Merge pull request #18 from NIGMS/llm-integration

Added util folder with gemini.py, added Gemini to Submodule 1, and ad…

Author: kyleoconnell-NIH

GoogleCloud/README.md

@@ -95,3 +95,22 @@ When you are finished running code, you can turn off your virtual machine to pre
 - If you are unable to interact with your Google Cloud Storage bucket using the `gsutil` command, check your `nextflow-service-account` roles. Make sure that you have `Storage Admin` added.
 - If you are trying to execute a terminal command in a Jupyter code cell and it is not working, make sure that you have an `!` before the command.
     - e.g., `mkdir example-1` -> `!mkdir example-1`
+ 
+## Gemini (Optional)
+
+Generative AI is available for this tutorial in the form of Gemini if you would like to use it. To run it, please reference Submodule 1, or run the following code within a submodule notebook.
+
+```!pip install -q google-generativeai google-cloud-secret-manager
+!pip install -q git+https://github.com/NIGMS/NIGMS-Sandbox-Repository-Template.git#subdirectory=llm_integrations
+!pip install -q ipywidgets
+
+import sys
+import os
+util_path = os.path.join(os.getcwd(), 'util')
+if util_path not in sys.path:
+    sys.path.append(util_path)
+
+from gemini import run_gemini_widget, create_gemini_chat_widget 
+from IPython.display import display
+
+run_gemini_widget()

GoogleCloud/Submodule_1_background.ipynb

@@ -44,7 +44,12 @@
     "\n",
     "6. **Introduce the Google Batch API:** Learners are introduced to the Google Batch API and its advantages for managing and executing workflows on cloud computing resources.\n",
     "\n",
-    "7. **Familiarize learners with Jupyter Notebooks:** The notebook provides instructions on how to navigate and use Jupyter Notebooks, including cell types and execution order."
+    "7. **Familiarize learners with Jupyter Notebooks:** The notebook provides instructions on how to navigate and use Jupyter Notebooks, including cell types and execution order.\n",
+    "\n",
+    "<div class=\"alert alert-block alert-success\">\n",
+    "    <i class=\"fa fa-hand-paper-o\" aria-hidden=\"true\"></i>\n",
+    "    <b>Tip: </b>  If you're having trouble with any part of this tutorial, feel free to leverage Gemini (Google's advanced generative AI model) at the bottom of this module.\n",
+    "</div>  "
    ]
   },
   {
@@ -508,11 +513,60 @@
     "\n",
     "Remember to proceed to the next notebook [`Submodule_2_annotation_only.ipynb`](./Submodule_2_annotation_only.ipynb) or shut down your instance if you are finished."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "82cfac8a-45f9-4e9d-8a83-0ade6fbfec81",
+   "metadata": {},
+   "source": [
+    "## Gemini (Optional)\n",
+    "--------\n",
+    "\n",
+    "If you're having trouble with this submodule (or others within this tutorial), feel free to leverage Gemini by running the cell below. Gemini is Google's advanced generative AI model designed to enhance the capabilities of AI applications across various domains."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "939b3e91-094b-4ef5-914a-4c9d1e7f3d8d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Ensure you have the necessary libraries installed\n",
+    "!pip install -q google-generativeai google-cloud-secret-manager\n",
+    "!pip install -q git+https://github.com/NIGMS/NIGMS-Sandbox-Repository-Template.git#subdirectory=llm_integrations\n",
+    "!pip install -q ipywidgets\n",
+    "\n",
+    "import sys\n",
+    "import os\n",
+    "util_path = os.path.join(os.getcwd(), 'util')\n",
+    "if util_path not in sys.path:\n",
+    "    sys.path.append(util_path)\n",
+    "\n",
+    "from gemini import run_gemini_widget, create_gemini_chat_widget \n",
+    "from IPython.display import display\n",
+    "\n",
+    "run_gemini_widget()"
+   ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel) (Local)",
+   "language": "python",
+   "name": "conda-base-py"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.16"
   }
  },
  "nbformat": 4,

GoogleCloud/util/gemini.py

@@ -0,0 +1,94 @@
+import gemini_helper.build as builder
+import google.generativeai as genai
+import ipywidgets as widgets
+
+_model = None # Private module-level variable for the model
+
+def _initialize_model():
+    """Initializes the Gemini model if not already initialized."""
+    global _model
+    if _model is None:
+        try:
+            key = builder.get_api_key()
+            genai.configure(api_key=key)
+            _model = genai.GenerativeModel("gemini-1.5-flash")
+            print("Gemini model initialized successfully.")
+        except Exception as e:
+            print(f"Error initializing Gemini model: {e}")
+            _model = None # Ensure it's None if initialization fails
+    return _model
+
+# --- Widget Creation and Logic ---
+def create_gemini_chat_widget():
+    """
+    Creates and returns the Ipywidgets for a Gemini chat interface.
+    The widgets should be displayed in the calling environment (e.g., Jupyter Notebook).
+    """
+    model = _initialize_model()
+    if not model:
+        # If model failed to initialize, return a message widget
+        error_message = widgets.HTML("Failed to initialize Gemini model. Please check API key and configuration.")
+        return (error_message,) # Return as a tuple for consistency with display
+
+    # Create a text box for input
+    prompt_input = widgets.Text(
+        value='',
+        placeholder='Type your prompt here',
+        description='Prompt:',
+        disabled=False
+    )
+
+    # Create an output area for the response
+    response_output = widgets.Output()
+
+    # Create a button to submit the prompt
+    submit_button = widgets.Button(description="Submit")
+
+    # Define the function to handle the button click
+    def on_submit_button_clicked(b):
+        # Ensure the model is available (it should be if we reached here)
+        if not _model:
+            with response_output:
+                response_output.clear_output()
+                print("Model is not available.")
+            return
+
+        with response_output:
+            response_output.clear_output() # Clear previous output
+            prompt_text = prompt_input.value
+            if not prompt_text.strip():
+                print("Please enter a prompt.")
+                return
+
+            # Indicate processing
+            print("Generating response...")
+            try:
+                # Generate the response using the Gemini model
+                response = _model.generate_content(prompt_text)
+                response_output.clear_output() # Clear "Generating response..."
+                print(response.text)
+            except Exception as e:
+                response_output.clear_output() # Clear "Generating response..."
+                print(f"Error generating content: {e}")
+
+    # Attach the click event handler to the button
+    submit_button.on_click(on_submit_button_clicked)
+
+    # Return the widgets to be displayed by the caller
+    return prompt_input, submit_button, response_output
+
+def run_gemini_widget():
+    """
+    An example "empty" function to create and immediately display the widget.
+    """
+    from IPython.display import display # Import display here, as it's for notebook environment
+
+    widgets_to_display = create_gemini_chat_widget()
+    if widgets_to_display: # Check if widgets were created
+        # If only one widget is returned (e.g., an error message), display it
+        if isinstance(widgets_to_display, tuple) and len(widgets_to_display) > 1:
+            display(*widgets_to_display)
+        else:
+            display(widgets_to_display)
+    else:
+        print("Could not create Gemini widget.")