[Docs] Add ruff linting to .ipynb files (#645)

examples/code_assistant/langgraph_code_assistant.ipynb

@@ -94,9 +94,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_openai import ChatOpenAI\n",
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "from langchain_core.pydantic_v1 import BaseModel, Field\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "### OpenAI\n",
     "\n",
@@ -125,6 +125,7 @@
     "    code: str = Field(description=\"Code block not including import statements\")\n",
     "    description = \"Schema for code solutions to questions about LCEL.\"\n",
     "\n",
+    "\n",
     "expt_llm = \"gpt-4-0125-preview\"\n",
     "llm = ChatOpenAI(temperature=0, model=expt_llm)\n",
     "code_gen_chain = code_gen_prompt | llm.with_structured_output(code)\n",
@@ -181,6 +182,7 @@
     "\n",
     "structured_llm_claude = llm.with_structured_output(code, include_raw=True)\n",
     "\n",
+    "\n",
     "# Optional: Check for errors in case tool use is flaky\n",
     "def check_claude_output(tool_output):\n",
     "    \"\"\"Check for parse error or failure to call the tool\"\"\"\n",
@@ -189,7 +191,7 @@
     "    if tool_output[\"parsing_error\"]:\n",
     "        # Report back output and parsing errors\n",
     "        print(\"Parsing error!\")\n",
-    "        raw_output = str(code_output[\"raw\"].content)\n",
+    "        raw_output = str(tool_output[\"raw\"].content)\n",
     "        error = tool_output[\"parsing_error\"]\n",
     "        raise ValueError(\n",
     "            f\"Error parsing your output! Be sure to invoke the tool. Output: {raw_output}. \\n Parse error: {error}\"\n",
@@ -199,15 +201,17 @@
     "    elif not tool_output[\"parsed\"]:\n",
     "        print(\"Failed to invoke tool!\")\n",
     "        raise ValueError(\n",
-    "            f\"You did not use the provided tool! Be sure to invoke the tool to structure the output.\"\n",
+    "            \"You did not use the provided tool! Be sure to invoke the tool to structure the output.\"\n",
     "        )\n",
     "    return tool_output\n",
     "\n",
+    "\n",
     "# Chain with output check\n",
     "code_chain_claude_raw = (\n",
     "    code_gen_prompt_claude | structured_llm_claude | check_claude_output\n",
     ")\n",
     "\n",
+    "\n",
     "def insert_errors(inputs):\n",
     "    \"\"\"Insert errors for tool parsing in the messages\"\"\"\n",
     "\n",
@@ -240,6 +244,7 @@
     "\n",
     "    return solution[\"parsed\"]\n",
     "\n",
+    "\n",
     "# Optional: With re-try to correct for failure to invoke tool\n",
     "code_gen_chain = code_gen_chain_re_try | parse_output\n",
     "\n",
@@ -281,7 +286,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from typing import Dict, TypedDict, List\n",
+    "from typing import List, TypedDict\n",
     "\n",
     "\n",
     "class GraphState(TypedDict):\n",
@@ -318,10 +323,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from operator import itemgetter\n",
     "from langchain_core.pydantic_v1 import BaseModel, Field\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_core.prompts import PromptTemplate\n",
     "\n",
     "### Parameter\n",
     "\n",
@@ -396,7 +398,6 @@
     "    iterations = state[\"iterations\"]\n",
     "\n",
     "    # Get solution components\n",
-    "    prefix = code_solution.prefix\n",
     "    imports = code_solution.imports\n",
     "    code = code_solution.code\n",
     "\n",
@@ -457,14 +458,6 @@
     "    code_solution = state[\"generation\"]\n",
     "\n",
     "    # Prompt reflection\n",
-    "    reflection_message = [\n",
-    "        (\n",
-    "            \"user\",\n",
-    "            \"\"\"You tried to solve this problem and failed a unit test. Reflect on this failure\n",
-    "                                    given the provided documentation. Write a few key suggestions based on the \n",
-    "                                    documentation to avoid making this mistake again.\"\"\",\n",
-    "        )\n",
-    "    ]\n",
     "\n",
     "    # Add reflection\n",
     "    reflections = code_gen_chain.invoke(\n",
@@ -613,7 +606,7 @@
     "    try:\n",
     "        exec(imports)\n",
     "        return {\"key\": \"import_check\", \"score\": 1}\n",
-    "    except:\n",
+    "    except Exception:\n",
     "        return {\"key\": \"import_check\", \"score\": 0}\n",
     "\n",
     "\n",
@@ -623,7 +616,7 @@
     "    try:\n",
     "        exec(imports + \"\\n\" + code)\n",
     "        return {\"key\": \"code_execution_check\", \"score\": 1}\n",
-    "    except:\n",
+    "    except Exception:\n",
     "        return {\"key\": \"code_execution_check\", \"score\": 0}"
    ]
   },
@@ -754,7 +747,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,