Les entretiens de retour d’absence sont essentiels pour la réintégration et la prévention des risques. L’automatisation planifie chaque entretien, notifie les RH, archive les comptes rendus et programme les suivis d’actions décidées. Ce suivi renforce la gestion des ressources humaines et la QVT.
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"name": "Chat with GitHub OpenAPI Specification using RAG (Pinecone and OpenAI)",
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"content": "## Indexing content in the vector databasenThis part of the workflow is responsible for extracting content, generating embeddings and sending them to the Pinecone vector store.nnIt requests the OpenAPI specifications from GitHub using a HTTP request. Then, it splits the file in chunks, generating embeddings for each chunk using OpenAI, and saving them in Pinecone vector DB."
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"content": "## Querying and response generation nnThis part of the workflow is responsible for the chat interface, querying the vector store and generating relevant responses.nnIt uses OpenAI GPT 4o-mini to generate responses."
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"mode": "list",
"value": "n8n-demo",
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"name": "PineconeApi account"
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"content": "## RAG workflow in n8nnnThis is an example of how to use RAG techniques to create a chatbot with n8n. It is an API documentation chatbot that can answer questions about the GitHub API. It uses OpenAI for generating embeddings, the gpt-4o-mini LLM for generating responses and Pinecone as a vector database.nn### Before using this templaten* create OpenAI and Pinecone accountsn* obtain API keys OpenAI and Pinecone n* configure credentials in n8n for bothn* ensure you have a Pinecone index named "n8n-demo" or adjust the workflow accordingly."
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}
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"Generate Embeddings": {
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"Window Buffer Memory": {
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"When chat message received": {
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"Generate User Query Embedding": {
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"When clicking u2018Test workflowu2019": {
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}