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eval to json decoding

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Xi Yan 2025-02-28 10:46:28 -08:00
parent 7f9b767277
commit 317bd21f81
1 changed files with 5 additions and 5 deletions
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10
llama_stack/providers/inline/eval/meta_reference/eval.py
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@ -3,6 +3,7 @@
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import json
from typing import Any, Dict, List, Optional
from tqdm import tqdm
@ -117,7 +118,7 @@ class MetaReferenceEvalImpl(
generations = []
for i, x in tqdm(enumerate(input_rows)):
assert ColumnName.chat_completion_input.value in x, "Invalid input row"
input_messages = eval(str(x[ColumnName.chat_completion_input.value]))
input_messages = json.loads(x[ColumnName.chat_completion_input.value])
input_messages = [UserMessage(**x) for x in input_messages]
# NOTE: only single-turn agent generation is supported. Create a new session for each input row
@ -159,7 +160,7 @@ class MetaReferenceEvalImpl(
generations = []
for x in tqdm(input_rows):
if ColumnName.completion_input.value in x:
input_content = eval(str(x[ColumnName.completion_input.value]))
input_content = json.loads(x[ColumnName.completion_input.value])
response = await self.inference_api.completion(
model=candidate.model,
content=input_content,
@ -167,9 +168,8 @@ class MetaReferenceEvalImpl(
)
generations.append({ColumnName.generated_answer.value: response.completion_message.content})
elif ColumnName.chat_completion_input.value in x:
chat_completion_input_str = str(x[ColumnName.chat_completion_input.value])
input_messages = eval(chat_completion_input_str)
input_messages = [UserMessage(**x) for x in input_messages]
chat_completion_input_json = json.loads(x[ColumnName.chat_completion_input.value])
input_messages = [UserMessage(**x) for x in chat_completion_input_json]
messages = []
if candidate.system_message:
messages.append(candidate.system_message)