Update app.py

app.py

@@ -26,7 +26,7 @@ chat_history = []
 global last_id
 last_id = None
 
-def chat(prompt, tools):
+def chat(prompt, tools, voice_choice):
     chat_history.append(
                     {"role": "user", "content": prompt}
     )
@@ -64,26 +64,29 @@ def chat(prompt, tools):
     )
     last_id = response.id
 
-    elita_text = response.output_text
-
-    voice_settings = {
-          "stability": 0.37,
-          "similarity_boost": 0.90,
-          "style": 0.0,
-          "speed": 1.05
-          }
-
-    audio_stream = elevenlabs.text_to_speech.convert(
-      text = elita_text,
-      voice_id = 'vxO9F6g9yqYJ4RsWvMbc',
-      model_id = 'eleven_multilingual_v2',
-      output_format='mp3_44100_128',
-      voice_settings=voice_settings
-    )
-
-    audio_converted = b"".join(audio_stream)
-    audio = base64.b64encode(audio_converted).decode("utf-8")
-    audio_player = f'<audio src="data:audio/mpeg;base64,{audio}" controls autoplay></audio>'
+    if voice_choice = "On":
+        elita_text = response.output_text
+    
+        voice_settings = {
+              "stability": 0.37,
+              "similarity_boost": 0.90,
+              "style": 0.0,
+              "speed": 1.05
+              }
+    
+        audio_stream = elevenlabs.text_to_speech.convert(
+          text = elita_text,
+          voice_id = 'vxO9F6g9yqYJ4RsWvMbc',
+          model_id = 'eleven_multilingual_v2',
+          output_format='mp3_44100_128',
+          voice_settings=voice_settings
+        )
+    
+        audio_converted = b"".join(audio_stream)
+        audio = base64.b64encode(audio_converted).decode("utf-8")
+        audio_player = f'<audio src="data:audio/mpeg;base64,{audio}" controls autoplay></audio>'
+    else:
+        audio_player = ''
     
     return "", chat_history, audio_player
 
@@ -93,18 +96,55 @@ def clear_history():
 	global last_id
 	last_id = None
 
+def voice_from_file(file_name):
+  audio_file = file_name
+  with open(audio_file, 'rb') as audio_bytes:
+              audio = base64.b64encode(audio_bytes.read()).decode("utf-8")
+  audio_player = f'<audio src="data:audio/mpeg;base64,{audio}" controls autoplay></audio>'
+  return audio_player
+    
+def prot_workflow():
+  elita_text = "Starting with a protein, try searching for Uniprot IDs, followed by Chembl IDs. \
+Then you can look for bioactive molecules for each Chembl ID. You can also search for crystal structures \
+in the PDB and get titles of those structures, sequences, numbers of chains, and small molecules in the structure. \
+Generate novel bioactive molecules based on a protein Chembl ID using a GPT, or predict an IC50 for a molecule \
+based on a protein Chembl ID using a gradient-boosting model."
+  messages = [{'role': 'assistant', 'content': elita_text}]
+  audio_player = voice_from_file('protein_chat.mp3')
+  return audio_player, messages
+
+def prot_accordions():
+  elita_text = 'Try queries like: find UNIPROT IDs for the protein MAOB; find PDB IDs for MAOB; how many chains \
+are in the PDB structure 4A7G; find PDB IDs matching the protein MAOB; list the bioactive molecules for the CHEMBL \
+ID CHEMBL2039; dock the molecule CCCC(F) in the protein DRD2; predict the IC50 value for CCCC(F) based on the CHEMBL \
+ID CHEMBL2039; or generate novel molecules based on the CHEMBL ID CHEMBL2039.'
+  messages = [{'role': 'assistant', 'content': elita_text}]
+  audio_player = voice_from_file('protein.mp3')
+  return audio_player, messages
+
 with gr.Blocks() as forest:
   gr.Markdown(
       """
-      # Chat with OpenAI 04-mini using the CafChem suite of tools.
-      ### Enter your messages below including a SMILES string for a molecule, \
-or choose a pre-set molecule from the list to auto-populate a question. You cans use the \
-CafChem tools to generate analogues of a hit molecule for hit expansion or find some \
-ADME properties of a molecule.
+      # Chat with MoDrAg! OpenAI 04-mini can tap into Modrag through an MCP and use all of your favourite drug design tools.
+      - Currently using the tools below:
       """)
+  with gr.Row():
+    with gr.Accordion("Protein Agent - Click to open/close.", open=False)as prot:
+      gr.Markdown('''
+                  - Find Uniprot IDs for a protein/gene name.
+                  - report the number of bioactive molecules for a protein, organized by Chembl ID.
+                  - report the SMILES and IC50 values of bioactive molecules for a particular Chembl ID.
+                  - find protein sequences, report number fo chains.
+                  - find small molecules present in a PDB structure.
+                  - find PDB IDs that match a protein.
+                  - predict the IC50 value of a small molecule based on a Chembl ID.
+                  - generate novel molecules based on a Chembl ID.
+      ''')
+    workflow = gr.Button(value = "Sample Workflow")
 
-  tools = gr.Radio(choices = ["Yes", "No"],label="Use CafChem tools?",
-                   interactive=True)
+  with gr.Row():
+    tools = gr.Radio(choices = ["Yes", "No"],label="Use CafChem tools?",interactive=True, value = "Yes", scale = 2)
+    voice_choice = gr.Radio(choices = ['On', 'Off'],label="Audio Voice Response?", interactive=True, value='Off', scale = 2)
   
   chatbot = gr.Chatbot()
 
@@ -113,12 +153,12 @@ ADME properties of a molecule.
     chat_btn = gr.Button(value = "Send", scale = 0)
   elitas_voice = gr.HTML() 
   
-      
   clear = gr.ClearButton([msg, chatbot])
   
-
-  chat_btn.click(chat, [msg, tools], [msg, chatbot, elitas_voice])
-  msg.submit(chat, [msg, tools], [msg, chatbot, elitas_voice])
+  chat_btn.click(chat, [msg, tools, voice_choice], [msg, chatbot, elitas_voice])
+  msg.submit(chat, [msg, tools, voice_choice], [msg, chatbot, elitas_voice])
+  workflow.click(prot_workflow, outputs=[elitas_voice, chatbot])
+  prot.expand(prot_accordions, outputs = [elitas_voice, chatbot])
   clear.click(clear_history)
 
 if __name__ == "__main__":