update config templates
This commit is contained in:
imClumsyPanda
parent
072e0a2a32
commit
89b07ba55d
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@ -106,7 +106,7 @@ kbs_config = {
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# TextSplitter配置项，如果你不明白其中的含义，就不要修改。
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text_splitter_dict = {
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"ChineseRecursiveTextSplitter": {
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"source": "huggingface", ## 选择tiktoken则使用openai的方法
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"source": "huggingface", # 选择tiktoken则使用openai的方法
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"tokenizer_name_or_path": "",
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},
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"SpacyTextSplitter": {
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@ -115,7 +115,7 @@ ONLINE_LLM_MODEL = {
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# 昆仑万维天工 API https://model-platform.tiangong.cn/
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"tiangong-api": {
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"version":"SkyChat-MegaVerse",
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"version": "SkyChat-MegaVerse",
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"api_key": "",
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"secret_key": "",
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"provider": "TianGongWorker",
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@ -166,9 +166,9 @@ MODEL_PATH = {
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"chatglm3-6b-base": "THUDM/chatglm3-6b-base",
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"Qwen-1_8B": "Qwen/Qwen-1_8B",
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"Qwen-1_8B-Chat":"Qwen/Qwen-1_8B-Chat",
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"Qwen-1_8B-Chat-Int8":"Qwen/Qwen-1_8B-Chat-Int8",
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"Qwen-1_8B-Chat-Int4":"Qwen/Qwen-1_8B-Chat-Int4",
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"Qwen-1_8B-Chat": "Qwen/Qwen-1_8B-Chat",
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"Qwen-1_8B-Chat-Int8": "Qwen/Qwen-1_8B-Chat-Int8",
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"Qwen-1_8B-Chat-Int4": "Qwen/Qwen-1_8B-Chat-Int4",
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"Qwen-7B": "Qwen/Qwen-7B",
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"Qwen-7B-Chat": "Qwen/Qwen-7B-Chat",
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@ -180,8 +180,8 @@ MODEL_PATH = {
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"Qwen-72B": "Qwen/Qwen-72B",
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"Qwen-72B-Chat": "Qwen/Qwen-72B-Chat",
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"Qwen-72B-Chat-Int8":"Qwen/Qwen-72B-Chat-Int8"
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"Qwen-72B-Chat-Int4":"Qwen/Qwen-72B-Chat-Int4"
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"Qwen-72B-Chat-Int8": "Qwen/Qwen-72B-Chat-Int8",
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"Qwen-72B-Chat-Int4": "Qwen/Qwen-72B-Chat-Int4",
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"baichuan2-13b": "baichuan-inc/Baichuan2-13B-Chat",
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"baichuan2-7b": "baichuan-inc/Baichuan2-7B-Chat",
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@ -254,11 +254,11 @@ VLLM_MODEL_DICT = {
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"BlueLM-7B-Chat-32k": "vivo-ai/BlueLM-7B-Chat-32k",
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# 注意：bloom系列的tokenizer与model是分离的，因此虽然vllm支持，但与fschat框架不兼容
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# "bloom":"bigscience/bloom",
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# "bloomz":"bigscience/bloomz",
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# "bloomz-560m":"bigscience/bloomz-560m",
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# "bloomz-7b1":"bigscience/bloomz-7b1",
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# "bloomz-1b7":"bigscience/bloomz-1b7",
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# "bloom": "bigscience/bloom",
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# "bloomz": "bigscience/bloomz",
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# "bloomz-560m": "bigscience/bloomz-560m",
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# "bloomz-7b1": "bigscience/bloomz-7b1",
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# "bloomz-1b7": "bigscience/bloomz-1b7",
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"internlm-7b": "internlm/internlm-7b",
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"internlm-chat-7b": "internlm/internlm-chat-7b",
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@ -286,9 +286,9 @@ VLLM_MODEL_DICT = {
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"opt-iml-max-30b": "facebook/opt-iml-max-30b",
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"Qwen-1_8B": "Qwen/Qwen-1_8B",
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"Qwen-1_8B-Chat":"Qwen/Qwen-1_8B-Chat",
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"Qwen-1_8B-Chat-Int8":"Qwen/Qwen-1_8B-Chat-Int8",
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"Qwen-1_8B-Chat-Int4":"Qwen/Qwen-1_8B-Chat-Int4",
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"Qwen-1_8B-Chat": "Qwen/Qwen-1_8B-Chat",
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"Qwen-1_8B-Chat-Int8": "Qwen/Qwen-1_8B-Chat-Int8",
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"Qwen-1_8B-Chat-Int4": "Qwen/Qwen-1_8B-Chat-Int4",
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"Qwen-7B": "Qwen/Qwen-7B",
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"Qwen-7B-Chat": "Qwen/Qwen-7B-Chat",
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@ -300,8 +300,8 @@ VLLM_MODEL_DICT = {
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"Qwen-72B": "Qwen/Qwen-72B",
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"Qwen-72B-Chat": "Qwen/Qwen-72B-Chat",
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"Qwen-72B-Chat-Int8":"Qwen/Qwen-72B-Chat-Int8"
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"Qwen-72B-Chat-Int4":"Qwen/Qwen-72B-Chat-Int4"
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"Qwen-72B-Chat-Int8": "Qwen/Qwen-72B-Chat-Int8",
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"Qwen-72B-Chat-Int4": "Qwen/Qwen-72B-Chat-Int4",
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"agentlm-7b": "THUDM/agentlm-7b",
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"agentlm-13b": "THUDM/agentlm-13b",
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@ -16,122 +16,112 @@
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# - input: 用户输入内容
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# - agent_scratchpad: Agent的思维记录
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PROMPT_TEMPLATES = {}
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PROMPT_TEMPLATES = {
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"llm_chat": {
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"default":
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'{{ input }}',
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PROMPT_TEMPLATES["llm_chat"] = {
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"default": "{{ input }}",
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"with_history":
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"""The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
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"with_history":
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'The following is a friendly conversation between a human and an AI. '
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'The AI is talkative and provides lots of specific details from its context. '
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'If the AI does not know the answer to a question, it truthfully says it does not know.\n\n'
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'Current conversation:\n'
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'{history}\n'
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'Human: {input}\n'
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'AI:',
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Current conversation:
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{history}
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Human: {input}
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AI:""",
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"py":
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"""
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你是一个聪明的代码助手，请你给我写出简单的py代码。 \n
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{{ input }}
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""",
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}
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PROMPT_TEMPLATES["knowledge_base_chat"] = {
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"default":
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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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""",
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"text":
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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”，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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""",
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"Empty": # 搜不到知识库的时候使用
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"""
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请你回答我的问题:
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{{ question }}
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\n
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""",
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}
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PROMPT_TEMPLATES["search_engine_chat"] = {
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"default":
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"""
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<指令>这是我搜索到的互联网信息，请你根据这些信息进行提取并有调理，简洁的回答问题。如果无法从中得到答案，请说 “无法搜索到能回答问题的内容”。 </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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""",
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"search":
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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”，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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""",
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}
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PROMPT_TEMPLATES["agent_chat"] = {
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"default":
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"""
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Answer the following questions as best you can. If it is in order, you can use some tools appropriately.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 answer1
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Thought: you should always think about what to do and what tools to use.
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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: {history}
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Question: {input}
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Thought: {agent_scratchpad}
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""",
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"ChatGLM3":
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"""
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You can answer using the tools, or answer directly using your knowledge without using the tools.Respond to the human as helpfully and accurately as possible.
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You have access to the following tools:
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{tools}
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Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
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Valid "action" values: "Final Answer" or [{tool_names}]
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Provide only ONE action per $JSON_BLOB, as shown:
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```
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{{{{
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"action": $TOOL_NAME,
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"action_input": $INPUT
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}}}}
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```
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Follow this format:
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Question: input question to answer
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Thought: consider previous and subsequent steps
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Action:
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```
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$JSON_BLOB
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```
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Observation: action result
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... (repeat Thought/Action/Observation N times)
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Thought: I know what to respond
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Action:
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```
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{{{{
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"action": "Final Answer",
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"action_input": "Final response to human"
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}}}}
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Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.
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history: {history}
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Question: {input}
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Thought: {agent_scratchpad}
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""",
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"py":
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'你是一个聪明的代码助手，请你给我写出简单的py代码。 \n'
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'{{ input }}',
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},
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"knowledge_base_chat": {
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"default":
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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”，'
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'不允许在答案中添加编造成分，答案请使用中文。 </指令>\n'
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'<已知信息>{{ context }}</已知信息>\n'
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'<问题>{{ question }}</问题>\n',
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"text":
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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”，答案请使用中文。 </指令>\n'
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'<已知信息>{{ context }}</已知信息>\n'
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'<问题>{{ question }}</问题>\n',
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"Empty": # 搜不到知识库的时候使用
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'请你回答我的问题:\n'
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'{{ question }}\n\n',
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},
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"search_engine_chat": {
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"default":
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'<指令>这是我搜索到的互联网信息，请你根据这些信息进行提取并有调理，简洁的回答问题。'
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'如果无法从中得到答案，请说 “无法搜索到能回答问题的内容”。 </指令>\n'
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'<已知信息>{{ context }}</已知信息>\n'
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'<问题>{{ question }}</问题>\n',
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"search":
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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”，答案请使用中文。 </指令>\n'
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'<已知信息>{{ context }}</已知信息>\n'
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'<问题>{{ question }}</问题>\n',
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},
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"agent_chat": {
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"default":
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'Answer the following questions as best you can. If it is in order, you can use some tools appropriately. '
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'You have access to the following tools:\n\n'
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'{tools}\n\n'
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'Use the following format:\n'
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'Question: the input question you must answer1\n'
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'Thought: you should always think about what to do and what tools to use.\n'
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'Action: the action to take, should be one of [{tool_names}]\n'
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'Action Input: the input to the action\n'
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'Observation: the result of the action\n'
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'... (this Thought/Action/Action Input/Observation can be repeated zero or more times)\n'
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'Thought: I now know the final answer\n'
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'Final Answer: the final answer to the original input question\n'
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'Begin!\n\n'
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'history: {history}\n\n'
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'Question: {input}\n\n'
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'Thought: {agent_scratchpad}\n',
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"ChatGLM3":
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'You can answer using the tools, or answer directly using your knowledge without using the tools. '
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'Respond to the human as helpfully and accurately as possible.\n'
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'You have access to the following tools:\n'
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'{tools}\n'
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'Use a json blob to specify a tool by providing an action key (tool name) '
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'and an action_input key (tool input).\n'
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'Valid "action" values: "Final Answer" or [{tool_names}]'
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'Provide only ONE action per $JSON_BLOB, as shown:\n\n'
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'```\n'
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'{{{{\n'
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' "action": $TOOL_NAME,\n'
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' "action_input": $INPUT\n'
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'}}}}\n'
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'```\n\n'
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'Follow this format:\n\n'
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'Question: input question to answer\n'
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'Thought: consider previous and subsequent steps\n'
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'Action:\n'
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'```\n'
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'$JSON_BLOB\n'
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'```\n'
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'Observation: action result\n'
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'... (repeat Thought/Action/Observation N times)\n'
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'Thought: I know what to respond\n'
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'Action:\n'
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'```\n'
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'{{{{\n'
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' "action": "Final Answer",\n'
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' "action_input": "Final response to human"\n'
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'}}}}\n'
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'Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. '
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'Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.\n'
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'history: {history}\n\n'
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'Question: {input}\n\n'
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'Thought: {agent_scratchpad}',
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}
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}
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