docs(genapi): add a langchain integration and update bolt.diy integration using GenAPIs

[reda-maizate]

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Description

• Add a langchain integration for function calling
• Update bolt.diy integration to warn customers about compatible models

[nerda-codes]

Suggested change

	Only models that have a maximum output token of at least 8000 tokens are supported. You can found the list of Generative APIs models [here](https://www.scaleway.com/en/docs/generative-apis/reference-content/supported-models/#chat-models).
	Only models that have a maximum output token of at least 8000 tokens are supported. Refer to the [list of Generative APIs models](/generative-apis/reference-content/supported-models/#chat-models) for more information.

[nerda-codes]

Suggested change

	1. Install LangChain and his dependencies.
	```bash
	pip install 'langchain>=0.3.24'
	pip install 'langchain-core>=0.3.55'
	pip install 'langchain-openai>=0.3.14'
	pip install 'langchain-text-splitters>=0.3.8'
	```
	2. Create a file `tools.py` and add the following code to it to import and create the tools examples:
	1. Run the following commands to install LangChain and its dependencies:
	```bash
	pip install 'langchain>=0.3.24'
	pip install 'langchain-core>=0.3.55'
	pip install 'langchain-openai>=0.3.14'
	pip install 'langchain-text-splitters>=0.3.8'
	```
	2. Create a file named `tools.py` and paste the code below into it to import and create the tools examples:

[nerda-codes]

Suggested change

	3. You can configure the `init_chat_model` function to use Scaleway's Generative APIs.
	3. Configure the `init_chat_model` function to use Scaleway's Generative APIs.

[nerda-codes]

Suggested change

	4. Everything is now set up, you can use the `llm` object and the `tools` list to generate a response to a query with the following code:
	4. Use the `llm` object and the `tools` list to generate a response to your query with the following code:

[nerda-codes]

Suggested change

	5. Finally, run the `tools.py`:
	```bash
	python tools.py
	```
	The response should display the result of the calculation:
	5. Run `tools.py`:
	```bash
	python tools.py

The result of the calculation should display in the output: