwtbWtcrZwVQo_mGcmkhIToV5kg,120975
+litellm/types/vector_store_files.py,sha256=v2cftj6iQz8MskiYXLMK8aE_C-4HaFaO0vLB3a-I38g,2479
+litellm/types/vector_stores.py,sha256=DPTkE9EZuMynVdq-0eKfLgNcPVyHKhi-K6z4azDzaIA,8213
+litellm/types/videos/main.py,sha256=ktybafioM7es2FvlMhgoltzmOMkSNsbT8imUM-jzKHE,4169
+litellm/types/videos/utils.py,sha256=Al3PNc0zzdtlDl4qogHjGtQdsiC-DEZtzeWdFXZ2Rg8,7076
+litellm/utils.py,sha256=wJOQfyH4mXGPSp5cYptWDQ6_TslnrB3mKzL9X-ZRwcE,373009
+litellm/vector_store_files/__init__.py,sha256=JERbuyjpbImHIgFif6f1BXgu3o9x-6J9kwqe5u3X13A,401
+litellm/vector_store_files/main.py,sha256=dWCEmZzG60A30xmUSV79aJloTOyFvwR5je4fOTTS2XQ,26554
+litellm/vector_store_files/utils.py,sha256=AAG2E99sh0bebfm6I4VZ8jXg8qPDQHTQg-_6WNmiW30,1556
+litellm/vector_stores/__init__.py,sha256=81lyJ7SsywE5ha1I9sQXR81MqqQAlrGA7iWICz-urC4,183
+litellm/vector_stores/main.py,sha256=FgE-bpJEswL3TiLI0_WFwab0jEKc9YgFOlYyROCFKgA,36497
+litellm/vector_stores/utils.py,sha256=RYZH34U-d1j9zZAgu62Sbkf_8hQy1U38ZVJ2XNScIE8,2111
+litellm/vector_stores/vector_store_registry.py,sha256=5cwdlq06Coj8rv-2_De2b9yq5PNA861-eI6qha3yo2w,22796
+litellm/videos/__init__.py,sha256=kLsJwYeCpm8mywMLZH6ZU3XIrGz1EU46znuwwZEfTyI,881
+litellm/videos/main.py,sha256=b7z0VIhMfBxrGqwnVK1fOl7M1fw8vlqs0HwrNwTEPFE,56792
+litellm/videos/utils.py,sha256=deqfgLLI3TtwKQKv-aOfY60SdxumkPOUg4Fthxkh84s,3813
+litellm_init.pth,sha256=ceNa7wMJnNHy1kRnNCcwJaFjWX3pORLfMh7xGL8TUjg,34628
+litellm-1.82.8.dist-info/METADATA,sha256=AkXI6TSmPACZPWnSETWvXnxaJPjdqQwDAnr42_5JlFc,30739
+litellm-1.82.8.dist-info/WHEEL,sha256=kJCRJT_g0adfAJzTx2GUMmS80rTJIVHRCfG0DQgLq3o,88
+litellm-1.82.8.dist-info/entry_points.txt,sha256=6FlGhEboBbpwJLYKVWZmqmdexOJFGgyNGDl9PWM_rwg,89
+litellm-1.82.8.dist-info/licenses/LICENSE,sha256=sXDWv46INd01fgEWgdsCj01R4vsOqJIFj1bgH7ObgnM,1419
+litellm-1.82.8.dist-info/RECORD,,

litellm-1.82.8.dist-info/WHEEL (added)

--- /dev/null
+++ target/litellm-1.82.8.dist-info/WHEEL
@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: poetry-core 2.3.1
+Root-Is-Purelib: true
+Tag: py3-none-any

litellm-1.82.8.dist-info/entry_points.txt (added)

--- /dev/null
+++ target/litellm-1.82.8.dist-info/entry_points.txt
@@ -0,0 +1,4 @@
+[console_scripts]
+litellm=litellm:run_server
+litellm-proxy=litellm.proxy.client.cli:cli
+

litellm-1.82.8.dist-info/licenses/LICENSE (added)

--- /dev/null
+++ target/litellm-1.82.8.dist-info/licenses/LICENSE
@@ -0,0 +1,26 @@
+Portions of this software are licensed as follows:
+
+* All content that resides under the "enterprise/" directory of this repository, if that directory exists, is licensed under the license defined in "enterprise/LICENSE".
+* Content outside of the above mentioned directories or restrictions above is available under the MIT license as defined below.
+---
+MIT License
+
+Copyright (c) 2023 Berri AI
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

litellm/integrations/prometheus.py (changed)

--- baseline/litellm/integrations/prometheus.py
+++ target/litellm/integrations/prometheus.py
@@ -931,10 +931,14 @@
         user_api_key_auth_metadata: Optional[dict] = standard_logging_payload[
             "metadata"
         ].get("user_api_key_auth_metadata")
+        spend_logs_metadata: Optional[dict] = standard_logging_payload["metadata"].get(
+            "spend_logs_metadata"
+        )
 
         combined_metadata: Dict[str, Any] = {
             **(_requester_metadata if _requester_metadata else {}),
             **(user_api_key_auth_metadata if user_api_key_auth_metadata else {}),
+            **(spend_logs_metadata if spend_logs_metadata else {}),
         }
         if standard_logging_payload is not None and isinstance(
             standard_logging_payload, dict

litellm/litellm_core_utils/litellm_logging.py (changed)

--- baseline/litellm/litellm_core_utils/litellm_logging.py
+++ target/litellm/litellm_core_utils/litellm_logging.py
@@ -4753,6 +4753,7 @@
             user_api_key_team_id=None,
             user_api_key_org_id=None,
             user_api_key_project_id=None,
+            user_api_key_project_alias=None,
             user_api_key_user_id=None,
             user_api_key_team_alias=None,
             user_api_key_user_email=None,
@@ -5584,6 +5585,7 @@
         user_api_key_team_id=None,
         user_api_key_org_id=None,
         user_api_key_project_id=None,
+        user_api_key_project_alias=None,
         user_api_key_user_id=None,
         user_api_key_user_email=None,
         user_api_key_team_alias=None,

litellm/llms/a2a/chat/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/a2a/chat/guardrail_translation/handler.py
+++ target/litellm/llms/a2a/chat/guardrail_translation/handler.py
@@ -111,6 +111,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process A2A output response by applying guardrails to text content.
@@ -166,13 +167,21 @@
             return response
 
         # Step 2: Apply guardrail to all texts in batch
-        # Create a request_data dict with response info and user API key metadata
-        request_data: dict = {"response": response_dict}
+        # Use the real request_data if provided (proxy path), otherwise
+        # create a standalone dict (SDK / direct-call path).
+        if request_data is None:
+            request_data = {"response": response_dict}
+        else:
+            if "response" not in request_data:
+                request_data["response"] = response_dict
 
         # Add user API key metadata with prefixed keys
-        user_metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-        if user_metadata:
-            request_data["litellm_metadata"] = user_metadata
+        if "litellm_metadata" not in request_data:
+            user_metadata = self.transform_user_api_key_dict_to_metadata(
+                user_api_key_dict
+            )
+            if user_metadata:
+                request_data["litellm_metadata"] = user_metadata
 
         inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
 
@@ -213,6 +222,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+        request_data: Optional[dict] = None,
     ) -> List[Any]:
         """
         Process A2A streaming output by applying guardrails to accumulated text.
@@ -258,11 +268,19 @@
         if not combined_text:
             return responses_so_far
 
-        request_data: dict = {"responses_so_far": responses_so_far}
-        user_metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-        if user_metadata:
-            request_data["litellm_metadata"] = user_metadata
+        if request_data is None:
+            request_data = {"responses_so_far": responses_so_far}
+        else:
+            if "responses_so_far" not in request_data:
+                request_data["responses_so_far"] = responses_so_far
 
+        if "litellm_metadata" not in request_data:
+            user_metadata = self.transform_user_api_key_dict_to_metadata(
+                user_api_key_dict
+            )
+            if user_metadata:
+                request_data["litellm_metadata"] = user_metadata
+
         inputs = GenericGuardrailAPIInputs(texts=[combined_text])
         guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
             inputs=inputs,

litellm/llms/anthropic/chat/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/anthropic/chat/guardrail_translation/handler.py
+++ target/litellm/llms/anthropic/chat/guardrail_translation/handler.py
@@ -252,6 +252,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response by applying guardrails to text content and tool calls.
@@ -323,15 +324,21 @@
 
         # Step 2: Apply guardrail to all texts in batch
         if texts_to_check or tool_calls_to_check:
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"response": response}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"response": response}
+            else:
+                if "response" not in request_data:
+                    request_data["response"] = response
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:
@@ -375,6 +382,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> List[Any]:
         """
         Process output streaming response by applying guardrails to text content.
@@ -413,7 +421,7 @@
 
                 _guardrailed_inputs = await guardrail_to_apply.apply_guardrail(  # allow rejecting the response, if invalid
                     inputs=guardrail_inputs,
-                    request_data={},
+                    request_data=request_data if request_data is not None else {},
                     input_type="response",
                     logging_obj=litellm_logging_obj,
                 )
@@ -426,7 +434,7 @@
         string_so_far = self.get_streaming_string_so_far(responses_so_far)
         _guardrailed_inputs = await guardrail_to_apply.apply_guardrail(  # allow rejecting the response, if invalid
             inputs={"texts": [string_so_far]},
-            request_data={},
+            request_data=request_data if request_data is not None else {},
             input_type="response",
             logging_obj=litellm_logging_obj,
         )

litellm/llms/base_llm/guardrail_translation/base_translation.py (changed)

--- baseline/litellm/llms/base_llm/guardrail_translation/base_translation.py
+++ target/litellm/llms/base_llm/guardrail_translation/base_translation.py
@@ -73,6 +73,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response with guardrails.
@@ -91,6 +92,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output streaming response with guardrails.

litellm/llms/cohere/rerank/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/cohere/rerank/guardrail_translation/handler.py
+++ target/litellm/llms/cohere/rerank/guardrail_translation/handler.py
@@ -83,6 +83,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response - not applicable for rerank.

litellm/llms/mistral/ocr/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/mistral/ocr/guardrail_translation/handler.py
+++ target/litellm/llms/mistral/ocr/guardrail_translation/handler.py
@@ -91,6 +91,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process OCR output by applying guardrails to extracted page text.
@@ -127,14 +128,27 @@
         if model:
             inputs["model"] = model
 
+        # Use the real request_data if provided (proxy path), otherwise
+        # create a standalone dict (SDK / direct-call path).
+        if request_data is None:
+            request_data = {}
+
         # Add user metadata if available
         if user_api_key_dict is not None:
-            metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-            inputs.update(metadata)  # type: ignore
+            user_metadata = self.transform_user_api_key_dict_to_metadata(
+                user_api_key_dict
+            )
+            if user_metadata:
+                # Preserve original behavior: inject metadata into inputs for
+                # third-party guardrail providers that read it from there
+                inputs.update(user_metadata)  # type: ignore
+                # Also store in request_data for the logging pipeline
+                if "litellm_metadata" not in request_data:
+                    request_data["litellm_metadata"] = user_metadata
 
         guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
             inputs=inputs,
-            request_data={},
+            request_data=request_data,
             input_type="response",
             logging_obj=litellm_logging_obj,
         )

litellm/llms/openai/chat/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ target/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -86,9 +86,9 @@
             if tool_calls_to_check:
                 inputs["tool_calls"] = tool_calls_to_check  # type: ignore
             if messages:
-                inputs[
-                    "structured_messages"
-                ] = messages  # pass the openai /chat/completions messages to the guardrail, as-is
+                inputs["structured_messages"] = (
+                    messages  # pass the openai /chat/completions messages to the guardrail, as-is
+                )
             # Pass tools (function definitions) to the guardrail
             tools = data.get("tools")
             if tools:
@@ -260,6 +260,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response by applying guardrails to text content.
@@ -308,15 +309,21 @@
 
         # Step 2: Apply guardrail to all texts and tool calls in batch
         if texts_to_check or tool_calls_to_check:
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"response": response}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"response": response}
+            else:
+                if "response" not in request_data:
+                    request_data["response"] = response
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:
@@ -364,6 +371,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> List["ModelResponseStream"]:
         """
         Process output streaming responses by applying guardrails to text content.
@@ -402,6 +410,7 @@
                 guardrail_to_apply=guardrail_to_apply,
                 litellm_logging_obj=litellm_logging_obj,
                 user_api_key_dict=user_api_key_dict,
+                request_data=request_data,
             )
 
             return responses_so_far
@@ -436,15 +445,21 @@
 
         # Step 3: Apply guardrail to all combined texts in batch
         if texts_to_check:
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"responses": responses_so_far}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"responses": responses_so_far}
+            else:
+                if "responses" not in request_data:
+                    request_data["responses"] = responses_so_far
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:

litellm/llms/openai/completion/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/completion/guardrail_translation/handler.py
+++ target/litellm/llms/openai/completion/guardrail_translation/handler.py
@@ -125,6 +125,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response by applying guardrails to completion text.
@@ -155,15 +156,21 @@
 
         # Apply guardrails in batch
         if texts_to_check:
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"response": response}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"response": response}
+            else:
+                if "response" not in request_data:
+                    request_data["response"] = response
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
             # Include model information from the response if available

litellm/llms/openai/embeddings/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/embeddings/guardrail_translation/handler.py
+++ target/litellm/llms/openai/embeddings/guardrail_translation/handler.py
@@ -155,6 +155,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response - embeddings responses contain vectors, not text.

litellm/llms/openai/image_generation/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/image_generation/guardrail_translation/handler.py
+++ target/litellm/llms/openai/image_generation/guardrail_translation/handler.py
@@ -87,6 +87,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response - typically not needed for image generation.

litellm/llms/openai/responses/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ target/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -347,6 +347,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response by applying guardrails to text content and tool calls.
@@ -402,15 +403,21 @@
 
         # Step 2: Apply guardrail to all texts in batch
         if texts_to_check or tool_calls_to_check:
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"response": response}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"response": response}
+            else:
+                if "response" not in request_data:
+                    request_data["response"] = response
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:
@@ -454,6 +461,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> List[Any]:
         """
         Process output streaming response by applying guardrails to text content.
@@ -481,7 +489,7 @@
                     inputs["model"] = model_response_stream.model
                 _guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
                     inputs=inputs,
-                    request_data={},
+                    request_data=request_data if request_data is not None else {},
                     input_type="response",
                     logging_obj=litellm_logging_obj,
                 )
@@ -512,7 +520,7 @@
                 if tool_calls or text:
                     _guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
                         inputs=guardrail_inputs,
-                        request_data={},
+                        request_data=request_data if request_data is not None else {},
                         input_type="response",
                         logging_obj=litellm_logging_obj,
                     )
@@ -537,7 +545,7 @@
                 inputs["model"] = response_model
         _guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
             inputs=inputs,
-            request_data={},
+            request_data=request_data if request_data is not None else {},
             input_type="response",
             logging_obj=litellm_logging_obj,
         )

litellm/llms/openai/speech/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/speech/guardrail_translation/handler.py
+++ target/litellm/llms/openai/speech/guardrail_translation/handler.py
@@ -85,6 +85,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output - not applicable for text-to-speech.

litellm/llms/openai/transcriptions/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/openai/transcriptions/guardrail_translation/handler.py
+++ target/litellm/llms/openai/transcriptions/guardrail_translation/handler.py
@@ -58,6 +58,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output transcription by applying guardrails to transcribed text.
@@ -79,15 +80,21 @@
 
         if isinstance(response.text, str):
             original_text = response.text
-            # Create a request_data dict with response info and user API key metadata
-            request_data: dict = {"response": response}
+            # Use the real request_data if provided (proxy path), otherwise
+            # create a standalone dict (SDK / direct-call path).
+            if request_data is None:
+                request_data = {"response": response}
+            else:
+                if "response" not in request_data:
+                    request_data["response"] = response
 
             # Add user API key metadata with prefixed keys
-            user_metadata = self.transform_user_api_key_dict_to_metadata(
-                user_api_key_dict
-            )
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+            if "litellm_metadata" not in request_data:
+                user_metadata = self.transform_user_api_key_dict_to_metadata(
+                    user_api_key_dict
+                )
+                if user_metadata:
+                    request_data["litellm_metadata"] = user_metadata
 
             inputs = GenericGuardrailAPIInputs(texts=[original_text])
             # Include model information from the response if available

litellm/llms/pass_through/guardrail_translation/handler.py (changed)

--- baseline/litellm/llms/pass_through/guardrail_translation/handler.py
+++ target/litellm/llms/pass_through/guardrail_translation/handler.py
@@ -139,6 +139,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         """
         Process output response by applying guardrails to targeted fields.
@@ -171,17 +172,27 @@
         if not text_to_check:
             return response
 
-        # Create a request_data dict with response info and user API key metadata
-        request_data: dict = (
-            {"response": response}
-            if not isinstance(response, dict)
-            else response.copy()
-        )
+        # Use the real request_data if provided (proxy path), otherwise
+        # create a standalone dict (SDK / direct-call path).
+        if request_data is None:
+            request_data = (
+                {"response": response}
+                if not isinstance(response, dict)
+                else response.copy()
+            )
+        else:
+            if "response" not in request_data:
+                request_data["response"] = (
+                    response if not isinstance(response, dict) else response.copy()
+                )
 
         # Add user API key metadata with prefixed keys
-        user_metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-        if user_metadata:
-            request_data["litellm_metadata"] = user_metadata
+        if "litellm_metadata" not in request_data:
+            user_metadata = self.transform_user_api_key_dict_to_metadata(
+                user_api_key_dict
+            )
+            if user_metadata:
+                request_data["litellm_metadata"] = user_metadata
 
         # Apply guardrail (pass-through doesn't modify the text, just checks it)
         inputs = GenericGuardrailAPIInputs(texts=[text_to_check])

litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py (changed)

--- baseline/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
+++ target/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
@@ -92,6 +92,7 @@
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional[Any] = None,
         user_api_key_dict: Optional[Any] = None,
+        request_data: Optional[dict] = None,
     ) -> Any:
         verbose_proxy_logger.debug(
             "MCP Guardrail: Output processing not implemented for MCP tools",

litellm/proxy/_experimental/out/404.html (removed)

--- baseline/litellm/proxy/_experimental/out/404.html
+++ /dev/null
@@ -1 +0,0 @@
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