Update app.py

app.py

@@ -26,6 +26,76 @@ available_function_defns = {
     key.split('_func')[0]: value['func']
     for key, value in dict_plugin_functions.items()
     }
+add_plugin_steps = """## Steps to add new Plugins to your Gradio ChatGPT Chatbot
+Do you want to open this information in a separate tab instead? - <a href="https://huggingface.co/spaces/ysharma/ChatGPT-Plugins-in-Gradio/blob/main/README.md" target="_blank">Click here</a>.
+
+1. **Acquire the API Endpoint**
+    - You need an API which you can query, and for this example let's consider using a text-to-speech demo hosted on Huggingface Spaces.
+    - **API Endpoint**: [https://gradio-neon-tts-plugin-coqui.hf.space/](https://gradio-neon-tts-plugin-coqui.hf.space/)
+
+2. **Create a Function to Query the API**
+    - You can access any Gradio demo as an API via the Gradio Python Client.
+    ```python
+    from gradio.client import Client
+
+    def texttospeech(input_text):
+        client = Client("https://gradio-neon-tts-plugin-coqui.hf.space/")
+        result = client.predict(
+            input_text,	# str  in 'Input' Textbox component
+            "en",	    # str  in 'Language' Radio component
+            api_name="/predict"
+        )
+        return result
+    ```
+
+3. **Describe the Function to GPT-3.5**
+    - You need to describe your function to GPT3.5/4. This function definition will get passed to gpt and will suck up your token. GPT may or may not use this function based on user inputs later on.  
+    - You can either use the Gradio demo for converting any given function to the required JSON format for GPT-3.5.
+      - Demo: [Function to JSON](https://huggingface.co/spaces/ysharma/function-to-JSON)
+      - Or, you can create the dictionary object on your own. Note that, the correct format is super important here.
+    - MAke sure to name your JSON object description as `<function_name>_func`.
+    ```python
+    texttospeech_func = {
+        "name": "texttospeech",
+        "description": "generate speech from the given input text",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "input_text": {
+                    "type": "string",
+                    "description": "text that will be used to generate speech"
+                }
+            },
+            "required": [
+                "input_text"
+            ]
+        }
+    }
+    ```
+
+4. **Add Function and JSON Object Details**
+    - Add the function definition and description to the `gpt_function_definitions.py` file (simply copy and paste).
+    - `dict_plugin_functions` is a dictionary of all available plugins. Add your plugin information to this dictionary in the required format.
+    ```python
+    'texttospeech_func': {
+        'dict': texttospeech_func,
+        'func': texttospeech
+    }
+    ```
+
+5. **Update the Chatbot Layout**
+    - Go to the Blocks Chatbot layout and add a new checkbox for your plugin as:
+    ```python
+    texttospeech = gr.Checkbox(label="📝🗣️Text-To-Speech", value=False)
+    ```
+    - Add the new checkbox component to your submit and click events for your chatbot and to the predict function accordingly.
+    - And also to the `plugins` list in `predict`
+      ```python
+      plugins = [music_gen, stable_diff, image_cap, top_news, texttospeech]
+      ```
+
+Thats it! you are have added your own brand new CHATGPT Plugin for yourself. Go PLAY!!
+"""
 
 # managing conversation with Plugins
 def run_conversation(user_input, function_call_decision):