Merge branch 'master' into cc/oai_responses

2025-08-20 01:49:51 +00:00 · 2025-03-12 04:23:20 -07:00 · 2025-03-12 04:23:20 -07:00 · 7b09f2fb1e
commit 7b09f2fb1e
parent deed6f680c 49bdd3b6fe
11 changed files with 1499 additions and 41 deletions
--- a/docs/docs/integrations/document_loaders/agentql.ipynb
+++ b/docs/docs/integrations/document_loaders/agentql.ipynb
@ -0,0 +1,265 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "wkUAAcGZNSJ3"
+      },
+      "source": [
+        "# AgentQLLoader\n",
+        "\n",
+        "[AgentQL](https://www.agentql.com/)'s document loader provides structured data extraction from any web page using an [AgentQL query](https://docs.agentql.com/agentql-query). AgentQL can be used across multiple languages and web pages without breaking over time and change.\n",
+        "\n",
+        "## Overview\n",
+        "\n",
+        "`AgentQLLoader` requires the following two parameters:\n",
+        "- `url`: The URL of the web page you want to extract data from.\n",
+        "- `query`: The AgentQL query to execute. Learn more about [how to write an AgentQL query in the docs](https://docs.agentql.com/agentql-query) or test one out in the [AgentQL Playground](https://dev.agentql.com/playground).\n",
+        "\n",
+        "Setting the following parameters are optional:\n",
+        "- `api_key`: Your AgentQL API key from [dev.agentql.com](https://dev.agentql.com). **`Optional`.**\n",
+        "- `timeout`: The number of seconds to wait for a request before timing out. **Defaults to `900`.**\n",
+        "- `is_stealth_mode_enabled`: Whether to enable experimental anti-bot evasion strategies. This feature may not work for all websites at all times. Data extraction may take longer to complete with this mode enabled. **Defaults to `False`.**\n",
+        "- `wait_for`: The number of seconds to wait for the page to load before extracting data. **Defaults to `0`.**\n",
+        "- `is_scroll_to_bottom_enabled`: Whether to scroll to bottom of the page before extracting data. **Defaults to `False`.**\n",
+        "- `mode`: `\"standard\"` uses deep data analysis, while `\"fast\"` trades some depth of analysis for speed and is adequate for most usecases. [Learn more about the modes in this guide.](https://docs.agentql.com/accuracy/standard-mode) **Defaults to `\"fast\"`.**\n",
+        "- `is_screenshot_enabled`: Whether to take a screenshot before extracting data. Returned in 'metadata' as a Base64 string. **Defaults to `False`.**\n",
+        "\n",
+        "AgentQLLoader is implemented with AgentQL's [REST API](https://docs.agentql.com/rest-api/api-reference)\n",
+        "\n",
+        "### Integration details\n",
+        "\n",
+        "| Class | Package | Local | Serializable | JS support |\n",
+        "| :--- | :--- | :---: | :---: |  :---: |\n",
+        "| AgentQLLoader| langchain-agentql | ✅ | ❌ | ❌ |\n",
+        "\n",
+        "### Loader features\n",
+        "| Source | Document Lazy Loading | Native Async Support\n",
+        "| :---: | :---: | :---: |\n",
+        "| AgentQLLoader | ✅ | ❌ |"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CaKa2QrnwPXq"
+      },
+      "source": [
+        "## Setup\n",
+        "\n",
+        "To use the AgentQL Document Loader, you will need to configure the `AGENTQL_API_KEY` environment variable, or use the `api_key` parameter. You can acquire an API key from our [Dev Portal](https://dev.agentql.com)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mZNJvUQBNSJ5"
+      },
+      "source": [
+        "### Installation\n",
+        "\n",
+        "Install **langchain-agentql**."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "IblRoJJDNSJ5"
+      },
+      "outputs": [],
+      "source": [
+        "%pip install -qU langchain_agentql"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SNsUT60YvfCm"
+      },
+      "source": [
+        "### Set Credentials"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "2D1EN7Egvk1c"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "\n",
+        "os.environ[\"AGENTQL_API_KEY\"] = \"YOUR_AGENTQL_API_KEY\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "D4hnJV_6NSJ5"
+      },
+      "source": [
+        "## Initialization\n",
+        "\n",
+        "Next instantiate your model object:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "id": "oMJdxL_KNSJ5"
+      },
+      "outputs": [],
+      "source": [
+        "from langchain_agentql.document_loaders import AgentQLLoader\n",
+        "\n",
+        "loader = AgentQLLoader(\n",
+        "    url=\"https://www.agentql.com/blog\",\n",
+        "    query=\"\"\"\n",
+        "    {\n",
+        "        posts[] {\n",
+        "            title\n",
+        "            url\n",
+        "            date\n",
+        "            author\n",
+        "        }\n",
+        "    }\n",
+        "    \"\"\",\n",
+        "    is_scroll_to_bottom_enabled=True,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SRxIOx90NSJ5"
+      },
+      "source": [
+        "## Load"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "bNnnCZ1oNSJ5",
+        "outputId": "d0eb8cb4-9742-4f0c-80f1-0509a3af1808"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Document(metadata={'request_id': 'bdb9dbe7-8a7f-427f-bc16-839ccc02cae6', 'generated_query': None, 'screenshot': None}, page_content=\"{'posts': [{'title': 'Launch Week Recap—make the web AI-ready', 'url': 'https://www.agentql.com/blog/2024-launch-week-recap', 'date': 'Nov 18, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Accurate data extraction from PDFs and images with AgentQL', 'url': 'https://www.agentql.com/blog/accurate-data-extraction-pdfs-images', 'date': 'Feb 1, 2025', 'author': 'Rachel-Lee Nabors'}, {'title': 'Introducing Scheduled Scraping Workflows', 'url': 'https://www.agentql.com/blog/scheduling', 'date': 'Dec 2, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Updates to Our Pricing Model', 'url': 'https://www.agentql.com/blog/2024-pricing-update', 'date': 'Nov 19, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Get data from any page: AgentQL’s REST API Endpoint—Launch week day 5', 'url': 'https://www.agentql.com/blog/data-rest-api', 'date': 'Nov 15, 2024', 'author': 'Rachel-Lee Nabors'}]}\")"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "docs = loader.load()\n",
+        "docs[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "wtPMNh72NSJ5",
+        "outputId": "59d529a4-3c22-445c-f5cf-dc7b24168906"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'request_id': 'bdb9dbe7-8a7f-427f-bc16-839ccc02cae6', 'generated_query': None, 'screenshot': None}\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(docs[0].metadata)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7RMuEwl4NSJ5"
+      },
+      "source": [
+        "## Lazy Load\n",
+        "\n",
+        "`AgentQLLoader` currently only loads one `Document` at a time. Therefore, `load()` and `lazy_load()` behave the same:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "FIYddZBONSJ5",
+        "outputId": "c39a7a6d-bc52-4ef9-b36f-e1d138590b79"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[Document(metadata={'request_id': '06273abd-b2ef-4e15-b0ec-901cba7b4825', 'generated_query': None, 'screenshot': None}, page_content=\"{'posts': [{'title': 'Launch Week Recap—make the web AI-ready', 'url': 'https://www.agentql.com/blog/2024-launch-week-recap', 'date': 'Nov 18, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Accurate data extraction from PDFs and images with AgentQL', 'url': 'https://www.agentql.com/blog/accurate-data-extraction-pdfs-images', 'date': 'Feb 1, 2025', 'author': 'Rachel-Lee Nabors'}, {'title': 'Introducing Scheduled Scraping Workflows', 'url': 'https://www.agentql.com/blog/scheduling', 'date': 'Dec 2, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Updates to Our Pricing Model', 'url': 'https://www.agentql.com/blog/2024-pricing-update', 'date': 'Nov 19, 2024', 'author': 'Rachel-Lee Nabors'}, {'title': 'Get data from any page: AgentQL’s REST API Endpoint—Launch week day 5', 'url': 'https://www.agentql.com/blog/data-rest-api', 'date': 'Nov 15, 2024', 'author': 'Rachel-Lee Nabors'}]}\")]"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "pages = [doc for doc in loader.lazy_load()]\n",
+        "pages"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For more information on how to use this integration, please refer to the [git repo](https://github.com/tinyfish-io/agentql-integrations/tree/main/langchain) or the [langchain integration documentation](https://docs.agentql.com/integrations/langchain)"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
--- a/docs/docs/integrations/providers/agentql.mdx
+++ b/docs/docs/integrations/providers/agentql.mdx
@ -0,0 +1,35 @@
+# AgentQL
+
+[AgentQL](https://www.agentql.com/) provides web interaction and structured data extraction from any web page using an [AgentQL query](https://docs.agentql.com/agentql-query) or a Natural Language prompt. AgentQL can be used across multiple languages and web pages without breaking over time and change.
+
+## Installation and Setup
+
+Install the integration package:
+
+```bash
+pip install langchain-agentql
+```
+
+## API Key
+
+Get an API Key from our [Dev Portal](https://dev.agentql.com/) and add it to your environment variables:
+```
+export AGENTQL_API_KEY="your-api-key-here"
+```
+
+## DocumentLoader
+AgentQL's document loader provides structured data extraction from any web page using an AgentQL query.
+
+```python
+from langchain_agentql.document_loaders import AgentQLLoader
+```
+See our [document loader documentation and usage example](/docs/integrations/document_loaders/agentql).
+
+## Tools and Toolkits
+AgentQL tools provides web interaction and structured data extraction from any web page using an AgentQL query or a Natural Language prompt.
+
+```python
+from langchain_agentql.tools import ExtractWebDataTool, ExtractWebDataBrowserTool, GetWebElementBrowserTool
+from langchain_agentql import AgentQLBrowserToolkit
+```
+See our [tools documentation and usage example](/docs/integrations/tools/agentql).
--- a/docs/docs/integrations/tools/agentql.ipynb
+++ b/docs/docs/integrations/tools/agentql.ipynb
--- a/docs/scripts/tool_feat_table.py
+++ b/docs/scripts/tool_feat_table.py
@ -147,6 +147,11 @@ WEBBROWSING_TOOL_FEAT_TABLE = {
        "interactions": True,
        "pricing": "40 free requests/day",
    },
+    "AgentQL Toolkit": {
+        "link": "/docs/integrations/tools/agentql",
+        "interactions": True,
+        "pricing": "Free trial, with pay-as-you-go and flat rate plans after",
+    },
 }

 DATABASE_TOOL_FEAT_TABLE = {
--- a/docs/src/theme/FeatureTables.js
+++ b/docs/src/theme/FeatureTables.js
@ -819,6 +819,13 @@ const FEATURE_TABLES = {
                source: "Platform for running and scaling headless browsers, can be used to scrape/crawl any site",
                api: "API",
                apiLink: "https://python.langchain.com/docs/integrations/document_loaders/hyperbrowser/"
+            },
+            {
+                name: "AgentQL",
+                link: "agentql",
+                source: "Web interaction and structured data extraction from any web page using an AgentQL query or a Natural Language prompt",
+                api: "API",
+                apiLink: "https://python.langchain.com/docs/integrations/document_loaders/agentql/"
            }
        ]
    },
--- a/libs/core/langchain_core/runnables/graph_mermaid.py
+++ b/libs/core/langchain_core/runnables/graph_mermaid.py
@ -56,37 +56,50 @@ def draw_mermaid(
        if with_styles
        else "graph TD;\n"
    )
+    # Group nodes by subgraph
+    subgraph_nodes: dict[str, dict[str, Node]] = {}
+    regular_nodes: dict[str, Node] = {}

-    if with_styles:
-        # Node formatting templates
-        default_class_label = "default"
-        format_dict = {default_class_label: "{0}({1})"}
-        if first_node is not None:
-            format_dict[first_node] = "{0}([{1}]):::first"
-        if last_node is not None:
-            format_dict[last_node] = "{0}([{1}]):::last"
+    for key, node in nodes.items():
+        if ":" in key:
+            # For nodes with colons, add them only to their deepest subgraph level
+            prefix = ":".join(key.split(":")[:-1])
+            subgraph_nodes.setdefault(prefix, {})[key] = node
+        else:
+            regular_nodes[key] = node

-        # Add nodes to the graph
-        for key, node in nodes.items():
-            node_name = node.name.split(":")[-1]
+    # Node formatting templates
+    default_class_label = "default"
+    format_dict = {default_class_label: "{0}({1})"}
+    if first_node is not None:
+        format_dict[first_node] = "{0}([{1}]):::first"
+    if last_node is not None:
+        format_dict[last_node] = "{0}([{1}]):::last"
+
+    def render_node(key: str, node: Node, indent: str = "\t") -> str:
+        """Helper function to render a node with consistent formatting."""
+        node_name = node.name.split(":")[-1]
+        label = (
+            f"<p>{node_name}</p>"
+            if node_name.startswith(tuple(MARKDOWN_SPECIAL_CHARS))
+            and node_name.endswith(tuple(MARKDOWN_SPECIAL_CHARS))
+            else node_name
+        )
+        if node.metadata:
            label = (
-                f"<p>{node_name}</p>"
-                if node_name.startswith(tuple(MARKDOWN_SPECIAL_CHARS))
-                and node_name.endswith(tuple(MARKDOWN_SPECIAL_CHARS))
-                else node_name
+                f"{label}<hr/><small><em>"
+                + "\n".join(f"{k} = {value}" for k, value in node.metadata.items())
+                + "</em></small>"
            )
-            if node.metadata:
-                label = (
-                    f"{label}<hr/><small><em>"
-                    + "\n".join(
-                        f"{key} = {value}" for key, value in node.metadata.items()
-                    )
-                    + "</em></small>"
-                )
-            node_label = format_dict.get(key, format_dict[default_class_label]).format(
-                _escape_node_label(key), label
-            )
-            mermaid_graph += f"\t{node_label}\n"
+        node_label = format_dict.get(key, format_dict[default_class_label]).format(
+            _escape_node_label(key), label
+        )
+        return f"{indent}{node_label}\n"
+
+    # Add non-subgraph nodes to the graph
+    if with_styles:
+        for key, node in regular_nodes.items():
+            mermaid_graph += render_node(key, node)

    # Group edges by their common prefixes
    edge_groups: dict[str, list[Edge]] = {}
@ -116,6 +129,11 @@ def draw_mermaid(
            seen_subgraphs.add(subgraph)
            mermaid_graph += f"\tsubgraph {subgraph}\n"

+            # Add nodes that belong to this subgraph
+            if with_styles and prefix in subgraph_nodes:
+                for key, node in subgraph_nodes[prefix].items():
+                    mermaid_graph += render_node(key, node)
+
        for edge in edges:
            source, target = edge.source, edge.target

@ -156,11 +174,25 @@ def draw_mermaid(
    # Start with the top-level edges (no common prefix)
    add_subgraph(edge_groups.get("", []), "")

-    # Add remaining subgraphs
+    # Add remaining subgraphs with edges
    for prefix in edge_groups:
        if ":" in prefix or prefix == "":
            continue
        add_subgraph(edge_groups[prefix], prefix)
+        seen_subgraphs.add(prefix)
+
+    # Add empty subgraphs (subgraphs with no internal edges)
+    if with_styles:
+        for prefix in subgraph_nodes:
+            if ":" not in prefix and prefix not in seen_subgraphs:
+                mermaid_graph += f"\tsubgraph {prefix}\n"
+
+                # Add nodes that belong to this subgraph
+                for key, node in subgraph_nodes[prefix].items():
+                    mermaid_graph += render_node(key, node)
+
+                mermaid_graph += "\tend\n"
+                seen_subgraphs.add(prefix)

    # Add custom styles for nodes
    if with_styles:
--- a/libs/core/pyproject.toml
+++ b/libs/core/pyproject.toml
@ -17,7 +17,7 @@ dependencies = [
    "pydantic<3.0.0,>=2.7.4; python_full_version >= \"3.12.4\"",
 ]
 name = "langchain-core"
-version = "0.3.43"
+version = "0.3.44"
 description = "Building applications with LLMs through composability"
 readme = "README.md"

--- a/libs/core/tests/unit_tests/runnables/snapshots/test_graph.ambr
+++ b/libs/core/tests/unit_tests/runnables/snapshots/test_graph.ambr
@ -5,9 +5,6 @@
  graph TD;
  	__start__([<p>__start__</p>]):::first
  	parent_1(parent_1)
-  	child_child_1_grandchild_1(grandchild_1)
-  	child_child_1_grandchild_2(grandchild_2<hr/><small><em>__interrupt = before</em></small>)
-  	child_child_2(child_2)
  	parent_2(parent_2)
  	__end__([<p>__end__</p>]):::last
  	__start__ --> parent_1;
@ -15,8 +12,11 @@
  	parent_1 --> child_child_1_grandchild_1;
  	parent_2 --> __end__;
  	subgraph child
+  	child_child_2(child_2)
  	child_child_1_grandchild_2 --> child_child_2;
  	subgraph child_1
+  	child_child_1_grandchild_1(grandchild_1)
+  	child_child_1_grandchild_2(grandchild_2<hr/><small><em>__interrupt = before</em></small>)
  	child_child_1_grandchild_1 --> child_child_1_grandchild_2;
  	end
  	end
@ -32,10 +32,6 @@
  graph TD;
  	__start__([<p>__start__</p>]):::first
  	parent_1(parent_1)
-  	child_child_1_grandchild_1(grandchild_1)
-  	child_child_1_grandchild_1_greatgrandchild(greatgrandchild)
-  	child_child_1_grandchild_2(grandchild_2<hr/><small><em>__interrupt = before</em></small>)
-  	child_child_2(child_2)
  	parent_2(parent_2)
  	__end__([<p>__end__</p>]):::last
  	__start__ --> parent_1;
@ -43,10 +39,14 @@
  	parent_1 --> child_child_1_grandchild_1;
  	parent_2 --> __end__;
  	subgraph child
+  	child_child_2(child_2)
  	child_child_1_grandchild_2 --> child_child_2;
  	subgraph child_1
+  	child_child_1_grandchild_1(grandchild_1)
+  	child_child_1_grandchild_2(grandchild_2<hr/><small><em>__interrupt = before</em></small>)
  	child_child_1_grandchild_1_greatgrandchild --> child_child_1_grandchild_2;
  	subgraph grandchild_1
+  	child_child_1_grandchild_1_greatgrandchild(greatgrandchild)
  	child_child_1_grandchild_1 --> child_child_1_grandchild_1_greatgrandchild;
  	end
  	end
@ -1996,10 +1996,6 @@
  graph TD;
  	__start__([<p>__start__</p>]):::first
  	outer_1(outer_1)
-  	inner_1_inner_1(inner_1)
-  	inner_1_inner_2(inner_2<hr/><small><em>__interrupt = before</em></small>)
-  	inner_2_inner_1(inner_1)
-  	inner_2_inner_2(inner_2)
  	outer_2(outer_2)
  	__end__([<p>__end__</p>]):::last
  	__start__ --> outer_1;
@ -2009,9 +2005,13 @@
  	outer_1 --> inner_2_inner_1;
  	outer_2 --> __end__;
  	subgraph inner_1
+  	inner_1_inner_1(inner_1)
+  	inner_1_inner_2(inner_2<hr/><small><em>__interrupt = before</em></small>)
  	inner_1_inner_1 --> inner_1_inner_2;
  	end
  	subgraph inner_2
+  	inner_2_inner_1(inner_1)
+  	inner_2_inner_2(inner_2)
  	inner_2_inner_1 --> inner_2_inner_2;
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
@ -2020,6 +2020,23 @@
  
  '''
 # ---
+# name: test_single_node_subgraph_mermaid[mermaid]
+  '''
+  %%{init: {'flowchart': {'curve': 'linear'}}}%%
+  graph TD;
+  	__start__([<p>__start__</p>]):::first
+  	__end__([<p>__end__</p>]):::last
+  	__start__ --> sub_meow;
+  	sub_meow --> __end__;
+  	subgraph sub
+  	sub_meow(meow)
+  	end
+  	classDef default fill:#f2f0ff,line-height:1.2
+  	classDef first fill-opacity:0
+  	classDef last fill:#bfb6fc
+  
+  '''
+# ---
 # name: test_trim
  dict({
    'edges': list([
--- a/libs/core/tests/unit_tests/runnables/test_graph.py
+++ b/libs/core/tests/unit_tests/runnables/test_graph.py
@ -448,6 +448,23 @@ def test_triple_nested_subgraph_mermaid(snapshot: SnapshotAssertion) -> None:
    assert graph.draw_mermaid() == snapshot(name="mermaid")


+def test_single_node_subgraph_mermaid(snapshot: SnapshotAssertion) -> None:
+    empty_data = BaseModel
+    nodes = {
+        "__start__": Node(
+            id="__start__", name="__start__", data=empty_data, metadata=None
+        ),
+        "sub:meow": Node(id="sub:meow", name="meow", data=empty_data, metadata=None),
+        "__end__": Node(id="__end__", name="__end__", data=empty_data, metadata=None),
+    }
+    edges = [
+        Edge(source="__start__", target="sub:meow", data=None, conditional=False),
+        Edge(source="sub:meow", target="__end__", data=None, conditional=False),
+    ]
+    graph = Graph(nodes, edges)
+    assert graph.draw_mermaid() == snapshot(name="mermaid")
+
+
 def test_runnable_get_graph_with_invalid_input_type() -> None:
    """Test that error isn't raised when getting graph with invalid input type."""

--- a/libs/core/uv.lock
+++ b/libs/core/uv.lock
@ -935,7 +935,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "0.3.43"
+version = "0.3.44"
 source = { editable = "." }
 dependencies = [
    { name = "jsonpatch" },
--- a/libs/packages.yml
+++ b/libs/packages.yml
@ -513,3 +513,6 @@ packages:
 - name: langchain-opengradient
  path: .
  repo: OpenGradient/og-langchain
+- name: langchain-agentql
+  path: langchain
+  repo: tinyfish-io/agentql-integrations