From fc600258b2624b4d179e56ac4ab7bb6f8ed85cff Mon Sep 17 00:00:00 2001
From: wenba0 <3054239545@qq.com>
Date: Tue, 23 Jun 2026 15:15:46 +0800
Subject: [PATCH 1/2] test ai

---
 .codex                                                      | 0
 ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py | 4 ++--
 2 files changed, 2 insertions(+), 2 deletions(-)
 create mode 100644 .codex

diff --git a/.codex b/.codex
new file mode 100644
index 00000000..e69de29b
diff --git a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
index 41d7dd63..d2b57dee 100644
--- a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
+++ b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
@@ -3,7 +3,7 @@
 from ais_bench.benchmark.openicl.icl_inferencer import GenInferencer
 from ais_bench.benchmark.datasets import TEXTVQADataset, TEXTEvaluator, TEXTEvaluatorForVita
 
-
+PROMPT = "Answer the question using a single word or phrase."
 textvqa_reader_cfg = dict(
     input_columns=['question', 'image'],
     output_column='answer'
@@ -16,7 +16,7 @@
         template=dict(
             round=[
                 dict(role="HUMAN", prompt_mm={
-                    "text": {"type": "text", "text": "{question} Answer the question using a single word or phrase."},
+                    "text": {"type": "text", "text": "{question} "+PROMPT},
                     "image": {"type": "image_url", "image_url": {"url": "file://{image}"}},
                 })
             ]

From 19c676f6c2f9b772b94da20afe4db99fd55b29be Mon Sep 17 00:00:00 2001
From: wenba0 <3054239545@qq.com>
Date: Tue, 23 Jun 2026 16:06:26 +0800
Subject: [PATCH 2/2] fix review

---
 ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py    | 2 +-
 .../benchmark/configs/datasets/textvqa/textvqa_gen_base64.py   | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
index d2b57dee..1d6d4b5e 100644
--- a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
+++ b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen.py
@@ -16,7 +16,7 @@
         template=dict(
             round=[
                 dict(role="HUMAN", prompt_mm={
-                    "text": {"type": "text", "text": "{question} "+PROMPT},
+                    "text": {"type": "text", "text": f"{{question}} {PROMPT}"},
                     "image": {"type": "image_url", "image_url": {"url": "file://{image}"}},
                 })
             ]
diff --git a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen_base64.py b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen_base64.py
index 1e567370..6ed3a76c 100644
--- a/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen_base64.py
+++ b/ais_bench/benchmark/configs/datasets/textvqa/textvqa_gen_base64.py
@@ -3,6 +3,7 @@
 from ais_bench.benchmark.openicl.icl_inferencer import GenInferencer
 from ais_bench.benchmark.datasets import TEXTVQADataset, TEXTEvaluator
 
+PROMPT = "Answer the question using a single word or phrase."
 
 textvqa_reader_cfg = dict(
     input_columns=['question', 'image'],
@@ -16,7 +17,7 @@
         template=dict(
             round=[
                 dict(role="HUMAN", prompt_mm={
-                    "text": {"type": "text", "text": "{question} Answer the question using a single word or phrase."},
+                    "text": {"type": "text", "text": f"{{question}} {PROMPT}"},
                     "image": {"type": "image_url", "image_url": {"url": "data:image/jpeg;base64,{image}"}},
                 })
             ]