Automatisez vos analyses SQL avec visualisations intégrées

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                "content": "### Overview  \n- This workflow aims to provide data visualization capabilities to a native SQL Agent.  \n- Together, they can help foster data analysis and data visualization within a team.  \n- It uses the native SQL Agent that works well and adds visualization capabilities thanks to OpenAI’s Structured Output and Quickchart.io.  \n\n### How it works  \n1. Information Extraction:  \n   - The Information Extractor identifies and extracts the user's question.  \n   - If the question includes a visualization aspect, the SQL Agent alone may not respond accurately.  \n2. SQL Querying:  \n   - It leverages a regular SQL Agent: it connects to a database, queries it, and translates the response into a human-readable format.  \n3. Chart Decision:  \n   - The Text Classifier determines whether the user would benefit from a chart to support the SQL Agent's response.  \n4. Chart Generation:  \n   - If a chart is needed, the sub-workflow dynamically generates a chart and appends it to the SQL Agent’s response.  \n   - If not, the SQL Agent’s response is output as is.  \n5. Calling OpenAI for Chart Definition:  \n   - The sub-workflow calls OpenAI via the HTTP Request node to retrieve a chart definition.  \n6. Building and Returning the Chart:  \n   - In the \"Set Response\" node, the chart definition is appended to a Quickchart.io URL, generating the final chart image.  \n   - The AI Agent returns the response along with the chart.  \n\n### How to use it  \n- Use an existing database or create a new one.  \n- For example, I've used [this Kaggle dataset](https:\/\/www.kaggle.com\/datasets\/ihelon\/coffee-sales\/versions\/15?resource=download) and uploaded it to a Supabase DB.  \n- Add the PostgreSQL or MySQL credentials.  \n- Alternatively, you can use SQLite binary files (check [this template](https:\/\/n8n.io\/workflows\/2292-talk-to-your-sqlite-database-with-a-langchain-ai-agent\/)).  \n- Activate the workflow.  \n- Start chatting with the AI SQL Agent.  \n- If the Text Classifier determines a chart would be useful, it will generate one in addition to the SQL Agent's response.  \n\n### Notes  \n- The full Quickchart.io specifications have not been fully integrated, so there may be some glitches (e.g., radar graphs may not display properly due to size limitations).  "
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                "content": "## Generate a Quickchart definition \n[Original template](https:\/\/n8n.io\/workflows\/2400-ai-agent-with-charts-capabilities-using-openai-structured-output-and-quickchart\/)\n\n**HTTP Request node**\n- Send the chart query to OpenAI, with a defined JSON response format - *using HTTP Request node as it has not yet been implemented in the OpenAI nodes*\n- The JSON structure is based on ChartJS and Quickchart.io definitions, that let us create nice looking graphs.\n- The output is a JSON containing the chart definition that is passed to the next node.\n\n**Set Response node**\n- Adds the chart definition at the end of a Quickchart.io URL ([see documentation](https:\/\/quickchart.io\/documentation\/usage\/parameters\/))\n- Note that in the parameters, we specify the width to 250 in order to be properly displayed in the chart interface."
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                "content": "### Information Extractor \n- This Information Extractor is added to extract the user's question\n- In some cases, if the question contains a visualization aspect, the SQL Agent may not responding accurately.\n\n### SQL Agent\n- This SQL Agent is connected to a Database.\n- It queries the Database for each user message.\n- In this example, the prompt has been slightly changed to address an issue with querying a Supabase DB. Feel free to change the `Prefix Prompt` to suit your needs.\n- This example uses the data from this [Kaggle dataset](https:\/\/www.kaggle.com\/datasets\/ihelon\/coffee-sales\/versions\/15?resource=download)"
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                "content": "### Respond with a text only or also include a chart \n- The text classifier determines if the response from the SQL Agent would benefit from a chart\n- If it does, then it executes the subworkflow to dynamically generate a chart, and append the chart to the response from the SQL Agent\n- If it doesn't, then the SQL Agent response is directly outputted. "
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                            "category": "chart_not_required",
                            "description": "if a chart doesn't help the user understand the response (e.g a single data point that doesn't require visualization).\n\"I don't know\" does fall into this category"
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                "content": "## Demo\n![Demo SQL Agent](https:\/\/media.licdn.com\/dms\/image\/v2\/D4E22AQERT4FEXEUncw\/feedshare-shrink_800\/feedshare-shrink_800\/0\/1731433289953?e=1741824000&v=beta&t=e6xUqjcsSq5U_NELeD-nn1mFROGYZLazkYC0eELTv5Y)"
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