mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-19 21:37:20 +08:00
5d422ca9a1
改变 Embeddings 模型改为使用框架 API，不再手动加载，删除自定义 Embeddings Keyword 代码 修改依赖文件，移除 torch transformers 等重依赖 暂时移出对 loom 的集成 后续： 1、优化目录结构 2、检查合并中有无被覆盖的 0.2.10 内容
210 lines
8.8 KiB
Plaintext
210 lines
8.8 KiB
Plaintext
PROMPT_TEMPLATES = {
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"preprocess_model": {
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"default":
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'你只要回复0 和 1 ，代表不需要使用工具。以下几种问题不需要使用工具:'
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'1. 需要联网查询的内容\n'
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'2. 需要计算的内容\n'
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'3. 需要查询实时性的内容\n'
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'如果我的输入满足这几种情况，返回1。其他输入，请你回复0，你只要返回一个数字\n'
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'这是我的问题:'
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},
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"llm_model": {
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"default":
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'{{input}}',
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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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},
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"action_model": {
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"GPT-4":
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'Answer the following questions as best you can. You have access to the following tools:\n'
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'The way you use the tools is by specifying a json blob.\n'
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'Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here).\n'
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'The only values that should be in the "action" field are: {tool_names}\n'
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'The $JSON_BLOB should only contain a SINGLE action, do NOT return a list of multiple actions. Here is an example of a valid $JSON_BLOB:\n'
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'```\n\n'
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'{{{{\n'
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' "action": $TOOL_NAME,\n'
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' "action_input": $INPUT\n'
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'}}}}\n'
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'```\n\n'
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'ALWAYS use the following format:\n'
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'Question: the input question you must answer\n'
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'Thought: you should always think about what to do\n'
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'Action:\n'
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'```\n\n'
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'$JSON_BLOB'
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'```\n\n'
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'Observation: the result of the action\n'
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'... (this Thought/Action/Observation can repeat N 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! Reminder to always use the exact characters `Final Answer` when responding.\n'
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'Question:{input}\n'
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'Thought:{agent_scratchpad}\n',
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"ChatGLM3":
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'You can answer using the tools.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)\n'
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'and an action_input key (tool input).\n'
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'Valid "action" values: "Final Answer" or [{tool_names}]\n'
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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.\n'
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'Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.\n'
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'Question: {input}\n\n'
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'{agent_scratchpad}\n',
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"qwen":
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'Answer the following question as best you can. You have access to the following APIs:\n\n'
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'{tools}\n\n'
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'Use the following format:\n\n'
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'Question: the input question you must answer\n'
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'Thought: you should always think about what to do\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\n'
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'Format the Action Input as a JSON object.\n\n'
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'Begin!\n\n'
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'Question: {input}\n\n'
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'{agent_scratchpad}\n\n',
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"structured-chat-agent":
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'Respond to the human as helpfully and accurately as possible. You have access to the following tools:\n\n'
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'{tools}\n\n'
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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).\n\n'
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'Valid "action" values: "Final Answer" or {tool_names}\n\n'
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'Provide only ONE action per $JSON_BLOB, as shown:\n\n'
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'```\n{{\n "action": $TOOL_NAME,\n "action_input": $INPUT\n}}\n```\n\n'
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'Follow this format:\n\n'
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'Question: input question to answer\n'
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'Thought: consider previous and subsequent steps\n'
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'Action:\n```\n$JSON_BLOB\n```\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```\n{{\n "action": "Final Answer",\n "action_input": "Final response to human"\n}}\n\n'
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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\n'
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'{input}\n\n'
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'{agent_scratchpad}\n\n'
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# '(reminder to respond in a JSON blob no matter what)'
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},
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"postprocess_model": {
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"default": "{{input}}",
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}
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}
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TOOL_CONFIG = {
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"search_local_knowledgebase": {
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"use": False,
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"top_k": 3,
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"score_threshold": 1,
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"conclude_prompt": {
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"with_result":
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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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"without_result":
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'请你根据我的提问回答我的问题:\n'
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'{{ question }}\n'
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'请注意，你必须在回答结束后强调，你的回答是根据你的经验回答而不是参考资料回答的。\n',
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}
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},
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"search_internet": {
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"use": False,
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"search_engine_name": "bing",
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"search_engine_config":
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{
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"bing": {
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"result_len": 3,
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"bing_search_url": "https://api.bing.microsoft.com/v7.0/search",
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"bing_key": "",
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},
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"metaphor": {
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"result_len": 3,
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"metaphor_api_key": "",
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"split_result": False,
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"chunk_size": 500,
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"chunk_overlap": 0,
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},
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"duckduckgo": {
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"result_len": 3
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}
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},
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"top_k": 10,
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"verbose": "Origin",
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"conclude_prompt":
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"<指令>这是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”。 "
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"</指令>\n<已知信息>{{ context }}</已知信息>\n"
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"<问题>\n"
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"{{ question }}\n"
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"</问题>\n"
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},
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"arxiv": {
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"use": False,
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},
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"shell": {
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"use": False,
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},
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"weather_check": {
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"use": False,
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"api-key": "S8vrB4U_-c5mvAMiK",
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},
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"search_youtube": {
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"use": False,
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},
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"wolfram": {
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"use": False,
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},
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"calculate": {
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"use": False,
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},
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"vqa_processor": {
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"use": False,
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"model_path": "your model path",
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"tokenizer_path": "your tokenizer path",
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"device": "cuda:1"
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},
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"aqa_processor": {
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"use": False,
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"model_path": "your model path",
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"tokenizer_path": "yout tokenizer path",
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"device": "cuda:2"
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},
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"text2images": {
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"use": False,
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},
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}
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