release: 0.4.1

.devcontainer/Dockerfile

@@ -3,7 +3,7 @@ FROM mcr.microsoft.com/vscode/devcontainers/python:0-${VARIANT}
 
 USER vscode
 
-RUN curl -sSf https://rye-up.com/get | RYE_VERSION="0.15.2" RYE_INSTALL_OPTION="--yes" bash
+RUN curl -sSf https://rye-up.com/get | RYE_VERSION="0.24.0" RYE_INSTALL_OPTION="--yes" bash
 ENV PATH=/home/vscode/.rye/shims:$PATH
 
 RUN echo "[[ -d .venv ]] && source .venv/bin/activate" >> /home/vscode/.bashrc

.github/workflows/ci.yml

@@ -21,7 +21,7 @@ jobs:
           curl -sSf https://rye-up.com/get | bash
           echo "$HOME/.rye/shims" >> $GITHUB_PATH
         env:
-          RYE_VERSION: 0.15.2
+          RYE_VERSION: 0.24.0
           RYE_INSTALL_OPTION: "--yes"
 
       - name: Install dependencies

.github/workflows/publish-pypi.yml

@@ -21,7 +21,7 @@ jobs:
           curl -sSf https://rye-up.com/get | bash
           echo "$HOME/.rye/shims" >> $GITHUB_PATH
         env:
-          RYE_VERSION: 0.15.2
+          RYE_VERSION: 0.24.0
           RYE_INSTALL_OPTION: "--yes"
 
       - name: Publish to PyPI

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-  ".": "0.4.0"
+  ".": "0.4.1"
 }

CHANGELOG.md

@@ -1,21 +1,27 @@
 # Changelog
 
-## 0.4.0 (2024-02-15)
+## 0.4.1 (2024-02-21)
 
-Full Changelog: [v0.1.0...v0.4.0](https://github.com/groq/groq-python/compare/v0.1.0...v0.4.0)
+Full Changelog: [v0.1.0...v0.4.1](https://github.com/groq/groq-python/compare/v0.1.0...v0.4.1)
 
 ### Features
 
+* Add initial Stainless SDK ([4de80db](https://github.com/groq/groq-python/commit/4de80dbe4c27d6ecbcc2d2b6192d27ade5da3866))
 * Add initial Stainless SDK ([d5a8512](https://github.com/groq/groq-python/commit/d5a851262e04e625dde130367ed91d8f95683599))
 * Add initial Stainless SDK ([316de2c](https://github.com/groq/groq-python/commit/316de2ccfeb76e36fe34bb8656ea90a8d42a7d00))
 * create default branch ([7e00266](https://github.com/groq/groq-python/commit/7e00266e3c691d92d508e753e2c14c03297c09f9))
+* update via SDK Studio ([#10](https://github.com/groq/groq-python/issues/10)) ([0c0d204](https://github.com/groq/groq-python/commit/0c0d20405a96167f060a03a2b8a58a49d9a1c7c8))
+* update via SDK Studio ([#14](https://github.com/groq/groq-python/issues/14)) ([153744e](https://github.com/groq/groq-python/commit/153744e8ca331900adb0bd88a688afedf9a4bf00))
 * update via SDK Studio ([#3](https://github.com/groq/groq-python/issues/3)) ([8d92c08](https://github.com/groq/groq-python/commit/8d92c086e320c2715e02bc79807ff872e84c0b0f))
 
 
 ### Chores
 
 * go live ([#2](https://github.com/groq/groq-python/issues/2)) ([ba81c42](https://github.com/groq/groq-python/commit/ba81c42d6d0fd6d47819e0d58962235cb70ca4f1))
+* go live ([#5](https://github.com/groq/groq-python/issues/5)) ([75ea081](https://github.com/groq/groq-python/commit/75ea081a84bbcf15702dcb53fd6411c8de497c83))
 * go live ([#5](https://github.com/groq/groq-python/issues/5)) ([af9a838](https://github.com/groq/groq-python/commit/af9a838e240bb0f7385bc33fb18ce246427ca2f7))
+* update branch ([#12](https://github.com/groq/groq-python/issues/12)) ([28f34e1](https://github.com/groq/groq-python/commit/28f34e1cc08b974d31744fd94bf31eafc9e6e867))
+* update branch ([#8](https://github.com/groq/groq-python/issues/8)) ([b9b55b4](https://github.com/groq/groq-python/commit/b9b55b41cb158efd155f9cda829808c877493afd))
 
 ## 0.1.0 (2024-02-10)
 

examples/chat_completion.py

@@ -10,43 +10,33 @@
         # Set an optional system message. This sets the behavior of the
         # assistant and can be used to provide specific instructions for
         # how it should behave throughout the conversation.
-        {
-            "role": "system",
-            "content": "you are a helpful assistant."
-        },
+        {"role": "system", "content": "you are a helpful assistant."},
         # Set a user message for the assistant to respond to.
         {
             "role": "user",
             "content": "Explain the importance of low latency LLMs",
         },
     ],
-
     # The language model which will generate the completion.
     model="mixtral-8x7b-32768",
-
     #
     # Optional parameters
     #
-
     # Controls randomness: lowering results in less random completions.
     # As the temperature approaches zero, the model will become deterministic
     # and repetitive.
     temperature=0.5,
-
     # The maximum number of tokens to generate. Requests can use up to
     # 2048 tokens shared between prompt and completion.
     max_tokens=1024,
-
     # Controls diversity via nucleus sampling: 0.5 means half of all
     # likelihood-weighted options are considered.
     top_p=1,
-
     # A stop sequence is a predefined or user-specified text string that
     # signals an AI to stop generating content, ensuring its responses
     # remain focused and concise. Examples include punctuation marks and
     # markers like "[end]".
     stop=None,
-
     # If set, partial message deltas will be sent.
     stream=False,
 )

examples/chat_completion_async.py

@@ -14,43 +14,33 @@ async def main() -> None:
             # Set an optional system message. This sets the behavior of the
             # assistant and can be used to provide specific instructions for
             # how it should behave throughout the conversation.
-            {
-                "role": "system",
-                "content": "you are a helpful assistant."
-            },
+            {"role": "system", "content": "you are a helpful assistant."},
             # Set a user message for the assistant to respond to.
             {
                 "role": "user",
                 "content": "Explain the importance of low latency LLMs",
             },
         ],
-
         # The language model which will generate the completion.
         model="mixtral-8x7b-32768",
-
         #
         # Optional parameters
         #
-
         # Controls randomness: lowering results in less random completions.
         # As the temperature approaches zero, the model will become
         # deterministic and repetitive.
         temperature=0.5,
-
         # The maximum number of tokens to generate. Requests can use up to
         # 2048 tokens shared between prompt and completion.
         max_tokens=1024,
-
         # Controls diversity via nucleus sampling: 0.5 means half of all
         # likelihood-weighted options are considered.
         top_p=1,
-
         # A stop sequence is a predefined or user-specified text string that
         # signals an AI to stop generating content, ensuring its responses
         # remain focused and concise. Examples include punctuation marks and
         # markers like "[end]".
         stop=None,
-
         # If set, partial message deltas will be sent.
         stream=False,
     )

examples/chat_completion_async_streaming.py

@@ -14,39 +14,30 @@ async def main() -> None:
             # Set an optional system message. This sets the behavior of the
             # assistant and can be used to provide specific instructions for
             # how it should behave throughout the conversation.
-            {
-                "role": "system",
-                "content": "you are a helpful assistant."
-            },
+            {"role": "system", "content": "you are a helpful assistant."},
             # Set a user message for the assistant to respond to.
             {
                 "role": "user",
                 "content": "Explain the importance of low latency LLMs",
             },
         ],
-
         # The language model which will generate the completion.
         model="mixtral-8x7b-32768",
-
         #
         # Optional parameters
         #
-
         # Controls randomness: lowering results in less random completions.
         # As the temperature approaches zero, the model will become
         # deterministic and repetitive.
         temperature=0.5,
-
         # The maximum number of tokens to generate. Requests can use up to
         # 2048 tokens shared between prompt and completion.
         max_tokens=1024,
-
         # A stop sequence is a predefined or user-specified text string that
         # signals an AI to stop generating content, ensuring its responses
         # remain focused and concise. Examples include punctuation marks and
         # markers like "[end]".
         stop=None,
-
         # Controls diversity via nucleus sampling: 0.5 means half of all
         # likelihood-weighted options are considered.
         stream=True,

examples/chat_completion_stop.py

@@ -10,37 +10,28 @@
         # Set an optional system message. This sets the behavior of the
         # assistant and can be used to provide specific instructions for
         # how it should behave throughout the conversation.
-        {
-            "role": "system",
-            "content": "you are a helpful assistant."
-        },
+        {"role": "system", "content": "you are a helpful assistant."},
         # Set a user message for the assistant to respond to.
         {
             "role": "user",
-            "content": "Count to 10.  Your response must begin with \"1, \".  example: 1, 2, 3, ...",
+            "content": 'Count to 10.  Your response must begin with "1, ".  example: 1, 2, 3, ...',
         },
     ],
-
     # The language model which will generate the completion.
     model="mixtral-8x7b-32768",
-
     #
     # Optional parameters
     #
-
     # Controls randomness: lowering results in less random completions.
     # As the temperature approaches zero, the model will become deterministic
     # and repetitive.
     temperature=0.5,
-
     # The maximum number of tokens to generate. Requests can use up to
     # 2048 tokens shared between prompt and completion.
     max_tokens=1024,
-
     # Controls diversity via nucleus sampling: 0.5 means half of all
     # likelihood-weighted options are considered.
     top_p=1,
-
     # A stop sequence is a predefined or user-specified text string that
     # signals an AI to stop generating content, ensuring its responses
     # remain focused and concise. Examples include punctuation marks and
@@ -49,7 +40,6 @@
     # If multiple stop values are needed, an array of string may be passed,
     # stop=[", 6", ", six", ", Six"]
     stop=", 6",
-
     # If set, partial message deltas will be sent.
     stream=False,
 )

examples/chat_completion_streaming.py

@@ -10,43 +10,33 @@
         # Set an optional system message. This sets the behavior of the
         # assistant and can be used to provide specific instructions for
         # how it should behave throughout the conversation.
-        {
-            "role": "system",
-            "content": "you are a helpful assistant."
-        },
+        {"role": "system", "content": "you are a helpful assistant."},
         # Set a user message for the assistant to respond to.
         {
             "role": "user",
             "content": "Explain the importance of low latency LLMs",
         },
     ],
-
     # The language model which will generate the completion.
     model="mixtral-8x7b-32768",
-
     #
     # Optional parameters
     #
-
     # Controls randomness: lowering results in less random completions.
     # As the temperature approaches zero, the model will become deterministic
     # and repetitive.
     temperature=0.5,
-
     # The maximum number of tokens to generate. Requests can use up to
     # 2048 tokens shared between prompt and completion.
     max_tokens=1024,
-
     # Controls diversity via nucleus sampling: 0.5 means half of all
     # likelihood-weighted options are considered.
     top_p=1,
-
     # A stop sequence is a predefined or user-specified text string that
     # signals an AI to stop generating content, ensuring its responses
     # remain focused and concise. Examples include punctuation marks and
     # markers like "[end]".
     stop=None,
-
     # If set, partial message deltas will be sent.
     stream=True,
 )

pyproject.toml

@@ -1,11 +1,11 @@
 [project]
 name = "groq"
-version = "0.4.0"
+version = "0.4.1"
 description = "The official Python library for the groq API"
 readme = "README.md"
 license = "Apache-2.0"
 authors = [
-{ name = "Groq", email = "grea@groq.com" },
+{ name = "Groq", email = "support@groq.com" },
 ]
 dependencies = [
     "httpx>=0.23.0, <1",

requirements-dev.lock

@@ -5,48 +5,92 @@
 #   pre: false
 #   features: []
 #   all-features: true
+#   with-sources: false
 
 -e file:.
 annotated-types==0.6.0
+    # via pydantic
 anyio==4.1.0
+    # via groq
+    # via httpx
 argcomplete==3.1.2
+    # via nox
 attrs==23.1.0
+    # via pytest
 certifi==2023.7.22
+    # via httpcore
+    # via httpx
 colorlog==6.7.0
+    # via nox
 dirty-equals==0.6.0
 distlib==0.3.7
+    # via virtualenv
 distro==1.8.0
+    # via groq
 exceptiongroup==1.1.3
+    # via anyio
 filelock==3.12.4
+    # via virtualenv
 h11==0.14.0
+    # via httpcore
 httpcore==1.0.2
+    # via httpx
 httpx==0.25.2
+    # via groq
+    # via respx
 idna==3.4
+    # via anyio
+    # via httpx
 importlib-metadata==7.0.0
 iniconfig==2.0.0
+    # via pytest
 mypy==1.7.1
 mypy-extensions==1.0.0
+    # via mypy
 nodeenv==1.8.0
+    # via pyright
 nox==2023.4.22
 packaging==23.2
+    # via nox
+    # via pytest
 platformdirs==3.11.0
+    # via virtualenv
 pluggy==1.3.0
+    # via pytest
 py==1.11.0
+    # via pytest
 pydantic==2.4.2
+    # via groq
 pydantic-core==2.10.1
+    # via pydantic
 pyright==1.1.332
 pytest==7.1.1
+    # via pytest-asyncio
 pytest-asyncio==0.21.1
 python-dateutil==2.8.2
+    # via time-machine
 pytz==2023.3.post1
+    # via dirty-equals
 respx==0.20.2
 ruff==0.1.9
+setuptools==68.2.2
+    # via nodeenv
 six==1.16.0
+    # via python-dateutil
 sniffio==1.3.0
+    # via anyio
+    # via groq
+    # via httpx
 time-machine==2.9.0
 tomli==2.0.1
+    # via mypy
+    # via pytest
 typing-extensions==4.8.0
+    # via groq
+    # via mypy
+    # via pydantic
+    # via pydantic-core
 virtualenv==20.24.5
+    # via nox
 zipp==3.17.0
-# The following packages are considered to be unsafe in a requirements file:
-setuptools==68.2.2
+    # via importlib-metadata