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‎docs/sample_images/RAG/create-index-1.png‎

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‎docs/sample_images/RAG/create-index-2.png‎

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‎docs/sample_images/RAG/create-storage-bucket-1.png‎

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‎docs/sample_images/RAG/create-storage-bucket-2.png‎

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‎docs/sample_images/RAG/indexes.png‎

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‎docs/sample_images/RAG/storage_buckets.png‎

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‎pyproject.toml‎

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[project]
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name = "uipath-llamaindex"
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version = "0.0.25"
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version = "0.0.26"
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description = "UiPath LlamaIndex SDK"
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readme = { file = "README.md", content-type = "text/markdown" }
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requires-python = ">=3.10"
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url = "https://test.pypi.org/simple/"
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publish-url = "https://test.pypi.org/legacy/"
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explicit = true
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‎samples/travel-agent-RAG/pyproject.toml‎

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[project]
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name = "travel-helper-RAG-agent"
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version = "0.0.4"
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description = "UiPath LlamaIndex Simple HITL Agent"
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authors = [{ name = "Radu Mocanu", email = "radu.mocanu@uipath.com" }]
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readme = { file = "README.md", content-type = "text/markdown" }
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requires-python = ">=3.10"
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dependencies = [
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"uipath-llamaindex>=0.0.26",
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"llama-index-llms-openai>=0.2.2"
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]
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[[tool.uv.index]]
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name = "testpypi"
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url = "https://test.pypi.org/simple/"
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publish-url = "https://test.pypi.org/legacy/"
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explicit = true
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[tool.uv.sources]
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uipath-llamaindex = { index = "testpypi" }

‎samples/travel-helper-RAG-agent/README.md‎

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# Travel helper RAG agent
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## Overview
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The **Travel helper RAG agent** project demonstrates the implementation of a Retrieval-Augmented Generation (RAG) system using [UiPath Context Grounding](https://docs.uipath.com/automation-cloud/automation-cloud/latest/admin-guide/about-context-grounding).
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It consists of a Llama Index agent that utilizes two `ContextGroundingQueryEngines`: one to retrieve relevant data about the company's travel policy and another to assess an individual's personal travel preferences.
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## System Architecture
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### Agent Graph
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```mermaid
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flowchart TD
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step__done["_done"]:::stepStyle
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step_add_data_to_index["add_data_to_index"]:::stepStyle
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step_combine_and_interpret_answers["combine_and_interpret_answers"]:::stepStyle
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step_create_sub_questions_plan["create_sub_questions_plan"]:::stepStyle
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step_handle_sub_question["handle_sub_question"]:::stepStyle
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step_wait_for_index_ingestion["wait_for_index_ingestion"]:::stepStyle
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step_workflow_entrypoint["workflow_entrypoint"]:::stepStyle
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event_AddDataToIndexEvent([<p>AddDataToIndexEvent</p>]):::defaultEventStyle
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event_WaitForIndexIngestion([<p>WaitForIndexIngestion</p>]):::defaultEventStyle
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event_AnswerEvent([<p>AnswerEvent</p>]):::defaultEventStyle
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event_OutputEvent([<p>OutputEvent</p>]):::stopEventStyle
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event_QueryEvent([<p>QueryEvent</p>]):::defaultEventStyle
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event_SubQuestionEvent([<p>SubQuestionEvent</p>]):::defaultEventStyle
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event_CustomStartEvent([<p>CustomStartEvent</p>]):::defaultEventStyle
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event_OutputEvent --> step__done
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step_add_data_to_index --> event_WaitForIndexIngestion
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event_AddDataToIndexEvent --> step_add_data_to_index
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step_combine_and_interpret_answers --> event_OutputEvent
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event_AnswerEvent --> step_combine_and_interpret_answers
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step_create_sub_questions_plan --> event_SubQuestionEvent
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event_QueryEvent --> step_create_sub_questions_plan
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step_handle_sub_question --> event_AnswerEvent
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event_SubQuestionEvent --> step_handle_sub_question
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step_wait_for_index_ingestion --> event_QueryEvent
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step_wait_for_index_ingestion --> event_OutputEvent
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event_WaitForIndexIngestion --> step_wait_for_index_ingestion
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step_workflow_entrypoint --> event_QueryEvent
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step_workflow_entrypoint --> event_AddDataToIndexEvent
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event_CustomStartEvent --> step_workflow_entrypoint
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classDef stepStyle fill:#f2f0ff,line-height:1.2
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classDef externalStyle fill:#f2f0ff,line-height:1.2
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classDef defaultEventStyle fill-opacity:0
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classDef stopEventStyle fill:#bfb6fc
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classDef inputRequiredStyle fill:#f2f0ff,line-height:1.2
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```
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## Agent Responsibilities
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- Accepts a user query with details about an upcoming business trip.
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- Initializes two `QueryEngineTools`, each based on distinct context-grounding indexes.
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- Breaks down the initial query into multiple `sub-questions`.
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- Assigns ReAct agents to address each `sub-question`.
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- Combines the responses to generate a travel summary, including the permitted budget, employee preferences, and recommendations.
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## Steps to Execute Project on UiPath Cloud Platform
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### Prerequisites
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1. **Create two Orchestrator Storage Buckets**
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For this demo we'll create them in the _Shared_ folder.
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![navigate to Storage Buckets page](../../docs/sample_images/RAG/create-storage-bucket-1.png)
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![create storage bucket](../../docs/sample_images/RAG/create-storage-bucket-2.png)
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![storage_buckets](../../docs/sample_images/RAG/storage_buckets.png)
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2. **Create two Context Grounding Indexes**
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Next, we'll create two Context Grounding Indexes.
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![navigate to Indexes page](../../docs/sample_images/RAG/create-index-1.png)
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When configuring _Index General Details_, we'll select the previously created storage buckets as data sources.
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Example for `company_policy` index:
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![create index](../../docs/sample_images/RAG/create-index-2.png)
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![create index](../../docs/sample_images/RAG/indexes.png)
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That's it! Next, we'll deploy the agent.
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### Deploy the agents
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1. **Clone the Repository**
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```bash
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git clone https://github.com/UiPath/uipath-llamaindex-python.git
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```
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2. **Navigate to the Sample Directory**
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- **Windows:**
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```bash
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cd .\uipath-llamaindex-python\samples\travel-helper-RAG-agent
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```
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- **Unix-like Systems (Linux, macOS):**
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```bash
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cd ./uipath-llamaindex-python/samples/travel-helper-RAG-agent
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```
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3. **Create and Activate a Virtual Python Environment**
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```bash
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pip install uv
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uv venv -p 3.11 .venv
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.venv\Scripts\activate # Windows
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source .venv/bin/activate # Unix-like Systems
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uv sync
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```
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4. **Authenticate with UiPath Cloud Platform**
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```bash
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uipath auth
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```
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> **Note:** After successful authentication in the browser, select the tenant for publishing the agent package.
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```
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👇 Select tenant:
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0: DefaultTenant
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1: Tenant2
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2: Tenant3
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...
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Select tenant: 2
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```
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5. **Package and Publish Agents**
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```bash
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uipath pack
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uipath publish --my-workspace
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```
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```
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⠋ Publishing most recent package: travel-helper-RAG-agent.1.0.0.nupkg ...
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✓ Package published successfully!
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⠇ Getting process information ...
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🔗 Process configuration link: [LINK]
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💡 Use the link above to configure any environment variables
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```
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> Note: when publishing to _my-workspace_ a process will be auto-provisioned for you.
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6**Run the agent on UiPath Cloud Platform**
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We can run the agent from _Processes_ page
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![run-process-button](../../docs/sample_images/RAG/run-process-1.png)
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![run-process](../../docs/sample_images/RAG/run-process-2.png)
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> ℹ️ Here is how we can easily copy any folder path.
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![folder-path](../../docs/sample_images/RAG/folder-path.png)
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8. **Conclusions**
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We can monitor our agent execution from the job info panel.
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![job-info](../../docs/sample_images/RAG/job-info.png)
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_Quiz-generator-RAG-agent_ may choose to invoke researcher agent
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multiple times before creating the quiz. The output should look like this:
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![agent-output](../../docs/sample_images/RAG/output.png)
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We can also check the storage bucket content.
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![click-storage-bucket](../../docs/sample_images/RAG/click-storage-bucket.png)
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This is the information fetched by our _researcher agent_ that the _quiz generator_ used to create the quiz using RAG.
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We can download this file/files to analyze them.
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![storage-bucket-content](../../docs/sample_images/RAG/storage-bucket-content.png)
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## Local Debugging
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You can locally debug individual agents by invoking them directly:
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#### Researcher Agent
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Run the researcher agent with:
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```bash
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uipath run researcher-RAG-agent '{"search_instructions":"Need data about spanish cuisine", "index_name":"sample-RAG-index", "index_folder_path":"<index_folder_path>"}'
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# or use .json file input
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uipath run researcher-RAG-agent -f input.example/researcher-debug-input.json
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```
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> **_NOTE:_** This assumes that an index named _sample-RAG-index_ is created in the folder identified by the index_folder_path parameter.
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#### Quiz Generator Agent
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Run the quiz generator agent with:
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```bash
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uipath run quiz-generator-RAG-agent '{"quiz_topic":"spanish cuisine", "index_name":"sample-RAG-index", "index_folder_path":"<index_folder_path>"}'
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# or use .json file input
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uipath run quiz-generator-RAG-agent -f input.example/quiz-generator-debug-input.json
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```
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> **_NOTE:_** This assumes that an agent named _researcher-RAG-agent_ is created in the folder identified by the folder_path parameter passed to _InvokeProcess_ method.
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> <br> ℹ️ check [researcher-RAG-agent.py](src/agents/quiz-generator-RAG-agent.py) file.
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‎samples/travel-helper-RAG-agent/agent.mermaid‎

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flowchart TD
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step__done["_done"]:::stepStyle
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step_add_data_to_index["add_data_to_index"]:::stepStyle
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step_combine_and_interpret_answers["combine_and_interpret_answers"]:::stepStyle
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step_create_sub_questions_plan["create_sub_questions_plan"]:::stepStyle
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step_handle_sub_question["handle_sub_question"]:::stepStyle
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step_wait_for_index_ingestion["wait_for_index_ingestion"]:::stepStyle
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step_workflow_entrypoint["workflow_entrypoint"]:::stepStyle
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event_AddDataToIndexEvent([<p>AddDataToIndexEvent</p>]):::defaultEventStyle
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event_WaitForIndexIngestion([<p>WaitForIndexIngestion</p>]):::defaultEventStyle
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event_AnswerEvent([<p>AnswerEvent</p>]):::defaultEventStyle
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event_OutputEvent([<p>OutputEvent</p>]):::stopEventStyle
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event_QueryEvent([<p>QueryEvent</p>]):::defaultEventStyle
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event_SubQuestionEvent([<p>SubQuestionEvent</p>]):::defaultEventStyle
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event_CustomStartEvent([<p>CustomStartEvent</p>]):::defaultEventStyle
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event_OutputEvent --> step__done
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step_add_data_to_index --> event_WaitForIndexIngestion
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event_AddDataToIndexEvent --> step_add_data_to_index
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step_combine_and_interpret_answers --> event_OutputEvent
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event_AnswerEvent --> step_combine_and_interpret_answers
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step_create_sub_questions_plan --> event_SubQuestionEvent
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event_QueryEvent --> step_create_sub_questions_plan
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step_handle_sub_question --> event_AnswerEvent
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event_SubQuestionEvent --> step_handle_sub_question
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step_wait_for_index_ingestion --> event_QueryEvent
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step_wait_for_index_ingestion --> event_OutputEvent
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event_WaitForIndexIngestion --> step_wait_for_index_ingestion
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step_workflow_entrypoint --> event_QueryEvent
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step_workflow_entrypoint --> event_AddDataToIndexEvent
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event_CustomStartEvent --> step_workflow_entrypoint
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classDef stepStyle fill:#f2f0ff,line-height:1.2
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classDef externalStyle fill:#f2f0ff,line-height:1.2
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classDef defaultEventStyle fill-opacity:0
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classDef stopEventStyle fill:#bfb6fc
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classDef inputRequiredStyle fill:#f2f0ff,line-height:1.2

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