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WikiDocs 02. Tool Binding (Binding Tools)

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Tool binding on LLM (Binding Tools)

In order for the LLM model to be able to call the tool, it is necessary to pass the tool schema to the model when making a chat request.

LangChain Chat Model supporting tool calling function .bind_tools() Implement a method to receive a list of LangChain tool objects, Pydantic classes or JSON schemas and bind to the chat model in the expected format by provider.

Subsequent calls to the bound Chat Model include a tool schema in every call to the model API.

# Configuration file for managing API KEY as environment variable
from dotenv import load_dotenv

# Load API KEY information
load_dotenv()
 True 
# LangSmith Set up tracking. https://smith.langchain.com
# !pip install -qU langchain-teddynote
from langchain_teddynote import logging

# Enter a project name.
logging.langsmith("CH15-Bind-Tools")
 Start tracking LangSmith. 
[Project name] 
CH15-Bind-Tools

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Tool definition to bind to LLM

Defines the tool for experimentation.

  • get_word_length : A function that returns the length of a word

  • add_function : A function that adds two numbers

  • naver_news_crawl : A function that crawls a Naver news article to return the text content

Reference

  • When defining tools @tool Define tools using decorators.

  • docstring is recommended to write in English whenever possible.

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Binding tools to LLM with bind_tools()

llm model bind_tools() Use to bind the tool.

Check the results.

result tool_calls Stored in. therefore, .tool_calls You can check the tool call result by checking.

Reference

  • name Means the name of the silver tool.

  • args means the factor passed to the tool.

Next llm_with_tools Wow JsonOutputToolsParser By connecting tool_calls Parsing to confirm the result.

The results of the run are as follows.

Reference

  • type : The name of the tool

  • args : Factors passed to the tool

Find and run tools that match tool names.

execute_tool_calls The function finds the tool and passes args to run the tool.

In other words, type Meaning the name of the silver tool args means the factor passed to the tool.

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bind_tools + Parser + Execution

This time, a series of processes are run at once.

  • llm_with_tools : Model with tools bound

  • JsonOutputToolsParser : Parser parsing tool call results

  • execute_tool_calls : Function running tool call result

Flow cleanup One. Binding tools to the model 2. Parsing tool call results 3. Run tool call results

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replaced by bind_tools > Agent & AgentExecutor

bind_tools() Provides a schema (tool) that can be used for models.

AgentExecutor It actually creates an execution loop for llm calls, routing, running, model re-calling, etc. with the right tools.

Reference

  • Agent Wow AgentExecutor The following chapters are covered in detail.

It doesn't end with a single run, but the model goes through the process of checking their results and calling themselves again.

This time, we will crawl the news results and make a request to summarize.

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