Merge remote-tracking branch 'upstream/main' into fix-pip-install-extra-proxy

docs/my-website/docs/routing.md

@@ -442,6 +442,8 @@ If a call fails after num_retries, fall back to another model group.
 
 If the error is a context window exceeded error, fall back to a larger model group (if given). 
 
+Fallbacks are done in-order - ["gpt-3.5-turbo, "gpt-4", "gpt-4-32k"], will do 'gpt-3.5-turbo' first, then 'gpt-4', etc.
+
 ```python
 from litellm import Router
 

docs/my-website/docs/tutorials/instructor.md

@@ -0,0 +1,95 @@
+# Instructor - Function Calling
+
+Use LiteLLM Router with [jxnl's instructor library](https://github.com/jxnl/instructor) for function calling in prod. 
+
+## Usage
+
+```python
+import litellm
+from litellm import Router
+import instructor
+from pydantic import BaseModel
+
+litellm.set_verbose = True # 👈 print DEBUG LOGS
+
+client = instructor.patch(
+    Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",  openai model name
+                "litellm_params": {  params for litellm completion/embedding call
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": os.getenv("AZURE_API_KEY"),
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ]
+    )
+)
+
+
+class UserDetail(BaseModel):
+    name: str
+    age: int
+
+
+user = client.chat.completions.create(
+    model="gpt-3.5-turbo",
+    response_model=UserDetail,
+    messages=[
+        {"role": "user", "content": "Extract Jason is 25 years old"},
+    ],
+)
+
+assert isinstance(user, UserDetail)
+assert user.name == "Jason"
+assert user.age == 25
+
+print(f"user: {user}")
+```
+
+## Async Calls
+
+```python
+import litellm
+from litellm import Router
+import instructor, asyncio
+from pydantic import BaseModel
+
+aclient = instructor.apatch(
+    Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {
+                    "model": "azure/chatgpt-v-2",
+                    "api_key": os.getenv("AZURE_API_KEY"),
+                    "api_version": os.getenv("AZURE_API_VERSION"),
+                    "api_base": os.getenv("AZURE_API_BASE"),
+                },
+            }
+        ],
+        default_litellm_params={"acompletion": True}, # 👈 IMPORTANT - tells litellm to route to async completion function.
+    )
+)
+
+
+class UserExtract(BaseModel):
+    name: str
+    age: int
+
+
+async def main():
+    model = await aclient.chat.completions.create(
+        model="gpt-3.5-turbo",
+        response_model=UserExtract,
+        messages=[
+            {"role": "user", "content": "Extract jason is 25 years old"},
+        ],
+    )
+    print(f"model: {model}")
+
+
+asyncio.run(main())
+```

docs/my-website/sidebars.js

@@ -188,6 +188,7 @@ const sidebars = {
       label: 'Tutorials',
       items: [
         'tutorials/azure_openai',
+        'tutorials/instructor',
         'tutorials/oobabooga',
         "tutorials/gradio_integration",
         'tutorials/huggingface_codellama',

litellm/main.py

@@ -116,24 +116,54 @@ class LiteLLM:
         default_headers: Optional[Mapping[str, str]] = None,
     ):
         self.params = locals()
-        self.chat = Chat(self.params)
+        self.chat = Chat(self.params, router_obj=None)
 
 
 class Chat:
-    def __init__(self, params):
+    def __init__(self, params, router_obj: Optional[Any]):
         self.params = params
-        self.completions = Completions(self.params)
+        if self.params.get("acompletion", False) == True:
+            self.params.pop("acompletion")
+            self.completions: Union[AsyncCompletions, Completions] = AsyncCompletions(
+                self.params, router_obj=router_obj
+            )
+        else:
+            self.completions = Completions(self.params, router_obj=router_obj)
 
 
 class Completions:
-    def __init__(self, params):
+    def __init__(self, params, router_obj: Optional[Any]):
         self.params = params
+        self.router_obj = router_obj
 
     def create(self, messages, model=None, **kwargs):
         for k, v in kwargs.items():
             self.params[k] = v
         model = model or self.params.get("model")
-        response = completion(model=model, messages=messages, **self.params)
+        if self.router_obj is not None:
+            response = self.router_obj.completion(
+                model=model, messages=messages, **self.params
+            )
+        else:
+            response = completion(model=model, messages=messages, **self.params)
+        return response
+
+
+class AsyncCompletions:
+    def __init__(self, params, router_obj: Optional[Any]):
+        self.params = params
+        self.router_obj = router_obj
+
+    async def create(self, messages, model=None, **kwargs):
+        for k, v in kwargs.items():
+            self.params[k] = v
+        model = model or self.params.get("model")
+        if self.router_obj is not None:
+            response = await self.router_obj.acompletion(
+                model=model, messages=messages, **self.params
+            )
+        else:
+            response = await acompletion(model=model, messages=messages, **self.params)
         return response
 
 

litellm/router.py

@@ -230,7 +230,7 @@ class Router:
         )  # dict to store aliases for router, ex. {"gpt-4": "gpt-3.5-turbo"}, all requests with gpt-4 -> get routed to gpt-3.5-turbo group
 
         # make Router.chat.completions.create compatible for openai.chat.completions.create
-        self.chat = litellm.Chat(params=default_litellm_params)
+        self.chat = litellm.Chat(params=default_litellm_params, router_obj=self)
 
         # default litellm args
         self.default_litellm_params = default_litellm_params

litellm/tests/test_class.py

@@ -4,6 +4,7 @@
 # import sys, os
 # import traceback
 # import pytest
+
 # sys.path.insert(
 #     0, os.path.abspath("../..")
 # )  # Adds the parent directory to the system path
@@ -16,51 +17,68 @@
 # from pydantic import BaseModel
 
 # # This enables response_model keyword
-# # # from client.chat.completions.create
+# # from client.chat.completions.create
-# # client = instructor.patch(Router(model_list=[{
+# client = instructor.patch(
-# #     "model_name": "gpt-3.5-turbo", # openai model name
+#     Router(
-# #     "litellm_params": { # params for litellm completion/embedding call
+#         model_list=[
-# #         "model": "azure/chatgpt-v-2",
+#             {
-# #         "api_key": os.getenv("AZURE_API_KEY"),
+#                 "model_name": "gpt-3.5-turbo",  # openai model name
-# #         "api_version": os.getenv("AZURE_API_VERSION"),
+#                 "litellm_params": {  # params for litellm completion/embedding call
-# #         "api_base": os.getenv("AZURE_API_BASE")
+#                     "model": "azure/chatgpt-v-2",
-# #     }
+#                     "api_key": os.getenv("AZURE_API_KEY"),
-# # }]))
+#                     "api_version": os.getenv("AZURE_API_VERSION"),
+#                     "api_base": os.getenv("AZURE_API_BASE"),
+#                 },
+#             }
+#         ]
+#     )
+# )
 
-# # class UserDetail(BaseModel):
-# #     name: str
-# #     age: int
 
-# # user = client.chat.completions.create(
+# class UserDetail(BaseModel):
-# #     model="gpt-3.5-turbo",
+#     name: str
-# #     response_model=UserDetail,
+#     age: int
-# #     messages=[
-# #         {"role": "user", "content": "Extract Jason is 25 years old"},
-# #     ]
-# # )
-# # assert isinstance(model, UserExtract)
 
-# # assert isinstance(user, UserDetail)
-# # assert user.name == "Jason"
-# # assert user.age == 25
 
-# # print(f"user: {user}")
+# user = client.chat.completions.create(
-# import instructor
+#     model="gpt-3.5-turbo",
-# from openai import AsyncOpenAI
+#     response_model=UserDetail,
+#     messages=[
+#         {"role": "user", "content": "Extract Jason is 25 years old"},
+#     ],
+# )
+
+# assert isinstance(user, UserDetail)
+# assert user.name == "Jason"
+# assert user.age == 25
+
+# print(f"user: {user}")
+# # import instructor
+# # from openai import AsyncOpenAI
+
+# aclient = instructor.apatch(
+#     Router(
+#         model_list=[
+#             {
+#                 "model_name": "gpt-3.5-turbo",  # openai model name
+#                 "litellm_params": {  # params for litellm completion/embedding call
+#                     "model": "azure/chatgpt-v-2",
+#                     "api_key": os.getenv("AZURE_API_KEY"),
+#                     "api_version": os.getenv("AZURE_API_VERSION"),
+#                     "api_base": os.getenv("AZURE_API_BASE"),
+#                 },
+#             }
+#         ],
+#         default_litellm_params={"acompletion": True},
+#     )
+# )
 
-# aclient = instructor.apatch(Router(model_list=[{
-#     "model_name": "gpt-3.5-turbo", # openai model name
-#     "litellm_params": { # params for litellm completion/embedding call
-#         "model": "azure/chatgpt-v-2",
-#         "api_key": os.getenv("AZURE_API_KEY"),
-#         "api_version": os.getenv("AZURE_API_VERSION"),
-#         "api_base": os.getenv("AZURE_API_BASE")
-#     }
-# }], default_litellm_params={"acompletion": True}))
 
 # class UserExtract(BaseModel):
 #     name: str
 #     age: int
+
+
 # async def main():
 #     model = await aclient.chat.completions.create(
 #         model="gpt-3.5-turbo",
@@ -71,4 +89,5 @@
 #     )
 #     print(f"model: {model}")
 
+
 # asyncio.run(main())

litellm/utils.py

@@ -1465,6 +1465,7 @@ class Logging:
                             self.langfuse_public_key != langFuseLogger.public_key
                             and self.langfuse_secret != langFuseLogger.secret_key
                         ):
+                            print_verbose("Instantiates langfuse client")
                             langFuseLogger = LangFuseLogger(
                                 langfuse_public_key=self.langfuse_public_key,
                                 langfuse_secret=self.langfuse_secret,

poetry.lock

@@ -553,47 +553,56 @@ files = [
 
 [[package]]
 name = "cryptography"
-version = "41.0.3"
+version = "42.0.5"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = true
 python-versions = ">=3.7"
 files = [
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+    {file = "cryptography-42.0.5-cp37-abi3-macosx_10_12_universal2.whl", hash = "sha256:a30596bae9403a342c978fb47d9b0ee277699fa53bbafad14706af51fe543d16"},
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+    {file = "cryptography-42.0.5-cp37-abi3-macosx_10_12_x86_64.whl", hash = "sha256:b7ffe927ee6531c78f81aa17e684e2ff617daeba7f189f911065b2ea2d526dec"},
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+    {file = "cryptography-42.0.5-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:cd65d75953847815962c84a4654a84850b2bb4aed3f26fadcc1c13892e1e29f6"},
+    {file = "cryptography-42.0.5-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:e807b3188f9eb0eaa7bbb579b462c5ace579f1cedb28107ce8b48a9f7ad3679e"},
+    {file = "cryptography-42.0.5-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:f12764b8fffc7a123f641d7d049d382b73f96a34117e0b637b80643169cec8ac"},
+    {file = "cryptography-42.0.5-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:37dd623507659e08be98eec89323469e8c7b4c1407c85112634ae3dbdb926fdd"},
+    {file = "cryptography-42.0.5.tar.gz", hash = "sha256:6fe07eec95dfd477eb9530aef5bead34fec819b3aaf6c5bd6d20565da607bfe1"},
 ]
 
 [package.dependencies]
-cffi = ">=1.12"
+cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
 
 [package.extras]
 docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
-docstest = ["pyenchant (>=1.6.11)", "sphinxcontrib-spelling (>=4.0.1)", "twine (>=1.12.0)"]
+docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
 nox = ["nox"]
-pep8test = ["black", "check-sdist", "mypy", "ruff"]
+pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -1931,17 +1940,17 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "python-multipart"
-version = "0.0.6"
+version = "0.0.9"
 description = "A streaming multipart parser for Python"
 optional = true
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "python_multipart-0.0.6-py3-none-any.whl", hash = "sha256:ee698bab5ef148b0a760751c261902cd096e57e10558e11aca17646b74ee1c18"},
+    {file = "python_multipart-0.0.9-py3-none-any.whl", hash = "sha256:97ca7b8ea7b05f977dc3849c3ba99d51689822fab725c3703af7c866a0c2b215"},
-    {file = "python_multipart-0.0.6.tar.gz", hash = "sha256:e9925a80bb668529f1b67c7fdb0a5dacdd7cbfc6fb0bff3ea443fe22bdd62132"},
+    {file = "python_multipart-0.0.9.tar.gz", hash = "sha256:03f54688c663f1b7977105f021043b0793151e4cb1c1a9d4a11fc13d622c4026"},
 ]
 
 [package.extras]
-dev = ["atomicwrites (==1.2.1)", "attrs (==19.2.0)", "coverage (==6.5.0)", "hatch", "invoke (==1.7.3)", "more-itertools (==4.3.0)", "pbr (==4.3.0)", "pluggy (==1.0.0)", "py (==1.11.0)", "pytest (==7.2.0)", "pytest-cov (==4.0.0)", "pytest-timeout (==2.1.0)", "pyyaml (==5.1)"]
+dev = ["atomicwrites (==1.4.1)", "attrs (==23.2.0)", "coverage (==7.4.1)", "hatch", "invoke (==2.2.0)", "more-itertools (==10.2.0)", "pbr (==6.0.0)", "pluggy (==1.4.0)", "py (==1.11.0)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-timeout (==2.2.0)", "pyyaml (==6.0.1)", "ruff (==0.2.1)"]
 
 [[package]]
 name = "pytz"
@@ -2698,4 +2707,4 @@ proxy = ["PyJWT", "apscheduler", "backoff", "cryptography", "fastapi", "fastapi-
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0, !=3.9.7"
-content-hash = "ac9ee16ff19c4126f36d7327447566c4681bc08b814f897e9ac3bb98f374071e"
+content-hash = "d511820d41457e61cbad0bbda2f3c1210a49b2b440e794942d8e2c2c7895d3c0"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "1.34.0"
+version = "1.34.1"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT"
@@ -33,8 +33,8 @@ orjson = {version = "^3.9.7", optional = true}
 apscheduler = {version = "^3.10.4", optional = true}
 fastapi-sso = { version = "^0.10.0", optional = true }
 PyJWT = { version = "^2.8.0", optional = true }
-python-multipart = { version = "^0.0.6", optional = true }
+python-multipart = { version = "^0.0.9", optional = true}
-cryptography = { version = "41.0.3", optional = true }
+cryptography = {version = "^42.0.5", optional = true}
 prisma = {version = "0.11.0", optional = true}
 azure-identity = {version = "^1.15.0", optional = true}
 azure-keyvault-secrets = {version = "^4.8.0", optional = true}
@@ -80,7 +80,7 @@ requires = ["poetry-core", "wheel"]
 build-backend = "poetry.core.masonry.api"
 
 [tool.commitizen]
-version = "1.34.0"
+version = "1.34.1"
 version_files = [
     "pyproject.toml:^version"
 ]

requirements.txt

@@ -23,7 +23,7 @@ orjson==3.9.15 # fast /embedding responses
 apscheduler==3.10.4 # for resetting budget in background 
 fastapi-sso==0.10.0 # admin UI, SSO
 pyjwt[crypto]==2.8.0
-python-multipart==0.0.6 # admin UI
+python-multipart==0.0.9 # admin UI
 ### LITELLM PACKAGE DEPENDENCIES
 python-dotenv>=0.2.0 # for env 
 tiktoken>=0.4.0 # for calculating usage