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feat(tools): added google maps and DSPy
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apps/docs/components/icons.tsx

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apps/docs/components/ui/icon-mapping.ts

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DiscordIcon,
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DocumentIcon,
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DropboxIcon,
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DsPyIcon,
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DuckDuckGoIcon,
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DynamoDBIcon,
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ElasticsearchIcon,
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GoogleFormsIcon,
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GoogleGroupsIcon,
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GoogleIcon,
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GoogleMapsIcon,
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GoogleSheetsIcon,
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GoogleSlidesIcon,
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GoogleVaultIcon,
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datadog: DatadogIcon,
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discord: DiscordIcon,
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dropbox: DropboxIcon,
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dspy: DsPyIcon,
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duckduckgo: DuckDuckGoIcon,
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dynamodb: DynamoDBIcon,
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elasticsearch: ElasticsearchIcon,
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google_drive: GoogleDriveIcon,
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google_forms: GoogleFormsIcon,
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google_groups: GoogleGroupsIcon,
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google_maps: GoogleMapsIcon,
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google_search: GoogleIcon,
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google_sheets_v2: GoogleSheetsIcon,
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google_slides: GoogleSlidesIcon,

apps/docs/content/docs/en/tools/calcom.mdx

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---
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title: CalCom
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title: Cal Com
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description: Manage Cal.com bookings, event types, schedules, and availability
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---
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---
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title: DSPy
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description: Run predictions using self-hosted DSPy programs
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---
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import { BlockInfoCard } from "@/components/ui/block-info-card"
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<BlockInfoCard
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type="dspy"
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color="#1E293B"
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/>
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{/* MANUAL-CONTENT-START:intro */}
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[DSPy](https://github.com/stanford-oval/dspy) is an open-source framework for programming—rather than prompting—language models. DSPy enables you to build interpretable and modular LLM-powered agents using Python functions, structured modules, and declarative signatures, making it easy to compose, debug, and reliably deploy language model applications.
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With DSPy in Sim, you can:
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- **Run custom predictions**: Connect your self-hosted DSPy server and invoke prediction endpoints for a variety of natural language tasks.
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- **Chain of Thought and ReAct reasoning**: Leverage advanced DSPy modules for step-by-step reasoning, multi-turn dialogs, and action-observation loops.
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- **Integrate with your workflows**: Automate LLM predictions and reasoning as part of any Sim automation or agent routine.
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- **Provide custom endpoints and context**: Flexibly call your own DSPy-powered APIs with custom authentication, endpoints, input fields, and context.
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These features let your Sim agents access modular, interpretable LLM-based programs for tasks like question answering, document analysis, decision support, and more—where you remain in control of the model, data, and logic.
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{/* MANUAL-CONTENT-END */}
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## Usage Instructions
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Integrate with your self-hosted DSPy programs for LLM-powered predictions. Supports Predict, Chain of Thought, and ReAct agents. DSPy is the framework for programming—not prompting—language models.
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## Tools
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### `dspy_predict`
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Run a prediction using a self-hosted DSPy program endpoint
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `baseUrl` | string | Yes | Base URL of the DSPy server \(e.g., https://your-dspy-server.com\) |
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| `apiKey` | string | No | API key for authentication \(if required by your server\) |
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| `endpoint` | string | No | API endpoint path \(defaults to /predict\) |
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| `input` | string | Yes | The input text to send to the DSPy program |
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| `inputField` | string | No | Name of the input field expected by the DSPy program \(defaults to "text"\) |
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| `context` | string | No | Additional context to provide to the DSPy program |
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| `additionalInputs` | json | No | Additional key-value pairs to include in the request body |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `answer` | string | The main output/answer from the DSPy program |
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| `reasoning` | string | The reasoning or rationale behind the answer \(if available\) |
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| `status` | string | Response status from the DSPy server \(success or error\) |
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| `rawOutput` | json | The complete raw output from the DSPy program \(result.toDict\(\)\) |
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### `dspy_chain_of_thought`
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `answer` | string | The answer/output from the DSPy program |
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| `reasoning` | string | The reasoning or rationale behind the answer |
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| `trajectory` | json | Step-by-step trajectory for ReAct \(thoughts, actions, observations\) |
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| `status` | string | Response status from the DSPy server |
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| `rawOutput` | json | Complete raw output from the DSPy program |
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### `dspy_react`
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Run a ReAct agent using a self-hosted DSPy ReAct program endpoint for multi-step reasoning and action
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `baseUrl` | string | Yes | Base URL of the DSPy server \(e.g., https://your-dspy-server.com\) |
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| `apiKey` | string | No | API key for authentication \(if required by your server\) |
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| `endpoint` | string | No | API endpoint path \(defaults to /predict\) |
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| `task` | string | Yes | The task or question for the ReAct agent to work on |
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| `context` | string | No | Additional context to provide for the task |
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| `maxIterations` | number | No | Maximum number of reasoning iterations \(defaults to server setting\) |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `answer` | string | The final answer or result from the ReAct agent |
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| `reasoning` | string | The overall reasoning summary from the agent |
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| `trajectory` | array | The step-by-step trajectory of thoughts, actions, and observations |
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|`thought` | string | The reasoning thought at this step |
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|`toolName` | string | The name of the tool/action called |
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|`toolArgs` | json | Arguments passed to the tool |
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|`observation` | string | The observation/result from the tool execution |
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| `status` | string | Response status from the DSPy server \(success or error\) |
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| `rawOutput` | json | The complete raw output from the DSPy program \(result.toDict\(\)\) |
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apps/docs/content/docs/en/tools/google_groups.mdx

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color="#E8F0FE"
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/>
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{/* MANUAL-CONTENT-START:intro */}
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[Google Groups](https://groups.google.com) is part of Google Workspace, providing email-based group communication, collaboration, and access control for teams and organizations. Google Groups lets you create mailing lists, manage membership, and control permissions for both internal and external users.
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This page explains how you can use Sim to automate the management of Google Groups in your workflows. With Sim, agents can create and configure groups, add or remove members, update group settings, and keep directory lists up-to-date automatically—ideal for onboarding workflows, syncing IT systems, or dynamically managing project teams.
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With Google Groups, you can:
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- **Centralize communications**: Create team or project mailing lists for group conversations
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- **Manage group membership**: Add, remove, or update members with granular roles (owner, manager, member)
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- **Control access**: Manage who can view, post, or join; set permissions for public/private visibility
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- **Collaborate across teams**: Streamline communication and document sharing via group-based access
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- **Automate IT tasks**: Use Sim to keep group memberships current as teams change
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In Sim, the Google Groups integration gives your agents API-driven control to automate common administrative tasks. Connect directly to your Google Workspace domain to add users to groups, manage lists, audit group settings, and ensure your organization’s access controls are always up-to-date—without manual overhead.
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{/* MANUAL-CONTENT-END */}
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## Usage Instructions
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Connect to Google Workspace to create, update, and manage groups and their members using the Admin SDK Directory API.

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