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diff --git a/checkpoints/llava-next-llama-3-8b-student-lora-merged-115124/README.md b/checkpoints/llava-next-llama-3-8b-student-lora-merged-115124/README.md
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+---
+library_name: peft
+base_model: Lin-Chen/open-llava-next-llama3-8b
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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diff --git a/checkpoints/llava-next-llama-3-8b-teacher-lora-merged-115124/README.md b/checkpoints/llava-next-llama-3-8b-teacher-lora-merged-115124/README.md
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+---
+library_name: peft
+base_model: Lin-Chen/open-llava-next-llama3-8b
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
diff --git a/checkpoints/llava-next-llama-3-8b-teacher-lora-merged-115124/adapter_config.json b/checkpoints/llava-next-llama-3-8b-teacher-lora-merged-115124/adapter_config.json
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-    {
-      "epoch": 1.0,
-      "step": 33589,
-      "total_flos": 4291503404843008.0,
-      "train_loss": 0.5519348401742088,
-      "train_runtime": 110010.7773,
-      "train_samples_per_second": 19.541,
-      "train_steps_per_second": 0.305
-    }
-  ],
-  "logging_steps": 1.0,
-  "max_steps": 33589,
-  "num_input_tokens_seen": 0,
-  "num_train_epochs": 1,
-  "save_steps": 5000,
-  "total_flos": 4291503404843008.0,
-  "train_batch_size": 8,
-  "trial_name": null,
-  "trial_params": null
-}
diff --git a/requirements.txt b/requirements.txt
index 5e4d37438dd970f010beb0b379cb6b6a07b0b55f..814157f099ec9e8162089dc32f93d56e65e84999 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,4 +5,5 @@ numpy<2
 peft
 sentencepiece
 protobuf
-loguru
\ No newline at end of file
+loguru
+gradio==4.29.0
\ No newline at end of file
diff --git a/src/__pycache__/__init__.cpython-310.pyc b/src/__pycache__/__init__.cpython-310.pyc
deleted file mode 100644
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diff --git a/src/__pycache__/constants.cpython-310.pyc b/src/__pycache__/constants.cpython-310.pyc
deleted file mode 100644
index 2bbc5ac562632fc7d43a675671e7c95e3ad58d7d..0000000000000000000000000000000000000000
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diff --git a/src/__pycache__/conversation.cpython-310.pyc b/src/__pycache__/conversation.cpython-310.pyc
deleted file mode 100644
index 17b7afd928f83d0c1505e53a56fe14e3ae0a51e9..0000000000000000000000000000000000000000
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diff --git a/src/__pycache__/utils.cpython-310.pyc b/src/__pycache__/utils.cpython-310.pyc
deleted file mode 100644
index 73bf2a53c36a9e82b0a107ed1698efe1241a9995..0000000000000000000000000000000000000000
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diff --git a/src/conversation.py b/src/conversation.py
index 5a972537a4408ee69f324a5a545f9db306bdd282..6a82287f88522259887f6728ae619a0c5d5ff8df 100644
--- a/src/conversation.py
+++ b/src/conversation.py
@@ -165,10 +165,10 @@ class Conversation:
                 ret += ""
             for i, (role, message) in enumerate(self.messages):
                 if message:
-                    logger.info("msg={}", message)
+                    logger.info("msg = {}", message)
                     if type(message) is tuple:
                         message, images = message
-                        message = "<image>" * len(images) + message
+                        message = "<image>" * len(images) + "\n" + message
                     ret += f"<|start_header_id|>{role}<|end_header_id|>\n\n"
                     ret += f"{message.strip()}<|eot_id|>"
                 else:
diff --git a/src/model/__pycache__/__init__.cpython-310.pyc b/src/model/__pycache__/__init__.cpython-310.pyc
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diff --git a/src/model/__pycache__/monkey_patch_non_inplace.cpython-310.pyc b/src/model/__pycache__/monkey_patch_non_inplace.cpython-310.pyc
index 53d49fb74ea33ed24687a74d5681ed9aea49b804..fe1860a339f61d5981e4877789d49a256a67352e 100644
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diff --git a/src/model/model_llava.py b/src/model/model_llava.py
index 0722c082aa6c72a0a7879e364d84d47999fc7c52..3ab0b294968dba25cebd70fc6598b00141e7e997 100644
--- a/src/model/model_llava.py
+++ b/src/model/model_llava.py
@@ -2,7 +2,6 @@ from llava.model.builder import load_pretrained_model
 from llava.mm_utils import get_model_name_from_path, process_images, tokenizer_image_token
 from llava.constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN
 from llava.conversation import conv_templates
-from loguru import logger
 
 from PIL import Image
 import requests
@@ -14,10 +13,14 @@ from io import BytesIO
 import base64
 #model_path = "/scratch/TecManDep/A_Models/llava-v1.6-vicuna-7b"
 #conv_template = "vicuna_v1" # Make sure you use correct chat template for different models
+from src.utils import (
+    build_logger,
+)
 
+logger = build_logger("model_llava", "model_llava.log")
 def load_llava_model(lora_checkpoint=None):
     model_path =  "Lin-Chen/open-llava-next-llama3-8b"
-    conv_template = "llama_v3"
+    conv_template = "llama_v3_student"
     model_name = get_model_name_from_path(model_path)
     device = "cuda"
     device_map = "auto"
@@ -30,12 +33,13 @@ def load_llava_model(lora_checkpoint=None):
 
     model.eval()
     model.tie_weights()
-    logger.info("model device {}", model.device)
+    logger.info(f"model device {model.device}")
     return tokenizer, model, image_processor, conv_template
 
 tokenizer_llava, model_llava, image_processor_llava, conv_template_llava = load_llava_model(None)
-tokenizer_llava_fire, model_llava_fire, image_processor_llava_fire, conv_template_llava = load_llava_model("checkpoints/")
+tokenizer_llava_fire, model_llava_fire, image_processor_llava_fire, conv_template_llava = load_llava_model("checkpoints/llava-next-llama-3-8b-student-lora-merged-115124")
 model_llava_fire.to("cuda")
+
 @spaces.GPU
 def inference():
     image = Image.open("assets/example.jpg").convert("RGB")
@@ -67,7 +71,7 @@ def inference():
     return text_outputs
 
 
-@spaces.GPU
+@spaces.GPU(duration=25)
 def inference_by_prompt_and_images(prompt, images):
     device = "cuda"
     if len(images) > 0 and type(images[0]) is str:
@@ -79,7 +83,7 @@ def inference_by_prompt_and_images(prompt, images):
     image_tensor = image_tensor.to(dtype=torch.float16, device=device)
     input_ids = tokenizer_image_token(prompt, tokenizer_llava, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).to(device)
     image_sizes = [image.size for image in images]
-    logger.info("Shape: {};{}; Devices: {};{}",input_ids.shape, image_tensor.shape, input_ids.device, image_tensor.device)
+    logger.info(f"Shape: {input_ids.shape};{image_tensor.shape}; Devices: {input_ids.device};{image_tensor.device}")
     with torch.inference_mode():
         cont = model_llava.generate(
             input_ids,
@@ -91,10 +95,10 @@ def inference_by_prompt_and_images(prompt, images):
             use_cache=True
         )
     text_outputs = tokenizer_llava.batch_decode(cont, skip_special_tokens=True)
-    logger.info("response={}", text_outputs)
+    
     return text_outputs
 
-@spaces.GPU
+@spaces.GPU(duration=25)
 def inference_by_prompt_and_images_fire(prompt, images):
     device = "cuda"
     if len(images) > 0 and type(images[0]) is str:
@@ -102,23 +106,23 @@ def inference_by_prompt_and_images_fire(prompt, images):
         for image in images:
             image_data.append(Image.open(BytesIO(base64.b64decode(image))))
         images = image_data
-    image_tensor = process_images(images, image_processor_llava, model_llava.config)
+    image_tensor = process_images(images, image_processor_llava_fire, model_llava_fire.config)
     image_tensor = image_tensor.to(dtype=torch.float16, device=device)
-    input_ids = tokenizer_image_token(prompt, tokenizer_llava, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).to(device)
+    input_ids = tokenizer_image_token(prompt, tokenizer_llava_fire, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).to(device)
     image_sizes = [image.size for image in images]
-    logger.info("Shape: {};{}; Devices: {};{}",input_ids.shape, image_tensor.shape, input_ids.device, image_tensor.device)
+    logger.info(f"Shape: {input_ids.shape};{image_tensor.shape}; Devices: {input_ids.device};{image_tensor.device}")
     with torch.inference_mode():
         cont = model_llava_fire.generate(
             input_ids,
-            images=image_tensor,
+            images=[image_tensor.squeeze(dim=0)],
             image_sizes=image_sizes,
             do_sample=False,
             temperature=0,
             max_new_tokens=256,
             use_cache=True
         )
-    text_outputs = tokenizer_llava.batch_decode(cont, skip_special_tokens=True)
-    logger.info("response={}", text_outputs)
+    text_outputs = tokenizer_llava_fire.batch_decode(cont, skip_special_tokens=True)
+    logger.info(f"response={text_outputs}")
     return text_outputs
 
 if __name__ == "__main__":
diff --git a/src/model/model_registry.py b/src/model/model_registry.py
index b61a7eb8c2053883633cdc2ae0c4c76f307145f6..19cc177cf51b82a3f5a26f49266c10e81e092aae 100644
--- a/src/model/model_registry.py
+++ b/src/model/model_registry.py
@@ -22,10 +22,14 @@ def get_model_info(name: str) -> ModelInfo:
     if name in ['llava-fire', 'llava-original']:
         description = {
             "llava-fire": "LLaVA fine-tuned from FIRE dataset",
-            "llava-original": "LLaVA-NeXT with LLaMA-3-8B as language decoder"
+            "llava-original": "LLaVA-NeXT with LLaMA-3-8B as the language decoder"
+        }
+        model_names = {
+            "llava-fire": "FIRE-LLaVA",
+            "llava-original": "LLaVA-NeXT-LLaMA-3-8B"
         }
         return ModelInfo(
-            name, "", description[name]
+            model_names[name], "", description[name]
         )
     if name in model_info:
         return model_info[name]
diff --git a/src/modules/__pycache__/__init__.cpython-310.pyc b/src/modules/__pycache__/__init__.cpython-310.pyc
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diff --git a/src/serve/__pycache__/gradio_web_server.cpython-310.pyc b/src/serve/__pycache__/gradio_web_server.cpython-310.pyc
deleted file mode 100644
index 01e776c76ff74e2693eeec834f5d25d5bf7490aa..0000000000000000000000000000000000000000
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diff --git a/src/serve/__pycache__/remote_logger.cpython-310.pyc b/src/serve/__pycache__/remote_logger.cpython-310.pyc
deleted file mode 100644
index 8d9fa9536136c55c950052dcd54c14f56d97f171..0000000000000000000000000000000000000000
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diff --git a/src/serve/gradio_block_arena_named.py b/src/serve/gradio_block_arena_named.py
index 887fa6b0ce194735ed63c129e154e139a53fe4d8..434ecddcee97ae4fdf421b41781eccf5a65c03ef 100644
--- a/src/serve/gradio_block_arena_named.py
+++ b/src/serve/gradio_block_arena_named.py
@@ -222,7 +222,7 @@ def add_text(
         ]
         * 6
     )
-
+import copy
 
 def bot_response_multi(
     state0,
@@ -243,7 +243,8 @@ def bot_response_multi(
             state1.to_gradio_chatbot(),
         ) + (no_change_btn,) * 6
         return
-
+    # set state 1 as fixed
+    # state1.conv.messages = copy.deepcopy(state0.conv.messages)
     states = [state0, state1]
     gen = []
     for i in range(num_sides):
diff --git a/src/serve/gradio_block_arena_vision_named.py b/src/serve/gradio_block_arena_vision_named.py
index 2048f545537e2c30a1b5abc4e2190130511fcc39..b40861a7beda5e2886bb8f099e28467f04a09641 100644
--- a/src/serve/gradio_block_arena_vision_named.py
+++ b/src/serve/gradio_block_arena_vision_named.py
@@ -243,7 +243,7 @@ def add_text(
 
 def build_side_by_side_vision_ui_named(models, random_questions=None):
     notice_markdown = """
-# ⚔️  Vision Arena ⚔️ : Benchmarking LLAVA-FIRE VS. LLAVA
+# ⚔️  Vision Arena ⚔️ : Benchmarking FIRE-LLaVA VS. LLaVA-NeXT
 
 ## 📜 Rules
 - Chat with any two models side-by-side and vote!
@@ -284,8 +284,18 @@ def build_side_by_side_vision_ui_named(models, random_questions=None):
                 with gr.Row():
                     for i in range(num_sides):
                         with gr.Column():
+                            model_names_dict = {
+                                "llava-fire": 'FIRE-LLaVA',
+                                "llava-original": "LLaVA-Next-LLaMA-3-8B"
+                            }
+                            model_choices = []
+                            for model_value in models:
+                                if model_value in model_names_dict:
+                                    model_choices.append((model_names_dict[model_value], model_value))
+                                else:
+                                    model_choices.append((model_value, model_value))
                             model_selectors[i] = gr.Dropdown(
-                                choices=models,
+                                choices=model_choices,
                                 value=models[i] if len(models) > i else "",
                                 interactive=True,
                                 show_label=False,
@@ -335,8 +345,12 @@ def build_side_by_side_vision_ui_named(models, random_questions=None):
         share_btn = gr.Button(value="📷  Share")
     with gr.Row():
         gr.Examples(examples=[
-            [{"files":["assets/chart.png"], "text": "What's the percentage value of Japan who have a favorable view of the US? Answer the question using a single word or phrase."}],
-            [{"files":["assets/clver_1.jpg"], "text": "Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No"}],
+            [
+                {
+                    "files": ["assets/test_10422.jpg"],
+                    "text": "Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: 如图，将一个长方形纸片按图示折叠，若∠1＝40°，则∠2的度数是（） \nChoices: \nA. 40° \nB. 50° \nC. 60° \nD. 70°"
+                }
+            ],
         ],inputs=[textbox])
     with gr.Accordion("Parameters", open=False) as parameter_row:
         temperature = gr.Slider(
diff --git a/src/serve/gradio_web_server.py b/src/serve/gradio_web_server.py
index 3e8472c95589121c033889836efd95414fe71d00..05b83c9c4db77adc5ba5a093205821c5830c58b8 100644
--- a/src/serve/gradio_web_server.py
+++ b/src/serve/gradio_web_server.py
@@ -440,7 +440,7 @@ def bot_response(
         api_endpoint_info[model_name] if model_name in api_endpoint_info else None
     )
     images = conv.get_images()
-    logger.info(f"model_name: {model_name}; model_api_dict: {model_api_dict}; msg: {conv.messages}")
+    logger.info(f"model_name: {model_name}; model_api_dict: {model_api_dict}; msg: {len(conv.messages)}")
     if model_api_dict is None:
         if model_name == "llava-original":
             from src.model.model_llava import inference_by_prompt_and_images
diff --git a/vision-tmp-2024-07-17-conv.json b/vision-tmp-2024-07-17-conv.json
new file mode 100644
index 0000000000000000000000000000000000000000..a2aeb618b1f4bc2d6422ede37ebaf3b7c65476a5
--- /dev/null
+++ b/vision-tmp-2024-07-17-conv.json
@@ -0,0 +1,10 @@
+{"tstamp": 1721187677.0849, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721187629.683, "finish": 1721187677.0849, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "4f508323a8c94301a6fca86688b99adf", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721187677.1121, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721187654.9088, "finish": 1721187677.1121, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we need to count the number of metal cars to the left of the tiny matte school bus and compare that to the number of tiny cyan double buses. From the image, there is one metal car to the left of the tiny matte school bus. As for the tiny cyan double buses, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buses (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "266d5b0744204770b823ac105d057e95", "model_name": "llava-original", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721187734.2595, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721187693.1243, "finish": 1721187734.2595, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"], ["user", "Your answer is incorrect"], ["assistant", "I apologize for the mistake. Upon re-examining the image, I can see that there are indeed two metal cars to the left of the tiny matte school bus. Therefore, the number of metal cars to the left of the tiny matte school bus (which is two) is greater than the number of tiny cyan double buss (which is one). The correct answer to the question is:\n\n(A) Yes"]], "offset": 0, "conv_id": "4f508323a8c94301a6fca86688b99adf", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721187734.2753, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721187713.7211, "finish": 1721187734.2753, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we need to count the number of metal cars to the left of the tiny matte school bus and compare that to the number of tiny cyan double buses. From the image, there is one metal car to the left of the tiny matte school bus. As for the tiny cyan double buses, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buses (which is also one). The correct answer to the question is:\n\n(B) No"], ["user", "Your answer is incorrect"], ["assistant", "I apologize for the mistake. Upon re-examining the image, there are no metal cars to the left of the tiny matte school bus. Therefore, the number of metal cars to the left of the tiny matte school bus (which is zero) is not greater than the number of tiny cyan double buses (which is one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "266d5b0744204770b823ac105d057e95", "model_name": "llava-original", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188104.5696, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188079.9165, "finish": 1721188104.5696, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "9e6e8cfe40e248138411b99dda4d90d5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188104.5946, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188100.1282, "finish": 1721188104.5946, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "9e6e8cfe40e248138411b99dda4d90d5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188220.454, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188197.5149, "finish": 1721188220.454, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"], ["user", "Your answer is incorrect"], ["assistant", "I apologize for the mistake. Upon re-examining the image, I can see that there are indeed two metal cars to the left of the tiny matte school bus. Therefore, the number of metal cars to the left of the tiny matte school bus (which is two) is greater than the number of tiny cyan double buss (which is one). The correct answer to the question is:\n\n(A) Yes"]], "offset": 0, "conv_id": "9e6e8cfe40e248138411b99dda4d90d5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188220.4721, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188217.3063, "finish": 1721188220.4721, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"], ["user", "Your answer is incorrect"], ["assistant", "I apologize for the mistake. Upon re-examining the image, I can see that there are indeed two metal cars to the left of the tiny matte school bus. Therefore, the number of metal cars to the left of the tiny matte school bus (which is two) is greater than the number of tiny cyan double buss (which is one). The correct answer to the question is:\n\n(A) Yes"]], "offset": 0, "conv_id": "9e6e8cfe40e248138411b99dda4d90d5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188388.7781, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188341.5433, "finish": 1721188388.7781, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "e4aeac72057d45c2a569b33b44ccb5bb", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
+{"tstamp": 1721188388.7999, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721188365.1456, "finish": 1721188388.7999, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end.\nQuestion: Is the number of metal cars that are left of the tiny matte school bus greater than the number of tiny cyan double buss?\nChoices:\n(A) Yes\n(B) No", ["64978d01710f95e409bd808432fcf5f6"]]], ["assistant", "To answer the question, we must identify the metal cars to the left of the tiny matte school bus and compare their number to the tiny cyan double buss. The tiny matte school bus is located towards the center of the image. To the left of this school bus, there is one metal car, which is the yellow one. As for the tiny cyan double buss, there is only one visible in the image. Therefore, the number of metal cars to the left of the tiny matte school bus (which is one) is not greater than the number of tiny cyan double buss (which is also one). The correct answer to the question is:\n\n(B) No"]], "offset": 0, "conv_id": "e4aeac72057d45c2a569b33b44ccb5bb", "model_name": "llava-fire", "has_csam_image": false}, "ip": "123.127.249.60"}
diff --git a/vision-tmp-2024-07-19-conv.json b/vision-tmp-2024-07-19-conv.json
new file mode 100644
index 0000000000000000000000000000000000000000..d50a2d63951833644ebff228376562a3f3ff5eca
--- /dev/null
+++ b/vision-tmp-2024-07-19-conv.json
@@ -0,0 +1,24 @@
+{"tstamp": 1721374334.7428, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721374294.0249, "finish": 1721374334.7428, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: A test to screen for cervical cancer was used and the results of the screening test were shown below. The sensitivity of the test was. \nChoices: \nA. 80% \nB. 20% \nC. 60% \nD. 40%", ["04a65c7c1a23e9c9f9150a01eccf98c3"]]], ["assistant", "The question pertains to the sensitivity of a cervical cancer screening test. The sensitivity of a test is defined as the proportion of true positives that are correctly identified by the test. In the context of the provided table, the sensitivity is represented by the percentage of cervical cancer patients who tested positive. The table shows that 200 cervical cancer patients were screened, and out of those, 80 were identified as positive. Therefore, the sensitivity of the test is 80%. \n\nThe correct answer to the question is:\nA. 80%"]], "offset": 0, "conv_id": "aff427b699af4b309f3c32231c36164c", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721374334.7481, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721374313.2401, "finish": 1721374334.7481, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: A test to screen for cervical cancer was used and the results of the screening test were shown below. The sensitivity of the test was. \nChoices: \nA. 80% \nB. 20% \nC. 60% \nD. 40%", ["04a65c7c1a23e9c9f9150a01eccf98c3"]]], ["assistant", "The question pertains to the sensitivity of a screening test for cervical cancer. The sensitivity of a test is the proportion of true positives that are correctly identified by the test. In the provided table, the \"positive\" column indicates the number of true positives, which is 800 for cervical cancer patients. The \"Total\" column shows the total number of cervical cancer patients screened, which is 1000. To calculate the sensitivity, we divide the number of true positives by the total number of patients screened:\n\nSensitivity = Number of true positives / Total number of patients screened\nSensitivity = 800 / 1000\nSensitivity = 0.8\n\nTherefore, the sensitivity of the test is 0.8, which is not listed in the provided choices. However, if we consider the closest option to 0.8, it would be A, which is 80%. This is not the exact answer, but it is the closest to the calculated sensitivity."]], "offset": 0, "conv_id": "18055f8047ea44c8bdbccff6c38167e1", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721375745.4355, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721375711.3796, "finish": 1721375745.4355, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "6b5c97753946444db06bf97730837165", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721375745.439, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721375729.2532, "finish": 1721375745.439, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "5cd86f83c8834be7aeb9d2954e3a206e", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721375771.7743, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721375765.7665, "finish": 1721375771.7743, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u9996\u5148\uff0c\u22203\u5e76\u4e0d\u662f180\u00b0\ufe63\u22201\uff0c\u22201\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22201=40\u00b0\uff0c\u6240\u4ee5\u22203=\u22201=40\u00b0\u3002\u5176\u6b21\uff0c\u22204\u548c\u22205\u5e76\u4e0d\u662f140\u00b0\uff0c\u800c\u662f\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\u51fa\u7684\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u6839\u636e\u6298\u53e0\u7684\u6027\u8d28\uff0c\u22204\uff1d\u22205\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2234\u22204\uff1d\u22205\uff1d0.5\u00d7\uff08180\u00b0\ufe63\u22203\uff09\uff1d70\u00b0\uff0c\u2234\u22202\uff1d\u22204\uff1d70\u00b0\uff0e\u6545\u9009\uff1aD\uff0e"]], "offset": 0, "conv_id": "6b5c97753946444db06bf97730837165", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721375771.7752, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721375768.3296, "finish": 1721375771.7752, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u9996\u5148\uff0c\u22203\u5e76\u4e0d\u662f180\u00b0\ufe63\u22201\uff0c\u22201\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22201=40\u00b0\uff0c\u6240\u4ee5\u22203=\u22201=40\u00b0\u3002\u5176\u6b21\uff0c\u22204\u548c\u22205\u5e76\u4e0d\u662f140\u00b0\uff0c\u800c\u662f\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\u51fa\u7684\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u975e\u5e38\u62b1\u6b49\uff0c\u6211\u7684\u56de\u7b54\u6709\u8bef\u3002\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d40\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d40\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe6340\u00b0\uff1d140\u00b0\uff0e\u6545\u9009\uff1aD\uff0e"]], "offset": 0, "conv_id": "5cd86f83c8834be7aeb9d2954e3a206e", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376018.9175, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721375986.235, "finish": 1721376018.9175, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "e0793fb6fff04843b60d41f8a3d15c4e", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376018.9194, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376003.1273, "finish": 1721376018.9194, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "fcfaf2d1c18542df9b3374128bdc2785", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376053.097, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376032.9718, "finish": 1721376053.097, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u867d\u7136\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22203\u7684\u5ea6\u6570\uff0c\u4f46\u4f60\u5ffd\u7565\u4e86\u6298\u53e0\u7684\u6027\u8d28\u3002\u8bf7\u6ce8\u610f\uff0c\u22202\u548c\u22203\u4e4b\u95f4\u6709\u4e00\u4e2a\u5173\u7cfb\u3002\u8bd5\u7740\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u5982\u56fe\uff0c\u2235AB\u2225CD\uff0c\u2234\u22201\uff1d\u22206\uff1d40\u00b0\uff0c\u2235\u7eb8\u7247\u5bf9\u8fb9\u5e73\u884c\u6298\u53e0\uff0c\u2234\u22203\uff1d\u22205\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "e0793fb6fff04843b60d41f8a3d15c4e", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376053.0981, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376049.731, "finish": 1721376053.0981, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u867d\u7136\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22203\u7684\u5ea6\u6570\uff0c\u4f46\u4f60\u5ffd\u7565\u4e86\u6298\u53e0\u7684\u6027\u8d28\u3002\u8bf7\u6ce8\u610f\uff0c\u22202\u548c\u22203\u4e4b\u95f4\u6709\u4e00\u4e2a\u5173\u7cfb\u3002\u8bd5\u7740\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u975e\u5e38\u62b1\u6b49\uff0c\u6211\u7684\u56de\u7b54\u6709\u8bef\u3002\u5982\u56fe\uff0c\u2235AB\u2225CD\uff0c\u2234\u22201\uff1d\u22206\uff1d40\u00b0\uff0c\u2235\u22202+\u22206+\u22205\uff1d180\u00b0\uff0c\u22205\uff1d\u22203\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22206\ufe63\u22205\uff1d180\u00b0\ufe6340\u00b0\ufe63140\u00b0\uff1d50\u00b0\uff0e\u6545\u9009\uff1aB\uff0e"]], "offset": 0, "conv_id": "fcfaf2d1c18542df9b3374128bdc2785", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376125.5601, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376090.4963, "finish": 1721376125.5601, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "7f9b82782a5c4b83a35f0a3df33782ca", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376125.5637, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376108.5239, "finish": 1721376125.5637, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "cee1cc75dca941d69c16b5561f98e6bb", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376347.6707, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376311.9197, "finish": 1721376347.6707, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "4e3dc73c184742108e709df0ef3d3af3", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376347.6731, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376330.7919, "finish": 1721376347.6731, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "fc123ad48c68419095c079dc60c2b1d1", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376392.7321, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376357.7773, "finish": 1721376392.7321, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u867d\u7136\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22203\u7684\u5ea6\u6570\uff0c\u4f46\u4f60\u5ffd\u7565\u4e86\u6298\u53e0\u7684\u6027\u8d28\u3002\u8bf7\u6ce8\u610f\uff0c\u22202\u548c\u22203\u4e4b\u95f4\u6709\u4e00\u4e2a\u5173\u7cfb\u3002\u8bd5\u7740\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u5982\u56fe\uff0c\u2235AB\u2225CD\uff0c\u2234\u22201\uff1d\u22206\uff1d40\u00b0\uff0c\u2235\u7eb8\u7247\u5bf9\u8fb9\u5e73\u884c\u6298\u53e0\uff0c\u2234\u22203\uff1d\u22205\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "4e3dc73c184742108e709df0ef3d3af3", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376392.7338, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376374.9444, "finish": 1721376392.7338, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u867d\u7136\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22203\u7684\u5ea6\u6570\uff0c\u4f46\u4f60\u5ffd\u7565\u4e86\u6298\u53e0\u7684\u6027\u8d28\u3002\u8bf7\u6ce8\u610f\uff0c\u22202\u548c\u22203\u4e4b\u95f4\u6709\u4e00\u4e2a\u5173\u7cfb\u3002\u8bd5\u7740\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u975e\u5e38\u62b1\u6b49\uff0c\u6211\u7684\u56de\u7b54\u6709\u8bef\u3002\u5982\u56fe\uff0c\u2235AB\u2225CD\uff0c\u2234\u22201\uff1d\u22204\uff1d40\u00b0\uff0c\u2235DE\u2225BC\uff0c\u2234\u22202\uff1d\u22203\uff1d\u22204\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "fc123ad48c68419095c079dc60c2b1d1", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376443.2323, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376408.0903, "finish": 1721376443.2323, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "a000314ac375409da1fce7622c63c535", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376443.2345, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376425.6812, "finish": 1721376443.2345, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "408b6ac211024d90a25466ecc3c5806e", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376486.023, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376450.7222, "finish": 1721376486.023, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22202\u7684\u5173\u7cfb\uff0c\u5e76\u4e14\u6b63\u786e\u5730\u4f7f\u7528\u4e86\u6298\u53e0\u7684\u6027\u8d28\u6765\u8ba1\u7b97\u2220\u03b1\u3002\u7136\u800c\uff0c\u4f60\u7684\u8ba1\u7b97\u6709\u8bef\u3002\u8bf7\u6ce8\u610f\uff0c\u2220\u03b1\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22202\u548c\u22203\u662f\u5bf9\u9876\u89d2\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u8fd9\u4e9b\u89d2\u7684\u5173\u7cfb\uff0c\u5e76\u91cd\u65b0\u8ba1\u7b97\u2220\u03b1\u3002"], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u2220\u03b1\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u2220\u03b1\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "a000314ac375409da1fce7622c63c535", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376486.0245, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376469.3381, "finish": 1721376486.0245, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u6b63\u786e\u5730\u8bc6\u522b\u4e86\u22201\u548c\u22202\u7684\u5173\u7cfb\uff0c\u5e76\u4e14\u6b63\u786e\u5730\u4f7f\u7528\u4e86\u6298\u53e0\u7684\u6027\u8d28\u6765\u8ba1\u7b97\u2220\u03b1\u3002\u7136\u800c\uff0c\u4f60\u7684\u8ba1\u7b97\u6709\u8bef\u3002\u8bf7\u6ce8\u610f\uff0c\u2220\u03b1\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22202\u548c\u22203\u662f\u5bf9\u9876\u89d2\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u8fd9\u4e9b\u89d2\u7684\u5173\u7cfb\uff0c\u5e76\u91cd\u65b0\u8ba1\u7b97\u2220\u03b1\u3002"], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u2220\u03b1\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u2220\u03b1\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "408b6ac211024d90a25466ecc3c5806e", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376656.7211, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376623.2282, "finish": 1721376656.7211, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "836255fbca344e2a8caafffdc4e1b8b5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376656.7231, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376640.4293, "finish": 1721376656.7231, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"]], "offset": 0, "conv_id": "673bc29303fc48d7a0859a653dbf4042", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376725.083, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376689.9415, "finish": 1721376725.083, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d180\u00b0\ufe63\u22201\uff1d140\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22204\uff1d\u22203\uff1d140\u00b0\uff0c\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\uff0c\u22205\uff1d\u22204\uff1d140\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe63140\u00b0\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u9996\u5148\uff0c\u22203\u5e76\u4e0d\u662f180\u00b0\ufe63\u22201\uff0c\u22201\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22201=40\u00b0\uff0c\u6240\u4ee5\u22203=\u22201=40\u00b0\u3002\u5176\u6b21\uff0c\u22204\u548c\u22205\u5e76\u4e0d\u662f140\u00b0\uff0c\u800c\u662f\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\u51fa\u7684\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u6839\u636e\u6298\u53e0\u7684\u6027\u8d28\uff0c\u22204\uff1d\u22205\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2234\u22204\uff1d\u22205\uff1d0.5\u00d7\uff08180\u00b0\ufe63\u22203\uff09\uff1d70\u00b0\uff0c\u2234\u22202\uff1d\u22204\uff1d70\u00b0\uff0e\u6545\u9009\uff1aD\uff0e"]], "offset": 0, "conv_id": "836255fbca344e2a8caafffdc4e1b8b5", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.106"}
+{"tstamp": 1721376725.0846, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721376708.2633, "finish": 1721376725.0846, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["Hint: Please answer the question and provide the correct option letter, e.g., A, B, C, D, at the end. \nQuestion: \u5982\u56fe\uff0c\u5c06\u4e00\u4e2a\u957f\u65b9\u5f62\u7eb8\u7247\u6309\u56fe\u793a\u6298\u53e0\uff0c\u82e5\u22201\uff1d40\u00b0\uff0c\u5219\u22202\u7684\u5ea6\u6570\u662f\uff08\uff09 \nChoices: \nA. 40\u00b0 \nB. 50\u00b0 \nC. 60\u00b0 \nD. 70\u00b0", ["b71a36d02ea33b090c0e506d61f58586"]]], ["assistant", "\u5982\u56fe\uff0c\u2235\u22201\uff1d40\u00b0\uff0c\u2234\u22203\uff1d\u22201\uff1d40\u00b0\uff0c\u2235AB\u2225CD\uff0c\u2234\u22202\uff1d\u22203\uff1d40\u00b0\uff0e\u6545\u9009\uff1aA\uff0e"], ["user", "\u4f60\u7684\u56de\u7b54\u6709\u4e00\u4e9b\u9519\u8bef\u3002\u9996\u5148\uff0c\u22203\u5e76\u4e0d\u662f180\u00b0\ufe63\u22201\uff0c\u22201\u548c\u22203\u662f\u540c\u4f4d\u89d2\uff0c\u4e14\u22201=40\u00b0\uff0c\u6240\u4ee5\u22203=\u22201=40\u00b0\u3002\u5176\u6b21\uff0c\u22204\u548c\u22205\u5e76\u4e0d\u662f140\u00b0\uff0c\u800c\u662f\u7531\u6298\u53e0\u7684\u6027\u8d28\u5f97\u51fa\u7684\u3002\u8bf7\u91cd\u65b0\u8003\u8651\u6298\u53e0\u7684\u6027\u8d28\u548c\u89d2\u5ea6\u7684\u5173\u7cfb\u3002"], ["assistant", "\u5982\u56fe\uff0c\u2235AB\u2225CD\uff0c\u2234\u22201\uff1d\u22204\uff1d40\u00b0\uff0c\u2235CD\u2225EF\uff0c\u2234\u22205\uff1d\u22204\uff1d40\u00b0\uff0c\u2234\u22202\uff1d180\u00b0\ufe63\u22205\uff1d180\u00b0\ufe6340\u00b0\uff1d140\u00b0\uff0e\u6545\u9009\uff1aD\uff0e"]], "offset": 0, "conv_id": "673bc29303fc48d7a0859a653dbf4042", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.106"}
diff --git a/vision-tmp-2024-07-23-conv.json b/vision-tmp-2024-07-23-conv.json
new file mode 100644
index 0000000000000000000000000000000000000000..20eb1c7b0baf792947cbe7bef31c8108d895ca76
--- /dev/null
+++ b/vision-tmp-2024-07-23-conv.json
@@ -0,0 +1,8 @@
+{"tstamp": 1721701705.7909, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721701640.609, "finish": 1721701705.7909, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, without additional context or botanical expertise, it is not possible to accurately determine the species of the flower or its common name. However, the bright yellow petals and prominent orange centers are characteristic of many species within the Asteraceae family, which includes daisies, sunflowers, and chrysanthemums, among others."]], "offset": 0, "conv_id": "13109662cd74483eb27c8945c9f51643", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721701705.7978, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721701666.99, "finish": 1721701705.7978, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, these flowers could be identified as a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."]], "offset": 0, "conv_id": "183137bc666b4d618a12df0d024b7ebc", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721701824.6996, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721701725.1572, "finish": 1721701824.6996, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, without additional context or botanical expertise, it is not possible to accurately determine the species of the flower or its common name. However, the bright yellow petals and prominent orange centers are characteristic of many species within the Asteraceae family, which includes daisies, sunflowers, and chrysanthemums, among others."], ["user", "Your answer correctly identifies the vibrant yellow petals and central disc, which are key features of the flowers in the image. However, the flowers in the image are not daisies. Daisies typically have a single large flower per stem, whereas these flowers have multiple blooms per stem. Additionally, the shape of the petals and the arrangement of the flowers are more characteristic of a different species. Try to focus on the overall structure and arrangement of the flowers to refine your identification."], ["assistant", "Thank you for the feedback. The flowers in the image do not resemble daisies, which typically have a single large flower per stem. Instead, the dense arrangement of multiple small flowers per stem, along with the vibrant yellow petals and prominent orange centers, are more characteristic of a species within the genus Solidago, commonly known as goldenrods. These flowers are known for their dense, terminal inflorescences and are often found in fields and meadows."]], "offset": 0, "conv_id": "13109662cd74483eb27c8945c9f51643", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721701824.7049, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721701805.5319, "finish": 1721701824.7049, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, these flowers could be identified as a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."], ["user", "Your answer correctly identifies the vibrant yellow petals and central disc, which are key features of the flowers in the image. However, the flowers in the image are not daisies. Daisies typically have a single large flower per stem, whereas these flowers have multiple blooms per stem. Additionally, the shape of the petals and the arrangement of the flowers are more characteristic of a different species. Try to focus on the overall structure and arrangement of the flowers to refine your identification."], ["assistant", "I apologize for the initial misidentification. Upon closer inspection, the flowers in the image are indeed not daisies but rather a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."]], "offset": 0, "conv_id": "183137bc666b4d618a12df0d024b7ebc", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721703498.4406, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721703462.5858, "finish": 1721703498.4406, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, without additional context or botanical expertise, it is not possible to accurately determine the species of the flower or its common name. However, the bright yellow petals and prominent orange centers are characteristic of many species within the Asteraceae family, which includes daisies, sunflowers, and chrysanthemums, among others."]], "offset": 0, "conv_id": "653fc4e74bf74cc4aa104e4e6ea87393", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721703498.4472, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721703480.6019, "finish": 1721703498.4472, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, these flowers could be identified as a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."]], "offset": 0, "conv_id": "5ea6e4d5082c4b78bf81a670a1093ae0", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721703602.0029, "type": "chat", "model": "llava-fire", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721703564.2737, "finish": 1721703602.0029, "state": {"template_name": "llava-fire", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, without additional context or botanical expertise, it is not possible to accurately determine the species of the flower or its common name. However, the bright yellow petals and prominent orange centers are characteristic of many species within the Asteraceae family, which includes daisies, sunflowers, and chrysanthemums, among others."], ["user", "Your answer correctly identifies the vibrant yellow petals and central disc, which are key features of the flowers in the image. However, the flowers in the image are not daisies. Daisies typically have a single large flower per stem, whereas these flowers have multiple blooms per stem. Additionally, the shape of the petals and the arrangement of the flowers are more characteristic of a different species. Try to focus on the overall structure and arrangement of the flowers to refine your identification."], ["assistant", "Thank you for the feedback. The flowers in the image do not resemble daisies, which typically have a single large flower per stem. Instead, the dense arrangement of multiple small flowers per stem, along with the vibrant yellow petals and prominent orange centers, are more characteristic of a species within the genus Solidago, commonly known as goldenrods. These flowers are known for their dense, terminal inflorescences and are often found in fields and meadows."]], "offset": 0, "conv_id": "653fc4e74bf74cc4aa104e4e6ea87393", "model_name": "llava-fire", "has_csam_image": false}, "ip": "46.3.240.104"}
+{"tstamp": 1721703602.0063, "type": "chat", "model": "llava-original", "gen_params": {"temperature": 0.7, "top_p": 1.0, "max_new_tokens": 1024}, "start": 1721703583.9252, "finish": 1721703602.0063, "state": {"template_name": "llava-original", "system_message": "You are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.", "roles": ["user", "assistant"], "messages": [["user", ["What species of flower could these be, and what is their common name?", ["ec3f8c5d6190cc6027d31e8726d168ac"]]], ["assistant", "Based on the image alone, these flowers could be identified as a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."], ["user", "Your answer correctly identifies the vibrant yellow petals and central disc, which are key features of the flowers in the image. However, the flowers in the image are not daisies. Daisies typically have a single large flower per stem, whereas these flowers have multiple blooms per stem. Additionally, the shape of the petals and the arrangement of the flowers are more characteristic of a different species. Try to focus on the overall structure and arrangement of the flowers to refine your identification."], ["assistant", "I apologize for the initial misidentification. Upon closer inspection, the flowers in the image are indeed not daisies but rather a species of the genus Solidago, commonly known as goldenrods. Goldenrods are known for their dense, terminal inflorescences and are often found in fields and meadows. The specific species would require a closer examination of the flower's structure and habitat, which is not possible from the image alone."]], "offset": 0, "conv_id": "5ea6e4d5082c4b78bf81a670a1093ae0", "model_name": "llava-original", "has_csam_image": false}, "ip": "46.3.240.104"}