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Hey, I had a similar scenario when working with Flowise. I was trying to automate API calls using data from an Excel file. Here's what worked for me: First, I set up a script to read the Excel file using Python's Here's a quick example of what my script looked like: import pandas as pd
df = pd.read_excel('user_details.xlsx')
user_data = df.loc[0].to_dict() # Adjust the index as neededNext, I uploaded this script to the same server where Flowise was running. I then modified my Flowise workflow to call this script using a task node. This node executed the script to retrieve and format the data whenever I needed it. For step 3, in the OpenAI chat prompt within Flowise, I integrated a mechanism to call this script. You can also consider using an API endpoint that your script exposes, which Flowise can hit to get the data. Finally, to pass the Excel sheet name, I added a parameter to my script where the filename could be specified. This allowed Flowise to dynamically pass in different filenames if needed. This approach worked well for me by automating the entire process of fetching and formatting the data before making API calls. If you're comfortable with Python, this method should integrate smoothly with Flowise. Let me know if you need more details on any step! |
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Hi,
I am new to Flowise.In flowise , I am using OpenAPI toolkit to invoke an external API which creates an user. Instead of providing the user details in JSON in the LLM prompt, I would like to take it from an Excel sheet .
Below is the high level flow i am targetting
1.Create an Excel with the attribute details like user's firstname,lastame etc
2.Upload this Excel to flowise or keep it in the server.
3.In the OpenAI chat prompt, give the prompt to create user
4.Provide the Excel sheet name
Can you please let me know how this can be achieved. Thanks in advance.
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