updated BAM models

app.py

@@ -20,6 +20,7 @@ from ibm_watson_machine_learning.metanames import GenTextParamsMetaNames as GenP
 from ibm_watson_machine_learning.foundation_models.utils.enums import DecodingMethods
 from ibm_watson_machine_learning.foundation_models import Model
 from ibm_watson_machine_learning.foundation_models.extensions.langchain import WatsonxLLM
+from ibm_watson_machine_learning.foundation_models.utils.enums import ModelTypes
 
 import genai
 
@@ -77,12 +78,13 @@ def setOaiApiKey(creds):
 def setBamApiKey(creds):
     creds = getBamCreds(creds)
     try:
-        genai.Model.models(credentials=creds['bam_creds'])
+        bam_models = genai.Model.models(credentials=creds['bam_creds'])
+        bam_models = sorted(x.id for x in bam_models)
         api_key_st = creds
-        return 'BAM credentials accepted.', *[x.update(interactive=False) for x in credComps_btn_tb], api_key_st
+        return 'BAM credentials accepted.', *[x.update(interactive=False) for x in credComps_btn_tb], api_key_st, model_dd.update(choices=getModelChoices(openAi_models, ModelTypes, bam_models))
     except Exception as e:
         gr.Warning(str(e))
-        return [x.update() for x in credComps_op]
+        return *[x.update() for x in credComps_op], model_dd.update()
 
 def setWxApiKey(key, p_id):
     creds = getWxCreds(key, p_id)
@@ -97,7 +99,7 @@ def setWxApiKey(key, p_id):
 
 # convert user uploaded data to vectorstore
 def uiData_vecStore(userFiles, userUrls, api_key_st, vsDict_st={}, progress=gr.Progress()):
-    opComponents = [data_ingest_btn, upload_fb, urls_tb]
+    opComponents = [data_ingest_btn, upload_fb, urls_tb, initChatbot_btn]
     # parse user data
     file_paths = []
     documents = []
@@ -129,7 +131,7 @@ def uiData_vecStore(userFiles, userUrls, api_key_st, vsDict_st={}, progress=gr.P
     src_str = str(src_str[1]) + ' source document(s) successfully loaded in vector store.'+'\n\n' + src_str[0]
     
     progress(1, 'Data loaded')
-    return vsDict_st, src_str, *[x.update(interactive=False) for x in [data_ingest_btn, upload_fb]], urls_tb.update(interactive=False, placeholder='')
+    return vsDict_st, src_str, *[x.update(interactive=False) for x in [data_ingest_btn, upload_fb]], urls_tb.update(interactive=False, placeholder=''), initChatbot_btn.update(interactive=True)
 
 # initialize chatbot function sets the QA Chain, and also sets/updates any other components to start chatting. updateQaChain function only updates QA chain and will be called whenever Adv Settings are updated.
 def initializeChatbot(temp, k, modelNameDD, stdlQs, api_key_st, vsDict_st, progress=gr.Progress()):
@@ -247,7 +249,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue='orange', secondary_hue='gray
                                     , placeholder=url_tb_ph)
                 data_ingest_btn = gr.Button("Load Data")
             status_tb = gr.TextArea(label='Status Info')
-            initChatbot_btn = gr.Button("Initialize Chatbot", variant="primary")
+            initChatbot_btn = gr.Button("Initialize Chatbot", variant="primary", interactive=False)
 
         credComps_btn_tb = [oaiKey_tb, oaiKey_btn, bamKey_tb, bamKey_btn, wxKey_tb, wxPid_tb, wxKey_btn]
         credComps_op = [status_tb] + credComps_btn_tb + [api_key_state]
@@ -266,7 +268,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue='orange', secondary_hue='gray
                         temp_sld = gr.Slider(minimum=0, maximum=1, step=0.1, value=0.7, label="Temperature", info='Sampling temperature to use when calling LLM. Defaults to 0.7')
                         k_sld = gr.Slider(minimum=1, maximum=10, step=1, value=mode.k, label="K", info='Number of relavant documents to return from Vector Store. Defaults to 4')
                         model_dd = gr.Dropdown(label='Model Name'\
-                                , choices=model_dd_choices, allow_custom_value=True\
+                                , choices=getModelChoices(openAi_models, ModelTypes, bam_models_old), allow_custom_value=True\
                                 , info=model_dd_info)
                     stdlQs_rb = gr.Radio(label='Standalone Question', info=stdlQs_rb_info\
                             , type='index', value=stdlQs_rb_choices[1]\
@@ -280,7 +282,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue='orange', secondary_hue='gray
     oaiKey_tb.submit(**oaiKey_btn_args)
 
     # BAM API button
-    bamKey_btn_args = {'fn':setBamApiKey, 'inputs':[bamKey_tb], 'outputs':credComps_op}
+    bamKey_btn_args = {'fn':setBamApiKey, 'inputs':[bamKey_tb], 'outputs':credComps_op+[model_dd]}
     bamKey_btn.click(**bamKey_btn_args)
     bamKey_tb.submit(**bamKey_btn_args)
 
@@ -289,7 +291,7 @@ with gr.Blocks(theme=gr.themes.Default(primary_hue='orange', secondary_hue='gray
     wxKey_btn.click(**wxKey_btn_args)
 
     # Data Ingest Button
-    data_ingest_event = data_ingest_btn.click(uiData_vecStore, [upload_fb, urls_tb, api_key_state, chromaVS_state], [chromaVS_state, status_tb, data_ingest_btn, upload_fb, urls_tb])
+    data_ingest_event = data_ingest_btn.click(uiData_vecStore, [upload_fb, urls_tb, api_key_state, chromaVS_state], [chromaVS_state, status_tb, data_ingest_btn, upload_fb, urls_tb, initChatbot_btn])
 
     # Adv Settings
     advSet_args = {'fn':updateQaChain, 'inputs':[temp_sld, k_sld, model_dd, stdlQs_rb, api_key_state, chromaVS_state], 'outputs':[qa_state, model_dd]}

ttyd_consts.py

@@ -1,5 +1,4 @@
 from langchain import PromptTemplate
-from ibm_watson_machine_learning.foundation_models.utils.enums import ModelTypes
 import os
 from dotenv import load_dotenv
 load_dotenv()
@@ -45,7 +44,7 @@ Question: {question} [/INST]
 
 promptLlama=PromptTemplate(input_variables=['context', 'question'], template=llamaPromptTemplate)
 
-bam_models = sorted(['bigscience/bloom',
+bam_models_old = sorted(['bigscience/bloom',
  'salesforce/codegen2-16b',
  'codellama/codellama-34b-instruct',
  'tiiuae/falcon-40b',
@@ -71,9 +70,9 @@ bam_models = sorted(['bigscience/bloom',
  'bigcode/starcoder',
  'google/ul2'])
 
-model_dd_info = 'Make sure your credentials are submitted before changing the model. You can also input any OpenAI model name or Watsonx/BAM model ID.' 
+openAi_models = ['gpt-3.5-turbo (openai)', 'gpt-3.5-turbo-16k (openai)', 'gpt-4 (openai)', 'text-davinci-003 (Legacy - openai)', 'text-curie-001 (Legacy - openai)', 'babbage-002 (openai)']
 
-model_dd_choices = ['gpt-3.5-turbo (openai)', 'gpt-3.5-turbo-16k (openai)', 'gpt-4 (openai)', 'text-davinci-003 (Legacy - openai)', 'text-curie-001 (Legacy - openai)', 'babbage-002 (openai)'] + [model.value+' (watsonx)' for model in ModelTypes] + [model + ' (bam)' for model in bam_models]
+model_dd_info = 'Make sure your credentials are submitted before changing the model. You can also input any OpenAI model name or Watsonx/BAM model ID.' 
 
 
 OaiDefaultModel = 'gpt-3.5-turbo (openai)'

ttyd_functions.py

@@ -372,3 +372,6 @@ def changeModel(oldModel, newModel):
         gr.Warning(warning)
         time.sleep(1)
     return newModel
+
+def getModelChoices(openAi_models, wml_models, bam_models):
+    return [model for model in openAi_models] + [model.value+' (watsonx)' for model in wml_models] + [model + ' (bam)' for model in bam_models]