Update visualizer_app.py
Browse files- visualizer_app.py +4 -8
visualizer_app.py
CHANGED
@@ -144,12 +144,8 @@ def client_instantiation(
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if project_client is not None:
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task_credentials_details = setup_task_credentials(project_client)
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elif deployment_client is not None:
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task_credentials_details = setup_task_credentials(deployment_client)
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elif project_client is not None and deployment_client is not None:
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task_credentials_details = setup_task_credentials(project_client)
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else:
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task_credentials_details =
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else:
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wx_credentials = None
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@@ -440,7 +436,7 @@ def active_client(client_selector):
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@app.cell
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def emb_model_selection(client, set_embedding_model_list):
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if
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model_specs = client.foundation_models.get_embeddings_model_specs()
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# model_specs = client.foundation_models.get_model_specs()
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resources = model_specs["resources"]
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@@ -517,7 +513,7 @@ def embedding_model():
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@app.cell
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def emb_model_parameters(emb_model_max_tk):
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from ibm_watsonx_ai.metanames import EmbedTextParamsMetaNames as EmbedParams
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if
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embed_params = {
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EmbedParams.TRUNCATE_INPUT_TOKENS: emb_model_max_tk,
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EmbedParams.RETURN_OPTIONS: {
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@@ -554,7 +550,7 @@ def emb_model_setup(embedding_model):
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@app.cell
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def emb_model_instantiation(
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from ibm_watsonx_ai.foundation_models import Embeddings
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if client is not None:
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embedding = Embeddings(
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if project_client is not None:
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task_credentials_details = setup_task_credentials(project_client)
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else:
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task_credentials_details = setup_task_credentials(deployment_client)
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else:
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wx_credentials = None
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@app.cell
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def emb_model_selection(client, set_embedding_model_list):
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if client is not None:
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model_specs = client.foundation_models.get_embeddings_model_specs()
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# model_specs = client.foundation_models.get_model_specs()
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resources = model_specs["resources"]
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@app.cell
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def emb_model_parameters(emb_model_max_tk):
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from ibm_watsonx_ai.metanames import EmbedTextParamsMetaNames as EmbedParams
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if embedding_model is not None:
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embed_params = {
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EmbedParams.TRUNCATE_INPUT_TOKENS: emb_model_max_tk,
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EmbedParams.RETURN_OPTIONS: {
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@app.cell
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def emb_model_instantiation(client, emb_model, embed_params):
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from ibm_watsonx_ai.foundation_models import Embeddings
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if client is not None:
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embedding = Embeddings(
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