kotaemon核心GraphRAG、Agent、多模态代码解读！

原创 PaperAgent 2024-09-06 10:19 湖北

可定制化RAG UI，混合索引（GraphRAG）、复杂推理Agent（ReAct、ReWOO、MemoryGIST 和 GraphReader）、多模态

要说最近RAG方面火热的项目当属kotaemon，短时间暴涨8k star

kotaemon的亮点是可定制化RAG UI，核心技术点是混合索引（Vector、Keyword、GraphRAG）、复杂推理Agent（ReAct、ReWOO、MemoryGIST 和 GraphReader）、多模态。

混合索引（GraphRAG）

混合索引主要是指：全文和矢量融合，这里还有一个选型就是集成了RAG的新范式：GraphRAG

看代码直接用的微软GraphRAG

检索后重排采用LLMReranker

RERANK_PROMPT_TEMPLATE = """Given the following question and context,return YES if the context is relevant to the question and NO if it isn't.
> Question: {question}> Context:>>>{context}>>>> Relevant (YES / NO):"""

复杂推理Agent

推理目前主要实现了react与rewoo，tools包括google搜索工具、llm工具、wikipedia工具，可以自定义扩展。

react还是经典的Thought、Action、Action Input、Observation模式

zero_shot_react_prompt = PromptTemplate(    template="""Answer the following questions as best you can. Give answer in {lang}. You have access to the following tools:{tool_description}Use the following format:
Question: the input question you must answerThought: you should always think about what to do
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action, should be different from the action input of the same action in previous steps.
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)#Thought: I now know the final answerFinal Answer: the final answer to the original input question
Begin! After each Action Input.
Question: {instruction}Thought:{agent_scratchpad}    """)

rewoo（Reasoning WithOut Observation），该范式将推理过程与外部观察分离

planner的prompt模版

from kotaemon.llms import PromptTemplate
zero_shot_planner_prompt = PromptTemplate(    template="""You are an AI agent who makes step-by-step plans to solve a problem under the help of external tools.For each step, make one plan followed by one tool-call, which will be executed later to retrieve evidence for that step.You should store each evidence into a distinct variable #E1, #E2, #E3 ... that can be referred to in later tool-call inputs.
##Available Tools##{tool_description}
##Output Format (Replace '<...>')###Plan1: <describe your plan here>#E1: <toolname>[<input here>] (eg. Search[What is Python])#Plan2: <describe next plan>#E2: <toolname>[<input here, you can use #E1 to represent its expected output>]And so on...
##Your Task##{task}
##Now Begin##""")

solver的prompt模版

zero_shot_solver_prompt = PromptTemplate(    template="""You are an AI agent who solves a problem with my assistance. I will provide step-by-step plans(#Plan) and evidences(#E) that could be helpful.Your task is to briefly summarize each step, then make a short final conclusion for your task. Give answer in {lang}.
##My Plans and Evidences##{plan_evidence}
##Example Output##First, I <did something> , and I think <...>; Second, I <...>, and I think <...>; ....So, <your conclusion>.
##Your Task##{task}
##Now Begin##""")

多模态

多模态体现在丰富的loader上面，多达十几种比如：html_loader.py、excel_loader.py、unstructured_loader.py等，可以借鉴用于其它场景哦

多模态测试，AdobeReader

https://github.com/Cinnamon/kotaemon

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