Let me go and show you the link.
Smith.
Trace.
So I first want to go and log in.
Let me go to the react algorithm project.
And we can see now the trace.
So we have two LM calls and one tool execution.
So let's start with the first LM call.
And we can see now that this was the input.
And the result was a tool call with the function of get text length with the text equals to dog as input.
So we can see also the tool call ID here.
Now one thing which I like about blacksmith, you can see now that the tools here was actually a call
tool.
So Langschmidt is able to do it because we propagate through the entire life cycle the tool call ID.
So Linkchain knows also to track it with Dan Smith.
So here we can see the tool execution of a the function of get text length.
Now we can see the input.
We can see the output.
Let me go and show you.
The last message to the LM.
And notice the list of messages we sent.
Here we send the input, which was the first message.
The second message was the tool call.
The third message was the tool result.
And then we get the output.
Amazing.
Let me go back to the code and let me commit everything.
So I opened Cloud code in the right here.
And I'm actually going to ask Cloud Code to create a commit message for me.
And I actually found cloud code commit messages very, very appealing because they're short, they're
descriptive.
And I really like the formatting here.
So let me simply write the prompt.
I'm going to give it a quick hint that this commit is about tool calling.
And you can see it's going to run the changed files.
Git status git diff.
Going to see exactly what we changed.
And it's going to draft now a commit message.
So let me say that we want to track the main.py file.
And boom we can see now the commit message.
And I'm always amazed by how amazing AI eyes.
And so check it out.
So in the description it's called replace react algorithm with link chain tool calling approach.
We remove the manual react prompt template in parsing logic.
We implemented the binding tools to direct integration with LLM.
And this is what amazes me.
Replaces the agent scratchpad tracking with message based conversation flow.
So this is this is simply amazing.
And let me say that I want to proceed and I want to commit this message.
So now it's going to run this command.
And once it's finished now I can go and push everything to the remote repository.
So let me go to the GitHub repo.
And here you can see the exact diff and everything we just showed you in the video.
And that will also be linking it in the courses and resources in the videos.
Resources.
So yeah that's pretty much about tool calling.
Hope you enjoyed this video.
Please let me know what you think.
And this is the natural evolution of the react prompt.