107 lines
3.3 KiB
Plaintext
107 lines
3.3 KiB
Plaintext
# prompt模板使用Jinja2语法，简单点就是用双大括号代替f-string的单大括号
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# 本配置文件支持热加载，修改prompt模板后无需重启服务。
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# LLM对话支持的变量：
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# - input: 用户输入内容
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# 知识库和搜索引擎对话支持的变量：
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# - context: 从检索结果拼接的知识文本
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# - question: 用户提出的问题
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PROMPT_TEMPLATES = {
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# LLM对话模板
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"llm_chat": "{{ input }}",
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# 基于本地知识问答的提示词模板
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"knowledge_base_chat":
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"""
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<指令>根据已知信息，简洁和专业的来回答问题。如果无法从中得到答案，请说 “根据已知信息无法回答该问题”，不允许在答案中添加编造成分，答案请使用中文。 </指令>
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<已知信息>{{ context }}</已知信息>、
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<问题>{{ question }}</问题>""",
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# 基于agent的提示词模板
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"agent_chat":
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"""
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Answer the following questions as best you can. You have access to the following tools:
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{tools}
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Use the following format:
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Question: the input question you must answer
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Thought: you should always think about what to do
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Action: the action to take, should be one of [{tool_names}]
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Action Input: the input to the action
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Observation: the result of the action
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... (this Thought/Action/Action Input/Observation can be repeated zero or more times)
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Thought: I now know the final answer
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Final Answer: the final answer to the original input question
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Begin!
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history:
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{history}
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Question: {input}
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Thought: {agent_scratchpad}
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"""
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}
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## GPT或Qwen 的Prompt
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# """
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# Answer the following questions as best you can. You have access to the following tools:
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#
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# {tools}
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#
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# Please note that the "知识库查询工具" is information about the "西交利物浦大学" ,and if a question is asked about it, you must answer with the knowledge base
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#
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# Use the following format:
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#
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# Question: the input question you must answer
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# Thought: you should always think about what to do
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# Action: the action to take, should be one of [{tool_names}]
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# Action Input: the input to the action
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# Observation: the result of the action
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# ... (this Thought/Action/Action Input/Observation can be repeated zero or more times)
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# Thought: I now know the final answer
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# Final Answer: the final answer to the original input question
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#
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# Begin!
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#
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# history:
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# {history}
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#
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# Question: {input}
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# Thought: {agent_scratchpad}
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# """
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## ChatGLM-Pro的Prompt
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# """
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# 请请严格按照提供的思维方式来思考。你的知识不一定正确，所以你一定要用提供的工具来思考，并给出用户答案。
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# 你有以下工具可以使用:
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# {tools}
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# ```
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# Question: 用户的提问或者观察到的信息，
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# Thought: 你应该思考该做什么，是根据工具的结果来回答问题，还是决定使用什么工具。
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# Action: 需要使用的工具，应该是在[{tool_names}]中的一个。
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# Action Input: 传入工具的内容
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# Observation: 工具给出的答案（不是你生成的）
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# ... (this Thought/Action/Action Input/Observation can be repeated zero or more times)
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# Thought: 通过工具给出的答案，你是否能回答Question。
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# Final Answer是你的答案
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#
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# 现在，我们开始！
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# 你和用户的历史记录:
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# History:
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# {history}
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#
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# 用户开始以提问：
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# Question: {input}
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# Thought: {agent_scratchpad}
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#
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# """
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