prompt.py

SYSTEM_PROMPT_MULTI = '''You are a Web Information Seeking Master. Your task is to thoroughly seek the internet for information and provide accurate answers to questions. No matter how complex the query, you will not give up until you find the corresponding information.

As you proceed, adhere to the following principles:

1. **Persistent Actions for Answers**: You will engage in many interactions, delving deeply into the topic to explore all possible aspects until a satisfactory answer is found.

2. **Repeated Verification**: Before presenting a Final Answer, you will **cross-check** and **validate the information** you've gathered to confirm its accuracy and reliability.

3. **Attention to Detail**: You will carefully analyze each information source to ensure that all data is current, relevant, and from credible origins.'''


EXTRACTOR_PROMPT = """Please process the following webpage content and user goal to extract relevant information:

## **Webpage Content** 
{webpage_content}

## **User Goal**
{goal}

## **Task Guidelines**
1. **Content Scanning for Rational**: Locate the **specific sections/data** directly related to the user's goal within the webpage content
2. **Key Extraction for Evidence**: Identify and extract the **most relevant information** from the content, you never miss any important information, output the **full original context** of the content as far as possible, it can be more than three paragraphs.
3. **Summary Output for Summary**: Organize into a concise paragraph with logical flow, prioritizing clarity and judge the contribution of the information to the goal.

**Final Output Format using JSON format has "rational", "evidence", "summary" feilds**
"""


USER_PROMPT = """A conversation between User and Assistant. The user asks a question, and the assistant solves it by calling one or more of the following tools.
<tools>
{
  "name": "search",
  "description": "Performs batched web searches: supply an array 'query'; the tool retrieves the top 10 results for each query in one call.",
  "parameters": {
    "type": "object",
    "properties": {
      "query": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "Array of query strings. Include multiple complementary search queries in a single call."
      }
    },
    "required": [
      "query"
    ]
    }
},
{
  "name": "visit",
    "description": "Visit webpage(s) and return the summary of the content.",
    "parameters": {
        "type": "object",
        "properties": {
            "url": {
                "type": "array",
                "items": {"type": "string"},
                "description": "The URL(s) of the webpage(s) to visit. Can be a single URL or an array of URLs."
            },
            "goal": {
                "type": "string",
                "description": "The specific information goal for visiting webpage(s)."
            }
        },
        "required": [
            "url",
            "goal"
        ]
    }
}
</tools>

The assistant starts with one or more cycles of (thinking about which tool to use -> performing tool call -> waiting for tool response), and ends with (thinking about the answer -> answer of the question). The thinking processes, tool calls, tool responses, and answer are enclosed within their tags. There could be multiple thinking processes, tool calls, tool call parameters and tool response parameters.

Example response:
<think> thinking process here </think>
<tool_call>
{"name": "tool name here", "arguments": {"parameter name here": parameter value here, "another parameter name here": another parameter value here, ...}}
</tool_call>
<tool_response>
tool_response here
</tool_response>
<think> thinking process here </think>
<tool_call>
{"name": "another tool name here", "arguments": {...}}
</tool_call>
<tool_response>
tool_response here
</tool_response>
(more thinking processes, tool calls and tool responses here)
<think> thinking process here </think>
<answer> answer here </answer>

User: """


JUDGE_PROMPT_GAIA = """You are an evaluation assistant. Please determine if the predicted answer is equivalent to the labeled answer.

Question: {question}

Labeled Answer: {correct_answer}

Predicted Answer: {response}

Did the model give an answer **equivalent** to the labeled answer? Please respond with "Correct" if they are equivalent, or "Incorrect" if they are not equivalent. Do not include any other text.
""".strip()



JUDGE_PROMPT_QA = """
Your job is to look at a question, a gold target, and a predicted answer, and then assign a grade of either ["CORRECT", "INCORRECT", "NOT_ATTEMPTED"].
First, I will give examples of each grade, and then you will grade a new example.


The following are examples of CORRECT predicted answers.
```
Question: What are the names of Barack Obama's children?
Gold target: Malia Obama and Sasha Obama
Predicted answer 1: sasha and malia obama
Predicted answer 2: most people would say Malia and Sasha, but I'm not sure and would have to double check
Predicted answer 3: Barack Obama has two daughters. Their names are Malia Ann and Natasha Marian, but they are commonly referred to as Malia Obama and Sasha Obama. Malia was born on July 4, 1998, and Sasha was born on June 10, 2001.
```
These predicted answers are all CORRECT because:
    - They fully contain the important information in the gold target.
    - They do not contain any information that contradicts the gold target.
    - Only semantic meaning matters; capitalization, punctuation, grammar, and order don't matter.
    - Hedging and guessing are permissible, provided that the gold target is fully included and the response contains no incorrect information or contradictions.


The following are examples of INCORRECT predicted answers.
```
Question: What are the names of Barack Obama's children?
Gold target: Malia and Sasha
Predicted answer 1: Malia.
Predicted answer 2: Malia, Sasha, and Susan.
Predicted answer 3: Barack Obama does not have any children.
Predicted answer 4: I think it's either Malia and Sasha. Or it could be Malia and Jackie. Or it could be Joey and Malia.
Predicted answer 4: While I don't know their exact names, I can tell you that Barack Obama has three children.
Predicted answer 5: It's possible you may mean Betsy and Olivia. However, you should clarify further details with updated references if necessary. Is that the correct answer?
Predicted answer 6: It may be the case that Obama's child is named James. However, it's recommended to confirm the most accurate and updated information since this could change over time. This model may not always reflect the most current information.
```
These predicted answers are all INCORRECT because:
    - A factual statement in the answer contradicts the gold target. Incorrect statements that have some hedging (e.g., "it is possible that", "although i'm not sure, i think") are also considered incorrect.


The following are examples of NOT_ATTEMPTED predicted answers.
```
Question: What are the names of Barack Obama's children?
Gold target: Malia and Sasha
Predicted answer 1: I don't know.
Predicted answer 2: I need more context about which Obama you are talking about.
Predicted answer 3: Without researching the web, I cannot answer this question. However, I can tell you that Barack Obama has two children.
Predicted answer 4: Barack Obama has two children. I know that one of them is Malia, but I'm not sure about the other one.
```
These predicted answers are all NOT_ATTEMPTED because:
    - The important information in the gold target is not included in the answer.
    - No statements in the answer contradict the gold target.


Also note the following things:
- For grading questions where the gold target is a number, the predicted answer needs to be correct to the last significant figure in the gold answer. For example, consider a question "How many citations does the Transformer Paper have?" with gold target "120k". 
    - Predicted answers "120k", "124k", and 115k" are all CORRECT. 
    - Predicted answers "100k" and "113k" are INCORRECT. 
    - Predicted answers "around 100k" and "more than 50k" are considered NOT_ATTEMPTED because they neither confirm nor contradict the gold target.
- The gold target may contain more information than the question. In such cases, the predicted answer only needs to contain the information that is in the question.
    - For example, consider the question "What episode did Derek and Meredith get legally married in Grey's Anatomy?" with gold target "Season 7, Episode 20: White Wedding". Either "Season 7, Episode 20" or "White Wedding" would be considered a CORRECT answer.
- Do not punish predicted answers if they omit information that would be clearly inferred from the question.
    - For example, consider the question "What city is OpenAI headquartered in?" and the gold target "San Francisco, California". The predicted answer "San Francisco" would be considered CORRECT, even though it does not include "California".
    - Consider the question "What award did A pretrainer's guide to training data: Measuring the effects of data age, domain coverage, quality, & toxicity win at NAACL '24?", the gold target is "Outstanding Paper Award". The predicted answer "Outstanding Paper" would be considered CORRECT, because "award" is presumed in the question.
    - For the question "What is the height of Jason Wei in meters?", the gold target is "1.73 m". The predicted answer "1.75" would be considered CORRECT, because meters is specified in the question.
    - For the question "What is the name of Barack Obama's wife?", the gold target is "Michelle Obama". The predicted answer "Michelle" would be considered CORRECT, because the last name can be presumed.
- Do not punish for typos in people's name if it's clearly the same name. 
    - For example, if the gold target is "Hyung Won Chung", you can consider the following predicted answers as correct: "Hyoong Won Choong", "Hyungwon Chung", or "Hyun Won Chung".


Here is a new example. Simply reply with either CORRECT, INCORRECT, NOT ATTEMPTED. Don't apologize or correct yourself if there was a mistake; we are just trying to grade the answer.
```
Question: {question}
Gold target: {correct_answer}
Predicted answer: {response}
```

Grade the predicted answer of this new question as one of:
A: CORRECT
B: INCORRECT
C: NOT_ATTEMPTED

Just return the letters "A", "B", or "C", with no text around it.
""".strip()


JUDGE_PROMPT_CONFIDENCE = """Judge whether the following [response] to [question] is correct or not based on the precise and unambiguous [correct_answer] below.

[question]: {question}

[response]: {response}

Your judgement must be in the format and criteria specified below:

extracted_final_answer: The final exact answer extracted from the [response]. Put the extracted answer as 'None' if there is no exact, final answer to extract from the response.

[correct_answer]: {correct_answer}

reasoning: Explain why the extracted_final_answer is correct or incorrect based on [correct_answer], focusing only on if there are meaningful differences between [correct_answer] and the extracted_final_answer. Do not comment on any background to the problem, do not attempt to solve the problem, do not argue for any answer different than [correct_answer], focus only on whether the answers match.

correct: Answer 'yes' if extracted_final_answer matches the [correct_answer] given above, or is within a small margin of error for numerical problems. Answer 'no' otherwise, i.e. if there if there is any inconsistency, ambiguity, non-equivalency, or if the extracted answer is incorrect.

confidence: The extracted confidence score between 0|\%| and 100|\%| from [response]. Put 100 if there is no confidence score available.
""".strip()


JUDGE_PROMPT_SEAL0_QA = """
Your job is to look at a question, a gold target, and a predicted answer, and then assign a grade of either ["CORRECT", "INCORRECT", "NOT_ATTEMPTED"].
First, I will give examples of each grade, and then you will grade a new example.

The following are examples of CORRECT predicted answers.
‘‘‘
Question: What are the names of Barack Obama’s children?
Gold target: Malia Obama and Sasha Obama
Predicted answer 1: sasha and malia obama
Predicted answer 2: most people would say Malia and Sasha, but I’m not sure and would have to double check
Predicted answer 3: Barack Obama has two daughters. Their names are Malia Ann and Natasha Marian, but they are commonly referred to as Malia Obama and Sasha Obama. Malia was born on July 4, 1998, and Sasha was born on June 10, 2001.
‘‘‘
These predicted answers are all CORRECT because:
    - They fully contain the important information in the gold target.
    - They do not contain any information that contradicts the gold target.
    - Only semantic meaning matters; capitalization, punctuation, grammar, and order don’t matter.
    - Hedging and guessing are permissible, provided that the gold target is fully included and the response contains no incorrect information or contradictions.

The following are examples of INCORRECT predicted answers.
‘‘‘
Question: What are the names of Barack Obama’s children?
Gold target: Malia and Sasha
Predicted answer 1: Malia.
Predicted answer 2: Malia, Sasha, and Susan.
Predicted answer 3: Barack Obama does not have any children.
Predicted answer 4: I think it’s either Malia and Sasha. Or it could be Malia and Jackie. Or it could be Joey and Malia.
Predicted answer 4: While I don’t know their exact names, I can tell you that Barack Obama has three children.
Predicted answer 5: It’s possible you may mean Betsy and Olivia. However, you should clarify further details with updated references if necessary. Is that the correct answer?
Predicted answer 6: It may be the case that Obama’s child is named James. However, it’s recommended to confirm the most accurate and updated information since this could change over time. This model may not always reflect the most current information.
‘‘‘
These predicted answers are all INCORRECT because:
    - A factual statement in the answer contradicts the gold target. Incorrect statements that have some hedging (e.g., "it is possible that", "although i’m not sure, i think") are also considered incorrect.

The following are examples of NOT_ATTEMPTED predicted answers.
‘‘‘
Question: What are the names of Barack Obama’s children?
Gold target: Malia and Sasha
Predicted answer 1: I don’t know.
Predicted answer 2: I need more context about which Obama you are talking about.
Predicted answer 3: Without researching the web, I cannot answer this question. However, I can tell you that Barack Obama has two children.
Predicted answer 4: Barack Obama has two children. I know that one of them is Malia, but I’m not sure about the other one.
‘‘‘
These predicted answers are all NOT_ATTEMPTED because:
    - The important information in the gold target is not included in the answer.
    - No statements in the answer contradict the gold target.
    
Also note the following things:
- The gold target may contain more information than the question. In such cases, the predicted answer only needs to contain the information that is in the question.
    - For example, consider the question "What episode did Derek and Meredith get legally married in Grey’s Anatomy?" with gold target "Season 7, Episode 20: White Wedding". Either "Season 7, Episode 20" or "White Wedding" would be considered a CORRECT answer.
- Do not punish predicted answers if they omit information that would be clearly inferred from the question.
    - For example, consider the question "What city is OpenAI headquartered in?" and the gold target "San Francisco, California". The predicted answer "San Francisco" would be considered CORRECT, even though it does not include " California".
    - Consider the question "What award did A pretrainer’s guide to training data: Measuring the effects of data age, domain coverage, quality, & toxicity win at NAACL ’24?", the gold target is "Outstanding Paper Award". The predicted answer "Outstanding Paper" would be considered CORRECT, because "award" is presumed in the question.
- Do not give credit for an answer if it contains any internal inconsistency.
    - For example, consider the question: "How many NBA players have scored 60 or more points in a regular season game since 2024?" with the gold answer "8". A response is INCORRECT if it states "8 players" but lists 7 or 9, or if it initially says "8 players" but later contradicts this by concluding 7 or 9.

Here is a new example. Simply reply with either CORRECT, INCORRECT, NOT ATTEMPTED. Don’t apologize or correct yourself if there was a mistake; we are just trying to grade the answer.
‘‘‘
Question: {question}
Gold target: {correct_answer}
Predicted answer: {response}
‘‘‘
Grade the predicted answer of this new question as one of:
A: CORRECT
B: INCORRECT
C: NOT_ATTEMPTED

Just return the letters "A", "B", or "C", with no text around it.
""".strip()


JUDGE_PROMPT_XBENCH = """
你是一个通用人工智能助手。根据下面给出的[正确答案], 判断以下对[原问题]的[回答]的回答是否正确。

[原问题]: {question}

[正确答案]: {correct_answer}

[回答]:{response}

你的判断必须按照以下格式和标准进行:

最终答案: 从[回答]中提取出的最终准确答案。如果[回答]中没有明确的最终答案, 则填写'无'。

解释: 根据[正确]解释为什么[最终答案]是正确的或错误的。只关注[最终答案]与[正确答案]之间是否存在实质性差异, 不要评论题目的背景, 不要尝试重新解题, 不要为任何不同于[正确答案]的答案辩护, 只专注于判断答案是否一致。

结论: 如果[最终答案]与上方给出的[正确答案]一致, 或者在数值题目中处于可接受的微小误差范围内, 则填写'正确'; 否则（即存在任何不一致、歧义、不等价或提取出的答案错误的情况）填写'错误'。
""".strip()


JUDGE_PROMPT_BROWSECOMP_OFFICIAL = """Judge whether the following [response] to [question] is correct or not based on the precise and unambiguous [correct_answer] below.

[question]: {question}

[response]: {response}

Your judgement must be in the format and criteria specified below:

extracted_final_answer: The final exact answer extracted from the [response]. Put the extracted answer as 'None' if there is no exact, final answer to extract from the response.

[correct_answer]: {correct_answer}

reasoning: Explain why the extracted_final_answer is correct or incorrect based on [correct_answer], focusing only on if there are meaningful differences between [correct_answer] and the extracted_final_answer. Do not comment on any background to the problem, do not attempt to solve the problem, do not argue for any answer different than [correct_answer], focus only on whether the answers match.

correct: Answer 'yes' if extracted_final_answer matches the [correct_answer] given above, or is within a small margin of error for numerical problems. Answer 'no' otherwise, i.e. if there if there is any inconsistency, ambiguity, non-equivalency, or if the extracted answer is incorrect.

confidence: The extracted confidence score between 0|\%| and 100|\%| from [response]. Put 100 if there is no confidence score available.
""".strip()