Linters, code auto-formatting and testing improvements

.devcontainer/devcontainer.json

@@ -23,9 +23,8 @@
         "[python]": {
           "editor.defaultFormatter": "ms-python.black-formatter"
         },
+        // TODO(dmu) HIGH: Make linter configuration consistent with .pre-commit-config.yaml
         "ruff.args": [
-          "--exclude",
-          "migrations",
           "--ignore",
           "E501,E711,E712",
           "--fix",

.github/workflows/integration-tests.yml

@@ -26,5 +26,4 @@ jobs:
           python -m pip install behave langchain openai
           if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
       - name: Run Integration Tests
-        run: |
-          behave
+        run: behave

.github/workflows/release.yml

@@ -16,10 +16,13 @@ jobs:
         uses: actions/setup-python@v5
         with:
           python-version: "3.8"
+
       - name: Install poetry
         run: pipx install poetry
+
       - name: Running poetry install
         run: poetry install
+
       - name: Build and publish
         env:
           POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_PASSWORD }}

.pre-commit-config.yaml

@@ -1,20 +1,15 @@
 repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: end-of-file-fixer
+        exclude: (app/utils/evaluate/(javascript_code_wrapper|python_code_wrapper)\.txt|langchain_prompts\.txt)
+      - id: trailing-whitespace
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.0.290
+    rev: v0.9.4
     hooks:
       - id: ruff
-        args:
-          [--exclude, features, --ignore, "E501", --fix, --exit-non-zero-on-fix]
-
-  - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 23.9.1
-    hooks:
-      - id: black
-        args: [--force-exclude, features]
-
-  - repo: https://github.com/pycqa/isort
-    rev: 5.12.0
-    hooks:
-      - id: isort
-        name: isort (python)
-        args: [--profile, black, --skip, features, --filter-files]
+        name: 'ruff: fix imports'
+        args: ["--select", "I", "--fix"]
+      - id: ruff
+      - id: ruff-format

Makefile

@@ -1,7 +1,13 @@
+RUN_TEST := test -f .env && set -a; . ./.env; set +a; poetry run pytest
+
 .PHONY: lint
 lint:
 	poetry run pre-commit run --all-files
 
 .PHONY: test
 test:
-	poetry run pytest
+	${RUN_TEST}
+
+.PHONY: test-sw
+test-sw:
+	${RUN_TEST} -vv --sw --show-capture=no

README.md

@@ -8,11 +8,11 @@
 <a href="https://docs.promptlayer.com"><img alt="Docs" src="https://custom-icon-badges.herokuapp.com/badge/docs-PL-green.svg?logo=cake&style=for-the-badge"></a>
 <a href="https://www.loom.com/share/196c42e43acd4a369d75e9a7374a0850"><img alt="Demo with Loom" src="https://img.shields.io/badge/Demo-loom-552586.svg?logo=loom&style=for-the-badge&labelColor=gray"></a>
 
----  
+---
 
 <div align="left">
 
-[PromptLayer](https://promptlayer.com/) is the first platform that allows you to track, manage, and share your GPT prompt engineering. PromptLayer acts a middleware between your code and OpenAI’s python library. 
+[PromptLayer](https://promptlayer.com/) is the first platform that allows you to track, manage, and share your GPT prompt engineering. PromptLayer acts a middleware between your code and OpenAI’s python library.
 
 PromptLayer records all your OpenAI API requests, allowing you to search and explore request history in the PromptLayer dashboard.
 
@@ -53,14 +53,14 @@ openai = promptlayer.openai
 
 ### Adding PromptLayer tags: `pl_tags`
 
-PromptLayer allows you to add tags through the `pl_tags` argument. This allows you to track and group requests in the dashboard. 
+PromptLayer allows you to add tags through the `pl_tags` argument. This allows you to track and group requests in the dashboard.
 
 *Tags are not required but we recommend them!*
 
 ```python
 openai.Completion.create(
-  engine="text-ada-001", 
-  prompt="My name is", 
+  engine="text-ada-001",
+  prompt="My name is",
   pl_tags=["name-guessing", "pipeline-2"]
 )
 ```
@@ -69,7 +69,7 @@ After making your first few requests, you should be able to see them in the Prom
 
 ## Using the REST API
 
-This Python library is a wrapper over PromptLayer's REST API. If you use another language, like Javascript, just interact directly with the API. 
+This Python library is a wrapper over PromptLayer's REST API. If you use another language, like Javascript, just interact directly with the API.
 
 Here is an example request below:
 

promptlayer/promptlayer_base.py

@@ -51,7 +51,7 @@ def __getattr__(self, name):
         ):
             return PromptLayerBase(
                 attr,
-                function_name=f'{object.__getattribute__(self, "_function_name")}.{name}',
+                function_name=f"{object.__getattribute__(self, '_function_name')}.{name}",
                 provider_type=object.__getattribute__(self, "_provider_type"),
                 api_key=object.__getattribute__(self, "_api_key"),
                 tracer=object.__getattribute__(self, "_tracer"),

promptlayer/track/__init__.py

@@ -1,8 +1,9 @@
-from promptlayer.track.track import agroup, ametadata, aprompt, ascore, group
+from promptlayer.track.track import agroup, ametadata, aprompt, ascore, group, prompt
 from promptlayer.track.track import metadata as metadata_
-from promptlayer.track.track import prompt
 from promptlayer.track.track import score as score_
 
+# TODO(dmu) LOW: Move this code to another file
+
 
 class TrackManager:
     def __init__(self, api_key: str):

promptlayer/utils.py

@@ -749,9 +749,9 @@ def cleaned_result(self):
                     hasattr(result.choices[0].delta, "content")
                     and result.choices[0].delta.content is not None
                 ):
-                    response["content"] = response[
-                        "content"
-                    ] = f"{response['content']}{result.choices[0].delta.content}"
+                    response["content"] = response["content"] = (
+                        f"{response['content']}{result.choices[0].delta.content}"
+                    )
             final_result = deepcopy(self.results[-1])
             final_result.choices[0] = response
             return final_result

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "promptlayer"
-version = "1.0.37"
+version = "1.0.38"
 description = "PromptLayer is a platform for prompt engineering and tracks your LLM requests."
 authors = ["Magniv <[email protected]>"]
 license = "Apache-2.0"