🔧 refactor(ai.py): reorder imports and improve code readability

🔧 refactor(Dockerfile): replace poetry build and pip install with poetry install for simplicity
🔧 refactor(.dockerignore, .gitignore): add newline at end of file for POSIX compliance
✨ feat(.flake8, .pre-commit-config.yaml): add flake8 and pre-commit configuration files for better code quality control

🎨 style(app.py, const.py, makefile): improve code readability by reformatting code and removing unnecessary whitespace
🔥 remove(anthropic): remove unused import in const.py for cleaner code

🔧 chore(pyproject.toml): add flake8, pre-commit to dev-dependencies for better code quality control
🔧 chore(pyproject.toml): configure isort and black for consistent code formatting
🎨 style(settings.py): improve code formatting to adhere to PEP8 standards

.dockerignore

@@ -16,4 +16,4 @@ __pycache__
 flagged
 gradio_cached_examples
 
-.venv
+.venv

.flake8

@@ -0,0 +1,5 @@
+[flake8]
+max-line-length = 88
+select = C,E,F,W,B,B9
+ignore = E203, E501, W503, E712, E301, F403, F405, E711
+exclude = .tox,.git,venv,__init__.py

.gitignore

@@ -16,4 +16,4 @@ __pycache__
 flagged
 gradio_cached_examples
 
-.venv
+.venv

.pre-commit-config.yaml

@@ -0,0 +1,52 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.0.1
+    hooks:
+      - id: trailing-whitespace
+        exclude: ^(.github/|.art/)
+      - id: end-of-file-fixer
+        exclude: ^(.github/|.art/)
+      - id: debug-statements
+
+  - repo: https://github.com/myint/autoflake
+    rev: v1.4
+    hooks:
+      - id: autoflake
+        args:
+          [
+            "--in-place",
+            "--remove-unused-variable",
+            "--ignore-init-module-imports",
+            "--remove-all-unused-imports",
+          ]
+
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v3.1.0
+    hooks:
+      - id: pyupgrade
+        args: ["--py3-plus"]
+
+  # - repo: https://github.com/asottile/seed-isort-config
+  #   rev: v2.2.0
+  #   hooks:
+  #     - id: seed-isort-config
+
+  - repo: https://github.com/pre-commit/mirrors-isort
+    rev: v5.9.1
+    hooks:
+      - id: isort
+
+  - repo: https://github.com/ambv/black
+    rev: 22.3.0
+    hooks:
+      - id: black
+        language_version: python3.10
+
+  - repo: local
+    hooks:
+      - id: flake8
+        name: flake8
+        types: [python]
+        language: system
+        entry: poetry run flake8 --config .flake8
+        exclude: run.py

Dockerfile

@@ -39,9 +39,7 @@ RUN python -m venv /venv
 RUN /venv/bin/pip install --upgrade pip wheel setuptools setuptools_rust
 COPY . .
 
-RUN poetry build && \
-    /venv/bin/pip install --upgrade pip wheel setuptools && \
-    /venv/bin/pip install dist/*.whl
+RUN poetry install
 
 COPY . .
 CMD ["python", "app.py"]

ai.py

@@ -1,25 +1,28 @@
-import anthropic
 import os
+
+import anthropic
 from dotenv import load_dotenv
 
+from settings import settings
+
 load_dotenv()
 
-from settings import settings
 
-syncClient = anthropic.Anthropic(api_key=settings.ANTHROPIC_API_KEY,
-                                 timeout=5)
-asyncClient = anthropic.AsyncAnthropic(api_key=settings.ANTHROPIC_API_KEY,
-                                       timeout=60)
-class AnthropicCustom():
+syncClient = anthropic.Anthropic(api_key=settings.ANTHROPIC_API_KEY, timeout=5)
+asyncClient = anthropic.AsyncAnthropic(api_key=settings.ANTHROPIC_API_KEY, timeout=60)
+
+
+class AnthropicCustom:
     def __init__(self, api_key, model, max_tokens=1000, prompt=""):
         self.api_key = api_key
         self.model = model
         self.max_tokens = max_tokens
         self.prompt = prompt
-        if os.environ.get('ANTHROPIC_API_KEY') is not None:
-            api_key = os.environ.get('ANTHROPIC_API_KEY')
+        if os.environ.get("ANTHROPIC_API_KEY") is not None:
+            api_key = os.environ.get("ANTHROPIC_API_KEY")
         else:
-            os.environ['ANTHROPIC_API_KEY'] = api_key
+            os.environ["ANTHROPIC_API_KEY"] = api_key
+
     def get_anthropic_response(self):
         response = syncClient.completions.create(
             prompt=self.prompt,
@@ -27,12 +30,15 @@ class AnthropicCustom():
             max_tokens_to_sample=self.max_tokens,
         )
         return response.completion
+
     async def get_anthropic_response_async(self):
         async for line in await asyncClient.completions.create(
             prompt=self.prompt,
             model=self.model,
             max_tokens_to_sample=self.max_tokens,
-            stop_sequences=[anthropic.HUMAN_PROMPT,],
+            stop_sequences=[
+                anthropic.HUMAN_PROMPT,
+            ],
             stream=True,
         ):
-            yield line.completion
+            yield line.completion

app.py

@@ -1,37 +1,58 @@
+import re
+
 import anthropic
 import gradio as gr
-from gradio.components import Dropdown, Checkbox,Textbox,IOComponent
-import re
-from ai import AnthropicCustom
-from const import ClaudeModels,ModelTokenLength,Prompts
+from gradio.components import Checkbox, Dropdown, IOComponent, Textbox
 
+from ai import AnthropicCustom
+from const import ClaudeModels, ModelTokenLength, Prompts
 
 # Define a global variable for the conversation history
 conversation_history = ""
 
-async def interact_with_ai(user_question,token, model, token_length, prompt, prompt_input, memory):
+
+async def interact_with_ai(
+    user_question, token, model, token_length, prompt, prompt_input, memory
+):
     global conversation_history
-        
+
     if memory:
-        prompt = Prompts[prompt].value.format(memory=conversation_history, question=user_question)
+        prompt = Prompts[prompt].value.format(
+            memory=conversation_history, question=user_question
+        )
     else:
         prompt = Prompts[prompt].value.format(memory="", question=user_question)
 
-    if prompt_input != re.search(r'Human: (.*?) \n\nConversations:', prompt).group(1):
-        prompt = re.sub(r'Human: (.*?) \n\nConversations:', f'Human: {prompt_input} \n\nConversations:', prompt)
-    
+    if prompt_input != re.search(r"Human: (.*?) \n\nConversations:", prompt).group(1):
+        prompt = re.sub(
+            r"Human: (.*?) \n\nConversations:",
+            f"Human: {prompt_input} \n\nConversations:",
+            prompt,
+        )
+
     # Create an instance of the custom class
-    anth = AnthropicCustom(api_key=token, model=model, max_tokens=token_length, prompt= prompt)
-    
+    anth = AnthropicCustom(
+        api_key=token, model=model, max_tokens=token_length, prompt=prompt
+    )
+
     # Create a generator to stream the response
     response_accumulated = ""
     async for response in anth.get_anthropic_response_async():
         response_accumulated += response
         conversation_history = f"{conversation_history} {anthropic.HUMAN_PROMPT} {user_question} {anthropic.AI_PROMPT} {response_accumulated}"
         yield response_accumulated
-    
 
-async def chat_with_ai(message, history, token,model, token_length, prompt, prompt_input, memory,):
+
+async def chat_with_ai(
+    message,
+    history,
+    token,
+    model,
+    token_length,
+    prompt,
+    prompt_input,
+    memory,
+):
     global conversation_history
     if memory:
         for conversation in history:
@@ -41,39 +62,105 @@ async def chat_with_ai(message, history, token,model, token_length, prompt, prom
     else:
         prompt = Prompts[prompt].value.format(memory="", question=message)
 
-    if prompt_input != re.search(r'Human: (.*?) \n\nConversations:', prompt).group(1):
-        prompt = re.sub(r'Human: (.*?) \n\nConversations:', f'Human: {prompt_input} \n\nConversations:', prompt)
-    
+    if prompt_input != re.search(r"Human: (.*?) \n\nConversations:", prompt).group(1):
+        prompt = re.sub(
+            r"Human: (.*?) \n\nConversations:",
+            f"Human: {prompt_input} \n\nConversations:",
+            prompt,
+        )
+
     # Create an instance of the custom class
-    anth = AnthropicCustom(api_key=token, model=model, max_tokens=token_length, prompt= prompt)
-    
+    anth = AnthropicCustom(
+        api_key=token, model=model, max_tokens=token_length, prompt=prompt
+    )
+
     # Create a generator to stream the response
     response_accumulated = ""
     async for response in anth.get_anthropic_response_async():
         response_accumulated += response
         yield response_accumulated
 
-promptDropdown:IOComponent = Dropdown(choices=list(Prompts.__members__.keys()),label="Prompt",value=list(Prompts.__members__.keys())[0])
-prompt_input :IOComponent = Textbox(label="Custom Prompt", placeholder="Enter a custom prompt here", lines=3, value=re.search(r'Human: (.*?) \n\nConversations:', Prompts[promptDropdown.value].value).group(1), )
-
 
-iface = gr.Interface(fn=interact_with_ai,
-                     flagging_options=["Inappropriate", "Disrespectful", "Spam"],
-                     allow_flagging='auto',
-                     title="Claude Space",
-                     inputs=[Textbox(label="Question", placeholder="Enter a question here"),Textbox(label="Token", placeholder="Enter a token here",type='password'),Dropdown(choices=[model.value for model in ClaudeModels],label="Model",value=[model.value for model in ClaudeModels][0]),Dropdown(choices=[token.value for token in ModelTokenLength],label="Token Length",value= [token.value for token in ModelTokenLength][0]),promptDropdown,prompt_input,Checkbox(label="Memory", value=False)], 
-                     outputs="markdown",
-                     cache_examples=True,
-                     )
+promptDropdown: IOComponent = Dropdown(
+    choices=list(Prompts.__members__.keys()),
+    label="Prompt",
+    value=list(Prompts.__members__.keys())[0],
+)
+prompt_input: IOComponent = Textbox(
+    label="Custom Prompt",
+    placeholder="Enter a custom prompt here",
+    lines=3,
+    value=re.search(
+        r"Human: (.*?) \n\nConversations:", Prompts[promptDropdown.value].value
+    ).group(1),
+)
 
-promptDropdown:IOComponent = Dropdown(choices=list(Prompts.__members__.keys()),label="Prompt",value=list(Prompts.__members__.keys())[0])
-prompt_input :IOComponent = Textbox(label="Custom Prompt", placeholder="Enter a custom prompt here", lines=3, value=re.search(r'Human: (.*?) \n\nConversations:', Prompts[promptDropdown.value].value).group(1), )
 
-cface = gr.ChatInterface(fn=chat_with_ai,additional_inputs=[Textbox(label="Token", placeholder="Enter a token here",type='password'),Dropdown(choices=[model.value for model in ClaudeModels],label="Model",value=[model.value for model in ClaudeModels][0]),Dropdown(choices=[token.value for token in ModelTokenLength],label="Token Length",value= [token.value for token in ModelTokenLength][0]),promptDropdown,prompt_input,Checkbox(label="Memory", value=True)])
+iface = gr.Interface(
+    fn=interact_with_ai,
+    flagging_options=["Inappropriate", "Disrespectful", "Spam"],
+    allow_flagging="auto",
+    title="Claude Space",
+    inputs=[
+        Textbox(label="Question", placeholder="Enter a question here"),
+        Textbox(label="Token", placeholder="Enter a token here", type="password"),
+        Dropdown(
+            choices=[model.value for model in ClaudeModels],
+            label="Model",
+            value=[model.value for model in ClaudeModels][0],
+        ),
+        Dropdown(
+            choices=[token.value for token in ModelTokenLength],
+            label="Token Length",
+            value=[token.value for token in ModelTokenLength][0],
+        ),
+        promptDropdown,
+        prompt_input,
+        Checkbox(label="Memory", value=False),
+    ],
+    outputs="markdown",
+    cache_examples=True,
+)
 
+promptDropdown: IOComponent = Dropdown(
+    choices=list(Prompts.__members__.keys()),
+    label="Prompt",
+    value=list(Prompts.__members__.keys())[0],
+)
+prompt_input: IOComponent = Textbox(
+    label="Custom Prompt",
+    placeholder="Enter a custom prompt here",
+    lines=3,
+    value=re.search(
+        r"Human: (.*?) \n\nConversations:", Prompts[promptDropdown.value].value
+    ).group(1),
+)
 
+cface = gr.ChatInterface(
+    fn=chat_with_ai,
+    additional_inputs=[
+        Textbox(label="Token", placeholder="Enter a token here", type="password"),
+        Dropdown(
+            choices=[model.value for model in ClaudeModels],
+            label="Model",
+            value=[model.value for model in ClaudeModels][0],
+        ),
+        Dropdown(
+            choices=[token.value for token in ModelTokenLength],
+            label="Token Length",
+            value=[token.value for token in ModelTokenLength][0],
+        ),
+        promptDropdown,
+        prompt_input,
+        Checkbox(label="Memory", value=True),
+    ],
+)
 
 
 if __name__ == "__main__":
-    gd = gr.TabbedInterface([iface, cface], tab_names=["Claude Space", "Claude Chat"],title="Claude Space")
-    gd.queue(concurrency_count=75, max_size=100).launch(debug=True, share=False,server_name='0.0.0.0', server_port=7864)
+    gd = gr.TabbedInterface(
+        [iface, cface], tab_names=["Claude Space", "Claude Chat"], title="Claude Space"
+    )
+    gd.queue(concurrency_count=75, max_size=100).launch(
+        debug=True, share=False, server_name="0.0.0.0", server_port=7864
+    )

const.py

@@ -1,16 +1,15 @@
 import enum
-import anthropic
 
 
 class ClaudeModels(str, enum.Enum):
     Inatant1_1: str = "claude-instant-1"
     Instant1_2: str = "claude-instant-1.2"
-    Instant1_3: str =  "claude-instant-1.3"
-    Claude2: str  = "claude-2"
-    
-    
+    Instant1_3: str = "claude-instant-1.3"
+    Claude2: str = "claude-2"
+
+
 class ModelTokenLength(str, enum.Enum):
-    ten : int = 10
+    ten: int = 10
     twenty_five: int = 25
     fifty: int = 50
     hundred: int = 100
@@ -21,8 +20,7 @@ class ModelTokenLength(str, enum.Enum):
     twenty_k: int = 20000
     fifty_k: int = 50000
     hundred_k: int = 100000
-    
-    
+
+
 class Prompts(str, enum.Enum):
     general: str = "\n\nHuman: You're a AI bot who loves to gossip. Listin user's query and answer in markdown using Conversations. \n\nConversations: {memory} \n\nQuery: {question} \n\nAssistant:"
-    

makefile

@@ -1,2 +1,2 @@
 start:
-	python app.py    
+	python app.py

poetry.lock

@@ -378,6 +378,23 @@ files = [
 docs = ["furo (>=2023.5.20)", "sphinx (>=7.0.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
 testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4.1)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
 
+[[package]]
+name = "flake8"
+version = "6.1.0"
+description = "the modular source code checker: pep8 pyflakes and co"
+category = "main"
+optional = false
+python-versions = ">=3.8.1"
+files = [
+    {file = "flake8-6.1.0-py2.py3-none-any.whl", hash = "sha256:ffdfce58ea94c6580c77888a86506937f9a1a227dfcd15f245d694ae20a6b6e5"},
+    {file = "flake8-6.1.0.tar.gz", hash = "sha256:d5b3857f07c030bdb5bf41c7f53799571d75c4491748a3adcd47de929e34cd23"},
+]
+
+[package.dependencies]
+mccabe = ">=0.7.0,<0.8.0"
+pycodestyle = ">=2.11.0,<2.12.0"
+pyflakes = ">=3.1.0,<3.2.0"
+
 [[package]]
 name = "fonttools"
 version = "4.42.1"
@@ -945,6 +962,18 @@ pillow = ">=6.2.0"
 pyparsing = ">=2.3.1,<3.1"
 python-dateutil = ">=2.7"
 
+[[package]]
+name = "mccabe"
+version = "0.7.0"
+description = "McCabe checker, plugin for flake8"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "mccabe-0.7.0-py2.py3-none-any.whl", hash = "sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e"},
+    {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"},
+]
+
 [[package]]
 name = "numpy"
 version = "1.25.2"
@@ -1199,6 +1228,18 @@ files = [
 docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
 tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
 
+[[package]]
+name = "pycodestyle"
+version = "2.11.0"
+description = "Python style guide checker"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pycodestyle-2.11.0-py2.py3-none-any.whl", hash = "sha256:5d1013ba8dc7895b548be5afb05740ca82454fd899971563d2ef625d090326f8"},
+    {file = "pycodestyle-2.11.0.tar.gz", hash = "sha256:259bcc17857d8a8b3b4a2327324b79e5f020a13c16074670f9c8c8f872ea76d0"},
+]
+
 [[package]]
 name = "pydantic"
 version = "2.3.0"
@@ -1350,6 +1391,18 @@ files = [
     {file = "pydub-0.25.1.tar.gz", hash = "sha256:980a33ce9949cab2a569606b65674d748ecbca4f0796887fd6f46173a7b0d30f"},
 ]
 
+[[package]]
+name = "pyflakes"
+version = "3.1.0"
+description = "passive checker of Python programs"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pyflakes-3.1.0-py2.py3-none-any.whl", hash = "sha256:4132f6d49cb4dae6819e5379898f2b8cce3c5f23994194c24b77d5da2e36f774"},
+    {file = "pyflakes-3.1.0.tar.gz", hash = "sha256:a0aae034c444db0071aa077972ba4768d40c830d9539fd45bf4cd3f8f6992efc"},
+]
+
 [[package]]
 name = "pyparsing"
 version = "3.0.9"
@@ -1908,4 +1961,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "3cfcceb51ce4dd46c33225e911d15ec8c8a2e209b8beccea43e726362e00795e"
+content-hash = "041957f123ae41db1e7ffaeaee6d89e51646954137366587e4ba343dca3b005e"

pyproject.toml

@@ -13,8 +13,37 @@ requests = "^2.31.0"
 gradio = "^3.41.2"
 anthropic = "^0.3.10"
 python-dotenv = "^1.0.0"
+flake8 = "^6.1.0"
 
+[tool.poetry.dev-dependencies]
+pre-commit = "^2.15.0"
 
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.isort]
+profile = "black"
+known_third_party = ["anthropic", "gradio", "dotenv"]
+
+[tool.black]
+line-length = 88
+include = '\.pyi?$'
+exclude = '''
+(
+  /(
+      \.eggs         # exclude a few common directories in the
+    | \.git          # root of the project
+    | \.hg
+    | \.mypy_cache
+    | \.tox
+    | \.venv
+    | _build
+    | buck-out
+    | build
+    | dist
+  )/
+  | foo.py           # also separately exclude a file named foo.py in
+                     # the root of the project
+)
+'''

settings.py

@@ -3,7 +3,7 @@ import os
 
 class Settings:
 
-    ANTHROPIC_API_KEY:str=os.environ.get('ANTHROPIC_API_KEY')
-    
+    ANTHROPIC_API_KEY: str = os.environ.get("ANTHROPIC_API_KEY")
 
-settings = Settings()
+
+settings = Settings()