Linting code base (#14)

* remove unused imports and variables
* put all rules in pyproject
* run lint and format ruff github action on PRs and pushes to main

Author: luiarthur

.github/workflows/ruff.yml

@@ -11,4 +11,6 @@ jobs:
       - uses: astral-sh/ruff-action@v3
         with:
           version: "0.12.10"
-          args: "format --check --diff"
+          args: "--version"
+      - run: ruff check
+      - run: ruff format --check

.pre-commit-config.yaml

@@ -4,7 +4,9 @@ repos:
   rev: v0.12.10
   hooks:
     # Run the linter.
-    # - id: ruff-check
-    #   args: [ --fix ]
+    - id: ruff-check
+      args: [ --fix ]
     # Run the formatter.
     - id: ruff-format
+
+# "src/**/__init__.py" = ["F401"]

CONTRIBUTING.md

@@ -1,10 +1,10 @@
 # Contributing
 
-## Formatting
+## Linting and Formatting
 
-You will need to format your code using [`ruff`][2]. The easiest way to
-automate formatting of code prior to each commit is via the [`pre-commit`][1]
-package, which simplifies management of git hooks.
+You will need to lint and format your code using [`ruff`][2]. The easiest way
+to automate linting/formatting of code prior to each commit is via the
+[`pre-commit`][1] package, which simplifies management of git hooks.
 
 If using pip, `pre-commit` will be installed when you install `ursa` in
 editable mode via
@@ -16,8 +16,8 @@ pip install -e .[dev]
 If using `uv`, `pre-commit` will be installed in your default (dev)
 environment.
 
-To install the ruff formatting git hook to your local `.git/hooks` folder, run
-in the following in the current directory:
+To install the ruff git hook to your local `.git/hooks` folder, run
+the following in the current directory:
 
 ```bash
 # If using pip with venv, first activate your environment, then
@@ -27,19 +27,33 @@ pre-commit install
 uv run pre-commit install
 ```
 
-Prior to subsequent `git commit` calls, `ruff` will first format code.
+Prior to subsequent `git commit` calls, `ruff` will first lint/format code.
 
-Instead of running git hooks, you can format code manually via
+Instead of running git hooks, you can lint/format code manually via running the
+following in the current directory:
 
 ```bash
-# In current directory:
+# Lint
+ruff check --fix
+
+# Format
 ruff format
 ```
 
+To continually lint while developing, you can
+run the following in your terminal
+
+```bash
+ruff check --watch
+```
+
+For editor (e.g., vim, VSCode) integration, see [here][4].
+
 (You can install via ruff following instructions [here][3].)
 
-If code is not formatted, PRs will be blocked.
+If code is not linted/formatted, PRs will be blocked.
 
 [1]: https://pre-commit.com
 [2]: https://github.com/astral-sh/ruff
 [3]: https://docs.astral.sh/ruff/installation
+[4]: https://docs.astral.sh/ruff/editors/setup

examples/combine_agents_examples/agent_graph.py

@@ -1,28 +1,31 @@
-import os, sys
-import coolname
+import os
+from typing import Annotated, Literal
 
+import coolname
 from langchain_core.messages import (
+    AIMessage,
     HumanMessage,
     SystemMessage,
-    AIMessage,
-    ToolMessage,
 )
+from langchain_core.tools import tool
 from langchain_litellm import ChatLiteLLM
 from langchain_openai import OpenAIEmbeddings
-
-from ursa.agents import ArxivAgent, RecallAgent, BaseAgent, BaseChatModel
-from ursa.agents import ExecutionAgent, ExecutionState
-from ursa.prompt_library.execution_prompts import summarize_prompt
-from ursa.util.memory_logger import AgentMemory
-
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
-from langgraph.prebuilt import ToolNode, InjectedState
-from langchain_core.tools import tool
-
-from typing import Annotated, Literal
+from langgraph.prebuilt import InjectedState, ToolNode
 from typing_extensions import TypedDict
 
+from ursa.agents import (
+    ArxivAgent,
+    BaseAgent,
+    BaseChatModel,
+    ExecutionAgent,
+    ExecutionState,
+    RecallAgent,
+)
+from ursa.prompt_library.execution_prompts import summarize_prompt
+from ursa.util.memory_logger import AgentMemory
+
 # --- ANSI color codes ---
 GREEN = "\033[92m"
 BLUE = "\033[94m"
@@ -51,14 +54,6 @@
 """
 
 
-class State(TypedDict):
-    messages: Annotated[list, add_messages]
-    current_progress: str
-    code_files: list[str]
-    workspace: str
-    arxiv_results: list[str]
-
-
 model = ChatLiteLLM(
     model="openai/o3",
     max_tokens=50000,
@@ -164,7 +159,7 @@ def runner(self, state: State) -> State:
             )
         os.makedirs(new_state["workspace"], exist_ok=True)
 
-        if type(new_state["messages"][0]) == SystemMessage:
+        if isinstance(new_state["messages"][0], SystemMessage):
             new_state["messages"][0] = SystemMessage(content=self.runner_prompt)
         else:
             new_state["messages"] = [
@@ -187,7 +182,7 @@ def summarize(self, state: ExecutionState) -> ExecutionState:
         memories = []
         # Handle looping through the messages
         for x in state["messages"]:
-            if not type(x) == AIMessage:
+            if not isinstance(x, AIMessage):
                 memories.append(x.content)
             elif not x.tool_calls:
                 memories.append(x.content)

examples/hitl_examples/hitl_basic.py

@@ -1,17 +1,18 @@
-import os, sqlite3
-
+import os
+import sqlite3
 from pathlib import Path
+
 from langchain_core.messages import HumanMessage
 from langchain_litellm import ChatLiteLLM
-from langgraph.checkpoint.sqlite import SqliteSaver
 from langchain_openai import OpenAIEmbeddings
+from langgraph.checkpoint.sqlite import SqliteSaver
 
 from ursa.agents import (
     ArxivAgent,
     ExecutionAgent,
     PlanningAgent,
-    WebSearchAgent,
     RecallAgent,
+    WebSearchAgent,
 )
 from ursa.util.memory_logger import AgentMemory
 

examples/single_agent_examples/arxiv_agent/high_entropy_alloy_papers.py

@@ -1,11 +1,9 @@
-import sys
 import time
 
-sys.path.append("../../.")
+from langchain_community.callbacks.openai_info import OpenAICallbackHandler
+from langchain_openai import ChatOpenAI, OpenAIEmbeddings
 
 from ursa.agents import ArxivAgent
-from langchain_openai import ChatOpenAI, OpenAIEmbeddings
-from langchain_community.callbacks.openai_info import OpenAICallbackHandler
 
 
 def main():
@@ -33,7 +31,7 @@ def main():
 
     t0 = time.time()
 
-    result = agent.run(
+    agent.run(
         arxiv_search_query="High Entropy Alloys",
         context="Find High entropy alloys suitable for application under extreme conditions. For candidates that you identify, provide the starting structure, crystal structure, lattice parameters, and space group.",
     )

examples/single_agent_examples/arxiv_agent/neutron_star_radius.py

@@ -1,20 +1,22 @@
-import sys
+from pathlib import Path
 
-from ursa.agents import ArxivAgent
 from langchain_litellm import ChatLiteLLM
 
+from ursa.agents import ArxivAgent
+
 
 def main():
     llm = ChatLiteLLM(model="openai/o3", max_completion_tokens=20000)
 
+    Path("workspace").mkdir(exist_ok=True)
     agent = ArxivAgent(
         llm=llm,
         summarize=True,
         process_images=True,
         max_results=3,
-        database_path="arxiv_papers_neutron_star",
-        summaries_path="arxiv_summaries_neutron_star",
-        vectorstore_path="arxiv_vectorstores_neutron_star",
+        database_path="workspace/arxiv_papers_neutron_star",
+        summaries_path="workspace/arxiv_summaries_neutron_star",
+        vectorstore_path="workspace/arxiv_vectorstores_neutron_star",
         download_papers=True,
     )
 

examples/single_agent_examples/execution_agent/bayesian_optimization.py

@@ -1,5 +1,3 @@
-import sys
-
 from langchain_core.messages import HumanMessage
 from langchain_litellm import ChatLiteLLM
 from langchain_openai import OpenAIEmbeddings

examples/single_agent_examples/execution_agent/integer_sum.py

@@ -5,18 +5,17 @@
 benchmarks them against each other and verifies the results mach.
 """
 
-from pathlib import Path
 import sqlite3
+from pathlib import Path
 
 from langchain_core.messages import HumanMessage
 from langchain_litellm import ChatLiteLLM
 from langgraph.checkpoint.sqlite import SqliteSaver
-
-from ursa.agents import ExecutionAgent
-
 from rich import get_console
 from rich.panel import Panel
 
+from ursa.agents import ExecutionAgent
+
 console = get_console()  # always returns the same instance
 
 # Define the workspace

examples/single_agent_examples/materials_project_agent/mpa_example.py

@@ -1,11 +1,4 @@
-import sys
-
-from langchain_core.messages import HumanMessage
-from langchain_litellm import ChatLiteLLM
-
-from ursa.agents import ExecutionAgent, MaterialsProjectAgent
-
-import json, os
+from ursa.agents import MaterialsProjectAgent
 
 # make sure your MP_API_KEY is set in env or pass it here
 agent = MaterialsProjectAgent(max_results=5)