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Movie Recommendation Chatbot Workflow

Movie Recommendation Chatbot Workflow is a 25-node automation blueprint connecting GitHub, OpenAI, Qdrant. Inspect its trigger, execution graph, branches, and implementation requirements.

GitHubOpenAIQdrant

Interactive system map

Follow the runtime. Inspect what supports it.

Solid horizontal paths show main-channel execution. Violet dependencies sit beneath the exact step they configure or empower.

25

Nodes

24

Links

3

Run groups

Connected tools

3 integrations

  • GitHub
  • OpenAI
  • Qdrant

Canvas controls

Fit wide systems, then zoom into any run group.

Movie Recommendation Chatbot Workflow execution lanes3 run groups containing 25 workflow nodes and 24 visible links. Solid horizontal lines are main-channel runtime links. Violet dashed lines connect typed dependencies beneath the runtime step they support. Focus any node to inspect its immediate path.When clicking ‘Test workflow’. trigger node, manualTrigger. 0 incoming and 1 outgoing connections.STARTWhen clicking ‘Test workf…TRIGGERMANUALTRIGGER0 IN / 1 OUTGitHub. GitHub node, github. 1 incoming and 1 outgoing connections.STEP 02GitHubGITHUBGITHUB1 IN / 1 OUTExtract from File. integration node, extractFromFile. 1 incoming and 1 outgoing connections.STEP 03Extract from FileINTEGRATIONEXTRACTFROMFILE1 IN / 1 OUTQdrant Vector Store. ai node, vectorStoreQdrant. 3 incoming and 0 outgoing connections.OUTCOMEQdrant Vector StoreAIVECTORSTOREQDRANT3 IN / 0 OUTEmbeddings OpenAI. OpenAI node, embeddingsOpenAi. 0 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 1Embeddings OpenAIOPENAIEMBEDDINGSOPENAI0 IN / 1 OUTDefault Data Loader. ai node, documentDefaultDataLoader. 1 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 1Default Data LoaderAIDOCUMENTDEFAULTDATALOAD1 IN / 1 OUTToken Splitter. ai node, textSplitterTokenSplitter. 0 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 2Token SplitterAITEXTSPLITTERTOKENSPLITT0 IN / 1 OUTWhen chat message received. trigger node, chatTrigger. 0 incoming and 1 outgoing connections.STARTWhen chat message receivedTRIGGERCHATTRIGGER0 IN / 1 OUTAI Agent. ai node, agent. 4 incoming and 0 outgoing connections.OUTCOMEAI AgentAIAGENT4 IN / 0 OUTOpenAI Chat Model. OpenAI node, lmChatOpenAi. 0 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 1OpenAI Chat ModelOPENAILMCHATOPENAI0 IN / 1 OUTWindow Buffer Memory. ai node, memoryBufferWindow. 0 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 1Window Buffer MemoryAIMEMORYBUFFERWINDOW0 IN / 1 OUTCall n8n Workflow Tool. ai node, toolWorkflow. 0 incoming and 1 outgoing connections.DEPENDENCY · DEPTH 1Call n8n Workflow ToolAITOOLWORKFLOW0 IN / 1 OUTExecute Workflow Trigger. trigger node, executeWorkflowTrigger. 0 incoming and 2 outgoing connections.STARTExecute Workflow TriggerTRIGGEREXECUTEWORKFLOWTRIGGER0 IN / 2 OUTEmbedding Recommendation Request with Open AI. OpenAI node, httpRequest. 1 incoming and 1 outgoing connections.STEP 02Embedding Recommendation …OPENAIHTTPREQUEST1 IN / 1 OUTEmbedding Anti-Recommendation Request with Open AI. OpenAI node, httpRequest. 1 incoming and 1 outgoing connections.STEP 02Embedding Anti-Recommenda…OPENAIHTTPREQUEST1 IN / 1 OUTExtracting Embedding. transform node, set. 1 incoming and 1 outgoing connections.STEP 03Extracting EmbeddingTRANSFORMSET1 IN / 1 OUTExtracting Embedding1. transform node, set. 1 incoming and 1 outgoing connections.STEP 03Extracting Embedding1TRANSFORMSET1 IN / 1 OUTMerge. decision node, merge. 2 incoming and 1 outgoing connections.STEP 04MergeDECISIONMERGE2 IN / 1 OUTCalling Qdrant Recommendation API. integration node, httpRequest. 1 incoming and 2 outgoing connections.STEP 05Calling Qdrant Recommenda…INTEGRATIONHTTPREQUEST1 IN / 2 OUTSplit Out1. transform node, splitOut. 1 incoming and 1 outgoing connections.STEP 06Split Out1TRANSFORMSPLITOUT1 IN / 1 OUTRetrieving Recommended Movies Meta Data. integration node, httpRequest. 1 incoming and 1 outgoing connections.STEP 06Retrieving Recommended Mo…INTEGRATIONHTTPREQUEST1 IN / 1 OUTSplit Out. transform node, splitOut. 1 incoming and 1 outgoing connections.STEP 07Split OutTRANSFORMSPLITOUT1 IN / 1 OUTMerge1. decision node, merge. 2 incoming and 1 outgoing connections.STEP 08Merge1DECISIONMERGE2 IN / 1 OUTSelecting Fields Relevant for Agent. transform node, set. 1 incoming and 1 outgoing connections.STEP 09Selecting Fields Relevant…TRANSFORMSET1 IN / 1 OUTAggregate. transform node, aggregate. 1 incoming and 0 outgoing connections.OUTCOMEAggregateTRANSFORMAGGREGATE1 IN / 0 OUT

Signal inspector

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Main-channel runtimeTyped dependencytriggeraidecisiontransformintegration
Scroll horizontally to follow every connected flow.25 connected nodesEnter or click to lock · Escape to clear

Runtime breakdown

Read the execution spine before its dependencies.

Each run group separates main-channel steps from the models, tools, retrievers, and data services that support them. Start and outcome labels apply only to runtime nodes.

01

Run Group

When clicking ‘Test workflow’

3 Execution Links3 Support Dependencies

  1. Start

    When clicking ‘Test workflow’

    Trigger

  2. Step 2

    GitHub

    Integration

  3. Step 3

    Extract from File

    Integration

  4. Outcome

    Qdrant Vector Store

    AI reasoning

Attached dependencies

These nodes support the runtime above; they are not additional starts or outcomes.

3 nodes

  • Embeddings OpenAI

    AI reasoning dependency

  • Default Data Loader

    AI reasoning dependency

  • Token Splitter

    AI reasoning dependency

02

Run Group

When chat message received

1 Execution Link3 Support Dependencies

  1. Start

    When chat message received

    Trigger

  2. Outcome

    AI Agent

    AI reasoning

Attached dependencies

These nodes support the runtime above; they are not additional starts or outcomes.

3 nodes

  • OpenAI Chat Model

    AI reasoning dependency

  • Window Buffer Memory

    AI reasoning dependency

  • Call n8n Workflow Tool

    AI reasoning dependency

03

Run Group

Execute Workflow Trigger

14 Execution Links

  1. Start

    Execute Workflow Trigger

    Trigger

  2. Step 2

    Embedding Recommendation Request with Open AI

    Integration

    Embedding Anti-Recommendation Request with Open AI

    Integration

  3. Step 3

    Extracting Embedding

    Transform

    Extracting Embedding1

    Transform

  4. Step 4

    Merge

    Decision

  5. Step 5

    Calling Qdrant Recommendation API

    Integration

  6. Step 6

    Split Out1

    Transform

    Retrieving Recommended Movies Meta Data

    Integration

  7. Step 7

    Split Out

    Transform

  8. Step 8

    Merge1

    Decision

  9. Step 9

    Selecting Fields Relevant for Agent

    Transform

  10. Outcome

    Aggregate

    Transform

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