From da42cbe0e7ad0a88639c4de1f0b2464dca660f8c Mon Sep 17 00:00:00 2001
From: "synacktra.work@gmail.com" <synacktra.work@gmail.com>
Date: Mon, 23 Sep 2024 04:52:09 +0530
Subject: [PATCH] Add langchain integration

---
 .github/actions/setup-poetry-env/action.yml   |    4 +-
 Makefile                                      |    2 +-
 README.md                                     |   60 +-
 cookbooks/gorillaLLM-integration.ipynb        | 4164 +++++++++++++++++
 cookbooks/langgraph-ollama-example.ipynb      |  141 +
 poetry.lock                                   |  630 ++-
 pyproject.toml                                |    5 +-
 tests/test_integration.py                     |   49 +
 tool_parse/_types.py                          |   19 +-
 tool_parse/compile.py                         |    4 +-
 tool_parse/integrations/__init__.py           |    0
 .../integrations/langchain.py                 |  185 +-
 tool_parse/marshal.py                         |    2 +-
 13 files changed, 5049 insertions(+), 216 deletions(-)
 create mode 100644 cookbooks/gorillaLLM-integration.ipynb
 create mode 100644 cookbooks/langgraph-ollama-example.ipynb
 create mode 100644 tests/test_integration.py
 create mode 100644 tool_parse/integrations/__init__.py
 rename integrations/langchain_extended_structured_tool.py => tool_parse/integrations/langchain.py (64%)

diff --git a/.github/actions/setup-poetry-env/action.yml b/.github/actions/setup-poetry-env/action.yml
index f8a978e..5cd2b98 100644
--- a/.github/actions/setup-poetry-env/action.yml
+++ b/.github/actions/setup-poetry-env/action.yml
@@ -52,10 +52,10 @@ runs:
 
     - name: Install dependencies on Windows
       if: runner.os == 'Windows'
-      run: poetry install -E pydantic --no-interaction
+      run: poetry install -E langchain --no-interaction
       shell: pwsh
 
     - name: Install dependencies on Linux/macOS
       if: runner.os != 'Windows'
-      run: poetry install -E pydantic --no-interaction
+      run: poetry install -E langchain --no-interaction
       shell: bash
diff --git a/Makefile b/Makefile
index 884ea05..0fe8c22 100644
--- a/Makefile
+++ b/Makefile
@@ -1,7 +1,7 @@
 .PHONY: install
 install: ## Install the poetry environment and install the pre-commit hooks
 	@echo "🚀 Creating virtual environment using poetry"
-	@poetry install -E pydantic
+	@poetry install -E langchain
 	@poetry run pre-commit install
 	@poetry shell
 
diff --git a/README.md b/README.md
index d77a3e6..8327204 100644
--- a/README.md
+++ b/README.md
@@ -24,10 +24,16 @@ pip install tool-parse
 ```
 
 - with `pydantic` support
+
   ```sh
   pip install "tool-parse[pydantic]"
   ```
 
+- with `langchain` based integration
+  ```sh
+  pip install "tool-parse[langchain]
+  ```
+
 ## 🌟 Key Features
 
 1. **Versatile Tool Management:**
@@ -73,7 +79,8 @@ pip install tool-parse
 
 ## Cookbooks
 
-- [GorillaLLM Integration](https://colab.research.google.com/drive/1C2WCgIZ7LnkpLt3KARL9ROh4iLwaACa6?usp=sharing)
+- [GorillaLLM Integration](./cookbooks/gorillaLLM-integration.ipynb)
+- [Langgraph+Ollama Example](./cookbooks//langgraph-ollama-example.ipynb)
 
 ## Usage 🤗
 
@@ -269,6 +276,57 @@ def calculate_discount(
 combined_registry = tr + new_registry
 ```
 
+## Third Party Integrations
+
+### Langchain
+
+Define the tools
+
+```python
+from tool_parse.integrations.langchain import ExtendedStructuredTool
+
+async def search_web(query: str, safe_search: bool = True):
+    """
+    Search the web.
+    :param query: Query to search for.
+    :param safe_search: If True, enable safe search.
+    """
+    return "not found"
+
+class UserInfo(NamedTuple):
+    """User information"""
+    name: str
+    age: int
+    role: Literal['admin', 'tester'] = 'tester'
+
+tools = [
+    ExtendedStructuredTool(func=search_web),
+    ExtendedStructuredTool(func=UserInfo, name="user_info", schema_spec='claude'),
+]
+# OR
+tools = ExtendedStructuredTool.from_objects(search_web, UserInfo, schema_spec='base')
+```
+
+Patch the chat model
+
+```python
+from langchain_ollama.chat_models import ChatOllama
+
+from tool_parse.integrations.langchain import patch_chat_model
+
+model = patch_chat_model(ChatOllama(model="llama3-groq-tool-use")) # Patch the instance
+# OR
+model = patch_chat_model(ChatOllama)(model="llama3-groq-tool-use") # Patch the class and then instantiate it
+```
+
+Bind the tools
+
+```python
+model.bind_tools(tools=tools)
+```
+
+> For langgraph agent usage, refer [Langgraph+Ollama Example](./cookbooks//langgraph-ollama-example.ipynb) cookbook
+
 ## 🤝 Contributing
 
 Contributions, issues, and feature requests are welcome! Feel free to check the [issues page](https://github.com/synacktraa/tool-parse/issues).
diff --git a/cookbooks/gorillaLLM-integration.ipynb b/cookbooks/gorillaLLM-integration.ipynb
new file mode 100644
index 0000000..d18fefc
--- /dev/null
+++ b/cookbooks/gorillaLLM-integration.ipynb
@@ -0,0 +1,4164 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Bheeth_Dur0Y"
+      },
+      "source": [
+        "<center>\n",
+        "  <p style=\"text-align:center\">\n",
+        "    Automating tool/function calling workflow\n",
+        "    <br>\n",
+        "    <a href=\"https://github.com/synacktraa/tool-parse\">Github</a>\n",
+        "    |\n",
+        "    <a href=\"https://pypi.org/project/tool-parse\">PyPI</a>\n",
+        "    |\n",
+        "    <a href=\"https://colab.research.google.com/drive/1C2WCgIZ7LnkpLt3KARL9ROh4iLwaACa6?usp=sharing\">Colab</a>\n",
+        "  </p>\n",
+        "</center>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-Eo0djkPhFFb",
+        "outputId": "6596b3bc-c04c-4a4a-e38e-f13119bf6194"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.8/2.8 MB\u001b[0m \u001b[31m41.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.5/137.5 MB\u001b[0m \u001b[31m4.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h"
+          ]
+        }
+      ],
+      "source": [
+        "#@title Install and import necessary libraries\n",
+        "%pip install -qU tool-parse[pydantic] duckduckgo_search\n",
+        "%pip install -qU sentencepiece accelerate bitsandbytes\n",
+        "\n",
+        "import json\n",
+        "import torch\n",
+        "from tool_parse import ToolRegistry\n",
+        "from transformers import (\n",
+        "    AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, pipeline\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "AsUbahs6immj"
+      },
+      "source": [
+        "### Creating a registry and registering tools"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "dWJX4hvZigcM"
+      },
+      "outputs": [],
+      "source": [
+        "from tool_parse import ToolRegistry\n",
+        "\n",
+        "from typing import Literal\n",
+        "from pydantic import BaseModel\n",
+        "from duckduckgo_search import DDGS\n",
+        "\n",
+        "tr = ToolRegistry()\n",
+        "ddgs = DDGS()\n",
+        "\n",
+        "@tr.register\n",
+        "def search_text(\n",
+        "  text: str,\n",
+        "  *, # Yes it supports positional and keyword arguments\n",
+        "  safe_search: bool = True,\n",
+        "  backend: Literal['api', 'html', 'lite'] = 'api',\n",
+        "  max_results: int = 1\n",
+        "):\n",
+        "    \"\"\"\n",
+        "    Search for text in the web.\n",
+        "    :param text: Text to search for.\n",
+        "    :param safe_search: If True, enable safe search.\n",
+        "    :param backend: Backend to use for retrieving results.\n",
+        "    :param max_results: Max results to return.\n",
+        "    \"\"\"\n",
+        "    return ddgs.text(\n",
+        "        keywords=text,\n",
+        "        safesearch=\"on\" if safe_search else \"off\",\n",
+        "        backend=backend,\n",
+        "        max_results=max_results\n",
+        "    )\n",
+        "\n",
+        "@tr.register(name='product_information')\n",
+        "class ProductInfo(BaseModel): # This can be TypedDict or NamedTuple if you don't want to install pydantic package.\n",
+        "    \"\"\"\n",
+        "    Information about the product.\n",
+        "    :param name: Name of the product.\n",
+        "    :param price: Price of the product.\n",
+        "    :param in_stock: If the product is in stock.\n",
+        "    \"\"\"\n",
+        "    name: str\n",
+        "    price: float\n",
+        "    in_stock: bool\n",
+        "\n",
+        "@tr.register\n",
+        "def get_translation(\n",
+        "    text: str,\n",
+        "    to: Literal['en', 'ja', 'hi', 'es', 'fr', 'de', 'zh'] = 'en'\n",
+        "):\n",
+        "    \"\"\"\n",
+        "    Translate the given text.\n",
+        "    :param text: Text to translate.\n",
+        "    :param to: what language to translate.\n",
+        "    \"\"\"\n",
+        "    return ddgs.translate(keywords=text, to=to)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "SP9V5lGFkeD6",
+        "outputId": "c750b19a-c285-4fe6-f5d8-f3201456c5d2"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'type': 'function',\n",
+              " 'function': {'name': 'search_text',\n",
+              "  'description': 'Search for text in the web.',\n",
+              "  'parameters': {'type': 'object',\n",
+              "   'properties': {'text': {'type': 'string',\n",
+              "     'description': 'Text to search for.'},\n",
+              "    'safe_search': {'type': 'boolean',\n",
+              "     'description': 'If True, enable safe search.'},\n",
+              "    'backend': {'enum': ['api', 'html', 'lite'],\n",
+              "     'type': 'string',\n",
+              "     'description': 'Backend to use for retrieving results.'},\n",
+              "    'max_results': {'type': 'integer',\n",
+              "     'description': 'Max results to return.'}},\n",
+              "   'required': ['text']}}}"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "\"\"\"\n",
+        "Lets take a look at each tool schema, we can get a particular tool schema from the registry like we're accessing a dictionary object with a key\n",
+        "\"\"\"\n",
+        "tr['search_text']"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HfYA9KjxonV9",
+        "outputId": "89ffd1d1-3daf-4a13-beb9-87abc656cbdc"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "False\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "{'type': 'function',\n",
+              " 'function': {'name': 'product_information',\n",
+              "  'description': 'Information about the product.',\n",
+              "  'parameters': {'type': 'object',\n",
+              "   'properties': {'name': {'type': 'string',\n",
+              "     'description': 'Name of the product.'},\n",
+              "    'price': {'type': 'number', 'description': 'Price of the product.'},\n",
+              "    'in_stock': {'type': 'boolean',\n",
+              "     'description': 'If the product is in stock.'}},\n",
+              "   'required': ['name', 'price', 'in_stock']}}}"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "print('ProductInfo' in tr) # Original name is ProductInfo but we gave it a custom name so it will return False\n",
+        "tr['product_information']"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Goo0IAp-o98B",
+        "outputId": "9b880952-4f10-4520-f3f9-18beecb00983"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'type': 'function',\n",
+              " 'function': {'name': 'get_translation',\n",
+              "  'description': 'Translate the given text.',\n",
+              "  'parameters': {'type': 'object',\n",
+              "   'properties': {'text': {'type': 'string',\n",
+              "     'description': 'Text to translate.'},\n",
+              "    'to': {'enum': ['en', 'ja', 'hi', 'es', 'fr', 'de', 'zh'],\n",
+              "     'type': 'string',\n",
+              "     'description': 'what language to translate.'}},\n",
+              "   'required': ['text']}}}"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "tr['get_translation']"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "tCAuNolapD83"
+      },
+      "source": [
+        "### Setting up Gorilla pipeline"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 337,
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+            ]
+          },
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+        },
+        {
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+            ]
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+      "source": [
+        "torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32\n",
+        "\n",
+        "# Quantization Setup\n",
+        "# This configuration compresses the model and makes it possible to use with Colab's GPU\n",
+        "bnb_config = BitsAndBytesConfig(\n",
+        "    load_in_4bit=True,\n",
+        "    bnb_4bit_use_double_quant=True,\n",
+        "    bnb_4bit_quant_type=\"nf4\",\n",
+        "    bnb_4bit_compute_dtype=torch_dtype\n",
+        ")\n",
+        "\n",
+        "# Model and tokenizer setup\n",
+        "model_id : str = \"gorilla-llm/gorilla-openfunctions-v2\"\n",
+        "tokenizer = AutoTokenizer.from_pretrained(model_id)\n",
+        "model = AutoModelForCausalLM.from_pretrained(\n",
+        "    model_id,\n",
+        "    torch_dtype=torch_dtype,\n",
+        "    quantization_config=bnb_config,\n",
+        "    low_cpu_mem_usage=True,\n",
+        "    device_map=\"auto\"\n",
+        ")\n",
+        "\n",
+        "# Create pipeline\n",
+        "pipe = pipeline(\n",
+        "    \"text-generation\",\n",
+        "    model=model,\n",
+        "    tokenizer=tokenizer,\n",
+        "    max_new_tokens=128,\n",
+        "    batch_size=16,\n",
+        "    torch_dtype=torch_dtype,\n",
+        ")\n",
+        "\n",
+        "# This function will return Gorilla's response\n",
+        "def get_gorilla_expression(query: str, functions: list[dict]) -> str:\n",
+        "    output = pipe(\n",
+        "        f\"USER: <<question>> {query} <<function>> {json.dumps(functions)}\\nASSISTANT: \"\n",
+        "    )[0]['generated_text'].splitlines()[-1]\n",
+        "    return output[output.index(\":\")+1:].strip().strip('<<function>>')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KgMj4vdmhK4v",
+        "outputId": "83b37b9d-a7fe-4677-b4cc-b9d34d415ecf"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[{'type': 'function',\n",
+              "  'function': {'name': 'search_text',\n",
+              "   'description': 'Search for text in the web.',\n",
+              "   'parameters': {'type': 'object',\n",
+              "    'properties': {'text': {'type': 'string',\n",
+              "      'description': 'Text to search for.'},\n",
+              "     'safe_search': {'type': 'boolean',\n",
+              "      'description': 'If True, enable safe search.'},\n",
+              "     'backend': {'enum': ['api', 'html', 'lite'],\n",
+              "      'type': 'string',\n",
+              "      'description': 'Backend to use for retrieving results.'},\n",
+              "     'max_results': {'type': 'integer',\n",
+              "      'description': 'Max results to return.'}},\n",
+              "    'required': ['text']}}},\n",
+              " {'type': 'function',\n",
+              "  'function': {'name': 'product_information',\n",
+              "   'description': 'Information about the product.',\n",
+              "   'parameters': {'type': 'object',\n",
+              "    'properties': {'name': {'type': 'string',\n",
+              "      'description': 'Name of the product.'},\n",
+              "     'price': {'type': 'number', 'description': 'Price of the product.'},\n",
+              "     'in_stock': {'type': 'boolean',\n",
+              "      'description': 'If the product is in stock.'}},\n",
+              "    'required': ['name', 'price', 'in_stock']}}},\n",
+              " {'type': 'function',\n",
+              "  'function': {'name': 'get_translation',\n",
+              "   'description': 'Translate the given text.',\n",
+              "   'parameters': {'type': 'object',\n",
+              "    'properties': {'text': {'type': 'string',\n",
+              "      'description': 'Text to translate.'},\n",
+              "     'to': {'enum': ['en', 'ja', 'hi', 'es', 'fr', 'de', 'zh'],\n",
+              "      'type': 'string',\n",
+              "      'description': 'what language to translate.'}},\n",
+              "    'required': ['text']}}}]"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# Getting schema of registered tools\n",
+        "\n",
+        "tools = tr.marshal('base')\n",
+        "tools"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "VQpRHlLXpaPG",
+        "outputId": "922107a8-3fd5-49d0-deaa-6f7c66ddb9c4"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "expression=\"search_text(text='gorilla')\"\n",
+            "output=[{'title': 'Gorilla - Wikipedia', 'href': 'https://en.wikipedia.org/wiki/Gorilla', 'body': 'The word gorilla comes from the history of Hanno the Navigator (c. 500 BC), a Carthaginian explorer on an expedition to the west African coast to the area that later became Sierra Leone. [1] [2] Members of the expedition encountered \"savage people, the greater part of whom were women, whose bodies were hairy, and whom our interpreters called Gorillae\".[3] [4] It is unknown whether what the ...'}]\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Search text\n",
+        "expression = get_gorilla_expression(\n",
+        "    query=\"Search for gorilla LLM benchmarks\", functions=tools\n",
+        ")\n",
+        "print(f\"{expression=}\")\n",
+        "\n",
+        "# Compile the expression to get the output\n",
+        "output = tr.compile(expression)\n",
+        "print(f\"{output=}\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "1M7Nt9yoqAL_",
+        "outputId": "b7609cea-228d-4f77-bdb3-0e98e2ea79ad"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "expression=\"product_information(name='RTX 4900', price=3500, in_stock=True)\"\n",
+            "output=ProductInfo(name='RTX 4900', price=3500.0, in_stock=True)\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Extracting product information\n",
+        "expression = get_gorilla_expression(\n",
+        "    query=\"Parse: Product RTX 4900, priced at $3.5k, is in stock.\", functions=tools\n",
+        ")\n",
+        "print(f\"{expression=}\")\n",
+        "\n",
+        "# Compile the expression to get the output\n",
+        "output = tr.compile(expression)\n",
+        "print(f\"{output=}\") # function/tool-calling is nothing but getting Structured output :>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8KcCJ7X3q3Sn",
+        "outputId": "afedf3b0-52a9-41cc-8e68-721998a1e51b"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "expression=\"get_translation(text='Tool calling is one of the best features of LLM', to='hi')\"\n",
+            "output=[{'detected_language': 'en', 'translated': 'टूल कॉलिंग एलएलएम की सबसे अच्छी विशेषताओं में से एक है', 'original': 'Tool calling is one of the best features of LLM'}]\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Translation\n",
+        "expression = get_gorilla_expression(\n",
+        "    query=\"'Tool calling is one of the best features of LLM' to hindi. Please utilize tool.\", functions=tools\n",
+        ") # It keeps translating the text itself, so I had to be specific regarding tool usage.\n",
+        "print(f\"{expression=}\")\n",
+        "\n",
+        "# Compile the expression to get the output\n",
+        "output = tr.compile(expression)\n",
+        "print(f\"{output=}\")"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
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+}
diff --git a/cookbooks/langgraph-ollama-example.ipynb b/cookbooks/langgraph-ollama-example.ipynb
new file mode 100644
index 0000000..dedc358
--- /dev/null
+++ b/cookbooks/langgraph-ollama-example.ipynb
@@ -0,0 +1,141 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#@title Install and import necessary libraries\n",
+    "%pip install -qU tool-parse[langchain] langchain-ollama langgraph duckduckgo-search\n",
+    "\n",
+    "from tool_parse.integrations.langchain import ExtendedStructuredTool, patch_chat_model\n",
+    "\n",
+    "import typing as t\n",
+    "from duckduckgo_search import DDGS\n",
+    "from langchain_core.messages import AIMessage, HumanMessage, ToolMessage\n",
+    "from langchain_ollama.chat_models import ChatOllama\n",
+    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.prebuilt import create_react_agent"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Define tools"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "async def search_text(\n",
+    "    text: str,\n",
+    "    *,\n",
+    "    safe_search: bool = True,\n",
+    "    backend: t.Literal[\"api\", \"html\", \"lite\"] = \"api\",\n",
+    "    max_results: int = 1,\n",
+    "):\n",
+    "    \"\"\"\n",
+    "    Search for text in the web.\n",
+    "    :param text: Text to search for.\n",
+    "    :param safe_search: If True, enable safe search.\n",
+    "    :param backend: Backend to use for retrieving results.\n",
+    "    :param max_results: Max results to return.\n",
+    "    \"\"\"\n",
+    "    return DDGS().text(\n",
+    "        keywords=text,\n",
+    "        safesearch=\"on\" if safe_search else \"off\",\n",
+    "        backend=backend,\n",
+    "        max_results=max_results,\n",
+    "    )\n",
+    "\n",
+    "class ProductInfo(t.NamedTuple):  # Can be t.TypedDict or pydantic.BaseModel\n",
+    "    \"\"\"\n",
+    "    Information about the product.\n",
+    "    :param name: Name of the product.\n",
+    "    :param price: Price of the product.\n",
+    "    :param in_stock: If the product is in stock.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    name: str\n",
+    "    price: float\n",
+    "    in_stock: bool = False\n",
+    "\n",
+    "tools = [\n",
+    "    ExtendedStructuredTool(func=search_text),\n",
+    "    ExtendedStructuredTool(func=ProductInfo, name=\"product_info\"),\n",
+    "]\n",
+    "# OR # tools = ExtendedStructuredTool.from_objects(search_text, ProductInfo)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Patch the langchain chat model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = patch_chat_model(ChatOllama(model=\"llama3-groq-tool-use\")) # Patch the instance\n",
+    "# OR\n",
+    "model = patch_chat_model(ChatOllama)(model=\"llama3-groq-tool-use\") # Patch the class and then instantiate it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = patch_chat_model(ChatOllama)(model=\"llama3-groq-tool-use\")\n",
+    "# OR # model = patch_chat_model(ChatOllama)(model=\"llama3-groq-tool-use\")\n",
+    "\n",
+    "agent_executor = create_react_agent(model, tools, checkpointer=MemorySaver())\n",
+    "config = {\"configurable\": {\"thread_id\": \"abc123\"}}\n",
+    "\n",
+    "def query_agent(__query: str):\n",
+    "    for chunk in agent_executor.stream({\"messages\": [HumanMessage(content=__query)]}, config):\n",
+    "        message = list(chunk.values())[0][\"messages\"][0]\n",
+    "        if isinstance(message, AIMessage):\n",
+    "            print(\"[AGENT]\")\n",
+    "            if message.tool_calls:\n",
+    "                print(\"Calling tool:\")\n",
+    "                metadata = message.tool_calls[0]\n",
+    "                print(f\"name={metadata['name']!r}\")\n",
+    "                print(f\"arguments={metadata['args']}\")\n",
+    "            else:\n",
+    "                print(message.content)\n",
+    "        elif isinstance(message, ToolMessage):\n",
+    "            print(f\"[{message.name!r} TOOL OUTPUT]\")\n",
+    "            print(message.content)\n",
+    "\n",
+    "        print(\"---\" * 20)\n",
+    "\n",
+    "query_agent(\"Search 5 sources for langgraph docs using lite backend\")\n",
+    "query_agent(\"Parse: Product RTX 4900, priced at $3.5k, is in stock.\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/poetry.lock b/poetry.lock
index acd59b0..76597f7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -14,6 +14,28 @@ files = [
 [package.dependencies]
 typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
 
+[[package]]
+name = "anyio"
+version = "4.6.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = true
+python-versions = ">=3.9"
+files = [
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
+
 [[package]]
 name = "cachetools"
 version = "5.5.0"
@@ -25,6 +47,17 @@ files = [
     {file = "cachetools-5.5.0.tar.gz", hash = "sha256:2cc24fb4cbe39633fb7badd9db9ca6295d766d9c2995f245725a46715d050f2a"},
 ]
 
+[[package]]
+name = "certifi"
+version = "2024.8.30"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"},
+    {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
+]
+
 [[package]]
 name = "cfgv"
 version = "3.4.0"
@@ -47,6 +80,105 @@ files = [
     {file = "chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7"},
 ]
 
+[[package]]
+name = "charset-normalizer"
+version = "3.3.2"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+optional = true
+python-versions = ">=3.7.0"
+files = [
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+]
+
 [[package]]
 name = "click"
 version = "8.1.7"
@@ -222,34 +354,105 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "filelock"
-version = "3.16.0"
+version = "3.16.1"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "filelock-3.16.0-py3-none-any.whl", hash = "sha256:f6ed4c963184f4c84dd5557ce8fece759a3724b37b80c6c4f20a2f63a4dc6609"},
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+    {file = "filelock-3.16.1-py3-none-any.whl", hash = "sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0"},
+    {file = "filelock-3.16.1.tar.gz", hash = "sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435"},
 ]
 
 [package.extras]
-docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.1.1)", "pytest (>=8.3.2)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.3)"]
+docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4.1)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.2)", "pytest (>=8.3.3)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.4)"]
 typing = ["typing-extensions (>=4.12.2)"]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = true
+python-versions = ">=3.7"
+files = [
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+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.27.2"
+description = "The next generation HTTP client."
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"},
+    {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+zstd = ["zstandard (>=0.18.0)"]
+
 [[package]]
 name = "identify"
-version = "2.6.0"
+version = "2.6.1"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"},
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+    {file = "identify-2.6.1-py2.py3-none-any.whl", hash = "sha256:53863bcac7caf8d2ed85bd20312ea5dcfc22226800f6d6881f232d861db5a8f0"},
+    {file = "identify-2.6.1.tar.gz", hash = "sha256:91478c5fb7c3aac5ff7bf9b4344f803843dc586832d5f110d672b19aa1984c98"},
 ]
 
 [package.extras]
 license = ["ukkonen"]
 
+[[package]]
+name = "idna"
+version = "3.10"
+description = "Internationalized Domain Names in Applications (IDNA)"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
+    {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
+]
+
+[package.extras]
+all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -261,6 +464,68 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "jsonpatch"
+version = "1.33"
+description = "Apply JSON-Patches (RFC 6902)"
+optional = true
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
+files = [
+    {file = "jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade"},
+    {file = "jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c"},
+]
+
+[package.dependencies]
+jsonpointer = ">=1.9"
+
+[[package]]
+name = "jsonpointer"
+version = "3.0.0"
+description = "Identify specific nodes in a JSON document (RFC 6901)"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"},
+    {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
+]
+
+[[package]]
+name = "langchain-core"
+version = "0.3.5"
+description = "Building applications with LLMs through composability"
+optional = true
+python-versions = "<4.0,>=3.9"
+files = [
+    {file = "langchain_core-0.3.5-py3-none-any.whl", hash = "sha256:2b5f86c1101beb013cb264c5722ad21931641493b4dc86e6f0575da698bf5cff"},
+    {file = "langchain_core-0.3.5.tar.gz", hash = "sha256:67e5510559454f3f7a0526e7ef91fd0f12b45c0cdc70720e44909f62b5becf5a"},
+]
+
+[package.dependencies]
+jsonpatch = ">=1.33,<2.0"
+langsmith = ">=0.1.125,<0.2.0"
+packaging = ">=23.2,<25"
+pydantic = {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""}
+PyYAML = ">=5.3"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+typing-extensions = ">=4.7"
+
+[[package]]
+name = "langsmith"
+version = "0.1.125"
+description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
+optional = true
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "langsmith-0.1.125-py3-none-any.whl", hash = "sha256:74ce8eb2663e1ed20bfcfc88d41e0712879306956c9938d1cdbab7d60458bdca"},
+    {file = "langsmith-0.1.125.tar.gz", hash = "sha256:2c0eb0c3cbf22cff55bf519b8e889041f9a591bcf97af5152c8e130333c5940e"},
+]
+
+[package.dependencies]
+httpx = ">=0.23.0,<1"
+orjson = ">=3.9.14,<4.0.0"
+pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
+requests = ">=2,<3"
+
 [[package]]
 name = "mypy"
 version = "1.11.2"
@@ -330,6 +595,72 @@ files = [
     {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"},
 ]
 
+[[package]]
+name = "orjson"
+version = "3.10.7"
+description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+optional = true
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 version = "24.1"
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 [package.dependencies]
@@ -513,13 +844,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pyproject-api"
-version = "1.7.1"
+version = "1.8.0"
 description = "API to interact with the python pyproject.toml based projects"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -527,8 +858,8 @@ packaging = ">=24.1"
 tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
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-testing = ["covdefaults (>=2.3)", "pytest (>=8.2.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "setuptools (>=70.1)"]
+docs = ["furo (>=2024.8.6)", "sphinx-autodoc-typehints (>=2.4.1)"]
+testing = ["covdefaults (>=2.3)", "pytest (>=8.3.3)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "setuptools (>=75.1)"]
 
 [[package]]
 name = "pytest"
@@ -632,6 +963,53 @@ files = [
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 ]
 
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+version = "2.32.3"
+description = "Python HTTP for Humans."
+optional = true
+python-versions = ">=3.8"
+files = [
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+charset-normalizer = ">=2,<4"
+idna = ">=2.5,<4"
+urllib3 = ">=1.21.1,<3"
+
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+use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
+
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+description = "Sniff out which async library your code is running under"
+optional = true
+python-versions = ">=3.7"
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+
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+version = "8.5.0"
+description = "Retry code until it succeeds"
+optional = true
+python-versions = ">=3.8"
+files = [
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+[package.extras]
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+test = ["pytest", "tornado (>=4.5)", "typeguard"]
+
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -645,13 +1023,13 @@ files = [
 
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+    {file = "tox-4.20.0.tar.gz", hash = "sha256:5b78a49b6eaaeab3ae4186415e7c97d524f762ae967c63562687c3e5f0ec23d5"},
 ]
 
 [package.dependencies]
@@ -681,15 +1059,32 @@ files = [
     {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
 
+[[package]]
+name = "urllib3"
+version = "2.2.3"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
 [[package]]
 name = "virtualenv"
-version = "20.26.4"
+version = "20.26.5"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.26.4-py3-none-any.whl", hash = "sha256:48f2695d9809277003f30776d155615ffc11328e6a0a8c1f0ec80188d7874a55"},
-    {file = "virtualenv-20.26.4.tar.gz", hash = "sha256:c17f4e0f3e6036e9f26700446f85c76ab11df65ff6d8a9cbfad9f71aabfcf23c"},
+    {file = "virtualenv-20.26.5-py3-none-any.whl", hash = "sha256:4f3ac17b81fba3ce3bd6f4ead2749a72da5929c01774948e243db9ba41df4ff6"},
+    {file = "virtualenv-20.26.5.tar.gz", hash = "sha256:ce489cac131aa58f4b25e321d6d186171f78e6cb13fafbf32a840cee67733ff4"},
 ]
 
 [package.dependencies]
@@ -702,9 +1097,10 @@ docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "s
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [extras]
+langchain = ["langchain-core", "pydantic"]
 pydantic = ["pydantic"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<=3.12"
-content-hash = "25a895ec474f8139a376016088c60983508acbbbf82918fff60f380c9f7c2cb3"
+content-hash = "526a54bd50f1280e3058ec6722e5c537529f2a754eeaea73b9b43518ce87db03"
diff --git a/pyproject.toml b/pyproject.toml
index c641fce..1eba9d9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,9 +14,11 @@ packages = [
 python = ">=3.8,<=3.12"
 docstring-parser = ">=0.15"
 pydantic = {version = ">=2.0", optional = true}
+langchain-core = {version = ">=0.3.0", optional = true, python = ">=3.9"}
 
 [tool.poetry.extras]
 pydantic = ["pydantic"]
+langchain = ["pydantic", "langchain_core"]
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.2.0"
@@ -39,10 +41,11 @@ check_untyped_defs = "True"
 warn_return_any = "True"
 warn_unused_ignores = "True"
 show_error_codes = "True"
-disable_error_code = ["arg-type", "no-any-return", "misc", "assignment", "import-not-found", "unused-ignore", "attr-defined"]
+disable_error_code = ["arg-type", "no-any-return", "misc", "assignment", "import-not-found", "unused-ignore", "attr-defined", "valid-type"]
 
 [tool.deptry]
 ignore = ["DEP001"]
+ignore_notebooks = true
 
 [tool.pytest.ini_options]
 testpaths = ["tests"]
diff --git a/tests/test_integration.py b/tests/test_integration.py
new file mode 100644
index 0000000..11cab19
--- /dev/null
+++ b/tests/test_integration.py
@@ -0,0 +1,49 @@
+import sys
+
+import pytest
+
+if sys.version_info >= (3, 9):
+    import asyncio
+    from typing import Literal, NamedTuple
+
+    from langchain_core.tools.structured import StructuredTool
+
+    from tool_parse.integrations.langchain import ExtendedStructuredTool
+
+    @pytest.fixture
+    def langchain_tools():
+        async def search_web(query: str, safe_search: bool = True):
+            """
+            Search the web.
+            :param query: Query to search for.
+            :param safe_search: If True, enable safe search.
+            """
+            return "not found"
+
+        class UserInfo(NamedTuple):
+            """User information"""
+
+            name: str
+            age: int
+            role: Literal["admin", "tester"] = "tester"
+
+        return [
+            StructuredTool.from_function(func=search_web),
+            ExtendedStructuredTool(func=UserInfo, name="user_info", schema_spec="claude"),
+        ]
+
+    def test_langchain_integration(langchain_tools):
+        async def __asyncio__():
+            assert len(langchain_tools) == 2
+
+            assert langchain_tools[0].name == "search_web"
+            assert (await langchain_tools[0].invoke(input={"query": "langchain"})) == "not found"
+
+            assert langchain_tools[1].name == "user_info"
+            assert "input_schema" in langchain_tools[1].json_schema["function"]
+            info = langchain_tools[1].invoke(input={"name": "synacktra", "age": "21"})
+            assert info.name == "synacktra"
+            assert info.age == 21
+            assert info.role == "tester"
+
+        asyncio.run(__asyncio__())
diff --git a/tool_parse/_types.py b/tool_parse/_types.py
index 738738f..b93d420 100644
--- a/tool_parse/_types.py
+++ b/tool_parse/_types.py
@@ -72,6 +72,11 @@ def check_subclass(__obj: t.Any, cls: t.Any):
     return isinstance(__obj, type) and isinstance(cls, type) and issubclass(__obj, cls)
 
 
+def fake_subclass_hook(cls, subcls):
+    """Fake subclass check to pass pydantic's validation error"""
+    return inspect.isclass(cls)
+
+
 class NameSpace(t.NamedTuple):
     globals: t.Dict[str, t.Any] | None
     locals: t.Dict[str, t.Any] | None
@@ -215,22 +220,24 @@ def extract_annotation_info(
 
 if sys.version_info >= (3, 10):
 
-    def get_signature(__f: Function | AsyncFunction):
+    def get_signature(__f: Function | AsyncFunction, *, namespace: NameSpace):
         """
         Get the signature of a function.
 
         :param __f: The function to get the signature for.
         """
-        return inspect.signature(__f, eval_str=True)
+        return inspect.signature(
+            __f, globals=namespace.globals, locals=namespace.locals, eval_str=True
+        )
 else:
 
-    def get_signature(__f: Function | AsyncFunction):
+    def get_signature(__f: Function | AsyncFunction, *, namespace: NameSpace):
         """
         Get the signature of a function.
 
         :param __f: The function to get the signature for.
         """
-        return inspect.signature(__f)
+        return inspect.signature(__f, globals=namespace.globals, locals=namespace.locals)
 
 
 def is_async(__fn) -> bool:
@@ -273,6 +280,8 @@ class TypedDictProtocol(t.Protocol):
         __required_keys__: t.ClassVar[t.FrozenSet[str]]
         __optional_keys__: t.ClassVar[t.FrozenSet[str]]
 
+    __subclasshook__ = classmethod(fake_subclass_hook)
+
 
 TypedDict = t.TypeVar("TypedDict", bound=TypedDictProtocol)
 """
@@ -306,6 +315,8 @@ class NamedTupleProtocol(t.Protocol[NTKeys]):
     _field_defaults: t.ClassVar[t.Dict[str, t.Any]]
     __annotations__: t.Dict[str, type]
 
+    __subclasshook__ = classmethod(fake_subclass_hook)
+
 
 NamedTuple = t.TypeVar("NamedTuple", bound=NamedTupleProtocol)
 """
diff --git a/tool_parse/compile.py b/tool_parse/compile.py
index 4e98e9f..5fc8e9d 100644
--- a/tool_parse/compile.py
+++ b/tool_parse/compile.py
@@ -85,7 +85,9 @@ def compile_function_object(
     args, kwargs = [], {}
     pos_args = arguments.pop("*args", [])
     p_args_len = len(pos_args)
-    for idx, (key, param) in enumerate(ts.get_signature(__fn).parameters.items()):
+    for idx, (key, param) in enumerate(
+        ts.get_signature(__fn, namespace=namespace).parameters.items()
+    ):
         is_default_none = param.default is None
         default = None if param.default is inspect._empty else param.default
         raw_value = pos_args[idx] if idx + 1 <= p_args_len else arguments.get(key)
diff --git a/tool_parse/integrations/__init__.py b/tool_parse/integrations/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/integrations/langchain_extended_structured_tool.py b/tool_parse/integrations/langchain.py
similarity index 64%
rename from integrations/langchain_extended_structured_tool.py
rename to tool_parse/integrations/langchain.py
index f6f1dd2..e1820bd 100644
--- a/integrations/langchain_extended_structured_tool.py
+++ b/tool_parse/integrations/langchain.py
@@ -1,24 +1,28 @@
 """
 Extended tool support for langchain-based integration.
-
-To run this file, run the following command: `pip install -U tool-parse langchain-core langchain-ollama duckduckgo-search`
 """
 
 from __future__ import annotations
 
 import asyncio
 import inspect
+import sys
 import typing as t
 import uuid
 from contextvars import copy_context
+from types import MethodType
 
 from langchain_core.callbacks import (
     AsyncCallbackManager,
     AsyncCallbackManagerForToolRun,
     CallbackManager,
     CallbackManagerForToolRun,
+    Callbacks,
 )
-from langchain_core.callbacks.manager import Callbacks
+from langchain_core.language_models import LanguageModelInput
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_core.messages import BaseMessage, ToolCall
+from langchain_core.runnables import Runnable
 from langchain_core.runnables.config import (
     RunnableConfig,
     _set_config_context,
@@ -36,9 +40,9 @@
 )
 from pydantic import PrivateAttr, ValidationError, model_validator
 
-from tool_parse import _types as tp_types
-from tool_parse.compile import compile_object
-from tool_parse.marshal import marshal_object
+from .. import _types as ts
+from ..compile import compile_object
+from ..marshal import marshal_object
 
 
 class ExtendedStructuredTool(BaseTool):
@@ -46,20 +50,28 @@ class ExtendedStructuredTool(BaseTool):
     """The unique name of the tool that clearly communicates its purpose."""
     description: str | None = None
     """Used to tell the model how/when/why to use the tool."""
-    func: t.Any
-    """The object to run when the tool is called.
-    `func` is used as attribute name because it used widely in other components in langchain."""
+    func: type[ts.TypedDict | ts.NamedTuple | ts.PydanticModel] | ts.AsyncFunction | ts.Function
+    """
+    The object to run when the tool is called.
+    `func` is used as attribute name because it used widely in other components in langchain.
+    """
+    schema_spec: t.Literal["base", "claude"] = "base"
+    """Schema spec to use. `base` works with most of the LLM."""
     _schema: dict = PrivateAttr
 
     @model_validator(mode="after")
     def validate_name_and_description(self):
         tool_schema = marshal_object(
-            self.func, spec="base", name=self.name, description=self.description
+            self.func,
+            spec=self.schema_spec,
+            name=self.name,
+            description=self.description,
+            frame=sys._getframe(1),
         )
-        if self.name is None:
+        if not self.name:
             self.name = tool_schema["function"]["name"]
 
-        if self.description is None:
+        if not self.description:
             if (fn_desc := tool_schema["function"].get("description")) is None:
                 raise ValueError("Function must have a docstring if description not provided.")
             self.description = fn_desc
@@ -68,14 +80,28 @@ def validate_name_and_description(self):
         return self
 
     @classmethod
-    def from_objects(cls, *__objs: t.Any, verbose: bool = False):
-        return [cls(func=obj, verbose=verbose) for obj in __objs]
+    def from_objects(
+        cls,
+        *__objs: type[ts.TypedDict | ts.NamedTuple | ts.PydanticModel]
+        | ts.AsyncFunction
+        | ts.Function,
+        schema_spec: t.Literal["base", "claude"] = "base",
+        **kwargs: t.Any,
+    ):
+        """
+        Create multiple tool at once.
+
+        :param __objs: The objects to add as tools.
+        :param schema_spec: Schema spec to use. `base` works with most of the LLM.
+        :returns: list of tools.
+        """
+        return [cls(func=obj, schema_spec=schema_spec, **kwargs) for obj in __objs]
 
     # --- Runnable ---
 
     async def ainvoke(
         self,
-        input: t.Union[str, t.Dict],  # noqa: A002
+        input: t.Union[str, dict, ToolCall],  # noqa: A002
         config: t.Optional[RunnableConfig] = None,
         **kwargs: t.Any,
     ) -> t.Any:
@@ -88,13 +114,14 @@ async def ainvoke(
     # --- Tool ---
 
     @property
-    def schema(self) -> tp_types.ToolSchema:
-        return getattr(self, "_schema", None)
+    def json_schema(self) -> ts.ToolSchema:
+        return getattr(self, "_schema", None)  # type: ignore[return-value]
 
     @property
     def args(self) -> t.Dict[str, t.Any]:
         """The tool's input arguments."""
-        return self.schema["function"]["parameters"]["properties"]
+        p_key = "parameters" if self.schema_spec == "base" else "input_schema"
+        return self.json_schema["function"][p_key]["properties"]  # type: ignore[literal-required]
 
     def _run(
         self,
@@ -109,7 +136,7 @@ def _run(
         if config_param := _get_runnable_config_param(self.func):
             kwargs[config_param] = config
 
-        return compile_object(self.func, arguments=kwargs)
+        return compile_object(self.func, arguments=kwargs, frame=sys._getframe(1))
 
     async def _arun(
         self,
@@ -125,8 +152,7 @@ async def _arun(
             if config_param := _get_runnable_config_param(self.func):
                 kwargs[config_param] = config
 
-            # Need to update tool-parse library so user can use await
-            return compile_object(self.func, arguments=kwargs)
+            return compile_object(self.func, arguments=kwargs, frame=sys._getframe(1))
 
         return await run_in_executor(
             None,
@@ -166,7 +192,6 @@ def run(  # noqa: C901
             self.metadata,
         )
 
-        # TODO: maybe also pass through run_manager is _run supports kwargs
         run_manager = callback_manager.on_tool_start(
             {"name": self.name, "description": self.description},
             str(tool_input),
@@ -274,7 +299,7 @@ async def arun(  # noqa: C901
                 tool_input[config_param] = config
             coro = context.run(self._arun, **tool_input)
             if asyncio_accepts_context():
-                response = await asyncio.create_task(coro, context=context)
+                response = await asyncio.create_task(coro, context=context)  # type: ignore[call-arg]
             else:
                 response = await coro
             if self.response_format == "content_and_artifact":
@@ -314,77 +339,61 @@ async def arun(  # noqa: C901
         return output
 
 
-if __name__ == "__main__":
-    from duckduckgo_search import DDGS
-    from langchain_core.messages import HumanMessage
-    from langchain_ollama.chat_models import ChatOllama
+ChatModel = t.TypeVar("ChatModel", bound=BaseChatModel)
 
-    async def search_text(
-        text: str,
-        *,
-        safe_search: bool = True,
-        backend: t.Literal["api", "html", "lite"] = "api",
-        max_results: int = 1,
-    ):
-        """
-        Search for text in the web.
-        :param text: Text to search for.
-        :param safe_search: If True, enable safe search.
-        :param backend: Backend to use for retrieving results.
-        :param max_results: Max results to return.
-        """
-        return DDGS().text(
-            keywords=text,
-            safesearch="on" if safe_search else "off",
-            backend=backend,
-            max_results=max_results,
-        )
 
-    class ProductInfo(t.NamedTuple):  # Can be t.TypedDict or pydantic.BaseModel
-        """
-        Information about the product.
-        :param name: Name of the product.
-        :param price: Price of the product.
-        :param in_stock: If the product is in stock.
-        """
+@t.overload
+def patch_chat_model(__model: ChatModel) -> ChatModel:
+    """
+    Patch a chat model instance to add support for `ExtendedStructuredTool`
 
-        name: str
-        price: float
-        in_stock: bool = False
+    :Example:
+    ```
+    from langchain_ollama.chat_models import ChatOllama
+    model = patch_chat_model(ChatOllama(model="<model-name>"))
+    ```
 
-    search_tool = ExtendedStructuredTool(func=search_text, description="Search the web.")
-    parse_product_tool = ExtendedStructuredTool(func=ProductInfo, name="product_info")
-    tools = [search_tool, parse_product_tool]
+    :param __model: Chat model instance to patch
+    :returns: Patched model instance
+    """
 
-    # OR tools = ExtendedStructuredTool.from_objects(search_text, ProductInfo)
 
-    model = ChatOllama(model="llama3-groq-tool-use").bind(tools=[tool.schema for tool in tools])
+@t.overload
+def patch_chat_model(__model: type[ChatModel]) -> type[ChatModel]:
+    """
+    Patch a chat model class to add support for `ExtendedStructuredTool`
 
-    def call_model(__query: str):
-        ai_message = model.invoke(input=[HumanMessage(content=__query)])
-        if ai_message.tool_calls:
-            metadata = ai_message.tool_calls[0]
-            print(f"name={metadata['name']!r}")
-            print(f"arguments={metadata['args']}")
-            if metadata["name"] == "search_text":
-                print(f"output={search_tool.invoke(input=metadata).content}")
-            elif metadata["name"] == "product_info":
-                print(f"output={parse_product_tool.invoke(input=metadata).content}")
-            else:
-                print("Tool not registered.")
-        else:
-            print(ai_message.content)
-        print("---" * 20)
+    :Example:
+    ```
+    from langchain_ollama.chat_models import ChatOllama
+    model = patch_chat_model(ChatOllama)(model="<model-name>")
+    ```
 
-    call_model("Search 5 sources for langgraph docs using lite backend")
-    call_model("Parse: Product RTX 4900, priced at $3.5k, is in stock.")
-    """
-    name='search_text'
-    arguments={'backend': 'lite', 'max_results': 5, 'text': 'langgraph docs'}
-    output=[{"title": "LangGraph - LangChain", "href": "https://www.langchain.com/langgraph", "body": "\n      While in beta, all LangSmith users on Plus and Enterprise plans can access LangGraph Cloud. Check out the docs. How are LangGraph and LangGraph Cloud different? LangGraph is a stateful, orchestration framework that brings added control to agent workflows. LangGraph Cloud is a service for deploying and scaling LangGraph applications, with a ...\n    "}, {"title": "️LangGraph - GitHub Pages", "href": "https://langchain-ai.github.io/langgraph/", "body": "\n      LangGraph is a framework for creating stateful, multi-actor applications with LLMs, using cycles, controllability, and persistence. Learn how to use LangGraph with examples, features, and integration with LangChain and LangSmith.\n    "}, {"title": "Introduction to LangGraph", "href": "https://academy.langchain.com/courses/intro-to-langgraph", "body": "\n      No. LangGraph is an orchestration framework for complex agentic systems and is more low-level and controllable than LangChain agents. On the other hand, LangChain provides a standard interface to interact with models and other components, useful for straight-forward chains and retrieval flows. How is LangGraph different from other agent frameworks?\n    "}, {"title": "Tutorials - GitHub Pages", "href": "https://langchain-ai.github.io/langgraph/tutorials/", "body": "\n      Learn how to use LangGraph, a framework for building language agents as graphs, through various examples and scenarios. Explore chatbots, code assistants, multi-agent systems, planning agents, reflection agents, and more.\n    "}, {"title": "Graphs - GitHub Pages", "href": "https://langchain-ai.github.io/langgraph/reference/graphs/", "body": "\n      Learn how to create and run graph workflows with LangGraph, a core abstraction of LangChain AI. See examples of StateGraph, ConditionalEdges, EntryPoint, FinishPoint, and Node methods.\n    "}]
-    ------------------------------------------------------------
-    name='product_info'
-    arguments={'in_stock': True, 'name': 'Product RTX 4900', 'price': 3500}
-    output=["Product RTX 4900", 3500.0, true] # Don't know why tuple is casted to list :>
-    ------------------------------------------------------------
+    :param __model: Chat model class to patch
+    :returns: Patched model class
     """
+
+
+def patch_chat_model(__model: ChatModel | type[ChatModel]):
+    class PatchedModel(BaseChatModel):
+        def bind_tools(
+            self,
+            tools: t.Sequence[t.Any],
+            **kwargs: t.Any,
+        ) -> Runnable[LanguageModelInput, BaseMessage]:
+            schema_list = []
+            for tool in tools:
+                if isinstance(tool, ExtendedStructuredTool):
+                    schema_list.append(tool.json_schema)
+                else:
+                    schema_list.extend(super().bind_tools(tools=[tool], **kwargs))
+            return self.bind(tools=schema_list, **kwargs)
+
+    if isinstance(__model, type):
+        # Patch the class
+        __model.bind_tools = PatchedModel.bind_tools
+    else:
+        # Patch the instance (pydantic is weird)
+        object.__setattr__(__model, "bind_tools", MethodType(PatchedModel.bind_tools, __model))
+
+    return __model
diff --git a/tool_parse/marshal.py b/tool_parse/marshal.py
index 30faa0b..e132340 100644
--- a/tool_parse/marshal.py
+++ b/tool_parse/marshal.py
@@ -79,7 +79,7 @@ def generate_function_metadata(
     :param description_map: A dictionary mapping parameter names to descriptions.
     :param namespace: Global and local nampespace for evaluating annotation.
     """
-    for label, param in ts.get_signature(__fn).parameters.items():
+    for label, param in ts.get_signature(__fn, namespace=namespace).parameters.items():
         annot_info = ts.extract_annotation_info(param.annotation, namespace=namespace)
         schema, is_optional = marshal_annotation(annot_info, namespace)
         if label in description_map: