Add initial "static" space for component demo

README.md

@@ -1,6 +1,6 @@
 ---
 title: Gradio Agent Inspector
-emoji: 👁
+emoji: 🕵️
 colorFrom: pink
 colorTo: indigo
 sdk: gradio
@@ -9,6 +9,384 @@ app_file: app.py
 pinned: false
 license: apache-2.0
 short_description: Agent Inspector to help debugging your agent
+tags:
+  - gradio-custom-component
+  - custom-component-track
+  - adk
+  - agent
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# `gradio_agent_inspector`
+<a href="https://pypi.org/project/gradio_agent_inspector/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_agent_inspector"></a>  
+
+Agent Inspector for ADK
+
+## Installation
+
+```bash
+pip install gradio_agent_inspector
+```
+
+## Usage
+
+```python
+import json
+from pathlib import Path
+import gradio as gr
+from gradio_agent_inspector import AgentInspector
+import os
+
+
+def simulate_conversation():
+    dir_path = Path(os.path.dirname(os.path.realpath(__file__)))
+
+    initial_state = {
+        "state": {},
+        "events": [],
+    }
+
+    states = []
+    for i in range(2):
+        session_value_p = dir_path / "session-sample" / f"value-{i}.json"
+        with session_value_p.open("r", encoding="utf-8") as f:
+            session_value = json.load(f)
+
+            # attach event trace and graph info to the event
+            for e in session_value["events"]:
+                event_trace_p = dir_path / "event-trace" / f"trace-{e['id']}.json"
+                if event_trace_p.exists():
+                    with event_trace_p.open("r", encoding="utf-8") as trace_f:
+                        event_trace = json.load(trace_f)
+                        if "gcp.vertex.agent.llm_request" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_request"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_request"]
+                            )
+                        if "gcp.vertex.agent.llm_response" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_response"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_response"]
+                            )
+                        e["trace"] = event_trace
+                event_graph_p = dir_path / "event-trace" / f"graph-{e['id']}.json"
+                if event_graph_p.exists():
+                    with event_graph_p.open("r", encoding="utf-8") as graph_f:
+                        event_graph = json.load(graph_f)
+                        e["graph"] = event_graph
+            states.append(session_value)
+
+    return initial_state, states
+
+
+def update_conversation_state(state_index, states):
+    if (state_index + 1) >= len(states):
+        return states[state_index], state_index
+    else:
+        new_index = state_index + 1
+        return states[new_index], new_index
+
+
+initial_state, conversation_states = simulate_conversation()
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Agent Inspector")
+
+    state_counter = gr.State(-1)
+
+    agent_inspector = AgentInspector(json.dumps(initial_state))
+
+    with gr.Row():
+        next_btn = gr.Button(
+            f"▶️ Next ({0} / {len(conversation_states)})", variant="primary"
+        )
+        reset_btn = gr.Button("🔄 Reset", variant="secondary")
+
+    def next_state(current_counter):
+        new_state, new_counter = update_conversation_state(
+            current_counter, conversation_states
+        )
+
+        json_state = json.dumps(new_state)
+        next_button_label = f"▶️ Next ({new_counter+1} / {len(conversation_states)})"
+
+        return json_state, new_counter, next_button_label
+
+    def reset_conversation():
+        json_state = json.dumps(initial_state)
+        next_button_label = f"▶️ Next ({0} / {len(conversation_states)})"
+
+        return json_state, -1, next_button_label
+
+    next_btn.click(
+        next_state,
+        inputs=[state_counter],
+        outputs=[agent_inspector, state_counter, next_btn],
+    )
+
+    reset_btn.click(
+        reset_conversation, outputs=[agent_inspector, state_counter, next_btn]
+    )
+
+    # examples = gr.Examples(
+    #     examples=[
+    #         s for s in conversation_states
+    #     ],
+    #     inputs=[initial_state],
+    # )
+
+if __name__ == "__main__":
+    demo.launch()
+
+```
+
+## `AgentInspector`
+
+### Initialization
+
+<table>
+<thead>
+<tr>
+<th align="left">name</th>
+<th align="left" style="width: 25%;">type</th>
+<th align="left">default</th>
+<th align="left">description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td align="left"><code>value</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+str | Callable | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">default text to provide in textbox. If a function is provided, the function will be called each time the app loads to set the initial value of this component.</td>
+</tr>
+
+<tr>
+<td align="left"><code>placeholder</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+str | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">placeholder hint to provide behind textbox.</td>
+</tr>
+
+<tr>
+<td align="left"><code>label</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+str | I18nData | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">the label for this component, displayed above the component if `show_label` is `True` and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component corresponds to.</td>
+</tr>
+
+<tr>
+<td align="left"><code>every</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+Timer | float | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.</td>
+</tr>
+
+<tr>
+<td align="left"><code>inputs</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+Component | Sequence[Component] | set[Component] | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.</td>
+</tr>
+
+<tr>
+<td align="left"><code>show_label</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+bool | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">if True, will display label.</td>
+</tr>
+
+<tr>
+<td align="left"><code>scale</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+int | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.</td>
+</tr>
+
+<tr>
+<td align="left"><code>min_width</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+int
+```
+
+</td>
+<td align="left"><code>160</code></td>
+<td align="left">minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.</td>
+</tr>
+
+<tr>
+<td align="left"><code>interactive</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+bool | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">if True, will be rendered as an editable textbox; if False, editing will be disabled. If not provided, this is inferred based on whether the component is used as an input or output.</td>
+</tr>
+
+<tr>
+<td align="left"><code>visible</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+bool
+```
+
+</td>
+<td align="left"><code>True</code></td>
+<td align="left">If False, component will be hidden.</td>
+</tr>
+
+<tr>
+<td align="left"><code>rtl</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+bool
+```
+
+</td>
+<td align="left"><code>False</code></td>
+<td align="left">If True and `type` is "text", sets the direction of the text to right-to-left (cursor appears on the left of the text). Default is False, which renders cursor on the right.</td>
+</tr>
+
+<tr>
+<td align="left"><code>elem_id</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+str | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.</td>
+</tr>
+
+<tr>
+<td align="left"><code>elem_classes</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+list[str] | str | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.</td>
+</tr>
+
+<tr>
+<td align="left"><code>render</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+bool
+```
+
+</td>
+<td align="left"><code>True</code></td>
+<td align="left">If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.</td>
+</tr>
+
+<tr>
+<td align="left"><code>key</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+int | str | tuple[int | str, ...] | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">in a gr.render, Components with the same key across re-renders are treated as the same component, not a new component. Properties set in 'preserved_by_key' are not reset across a re-render.</td>
+</tr>
+
+<tr>
+<td align="left"><code>preserved_by_key</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+list[str] | str | None
+```
+
+</td>
+<td align="left"><code>"value"</code></td>
+<td align="left">A list of parameters from this component's constructor. Inside a gr.render() function, if a component is re-rendered with the same key, these (and only these) parameters will be preserved in the UI (if they have been changed by the user or an event listener) instead of re-rendered based on the values provided during constructor.</td>
+</tr>
+</tbody></table>
+
+
+### Events
+
+| name | description |
+|:-----|:------------|
+| `change` | Triggered when the value of the AgentInspector changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input. |
+| `input` | This listener is triggered when the user changes the value of the AgentInspector. |
+| `submit` | This listener is triggered when the user presses the Enter key while the AgentInspector is focused. |
+
+
+
+### User function
+
+The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).
+
+- When used as an Input, the component only impacts the input signature of the user function.
+- When used as an output, the component only impacts the return signature of the user function.
+
+The code snippet below is accurate in cases where the component is used as both an input and an output.
+
+- **As output:** Is passed, passes text value as a {str} into the function.
+- **As input:** Should return, expects a {str} returned from function and sets textarea value to it.
+
+ ```python
+ def predict(
+     value: str | None
+ ) -> str | None:
+     return value
+ ```
+ 

app.py

@@ -0,0 +1,104 @@
+import json
+from pathlib import Path
+import gradio as gr
+from gradio_agent_inspector import AgentInspector
+import os
+
+
+def simulate_conversation():
+    dir_path = Path(os.path.dirname(os.path.realpath(__file__)))
+
+    initial_state = {
+        "state": {},
+        "events": [],
+    }
+
+    states = []
+    for i in range(2):
+        session_value_p = dir_path / "session-sample" / f"value-{i}.json"
+        with session_value_p.open("r", encoding="utf-8") as f:
+            session_value = json.load(f)
+
+            # attach event trace and graph info to the event
+            for e in session_value["events"]:
+                event_trace_p = dir_path / "event-trace" / f"trace-{e['id']}.json"
+                if event_trace_p.exists():
+                    with event_trace_p.open("r", encoding="utf-8") as trace_f:
+                        event_trace = json.load(trace_f)
+                        if "gcp.vertex.agent.llm_request" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_request"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_request"]
+                            )
+                        if "gcp.vertex.agent.llm_response" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_response"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_response"]
+                            )
+                        e["trace"] = event_trace
+                event_graph_p = dir_path / "event-trace" / f"graph-{e['id']}.json"
+                if event_graph_p.exists():
+                    with event_graph_p.open("r", encoding="utf-8") as graph_f:
+                        event_graph = json.load(graph_f)
+                        e["graph"] = event_graph
+            states.append(session_value)
+
+    return initial_state, states
+
+
+def update_conversation_state(state_index, states):
+    if (state_index + 1) >= len(states):
+        return states[state_index], state_index
+    else:
+        new_index = state_index + 1
+        return states[new_index], new_index
+
+
+initial_state, conversation_states = simulate_conversation()
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Agent Inspector")
+
+    state_counter = gr.State(-1)
+
+    agent_inspector = AgentInspector(json.dumps(initial_state))
+
+    with gr.Row():
+        next_btn = gr.Button(
+            f"▶️ Next ({0} / {len(conversation_states)})", variant="primary"
+        )
+        reset_btn = gr.Button("🔄 Reset", variant="secondary")
+
+    def next_state(current_counter):
+        new_state, new_counter = update_conversation_state(
+            current_counter, conversation_states
+        )
+
+        json_state = json.dumps(new_state)
+        next_button_label = f"▶️ Next ({new_counter+1} / {len(conversation_states)})"
+
+        return json_state, new_counter, next_button_label
+
+    def reset_conversation():
+        json_state = json.dumps(initial_state)
+        next_button_label = f"▶️ Next ({0} / {len(conversation_states)})"
+
+        return json_state, -1, next_button_label
+
+    next_btn.click(
+        next_state,
+        inputs=[state_counter],
+        outputs=[agent_inspector, state_counter, next_btn],
+    )
+
+    reset_btn.click(
+        reset_conversation, outputs=[agent_inspector, state_counter, next_btn]
+    )
+
+    # examples = gr.Examples(
+    #     examples=[
+    #         s for s in conversation_states
+    #     ],
+    #     inputs=[initial_state],
+    # )
+
+if __name__ == "__main__":
+    demo.launch()

css.css

@@ -0,0 +1,157 @@
+html {
+	font-family: Inter;
+	font-size: 16px;
+	font-weight: 400;
+	line-height: 1.5;
+	-webkit-text-size-adjust: 100%;
+	background: #fff;
+	color: #323232;
+	-webkit-font-smoothing: antialiased;
+	-moz-osx-font-smoothing: grayscale;
+	text-rendering: optimizeLegibility;
+}
+
+:root {
+	--space: 1;
+	--vspace: calc(var(--space) * 1rem);
+	--vspace-0: calc(3 * var(--space) * 1rem);
+	--vspace-1: calc(2 * var(--space) * 1rem);
+	--vspace-2: calc(1.5 * var(--space) * 1rem);
+	--vspace-3: calc(0.5 * var(--space) * 1rem);
+}
+
+.app {
+	max-width: 748px !important;
+}
+
+.prose p {
+	margin: var(--vspace) 0;
+	line-height: var(--vspace * 2);
+	font-size: 1rem;
+}
+
+code {
+	font-family: "Inconsolata", sans-serif;
+	font-size: 16px;
+}
+
+h1,
+h1 code {
+	font-weight: 400;
+	line-height: calc(2.5 / var(--space) * var(--vspace));
+}
+
+h1 code {
+	background: none;
+	border: none;
+	letter-spacing: 0.05em;
+	padding-bottom: 5px;
+	position: relative;
+	padding: 0;
+}
+
+h2 {
+	margin: var(--vspace-1) 0 var(--vspace-2) 0;
+	line-height: 1em;
+}
+
+h3,
+h3 code {
+	margin: var(--vspace-1) 0 var(--vspace-2) 0;
+	line-height: 1em;
+}
+
+h4,
+h5,
+h6 {
+	margin: var(--vspace-3) 0 var(--vspace-3) 0;
+	line-height: var(--vspace);
+}
+
+.bigtitle,
+h1,
+h1 code {
+	font-size: calc(8px * 4.5);
+	word-break: break-word;
+}
+
+.title,
+h2,
+h2 code {
+	font-size: calc(8px * 3.375);
+	font-weight: lighter;
+	word-break: break-word;
+	border: none;
+	background: none;
+}
+
+.subheading1,
+h3,
+h3 code {
+	font-size: calc(8px * 1.8);
+	font-weight: 600;
+	border: none;
+	background: none;
+	letter-spacing: 0.1em;
+	text-transform: uppercase;
+}
+
+h2 code {
+	padding: 0;
+	position: relative;
+	letter-spacing: 0.05em;
+}
+
+blockquote {
+	font-size: calc(8px * 1.1667);
+	font-style: italic;
+	line-height: calc(1.1667 * var(--vspace));
+	margin: var(--vspace-2) var(--vspace-2);
+}
+
+.subheading2,
+h4 {
+	font-size: calc(8px * 1.4292);
+	text-transform: uppercase;
+	font-weight: 600;
+}
+
+.subheading3,
+h5 {
+	font-size: calc(8px * 1.2917);
+	line-height: calc(1.2917 * var(--vspace));
+
+	font-weight: lighter;
+	text-transform: uppercase;
+	letter-spacing: 0.15em;
+}
+
+h6 {
+	font-size: calc(8px * 1.1667);
+	font-size: 1.1667em;
+	font-weight: normal;
+	font-style: italic;
+	font-family: "le-monde-livre-classic-byol", serif !important;
+	letter-spacing: 0px !important;
+}
+
+#start .md > *:first-child {
+	margin-top: 0;
+}
+
+h2 + h3 {
+	margin-top: 0;
+}
+
+.md hr {
+	border: none;
+	border-top: 1px solid var(--block-border-color);
+	margin: var(--vspace-2) 0 var(--vspace-2) 0;
+}
+.prose ul {
+	margin: var(--vspace-2) 0 var(--vspace-1) 0;
+}
+
+.gap {
+	gap: 0;
+}

event-trace/graph-4nNtOvIp.json

@@ -0,0 +1,3 @@
+{
+  "dotSrc": "digraph {\n\tgraph [bgcolor=\"#333537\" rankdir=LR]\n\tweather_agent_v1 [label=\"🤖 weather_agent_v1\" color=\"#0F5223\" fillcolor=\"#0F5223\" fontcolor=\"#cccccc\" shape=ellipse style=\"filled,rounded\"]\n\tget_weather [label=\"🔧 get_weather\" color=\"#cccccc\" fontcolor=\"#cccccc\" shape=box style=rounded]\n\tweather_agent_v1 -> get_weather [arrowhead=none color=\"#cccccc\"]\n}\n"
+}

event-trace/graph-HPTxQshW.json

@@ -0,0 +1,3 @@
+{
+  "dotSrc": "digraph {\n\tgraph [bgcolor=\"#333537\" rankdir=LR]\n\tweather_agent_v1 [label=\"🤖 weather_agent_v1\" color=\"#cccccc\" fontcolor=\"#cccccc\" shape=ellipse style=rounded]\n\tget_weather [label=\"🔧 get_weather\" color=\"#cccccc\" fontcolor=\"#cccccc\" shape=box style=rounded]\n\tweather_agent_v1 -> get_weather [arrowhead=none color=\"#cccccc\"]\n}\n"
+}

event-trace/graph-J0thtik1.json

@@ -0,0 +1,3 @@
+{
+  "dotSrc": "digraph {\n\tgraph [bgcolor=\"#333537\" rankdir=LR]\n\tweather_agent_v1 [label=\"🤖 weather_agent_v1\" color=\"#cccccc\" fontcolor=\"#cccccc\" shape=ellipse style=rounded]\n\tget_weather [label=\"🔧 get_weather\" color=\"#cccccc\" fontcolor=\"#cccccc\" shape=box style=rounded]\n\tweather_agent_v1 -> get_weather [arrowhead=none color=\"#cccccc\"]\n}\n"
+}

event-trace/graph-mizs2Mpl.json

@@ -0,0 +1,3 @@
+{
+  "dotSrc": "digraph {\n\tgraph [bgcolor=\"#333537\" rankdir=LR]\n\tweather_agent_v1 [label=\"🤖 weather_agent_v1\" color=\"#0F5223\" fillcolor=\"#0F5223\" fontcolor=\"#cccccc\" shape=ellipse style=\"filled,rounded\"]\n\tget_weather [label=\"🔧 get_weather\" color=\"#0F5223\" fillcolor=\"#0F5223\" fontcolor=\"#cccccc\" shape=box style=\"filled,rounded\"]\n\tweather_agent_v1 -> get_weather [color=\"#69CB87\" dir=back]\n}\n"
+}

event-trace/graph-pjqr5AM1.json

@@ -0,0 +1,3 @@
+{
+  "dotSrc": "digraph {\n\tgraph [bgcolor=\"#333537\" rankdir=LR]\n\tweather_agent_v1 [label=\"🤖 weather_agent_v1\" color=\"#0F5223\" fillcolor=\"#0F5223\" fontcolor=\"#cccccc\" shape=ellipse style=\"filled,rounded\"]\n\tget_weather [label=\"🔧 get_weather\" color=\"#0F5223\" fillcolor=\"#0F5223\" fontcolor=\"#cccccc\" shape=box style=\"filled,rounded\"]\n\tweather_agent_v1 -> get_weather [color=\"#69CB87\"]\n}\n"
+}

event-trace/trace-4nNtOvIp.json

@@ -0,0 +1,11 @@
+{
+  "gen_ai.system": "gcp.vertex.agent",
+  "gen_ai.request.model": "gemini-2.0-flash",
+  "gcp.vertex.agent.invocation_id": "e-46b87f9c-6deb-4d6e-8031-0d8194aaae00",
+  "gcp.vertex.agent.session_id": "d6de8f93-5b2c-487f-9f54-bd6abfd06bbe",
+  "gcp.vertex.agent.event_id": "4nNtOvIp",
+  "gcp.vertex.agent.llm_request": "{\"model\": \"gemini-2.0-flash\", \"config\": {\"system_instruction\": \"You are a helpful weather assistant. Your primary goal is to provide current weather reports. When the user asks for the weather in a specific city, you MUST use the 'get_weather' tool to find the information. Analyze the tool's response: if the status is 'error', inform the user politely about the error message. If the status is 'success', present the weather 'report' clearly and concisely to the user. Only use the tool when a city is mentioned for a weather request.\\n\\nYou are an agent. Your internal name is \\\"weather_agent_v1\\\".\\n\\n The description about you is \\\"Provides weather information for specific cities.\\\"\", \"tools\": [{\"function_declarations\": [{\"description\": \"Retrieves the current weather report for a specified city.\\n\\n    Args:\\n        city (str): The name of the city (e.g., \\\"New York\\\", \\\"London\\\", \\\"Tokyo\\\").\\n\\n    Returns:\\n        dict: A dictionary containing the weather information.\\n              Includes a 'status' key ('success' or 'error').\\n              If 'success', includes a 'report' key with weather details.\\n              If 'error', includes an 'error_message' key.\\n    \", \"name\": \"get_weather\", \"parameters\": {\"properties\": {\"city\": {\"type\": \"STRING\"}}, \"required\": [\"city\"], \"type\": \"OBJECT\"}}]}]}, \"contents\": [{\"parts\": [{\"text\": \"hi\"}], \"role\": \"user\"}]}",
+  "gcp.vertex.agent.llm_response": "{\"content\":{\"parts\":[{\"text\":\"Hi there! How can I help you today?\\n\"}],\"role\":\"model\"},\"usage_metadata\":{\"candidates_token_count\":11,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":11}],\"prompt_token_count\":246,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":246}],\"total_token_count\":257}}",
+  "trace_id": 2.590244190807234e+37,
+  "span_id": 4003274593459785700
+}

event-trace/trace-HPTxQshW.json

@@ -0,0 +1,11 @@
+{
+  "gen_ai.system": "gcp.vertex.agent",
+  "gen_ai.request.model": "gemini-2.0-flash",
+  "gcp.vertex.agent.invocation_id": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+  "gcp.vertex.agent.session_id": "d6de8f93-5b2c-487f-9f54-bd6abfd06bbe",
+  "gcp.vertex.agent.event_id": "HPTxQshW",
+  "gcp.vertex.agent.llm_request": "{\"model\": \"gemini-2.0-flash\", \"config\": {\"system_instruction\": \"You are a helpful weather assistant. Your primary goal is to provide current weather reports. When the user asks for the weather in a specific city, you MUST use the 'get_weather' tool to find the information. Analyze the tool's response: if the status is 'error', inform the user politely about the error message. If the status is 'success', present the weather 'report' clearly and concisely to the user. Only use the tool when a city is mentioned for a weather request.\\n\\nYou are an agent. Your internal name is \\\"weather_agent_v1\\\".\\n\\n The description about you is \\\"Provides weather information for specific cities.\\\"\", \"tools\": [{\"function_declarations\": [{\"description\": \"Retrieves the current weather report for a specified city.\\n\\n    Args:\\n        city (str): The name of the city (e.g., \\\"New York\\\", \\\"London\\\", \\\"Tokyo\\\").\\n\\n    Returns:\\n        dict: A dictionary containing the weather information.\\n              Includes a 'status' key ('success' or 'error').\\n              If 'success', includes a 'report' key with weather details.\\n              If 'error', includes an 'error_message' key.\\n    \", \"name\": \"get_weather\", \"parameters\": {\"properties\": {\"city\": {\"type\": \"STRING\"}}, \"required\": [\"city\"], \"type\": \"OBJECT\"}}]}]}, \"contents\": [{\"parts\": [{\"text\": \"hi\"}], \"role\": \"user\"}, {\"parts\": [{\"text\": \"Hi there! How can I help you today?\\n\"}], \"role\": \"model\"}, {\"parts\": [{\"text\": \"what is the weather in new york\"}], \"role\": \"user\"}, {\"parts\": [{\"function_call\": {\"args\": {\"city\": \"New York\"}, \"name\": \"get_weather\"}}], \"role\": \"model\"}, {\"parts\": [{\"function_response\": {\"name\": \"get_weather\", \"response\": {\"status\": \"success\", \"report\": \"The weather in New york is sunny with a temperature of 25°C.\"}}}], \"role\": \"user\"}]}",
+  "gcp.vertex.agent.llm_response": "{\"content\":{\"parts\":[{\"text\":\"The weather in New York is sunny with a temperature of 25°C.\\n\"}],\"role\":\"model\"},\"usage_metadata\":{\"candidates_token_count\":18,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":18}],\"prompt_token_count\":293,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":293}],\"total_token_count\":311}}",
+  "trace_id": 1.585818373009333e+38,
+  "span_id": 11193696278902387000
+}

event-trace/trace-mizs2Mpl.json

@@ -0,0 +1,14 @@
+{
+  "gen_ai.system": "gcp.vertex.agent",
+  "gen_ai.operation.name": "execute_tool",
+  "gen_ai.tool.name": "get_weather",
+  "gen_ai.tool.description": "Retrieves the current weather report for a specified city.\n\nArgs:\n    city (str): The name of the city (e.g., \"New York\", \"London\", \"Tokyo\").\n\nReturns:\n    dict: A dictionary containing the weather information.\n          Includes a 'status' key ('success' or 'error').\n          If 'success', includes a 'report' key with weather details.\n          If 'error', includes an 'error_message' key.",
+  "gen_ai.tool.call.id": "adk-b488c3ed-5875-4999-89ed-383b0c94826d",
+  "gcp.vertex.agent.tool_call_args": "{\"city\": \"New York\"}",
+  "gcp.vertex.agent.event_id": "mizs2Mpl",
+  "gcp.vertex.agent.tool_response": "{\"status\": \"success\", \"report\": \"The weather in New york is sunny with a temperature of 25°C.\"}",
+  "gcp.vertex.agent.llm_request": "{}",
+  "gcp.vertex.agent.llm_response": "{}",
+  "trace_id": 1.585818373009333e+38,
+  "span_id": 17506961790282844000
+}

event-trace/trace-pjqr5AM1.json

@@ -0,0 +1,11 @@
+{
+  "gen_ai.system": "gcp.vertex.agent",
+  "gen_ai.request.model": "gemini-2.0-flash",
+  "gcp.vertex.agent.invocation_id": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+  "gcp.vertex.agent.session_id": "d6de8f93-5b2c-487f-9f54-bd6abfd06bbe",
+  "gcp.vertex.agent.event_id": "pjqr5AM1",
+  "gcp.vertex.agent.llm_request": "{\"model\": \"gemini-2.0-flash\", \"config\": {\"system_instruction\": \"You are a helpful weather assistant. Your primary goal is to provide current weather reports. When the user asks for the weather in a specific city, you MUST use the 'get_weather' tool to find the information. Analyze the tool's response: if the status is 'error', inform the user politely about the error message. If the status is 'success', present the weather 'report' clearly and concisely to the user. Only use the tool when a city is mentioned for a weather request.\\n\\nYou are an agent. Your internal name is \\\"weather_agent_v1\\\".\\n\\n The description about you is \\\"Provides weather information for specific cities.\\\"\", \"tools\": [{\"function_declarations\": [{\"description\": \"Retrieves the current weather report for a specified city.\\n\\n    Args:\\n        city (str): The name of the city (e.g., \\\"New York\\\", \\\"London\\\", \\\"Tokyo\\\").\\n\\n    Returns:\\n        dict: A dictionary containing the weather information.\\n              Includes a 'status' key ('success' or 'error').\\n              If 'success', includes a 'report' key with weather details.\\n              If 'error', includes an 'error_message' key.\\n    \", \"name\": \"get_weather\", \"parameters\": {\"properties\": {\"city\": {\"type\": \"STRING\"}}, \"required\": [\"city\"], \"type\": \"OBJECT\"}}]}]}, \"contents\": [{\"parts\": [{\"text\": \"hi\"}], \"role\": \"user\"}, {\"parts\": [{\"text\": \"Hi there! How can I help you today?\\n\"}], \"role\": \"model\"}, {\"parts\": [{\"text\": \"what is the weather in new york\"}], \"role\": \"user\"}]}",
+  "gcp.vertex.agent.llm_response": "{\"content\":{\"parts\":[{\"function_call\":{\"args\":{\"city\":\"New York\"},\"name\":\"get_weather\"}}],\"role\":\"model\"},\"usage_metadata\":{\"candidates_token_count\":6,\"candidates_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":6}],\"prompt_token_count\":264,\"prompt_tokens_details\":[{\"modality\":\"TEXT\",\"token_count\":264}],\"total_token_count\":270}}",
+  "trace_id": 1.585818373009333e+38,
+  "span_id": 15023233232456225000
+}

requirements.txt

@@ -0,0 +1 @@
+gradio_agent_inspector

session-sample/value-0.json

@@ -0,0 +1,68 @@
+{
+  "id": "d6de8f93-5b2c-487f-9f54-bd6abfd06bbe",
+  "appName": "weather_agent",
+  "userId": "user",
+  "state": {
+    "last_response": "Hi there! How can I help you today?\n"
+  },
+  "events": [
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "hi"
+          }
+        ],
+        "role": "user"
+      },
+      "invocationId": "e-46b87f9c-6deb-4d6e-8031-0d8194aaae00",
+      "author": "user",
+      "actions": {
+        "stateDelta": {},
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "UuzEKV1U",
+      "timestamp": 1749409305.556533
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "Hi there! How can I help you today?\n"
+          }
+        ],
+        "role": "model"
+      },
+      "usageMetadata": {
+        "candidatesTokenCount": 11,
+        "candidatesTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 11
+          }
+        ],
+        "promptTokenCount": 246,
+        "promptTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 246
+          }
+        ],
+        "totalTokenCount": 257
+      },
+      "invocationId": "e-46b87f9c-6deb-4d6e-8031-0d8194aaae00",
+      "author": "weather_agent_v1",
+      "actions": {
+        "stateDelta": {
+          "last_response": "Hi there! How can I help you today?\n"
+        },
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "4nNtOvIp",
+      "timestamp": 1749409305.556533
+    }
+  ],
+  "lastUpdateTime": 1749409305.556533
+}

session-sample/value-1.json

@@ -0,0 +1,197 @@
+{
+  "id": "d6de8f93-5b2c-487f-9f54-bd6abfd06bbe",
+  "appName": "weather_agent",
+  "userId": "user",
+  "state": {
+    "last_response": "The weather in New York is sunny with a temperature of 25°C.\n",
+    "last_city_checked_stateful": "New York"
+  },
+  "events": [
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "hi"
+          }
+        ],
+        "role": "user"
+      },
+      "invocationId": "e-46b87f9c-6deb-4d6e-8031-0d8194aaae00",
+      "author": "user",
+      "actions": {
+        "stateDelta": {},
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "UuzEKV1U",
+      "timestamp": 1749409305.556533
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "Hi there! How can I help you today?\n"
+          }
+        ],
+        "role": "model"
+      },
+      "usageMetadata": {
+        "candidatesTokenCount": 11,
+        "candidatesTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 11
+          }
+        ],
+        "promptTokenCount": 246,
+        "promptTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 246
+          }
+        ],
+        "totalTokenCount": 257
+      },
+      "invocationId": "e-46b87f9c-6deb-4d6e-8031-0d8194aaae00",
+      "author": "weather_agent_v1",
+      "actions": {
+        "stateDelta": {
+          "last_response": "Hi there! How can I help you today?\n"
+        },
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "4nNtOvIp",
+      "timestamp": 1749409305.556533
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "what is the weather in new york"
+          }
+        ],
+        "role": "user"
+      },
+      "invocationId": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+      "author": "user",
+      "actions": {
+        "stateDelta": {},
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "J0thtik1",
+      "timestamp": 1749409604.09957
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "functionCall": {
+              "id": "adk-b488c3ed-5875-4999-89ed-383b0c94826d",
+              "args": {
+                "city": "New York"
+              },
+              "name": "get_weather"
+            }
+          }
+        ],
+        "role": "model"
+      },
+      "usageMetadata": {
+        "candidatesTokenCount": 6,
+        "candidatesTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 6
+          }
+        ],
+        "promptTokenCount": 264,
+        "promptTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 264
+          }
+        ],
+        "totalTokenCount": 270
+      },
+      "invocationId": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+      "author": "weather_agent_v1",
+      "actions": {
+        "stateDelta": {},
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "longRunningToolIds": [],
+      "id": "pjqr5AM1",
+      "timestamp": 1749409604.09957
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "functionResponse": {
+              "id": "adk-b488c3ed-5875-4999-89ed-383b0c94826d",
+              "name": "get_weather",
+              "response": {
+                "status": "success",
+                "report": "The weather in New york is sunny with a temperature of 25°C."
+              }
+            }
+          }
+        ],
+        "role": "user"
+      },
+      "invocationId": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+      "author": "weather_agent_v1",
+      "actions": {
+        "stateDelta": {
+          "last_city_checked_stateful": "New York"
+        },
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "mizs2Mpl",
+      "timestamp": 1749409604.677217
+    },
+    {
+      "content": {
+        "parts": [
+          {
+            "text": "The weather in New York is sunny with a temperature of 25°C.\n"
+          }
+        ],
+        "role": "model"
+      },
+      "usageMetadata": {
+        "candidatesTokenCount": 18,
+        "candidatesTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 18
+          }
+        ],
+        "promptTokenCount": 293,
+        "promptTokensDetails": [
+          {
+            "modality": "TEXT",
+            "tokenCount": 293
+          }
+        ],
+        "totalTokenCount": 311
+      },
+      "invocationId": "e-cee39ecc-0cef-4e03-9047-0b8d5e728964",
+      "author": "weather_agent_v1",
+      "actions": {
+        "stateDelta": {
+          "last_response": "The weather in New York is sunny with a temperature of 25°C.\n"
+        },
+        "artifactDelta": {},
+        "requestedAuthConfigs": {}
+      },
+      "id": "HPTxQshW",
+      "timestamp": 1749409604.677217
+    }
+  ],
+  "lastUpdateTime": 1749409604.677217
+}

session-sample/value-init.json

@@ -0,0 +1,8 @@
+{
+  "id": "7b31fe12-e9a7-44ab-8b8f-712168050621",
+  "appName": "agent",
+  "userId": "user",
+  "state": {},
+  "events": [],
+  "lastUpdateTime": 1748896263.8251631
+}

space.py

@@ -0,0 +1,226 @@
+
+import gradio as gr
+from app import demo as app
+import os
+
+_docs = {'AgentInspector': {'description': 'Creates a very simple textbox for user to enter string input or display string output.', 'members': {'__init__': {'value': {'type': 'str | Callable | None', 'default': 'None', 'description': 'default text to provide in textbox. If a function is provided, the function will be called each time the app loads to set the initial value of this component.'}, 'placeholder': {'type': 'str | None', 'default': 'None', 'description': 'placeholder hint to provide behind textbox.'}, 'label': {'type': 'str | I18nData | None', 'default': 'None', 'description': 'the label for this component, displayed above the component if `show_label` is `True` and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component corresponds to.'}, 'every': {'type': 'Timer | float | None', 'default': 'None', 'description': 'Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.'}, 'inputs': {'type': 'Component | Sequence[Component] | set[Component] | None', 'default': 'None', 'description': 'Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.'}, 'show_label': {'type': 'bool | None', 'default': 'None', 'description': 'if True, will display label.'}, 'scale': {'type': 'int | None', 'default': 'None', 'description': 'relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.'}, 'min_width': {'type': 'int', 'default': '160', 'description': 'minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.'}, 'interactive': {'type': 'bool | None', 'default': 'None', 'description': 'if True, will be rendered as an editable textbox; if False, editing will be disabled. If not provided, this is inferred based on whether the component is used as an input or output.'}, 'visible': {'type': 'bool', 'default': 'True', 'description': 'If False, component will be hidden.'}, 'rtl': {'type': 'bool', 'default': 'False', 'description': 'If True and `type` is "text", sets the direction of the text to right-to-left (cursor appears on the left of the text). Default is False, which renders cursor on the right.'}, 'elem_id': {'type': 'str | None', 'default': 'None', 'description': 'An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.'}, 'elem_classes': {'type': 'list[str] | str | None', 'default': 'None', 'description': 'An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.'}, 'render': {'type': 'bool', 'default': 'True', 'description': 'If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.'}, 'key': {'type': 'int | str | tuple[int | str, ...] | None', 'default': 'None', 'description': "in a gr.render, Components with the same key across re-renders are treated as the same component, not a new component. Properties set in 'preserved_by_key' are not reset across a re-render."}, 'preserved_by_key': {'type': 'list[str] | str | None', 'default': '"value"', 'description': "A list of parameters from this component's constructor. Inside a gr.render() function, if a component is re-rendered with the same key, these (and only these) parameters will be preserved in the UI (if they have been changed by the user or an event listener) instead of re-rendered based on the values provided during constructor."}}, 'postprocess': {'value': {'type': 'str | None', 'description': 'Expects a {str} returned from function and sets textarea value to it.'}}, 'preprocess': {'return': {'type': 'str | None', 'description': 'Passes text value as a {str} into the function.'}, 'value': None}}, 'events': {'change': {'type': None, 'default': None, 'description': 'Triggered when the value of the AgentInspector changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input.'}, 'input': {'type': None, 'default': None, 'description': 'This listener is triggered when the user changes the value of the AgentInspector.'}, 'submit': {'type': None, 'default': None, 'description': 'This listener is triggered when the user presses the Enter key while the AgentInspector is focused.'}}}, '__meta__': {'additional_interfaces': {}, 'user_fn_refs': {'AgentInspector': []}}}
+
+abs_path = os.path.join(os.path.dirname(__file__), "css.css")
+
+with gr.Blocks(
+    css=abs_path,
+    theme=gr.themes.Default(
+        font_mono=[
+            gr.themes.GoogleFont("Inconsolata"),
+            "monospace",
+        ],
+    ),
+) as demo:
+    gr.Markdown(
+"""
+# `gradio_agent_inspector`
+
+<div style="display: flex; gap: 7px;">
+<a href="https://pypi.org/project/gradio_agent_inspector/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_agent_inspector"></a>  
+</div>
+
+Agent Inspector for ADK
+""", elem_classes=["md-custom"], header_links=True)
+    app.render()
+    gr.Markdown(
+"""
+## Installation
+
+```bash
+pip install gradio_agent_inspector
+```
+
+## Usage
+
+```python
+import json
+from pathlib import Path
+import gradio as gr
+from gradio_agent_inspector import AgentInspector
+import os
+
+
+def simulate_conversation():
+    dir_path = Path(os.path.dirname(os.path.realpath(__file__)))
+
+    initial_state = {
+        "state": {},
+        "events": [],
+    }
+
+    states = []
+    for i in range(2):
+        session_value_p = dir_path / "session-sample" / f"value-{i}.json"
+        with session_value_p.open("r", encoding="utf-8") as f:
+            session_value = json.load(f)
+
+            # attach event trace and graph info to the event
+            for e in session_value["events"]:
+                event_trace_p = dir_path / "event-trace" / f"trace-{e['id']}.json"
+                if event_trace_p.exists():
+                    with event_trace_p.open("r", encoding="utf-8") as trace_f:
+                        event_trace = json.load(trace_f)
+                        if "gcp.vertex.agent.llm_request" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_request"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_request"]
+                            )
+                        if "gcp.vertex.agent.llm_response" in event_trace:
+                            event_trace["gcp.vertex.agent.llm_response"] = json.loads(
+                                event_trace["gcp.vertex.agent.llm_response"]
+                            )
+                        e["trace"] = event_trace
+                event_graph_p = dir_path / "event-trace" / f"graph-{e['id']}.json"
+                if event_graph_p.exists():
+                    with event_graph_p.open("r", encoding="utf-8") as graph_f:
+                        event_graph = json.load(graph_f)
+                        e["graph"] = event_graph
+            states.append(session_value)
+
+    return initial_state, states
+
+
+def update_conversation_state(state_index, states):
+    if (state_index + 1) >= len(states):
+        return states[state_index], state_index
+    else:
+        new_index = state_index + 1
+        return states[new_index], new_index
+
+
+initial_state, conversation_states = simulate_conversation()
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Agent Inspector")
+
+    state_counter = gr.State(-1)
+
+    agent_inspector = AgentInspector(json.dumps(initial_state))
+
+    with gr.Row():
+        next_btn = gr.Button(
+            f"▶️ Next ({0} / {len(conversation_states)})", variant="primary"
+        )
+        reset_btn = gr.Button("🔄 Reset", variant="secondary")
+
+    def next_state(current_counter):
+        new_state, new_counter = update_conversation_state(
+            current_counter, conversation_states
+        )
+
+        json_state = json.dumps(new_state)
+        next_button_label = f"▶️ Next ({new_counter+1} / {len(conversation_states)})"
+
+        return json_state, new_counter, next_button_label
+
+    def reset_conversation():
+        json_state = json.dumps(initial_state)
+        next_button_label = f"▶️ Next ({0} / {len(conversation_states)})"
+
+        return json_state, -1, next_button_label
+
+    next_btn.click(
+        next_state,
+        inputs=[state_counter],
+        outputs=[agent_inspector, state_counter, next_btn],
+    )
+
+    reset_btn.click(
+        reset_conversation, outputs=[agent_inspector, state_counter, next_btn]
+    )
+
+    # examples = gr.Examples(
+    #     examples=[
+    #         s for s in conversation_states
+    #     ],
+    #     inputs=[initial_state],
+    # )
+
+if __name__ == "__main__":
+    demo.launch()
+
+```
+""", elem_classes=["md-custom"], header_links=True)
+
+
+    gr.Markdown("""
+## `AgentInspector`
+
+### Initialization
+""", elem_classes=["md-custom"], header_links=True)
+
+    gr.ParamViewer(value=_docs["AgentInspector"]["members"]["__init__"], linkify=[])
+
+
+    gr.Markdown("### Events")
+    gr.ParamViewer(value=_docs["AgentInspector"]["events"], linkify=['Event'])
+
+
+
+
+    gr.Markdown("""
+
+### User function
+
+The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).
+
+- When used as an Input, the component only impacts the input signature of the user function.
+- When used as an output, the component only impacts the return signature of the user function.
+
+The code snippet below is accurate in cases where the component is used as both an input and an output.
+
+- **As input:** Is passed, passes text value as a {str} into the function.
+- **As output:** Should return, expects a {str} returned from function and sets textarea value to it.
+
+ ```python
+def predict(
+    value: str | None
+) -> str | None:
+    return value
+```
+""", elem_classes=["md-custom", "AgentInspector-user-fn"], header_links=True)
+
+
+
+
+    demo.load(None, js=r"""function() {
+    const refs = {};
+    const user_fn_refs = {
+          AgentInspector: [], };
+    requestAnimationFrame(() => {
+
+        Object.entries(user_fn_refs).forEach(([key, refs]) => {
+            if (refs.length > 0) {
+                const el = document.querySelector(`.${key}-user-fn`);
+                if (!el) return;
+                refs.forEach(ref => {
+                    el.innerHTML = el.innerHTML.replace(
+                        new RegExp("\\b"+ref+"\\b", "g"),
+                        `<a href="#h-${ref.toLowerCase()}">${ref}</a>`
+                    );
+                })
+            }
+        })
+
+        Object.entries(refs).forEach(([key, refs]) => {
+            if (refs.length > 0) {
+                const el = document.querySelector(`.${key}`);
+                if (!el) return;
+                refs.forEach(ref => {
+                    el.innerHTML = el.innerHTML.replace(
+                        new RegExp("\\b"+ref+"\\b", "g"),
+                        `<a href="#h-${ref.toLowerCase()}">${ref}</a>`
+                    );
+                })
+            }
+        })
+    })
+}
+
+""")
+
+demo.launch()