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fix security update
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This commit is contained in:
Angel Nunez Mencias 2025-06-03 20:07:06 +02:00
parent 8943b283e9
commit b174effe05
Signed by: angel.nunez
SSH key fingerprint: SHA256:z1nFAg1v1AfbhEHrgBetByUJUwziv2R2f4VyN75opcg
14 changed files with 45 additions and 41 deletions
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8
llama_stack/distribution/ui/page/evaluations/app_eval.py
View file

@ -9,7 +9,7 @@ import json
import pandas as pd
import streamlit as st
from llama_stack.distribution.ui.modules.api import llama_stack_api
from llama_stack.distribution.ui.modules.api import LlamaStackApi
from llama_stack.distribution.ui.modules.utils import process_dataset
@ -39,7 +39,7 @@ def application_evaluation_page():
# Select Scoring Functions to Run Evaluation On
st.subheader("Select Scoring Functions")
scoring_functions = llama_stack_api.client.scoring_functions.list()
scoring_functions = LlamaStackApi().client.scoring_functions.list()
scoring_functions = {sf.identifier: sf for sf in scoring_functions}
scoring_functions_names = list(scoring_functions.keys())
selected_scoring_functions = st.multiselect(
@ -48,7 +48,7 @@ def application_evaluation_page():
help="Choose one or more scoring functions.",
)
available_models = llama_stack_api.client.models.list()
available_models = LlamaStackApi().client.models.list()
available_models = [m.identifier for m in available_models]
scoring_params = {}
@ -108,7 +108,7 @@ def application_evaluation_page():
progress_bar.progress(progress, text=progress_text)
# Run evaluation for current row
score_res = llama_stack_api.run_scoring(
score_res = LlamaStackApi().run_scoring(
r,
scoring_function_ids=selected_scoring_functions,
scoring_params=scoring_params,

10
llama_stack/distribution/ui/page/evaluations/native_eval.py
View file

@ -9,13 +9,13 @@ import json
import pandas as pd
import streamlit as st
from llama_stack.distribution.ui.modules.api import llama_stack_api
from llama_stack.distribution.ui.modules.api import LlamaStackApi
def select_benchmark_1():
# Select Benchmarks
st.subheader("1. Choose An Eval Task")
benchmarks = llama_stack_api.client.benchmarks.list()
benchmarks = LlamaStackApi().client.benchmarks.list()
benchmarks = {et.identifier: et for et in benchmarks}
benchmarks_names = list(benchmarks.keys())
selected_benchmark = st.selectbox(
@ -47,7 +47,7 @@ def define_eval_candidate_2():
# Define Eval Candidate
candidate_type = st.radio("Candidate Type", ["model", "agent"])
available_models = llama_stack_api.client.models.list()
available_models = LlamaStackApi().client.models.list()
available_models = [model.identifier for model in available_models]
selected_model = st.selectbox(
"Choose a model",
@ -167,7 +167,7 @@ def run_evaluation_3():
eval_candidate = st.session_state["eval_candidate"]
dataset_id = benchmarks[selected_benchmark].dataset_id
rows = llama_stack_api.client.datasets.iterrows(
rows = LlamaStackApi().client.datasets.iterrows(
dataset_id=dataset_id,
)
total_rows = len(rows.data)
@ -208,7 +208,7 @@ def run_evaluation_3():
progress = i / len(rows)
progress_bar.progress(progress, text=progress_text)
# Run evaluation for current row
eval_res = llama_stack_api.client.eval.evaluate_rows(
eval_res = LlamaStackApi().client.eval.evaluate_rows(
benchmark_id=selected_benchmark,
input_rows=[r],
scoring_functions=benchmarks[selected_benchmark].scoring_functions,