Fix wording in the intro to agents

This commit is contained in:
Aymeric 2024-12-31 12:26:40 +01:00
parent a3fe084e68
commit b21c1817dc
2 changed files with 10 additions and 8 deletions

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@ -97,14 +97,16 @@ But once you start going for more complicated behaviours like letting an LLM cal
- for a multi-step agent where the LLM output determines the loop, you need to give a different prompt to the LLM based on what happened in the last loop iteration: so you need some kind of memory.
See? With these two examples, we already found the need for a few items to help us:
- of course an LLM that acts as the engine powering the system
- a list of tools that the agent can access
- a parser that extracts tool calls from the LLM output
- system prompt synced with the parser
- memory
But wait, since we give room to LLMs in decisions, surely they will make mistakes, so for better performance we need error logging and retry mechanism?
These will not be that straightforward to implement correctly, especially not together. That's why we decided that we needed to build a few abstractions to help people use these.
- Of course, an LLM that acts as the engine powering the system
- A list of tools that the agent can access
- A parser that extracts tool calls from the LLM output
- A system prompt synced with the parser
- A memory
But wait, since we give room to LLMs in decisions, surely they will make mistakes: so we need error logging and retry mechanisms.
All these elements need tight coupling to make a well-functioning system. That's why we decided we needed to make basic building blocks to make all this stuff work together.
### Code agents

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@ -115,7 +115,7 @@ def get_weather_api(location: str, date_time: str) -> str:
In general, to ease the load on your LLM, the good question to ask yourself is: "How easy would it be for me, if I was dumb and using this tool for the first time ever, to program with this tool and correct my own errors?".
### Give more stuff to the agent
### Give more arguments to the agent
To pass some additional objects to your agent than thes smple string that tells it the task to run, you can use argument `additional_args` to pass any type of object: