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docs: add Tilores provider and tools (#29244)
Description: This PR adds documentation for the Tilores provider and tools. Issue: closes #26320
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105
docs/docs/integrations/providers/tilores.ipynb
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docs/docs/integrations/providers/tilores.ipynb
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tilores\n",
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"\n",
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"[Tilores](https://tilores.io) is a platform that provides advanced entity resolution solutions for data integration and management. Using cutting-edge algorithms, machine learning, and a user-friendly interfaces, Tilores helps organizations match, resolve, and consolidate data from disparate sources, ensuring high-quality, consistent information."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Installation and Setup"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "y8ku6X96sebl"
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},
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"outputs": [],
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"source": [
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"%pip install --upgrade tilores-langchain"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To access Tilores, you need to [create and configure an instance](https://app.tilores.io). If you prefer to test out Tilores first, you can use the [read-only demo credentials](https://github.com/tilotech/identity-rag-customer-insights-chatbot?tab=readme-ov-file#1-configure-customer-data-access)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"from tilores import TiloresAPI\n",
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"\n",
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"os.environ[\"TILORES_API_URL\"] = \"<api-url>\"\n",
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"os.environ[\"TILORES_TOKEN_URL\"] = \"<token-url>\"\n",
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"os.environ[\"TILORES_CLIENT_ID\"] = \"<client-id>\"\n",
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"os.environ[\"TILORES_CLIENT_SECRET\"] = \"<client-secret>\"\n",
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"\n",
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"tilores = TiloresAPI.from_environ()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Please refer to the [Tilores documentation](https://docs.tilotech.io/tilores/publicsaaswalkthrough/) on how to create your own instance."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Toolkits\n",
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"\n",
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"You can use the [`TiloresTools`](/docs/integrations/tools/tilores) to query data from Tilores:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from tilores_langchain import TiloresTools"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "langchain",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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350
docs/docs/integrations/tools/tilores.ipynb
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docs/docs/integrations/tools/tilores.ipynb
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{
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"cells": [
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{
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"cell_type": "raw",
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"id": "10238e62-3465-4973-9279-606cbb7ccf16",
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"metadata": {},
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"source": [
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"---\n",
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"sidebar_label: Tilores\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a6f91f20",
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"metadata": {},
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"source": [
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"# Tilores\n",
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"\n",
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"This notebook covers how to get started with the [Tilores](/docs/integrations/providers/tilores) tools.\n",
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"For a more complex example you can checkout our [customer insights chatbot example](https://github.com/tilotech/identity-rag-customer-insights-chatbot).\n",
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"\n",
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"## Overview\n",
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"\n",
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"### Integration details\n",
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"\n",
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"| Class | Package | Serializable | JS support | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :---: |\n",
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"| TiloresTools | [tilores-langchain](https://pypi.org/project/tilores-langchain/) | ❌ | ❌ |  |\n",
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"\n",
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"## Setup\n",
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"\n",
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"The integration requires the following packages:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 72,
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"id": "f85b4089",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"%pip install --quiet -U tilores-langchain langchain"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b15e9266",
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"metadata": {},
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"source": [
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"### Credentials\n",
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"\n",
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"To access Tilores, you need to [create and configure an instance](https://app.tilores.io). If you prefer to test out Tilores first, you can use the [read-only demo credentials](https://github.com/tilotech/identity-rag-customer-insights-chatbot?tab=readme-ov-file#1-configure-customer-data-access)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 73,
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"id": "e0b178a2-8816-40ca-b57c-ccdd86dde9c9",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ[\"TILORES_API_URL\"] = \"<api-url>\"\n",
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"os.environ[\"TILORES_TOKEN_URL\"] = \"<token-url>\"\n",
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"os.environ[\"TILORES_CLIENT_ID\"] = \"<client-id>\"\n",
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"os.environ[\"TILORES_CLIENT_SECRET\"] = \"<client-secret>\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "1c97218f-f366-479d-8bf7-fe9f2f6df73f",
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"metadata": {},
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"source": [
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"## Instantiation\n",
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"\n",
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"Here we show how to instantiate an instance of the Tilores tools:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 74,
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"id": "8b3ddfe9-ca79-494c-a7ab-1f56d9407a64",
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"metadata": {},
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"outputs": [],
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"source": [
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"from tilores import TiloresAPI\n",
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"from tilores_langchain import TiloresTools\n",
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"\n",
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"tilores = TiloresAPI.from_environ()\n",
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"tilores_tools = TiloresTools(tilores)\n",
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"search_tool = tilores_tools.search_tool()\n",
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"edge_tool = tilores_tools.edge_tool()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "74147a1a",
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"metadata": {},
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"source": [
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"## Invocation\n",
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"\n",
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"The parameters for the `tilores_search` tool are dependent on the [configured schema](https://docs.tilotech.io/tilores/schema/) within Tilores. The following examples will use the schema for the demo instance with generated data.\n",
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"\n",
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"### [Invoke directly with args](/docs/concepts/tools)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "010aea95",
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"metadata": {},
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"source": [
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"The following example searches for a person called Sophie Müller in Berlin. The Tilores data contains multiple such persons and returns their known email addresses and phone numbers."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 75,
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"id": "65310a8b-eb0c-4d9e-a618-4f4abe2414fc",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Number of entities: 3\n",
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"Number of records: 3\n",
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"Email Addresses: ['s.mueller@newcompany.de', 'sophie.mueller@email.de']\n",
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"Phone Numbers: ['30987654', '30987654', '30987654']\n",
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"Number of records: 5\n",
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"Email Addresses: ['mueller.sophie@uni-berlin.de', 'sophie.m@newshipping.de', 's.mueller@newfinance.de']\n",
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"Phone Numbers: ['30135792', '30135792']\n",
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"Number of records: 2\n",
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"Email Addresses: ['s.mueller@company.de']\n",
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"Phone Numbers: ['30123456', '30123456']\n"
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]
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}
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],
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"source": [
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"result = search_tool.invoke(\n",
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" {\n",
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" \"searchParams\": {\n",
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" \"name\": \"Sophie Müller\",\n",
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" \"city\": \"Berlin\",\n",
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" },\n",
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" \"recordFieldsToQuery\": {\n",
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" \"email\": True,\n",
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" \"phone\": True,\n",
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" },\n",
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" }\n",
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")\n",
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"print(\"Number of entities:\", len(result[\"data\"][\"search\"][\"entities\"]))\n",
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"for entity in result[\"data\"][\"search\"][\"entities\"]:\n",
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" print(\"Number of records:\", len(entity[\"records\"]))\n",
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" print(\n",
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" \"Email Addresses:\",\n",
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" [record[\"email\"] for record in entity[\"records\"] if record.get(\"email\")],\n",
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" )\n",
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" print(\n",
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" \"Phone Numbers:\",\n",
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" [record[\"phone\"] for record in entity[\"records\"] if record.get(\"phone\")],\n",
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" )"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ab5c77ef",
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"metadata": {},
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"source": [
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"If we're interested how the records from the first entity are related, we can use the edge_tool. Note that the Tilores entity resolution engine figured out the relation between those records automatically. Please refer to the [edge documentation](https://docs.tilotech.io/tilores/rules/#edges) for more details."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 76,
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"id": "430e425c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Number of edges: 7\n",
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"Edges: ['e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6:f2g3h4i5-j6k7-l8m9-n0o1-p2q3r4s5t6u7:L1', 'e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6:g3h4i5j6-k7l8-m9n0-o1p2-q3r4s5t6u7v8:L4', 'e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6:f2g3h4i5-j6k7-l8m9-n0o1-p2q3r4s5t6u7:L2', 'f2g3h4i5-j6k7-l8m9-n0o1-p2q3r4s5t6u7:g3h4i5j6-k7l8-m9n0-o1p2-q3r4s5t6u7v8:L1', 'f2g3h4i5-j6k7-l8m9-n0o1-p2q3r4s5t6u7:g3h4i5j6-k7l8-m9n0-o1p2-q3r4s5t6u7v8:L4', 'e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6:g3h4i5j6-k7l8-m9n0-o1p2-q3r4s5t6u7v8:L1', 'e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6:f2g3h4i5-j6k7-l8m9-n0o1-p2q3r4s5t6u7:L4']\n"
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]
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}
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],
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"source": [
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"edge_result = edge_tool.invoke(\n",
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" {\"entityID\": result[\"data\"][\"search\"][\"entities\"][0][\"id\"]}\n",
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")\n",
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"edges = edge_result[\"data\"][\"entity\"][\"entity\"][\"edges\"]\n",
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"print(\"Number of edges:\", len(edges))\n",
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"print(\"Edges:\", edges)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d6e73897",
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"metadata": {},
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"source": [
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"### [Invoke with ToolCall](/docs/concepts/tools)\n",
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"\n",
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"We can also invoke the tool with a model-generated ToolCall, in which case a ToolMessage will be returned:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 77,
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"id": "f90e33a7",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"ToolMessage(content='{\"data\": {\"search\": {\"entities\": [{\"id\": \"9601cf3b-e85f-46ab-aaa8-ffb8b46f1c5b\", \"hits\": {\"c3d4e5f6-g7h8-i9j0-k1l2-m3n4o5p6q7r8\": [\"L1\"]}, \"records\": [{\"email\": \"\", \"phone\": \"30123456\"}, {\"email\": \"s.mueller@company.de\", \"phone\": \"30123456\"}]}, {\"id\": \"03da2e11-0aa2-4d17-8aaa-7b32c52decd9\", \"hits\": {\"e1f2g3h4-i5j6-k7l8-m9n0-o1p2q3r4s5t6\": [\"L1\"], \"g3h4i5j6-k7l8-m9n0-o1p2-q3r4s5t6u7v8\": [\"L1\"]}, \"records\": [{\"email\": \"s.mueller@newcompany.de\", \"phone\": \"30987654\"}, {\"email\": \"\", \"phone\": \"30987654\"}, {\"email\": \"sophie.mueller@email.de\", \"phone\": \"30987654\"}]}, {\"id\": \"4d896fb5-0d08-4212-a043-b5deb0347106\", \"hits\": {\"j6k7l8m9-n0o1-p2q3-r4s5-t6u7v8w9x0y1\": [\"L1\"], \"l8m9n0o1-p2q3-r4s5-t6u7-v8w9x0y1z2a3\": [\"L1\"], \"m9n0o1p2-q3r4-s5t6-u7v8-w9x0y1z2a3b4\": [\"L1\"], \"n0o1p2q3-r4s5-t6u7-v8w9-x0y1z2a3b4c5\": [\"L1\"]}, \"records\": [{\"email\": \"mueller.sophie@uni-berlin.de\", \"phone\": \"\"}, {\"email\": \"sophie.m@newshipping.de\", \"phone\": \"\"}, {\"email\": \"\", \"phone\": \"30135792\"}, {\"email\": \"\", \"phone\": \"\"}, {\"email\": \"s.mueller@newfinance.de\", \"phone\": \"30135792\"}]}]}}}', name='tilores_search', tool_call_id='1')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 77,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"# This is usually generated by a model, but we'll create a tool call directly for demo purposes.\n",
|
||||||
|
"model_generated_tool_call = {\n",
|
||||||
|
" \"args\": {\n",
|
||||||
|
" \"searchParams\": {\n",
|
||||||
|
" \"name\": \"Sophie Müller\",\n",
|
||||||
|
" \"city\": \"Berlin\",\n",
|
||||||
|
" },\n",
|
||||||
|
" \"recordFieldsToQuery\": {\n",
|
||||||
|
" \"email\": True,\n",
|
||||||
|
" \"phone\": True,\n",
|
||||||
|
" },\n",
|
||||||
|
" },\n",
|
||||||
|
" \"id\": \"1\",\n",
|
||||||
|
" \"name\": search_tool.name,\n",
|
||||||
|
" \"type\": \"tool_call\",\n",
|
||||||
|
"}\n",
|
||||||
|
"search_tool.invoke(model_generated_tool_call)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "659f9fbd-6fcf-445f-aa8c-72d8e60154bd",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Chaining\n",
|
||||||
|
"\n",
|
||||||
|
"We can use our tool in a chain by first binding it to a [tool-calling model](/docs/how_to/tool_calling/) and then calling it:\n",
|
||||||
|
"\n",
|
||||||
|
"import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
|
||||||
|
"\n",
|
||||||
|
"<ChatModelTabs customVarName=\"llm\" />\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "af3123ad-7a02-40e5-b58e-7d56e23e5830",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# | output: false\n",
|
||||||
|
"# | echo: false\n",
|
||||||
|
"\n",
|
||||||
|
"# !pip install -qU langchain langchain-openai\n",
|
||||||
|
"from langchain.chat_models import init_chat_model\n",
|
||||||
|
"\n",
|
||||||
|
"llm = init_chat_model(model=\"gpt-4o\", model_provider=\"openai\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "fdbf35b5-3aaf-4947-9ec6-48c21533fb95",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from langchain_core.prompts import ChatPromptTemplate\n",
|
||||||
|
"from langchain_core.runnables import RunnableConfig, chain\n",
|
||||||
|
"\n",
|
||||||
|
"prompt = ChatPromptTemplate(\n",
|
||||||
|
" [\n",
|
||||||
|
" (\"system\", \"You are a helpful assistant.\"),\n",
|
||||||
|
" (\"human\", \"{user_input}\"),\n",
|
||||||
|
" (\"placeholder\", \"{messages}\"),\n",
|
||||||
|
" ]\n",
|
||||||
|
")\n",
|
||||||
|
"\n",
|
||||||
|
"# specifying tool_choice will force the model to call this tool.\n",
|
||||||
|
"llm_with_tools = llm.bind_tools([search_tool], tool_choice=search_tool.name)\n",
|
||||||
|
"\n",
|
||||||
|
"llm_chain = prompt | llm_with_tools\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"@chain\n",
|
||||||
|
"def tool_chain(user_input: str, config: RunnableConfig):\n",
|
||||||
|
" input_ = {\"user_input\": user_input}\n",
|
||||||
|
" ai_msg = llm_chain.invoke(input_, config=config)\n",
|
||||||
|
" tool_msgs = search_tool.batch(ai_msg.tool_calls, config=config)\n",
|
||||||
|
" return llm_chain.invoke({**input_, \"messages\": [ai_msg, *tool_msgs]}, config=config)\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"tool_chain.invoke(\"Tell me the email addresses from Sophie Müller from Berlin.\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "4ac8146c",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## API reference\n",
|
||||||
|
"\n",
|
||||||
|
"For detailed documentation of all Tilores features and configurations head to the official documentation: https://docs.tilotech.io/tilores/"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "langchain",
|
||||||
|
"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": "3.12.8"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
@ -346,6 +346,11 @@ packages:
|
|||||||
path: .
|
path: .
|
||||||
repo: MehdiZare/langchain-fmp-data
|
repo: MehdiZare/langchain-fmp-data
|
||||||
downloads: 0
|
downloads: 0
|
||||||
|
- name: tilores-langchain
|
||||||
|
path: .
|
||||||
|
repo: tilotech/tilores-langchain
|
||||||
|
provider_page: tilores
|
||||||
|
downloads: 0
|
||||||
- name: langchain-pipeshift
|
- name: langchain-pipeshift
|
||||||
path: .
|
path: .
|
||||||
repo: pipeshift-org/langchain-pipeshift
|
repo: pipeshift-org/langchain-pipeshift
|
||||||
|
Loading…
Reference in New Issue
Block a user