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For sure. Let's use an example, like this: https://github.com/simonmesmith/agentflow/blob/main/agentflow/flows/example_with_variables.json https://github.com/s
by simonmesmith 3y ago
For sure.
Let's use an example, like this: https://github.com/simonmesmith/agentflow/blob/main/agentflow/flows/example_with_variables.json https://github.com/simonmesmith/agentflow/blob/main/agentflo...
This is a workflow for coming up with a product idea and illustrating it with an image.
This workflow has 9 steps, starting with brainstorming ideas, and ending with saving an HTML file containing the product name, description, and image.
It also has two variables, {market} for the target market, and {price_point} for the price point.
To run this workflow, you simply enter this in the command line:
python -m run --flow=example_with_variables --variables 'market=college students' 'price_point=$50'
You don't need to write any code with LangChain.
You simply specify your workflow in a JSON file, and execute it.
Does that help to clarify?
- rexreed 3y agoThanks - this does help. Curious about the function calls, especially around image generation. Also, can you clarify what you mean by "You don't need to write any code with LangChain."?
- simonmesmith 3y agoSure! In Agentflow, you write functions by inheriting from the BaseFunction class. You need to provide the definition in JSON that GPT-3.5/4 uses to understand how to call a function, and also the function logic itself. This just means creating a get_definition() function that returns a JSON Schema object, and an execute() function that performs your logic and returns a string. Once you have those, you can then just use the function in your workflow by adding "function_call": "your_function". The application does the rest. Here's the create_image function, for example, which uses the Dall-e API: https://github.com/simonmesmith/agentflow/blob/main/agentflow/functions/create_image.py https://github.com/simonmesmith/agentflow/blob/main/agentflo... What I mean by "you don't need to write any code with LangChain" is that you don't need to write any Python at all to use Agentflow, unless you want to create a new function. Creating workflows just involves creating JSON files. It's not like LangChain, for which you'd have to chain together multiple prompts in Python. Does that help clarify? PS: You'll notice heavy documentation in the link above. I want to experiment with automatically generating documentation using Sphinx, so I documented everything with Sphinx formatting. It might be overkill.
- rexreed 3y agoThanks! I'll check this out!