Convert FMP data documentation notebook to markdown format

Switches the `.ipynb` file to a markdown-based format using delimited code blocks. Simplifies maintainability, improves readability, and aligns with standard documentation practices.
langchain-ai · Jan 12, 2025 · 40d7505 · 40d7505
1 parent 55e579c
commit 40d7505
Showing 1 changed file with 85 additions and 4 deletions.
diff --git a/docs/docs/integrations/tools/fmp-data.ipynb b/docs/docs/integrations/tools/fmp-data.ipynb
@@ -83,7 +83,8 @@
    "execution_count": null,
    "source": [
     "from langchain_fmp_data import FMPDataToolkit\n",
-    "query=\"Get stock market prices and technical indicators\"\n",
+    "\n",
+    "query = \"Get stock market prices and technical indicators\"\n",
     "# Basic instantiation\n",
     "toolkit = FMPDataToolkit(query=query)\n",
     "\n",
@@ -216,7 +217,7 @@
     "# Initialize with custom settings\n",
     "advanced_tool = FMPDataTool(\n",
     "    max_iterations=50,  # Increase max iterations for complex queries\n",
-    "    temperature=0.2,     # Adjust temperature for more/less focused responses\n",
+    "    temperature=0.2,  # Adjust temperature for more/less focused responses\n",
     ")\n",
     "\n",
     "# Example of a complex multi-part analysis\n",
@@ -276,7 +277,10 @@
     "\n",
     "\n",
     "## API Reference\n",
-    "## FMPDataToolkit\n"
+    "\n",
+    "### FMPDataToolkit\n",
+    "Main class for creating collections of FMP API tools:\n",
+    "\n"
    ],
    "id": "9b9dc04b8a68e94c"
   },
@@ -285,8 +289,85 @@
    "cell_type": "code",
    "outputs": [],
    "execution_count": null,
-   "source": "",
+   "source": [
+    "from typing import Any\n",
+    "from langchain.tools import Tool\n",
+    "\n",
+    "\n",
+    "class FMPDataToolkit:\n",
+    "    \"\"\"Creates a collection of FMP data tools based on queries.\"\"\"\n",
+    "\n",
+    "    def __init__(\n",
+    "            self,\n",
+    "            query: str | None = None,\n",
+    "            num_results: int = 3,\n",
+    "            similarity_threshold: float = 0.3,\n",
+    "            cache_dir: str | None = None\n",
+    "    ): ...\n",
+    "\n",
+    "    def get_tools(self) -> list[Tool]:\n",
+    "        \"\"\"Returns a list of relevant FMP API tools based on the query.\"\"\"\n",
+    "        ..."
+   ],
    "id": "4b6604b7cf72c1a0"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "### FMPDataTool\n",
+    "Unified tool that automatically selects appropriate FMP endpoints:\n"
+   ],
+   "id": "7524eb1099d5e7e7"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "class FMPDataTool:\n",
+    "    \"\"\"Single unified tool for accessing FMP data through natural language.\"\"\"\n",
+    "\n",
+    "    def __init__(\n",
+    "            self,\n",
+    "            max_iterations: int = 3,\n",
+    "            temperature: float = 0.0\n",
+    "    ): ...\n",
+    "\n",
+    "    def invoke(\n",
+    "            self,\n",
+    "            input: dict[str, Any]\n",
+    "    ) -> str | dict[str, Any]:\n",
+    "        \"\"\"Execute a natural language query against FMP API.\"\"\"\n",
+    "        ..."
+   ],
+   "id": "aec521045bd34060"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "### ResponseFormat\n",
+    "Enum for controlling response format:\n"
+   ],
+   "id": "1807550e3c40e3e8"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from enum import Enum\n",
+    "\n",
+    "\n",
+    "class ResponseFormat(str, Enum):\n",
+    "    RAW = \"raw\"  # Raw API response\n",
+    "    ANALYSIS = \"text\"  # Natural language analysis\n",
+    "    BOTH = \"both\"  # Both raw data and analysis"
+   ],
+   "id": "fa7c1c255f0820c2"
   }
  ],
  "metadata": {