Azure OpenAI citations with message correlation

题意:"Azure OpenAI 引用与消息关联"

问题背景:

I am trying out Azure OpenAI with my own data. The data is uploaded to Azure Blob Storage and indexed for use with Azure AI search

"我正在尝试使用自己的数据进行 Azure OpenAI。数据已上传到 Azure Blob 存储并为 Azure AI 搜索进行了索引。"

I do a call to the endpoint in the form of POST {endpoint}/openai/deployments/{deployment-id}/chat/completions?api-version={api-version}, as referenced here.

"我对端点进行了一次调用,形式为 `POST {endpoint}/openai/deployments/{deployment-id}/chat/completions?api-version={api-version}`,就像这里所引用的。"

However, in the response I cannot figure out how the choices[0]['message']['context']['citations'] field correspond to the choices[0]['message']['content'].

"然而,在响应中,我无法弄清楚 `choices[0]['message']['context']['citations']` 字段是如何与 `choices[0]['message']['content']` 对应的。"

For example, I can have a content as something like:

"例如,我的 `content` 可能是这样的:"

cs 复制代码
I have a pear [doc1][doc2]. I have an apple [doc1][doc3].

However, in my citations it looks like:

"然而,在我的 `citations` 中,它看起来像这样:"

cs 复制代码
citations[0].filepath == 'file1.pdf'
citations[1].filepath == 'file2.pdf'
citations[2].filepath == 'file1.pdf'
citations[3].filepath == 'file3.pdf'
citations[4].filepath == 'file4.pdf'

In summary, my question is whether if there is some sort of mapping from doc as shown in the message to the citations.filepath.

"总而言之,我的问题是是否存在一种映射,将消息中显示的 `doc` 与 `citations.filepath` 关联起来。"

问题解决:

Actually, it is not about the length of the citations; it is about how many times the file is referred.

"实际上,这与 `citations` 的长度无关,而是与文件被引用的次数有关。"

If you observe clearly, you can see 'file1.pdf' is referred twice, so mappings will be based on the first appearance and reuse of docs like below:

"如果你仔细观察,可以看到 `file1.pdf` 被引用了两次,因此映射将基于第一次出现和重用文档,如下所示:"

  • doc1 -> citations[0] (file1.pdf).
  • doc2 -> citations[1] (file2.pdf).
  • Reuse of doc1 -> Refers back to the first document (citations[2], file1.pdf).
  • doc3 -> citations[3] (file3.pdf).

Use the code below to get mappings and use it in the content.

"使用下面的代码来获取映射,并在内容中使用它。"

cs 复制代码
import re

def map_citations(content, citations):
    
    pattern = re.compile(r'\[doc(\d+)\]')
    segments = pattern.split(content)
    
    doc_numbers = []
    for segment in segments:
        if segment.isdigit():
            doc_numbers.append(int(segment))
    
    

    doc_to_file_map = {}
    for i, doc_num in enumerate(doc_numbers):
        doc_to_file_map[f'doc{doc_num}'] = citations[i]['filepath']

    print(doc_to_file_map)
    
    def replace_placeholder(match):
        doc_num = match.group(1)
        return f"[{doc_to_file_map[f'doc{doc_num}']}]"
    
    mapped_content = pattern.sub(replace_placeholder, content)
    
    return mapped_content

content = "I have a pear [doc1][doc2]. I have an apple [doc1][doc3]."
citations = [
    {'filepath': 'file1.pdf'},
    {'filepath': 'file2.pdf'},
    {'filepath': 'file1.pdf'},
    {'filepath': 'file3.pdf'},
    {'filepath': 'file4.pdf'}
]

mapped_content = map_citations(content, citations)
print(mapped_content)
相关推荐
武子康15 分钟前
AI-调查研究-107-具身智能 强化学习与机器人训练数据格式解析:从状态-动作对到多模态轨迹标准
人工智能·深度学习·机器学习·ai·系统架构·机器人·具身智能
insight^tkk36 分钟前
【Docker】记录一次使用docker部署dify网段冲突的问题
运维·人工智能·docker·ai·容器
数据智能老司机2 小时前
使用 OpenAI Agents SDK 构建智能体——记忆与知识
llm·openai·agent
数据智能老司机2 小时前
使用 OpenAI Agents SDK 构建智能体——代理工具与 MCP
llm·openai·agent
哥布林学者13 小时前
吴恩达深度学习课程一:神经网络和深度学习 第三周:浅层神经网络(二)
深度学习·ai
weixin_5195357713 小时前
从ChatGPT到新质生产力:一份数据驱动的AI研究方向指南
人工智能·深度学习·机器学习·ai·chatgpt·数据分析·aigc
OpenCSG13 小时前
【活动预告】2025斗拱开发者大会,共探支付与AI未来
人工智能·ai·开源·大模型·支付安全
万俟淋曦16 小时前
【论文速递】2025年第28周(Jul-06-12)(Robotics/Embodied AI/LLM)
人工智能·ai·机器人·大模型·论文·robotics·具身智能
Larcher19 小时前
n8n 入门笔记:用零代码工作流自动化重塑效率边界
前端·openai
万俟淋曦19 小时前
【论文速递】2025年第29周(Jul-13-19)(Robotics/Embodied AI/LLM)
人工智能·ai·机器人·论文·robotics·具身智能