- Installation [Installing Miniconda - Anaconda](https://www.anaconda.com/docs/getting-started/miniconda/install#macos-linux-installation:manual-shell-initialization)
- **LangSmith** is here to support you at every step of your development journey with tools for observability, evaluation, and prompt engineering.
	- As you start building your agent, you may need to debug unexpected outputs or performance bottlenecks. That’s where **tracing** in LangSmith comes in.
	- Tracing can help you pinpoint issues and track how each part of your agent contributes to the output. You can also share traces with your team for seamless debugging – here’s [an example](https://track.pstmrk.it/3s/smith.langchain.com%2Fpublic%2F2f75dddd-fa65-4dd1-a9c7-09c11032b267%2Fr/Tpyp/a8W-AQ/AQ/fdde9c53-e164-482b-99dd-eeea3c2a9a20/1/L6vVzrWDEB).
	- Ready to log your first trace in LangSmith? 🤓 Watch this quick 5-minute video to get started, and follow along with the code [here](https://track.pstmrk.it/3s/github.com%2Fxuro-langchain%2Feli5/Tpyp/a8W-AQ/AQ/fdde9c53-e164-482b-99dd-eeea3c2a9a20/2/OCP0-lehao).
	- https://track.pstmrk.it/3s/www.youtube.com%2Fwatch%3Fv%3DfA9b4D8IsPQ/Tpyp/a8W-AQ/AQ/fdde9c53-e164-482b-99dd-eeea3c2a9a20/3/9ETeFMFTSD
	- If you need a hand getting started, our [Quick Start](https://track.pstmrk.it/3s/docs.smith.langchain.com%2Fobservability/Tpyp/a8W-AQ/AQ/fdde9c53-e164-482b-99dd-eeea3c2a9a20/4/1-h5s_hKG0) and [Tracing docs](https://track.pstmrk.it/3s/docs.smith.langchain.com%2Fobservability%2Fhow_to_guides%23tracing-configuration/Tpyp/a8W-AQ/AQ/fdde9c53-e164-482b-99dd-eeea3c2a9a20/5/BFX-Zbfit0#tracing-configuration) have you covered 🥳
	- Over the next 5 emails in our onboarding series, we’ll dive into LangSmith’s core features and show you how to use them. I’ll be back soon with more on the LangSmith Playground!
- [[Conda]] is a package and environment manager, originated from Python even though it is language agnostic.
	- While pip is excellent for managing Python-only packages, Conda can manage dependencies for projects that require non-Python libraries and complex dependency trees
	- Conda environments can be exported to a YAML file, which permits to recreate the exact same environment, ensuring reproducibility for collaboration and deployment
		- I think it's a kind of Maven or Gradle framework even though it is not specific to only one language
	- Conda is a popular choice for data scientists and AI developers
- Conda can manage different environments [Getting started with conda — conda 25.7.1.dev23 documentation](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html) es
	- ```
	  conda create -n <env-name>
	  ```
- [[Anaconda]] and [[Miniconda]] are software distributions, which means they are collections of pre-built tools specifically designed for data science.
	- Coda is included in Anaconda and Miniconda
- Init commands
	- ```bash
	  source <PATH_TO_CONDA>/bin/activate
	  conda init --all
	  conda init --reverse bash
	  ```
- Then
	- ```bash
	  conda create -n langchain-book python=3.11
	  ```
- From VS code I opened a Jupyter notebook of the book and I selected the langchain-book environment.
- I executed
	- ```bash
	  pip install -r requirements.txt
	  ```
- To execute python code outside Jupyter it is necessary to select the correct interpreter
	- [Python environments in VS Code](https://code.visualstudio.com/docs/python/environments#_manually-specify-an-interpreter)
	- CTRL+SHIFT P
		- ![image.png](../assets/image_1755872606461_0.png){:height 867, :width 1154}
-