add: dropdown and feedback

Author: geemi725

chapter_1/background.md

@@ -74,6 +74,12 @@ AI has proven capable of extracting intricate patterns from large datasets in ge
 
 - [Geoffrey Hinton: The 60 Minutes Interview](https://www.youtube.com/watch?v=Rl9nHNeketE)
 
+## Providing Feedback
+
+We’d love to hear from you! Whether you run into issues, have ideas for improving the tutorials, or want to suggest new topics, feel free to reach out. 
+
+Email us at: [tutorials@futurehouse.org](tutorials@futurehouse.org)
+
 ## References
 
 ```{bibliography}

chapter_2/background.md

@@ -12,7 +12,46 @@ These examples will teach you how to build AI systems that:
 
 - Extract structured information from online, open-source datasets
 
-
 The accompanying `python notebooks` provide step-by-step implementations that readers can run and modify for their own research projects. These notebooks demonstrate techniques such as retrieval-augmented generation (RAG) for literature search and LLM model–based dataset parsing for biological data analysis.
 
-To run the code snippets, you should click the 🚀 at the top of the page to launch the page as an interactive Google Colab notebook.
+:::{admonition} 🚀 How to run the notebooks
+
+Tutorials can be launched using the rocket (🚀) button at the top of the page.
+
+### Option 1 — Google Colab (**recommended**)
+Opens the notebook in Google Colab with the fastest and most reliable experience.
+
+Before running the tutorial, add your API keys using **either**:
+
+- a `.env` file, or
+- **Colab Secrets** (`🔑 Secrets` tab in the left sidebar)
+
+Example `.env`:
+```bash
+OPENAI_API_KEY=your_key_here
+ANTHROPIC_API_KEY=your_key_here
+```
+
+### Option 2 — MyBinder
+Launches a temporary cloud Jupyter environment directly in your browser.
+
+⚠️ Binder environments can take a few minutes to build and start.
+
+After the notebook loads, create a `.env` file in the notebook directory containing your API keys:
+
+```bash
+OPENAI_API_KEY=your_key_here
+ANTHROPIC_API_KEY=your_key_here
+```
+
+### Notes
+- You only need API keys for the providers used in a given notebook.
+- Never commit or publicly share your API keys.
+- If a cell fails due to missing credentials, verify that your keys were loaded correctly before rerunning the cell.
+:::
+
+**Providing Feedback**
+
+We’d love to hear from you! Whether you run into issues, have ideas for improving the tutorials, or want to suggest new topics, feel free to reach out. 
+
+Email us at: [tutorials@futurehouse.org](tutorials@futurehouse.org)

chapter_2/llms_for_biology.ipynb

@@ -13,10 +13,10 @@
         "\n",
         "As the volume of scientific literature continues to grow rapidly, manually extracting and organizing this information becomes increasingly difficult and time-consuming. Therefore, automating data extraction from the literature using AI can help researchers to rapidly identify relevant findings, convert unstructured text into structured datasets, and integrate knowledge across thousands of publications. \n",
         "\n",
-        ":::{admonition} 🚀 Getting Started\n",
-        ":class: tip\n",
+        ":::{dropdown} 🚀 How to run the notebook\n",
+        ":animate: fade-in-slide-down\n",
         "\n",
-        "This tutorial can be launched using the rocket button at the top of the page.\n",
+        "This tutorial can be launched using the rocket (🚀) button at the top of the page.\n",
         "\n",
         "### Option 1 — Google Colab (**recommended**)\n",
         "Opens the notebook in Google Colab with the fastest and most reliable experience.\n",

chapter_2/uniprot_example.ipynb

@@ -8,8 +8,8 @@
     "# 2.3 Integrating External Databases\n",
     "The goal of this section is to show you how LLMs can easily be integrated into research workflows to accelerate scientific discovery. On top of everything, AI can take care of the most mundane trivial tasks.\n",
     "\n",
-    ":::{admonition} 🚀 Getting Started\n",
-    ":class: tip\n",
+    ":::{dropdown} 🚀 How to run the notebook\n",
+    ":animate: fade-in-slide-down\n",
     "\n",
     "This tutorial can be launched using the rocket button at the top of the page.\n",
     "\n",

chapter_3/agent_implementation.ipynb

@@ -20,8 +20,8 @@
     "- `summarize_protein_role` — asks the AI to summarize biological context\n",
     "\n",
     "\n",
-    ":::{admonition} 🚀 Getting Started\n",
-    ":class: tip\n",
+    ":::{dropdown} 🚀 How to run the notebook\n",
+    ":animate: fade-in-slide-down\n",
     "\n",
     "This tutorial can be launched using the rocket button at the top of the page.\n",
     "\n",

chapter_3/agent_mcp_example.ipynb

@@ -8,8 +8,8 @@
     "\n",
     "In chapters 3.2 and 3.3 we learned how to write boilerplate code and implement agents. But the problem is, if you are not a python programmer you might find this to be tedious. This may not be the main problem you want to solve and might be interested in a simpler solution.\n",
     "\n",
-    ":::{admonition} 🚀 Getting Started\n",
-    ":class: tip\n",
+    ":::{dropdown} 🚀 How to run the notebook\n",
+    ":animate: fade-in-slide-down\n",
     "\n",
     "This tutorial can be launched using the rocket button at the top of the page.\n",
     "\n",

chapter_3/agents.md

@@ -87,3 +87,9 @@ As introduced in chapter 2, [PaperQA2](https://github.com/Future-House/paper-qa)
 ## 3.1.4 Additional Reading
 - More mathematical explanations can be found in this paper: [Aviary: training language agents on challenging scientific tasks](https://arxiv.org/abs/2412.21154)
 - [AI Agents - IBM tutorials](https://www.ibm.com/think/topics/ai-agents)
+
+## Providing Feedback
+
+We’d love to hear from you! Whether you run into issues, have ideas for improving the tutorials, or want to suggest new topics, feel free to reach out. 
+
+Email us at: [tutorials@futurehouse.org](tutorials@futurehouse.org)

chapter_3/aviary_agent_implementation.ipynb

@@ -20,8 +20,8 @@
         "Figure 3.2.1: An agent iteratively received observations from the environment, takes an action based on the observation until the task is completed.\n",
         "```\n",
         "\n",
-        ":::{admonition} 🚀 Getting Started\n",
-        ":class: tip\n",
+        ":::{dropdown} 🚀 How to run the notebook\n",
+        ":animate: fade-in-slide-down\n",
         "\n",
         "This tutorial can be launched using the rocket button at the top of the page.\n",
         "\n",