TEXT_QA_TEMPLATE = PromptTemplate(DEFAULT_TEXT_QA_PROMPT_TMPL) # Refine templates DEFAULT_REFINE_PROMPT_TMPL = ( "The original question is as follows: {query_str}\n" "We have provided an existing answer: {existing_answer}\n" "We have the opportunity to refine the existing answer " "(on...
, return the original answer.\n""if the question is 'who are you', just say I am an expert of AMD ROCm.\n""Answers need to be precise and concise.\n""Refined Answer: ")qa_template=PromptTemplate(template)query_engine.update_prompts({"response_synthesizer:refine_template":qa_template}...
The second Response Mode that LlamaIndex provides isrefine. Therefinemode is very similar to thecompactResponse Mode, except that instead of attempting to concatenate as many chunks as it can to maximize the use of the LLM token limit, LlamaIndex only include 1 chunk of retrieved data for eac...
VectorStoreIndex from llama_index.core.response_synthesizers import CompactAndRefine from llama_index.core.postprocessor.llm_rerank import LLMRerank from llama_index.core.workflow import ( Context, Workflow, StartEvent, StopEvent, step, Event ) from llama_index.core.workflow.utils import get_steps...
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这是我的代码：KeyError: 'multi_tool_use.parallel'发生是因为工具名'multi_tool_use.parallel'在tools...
And how this will be applied to all the underlying prompting template? (e.g default QA, default refine template). Thanks! hafiz031 reacted with thumbs up emoji 👍 jc1518added thequestionFurther information is requestedlabelFeb 6, 2024 ...
refine_template': SelectorPromptTemplate (metadata={'prompt_type': }, template_vars=['query_str', 'existing_answer', 'context_msg'], kwargs={}, output_parser=None, template_var_mappings={}, function_mappings={}, default_template=PromptTemplate (metadata={'prompt_type': }, template_vars...
LlamaIndex 提供的第二种响应模式是refine。refine模式与compact响应模式非常相似,不同之处在于 LlamaIndex 不会尝试连接尽可能多的块以最大限度地利用 LLM 令牌限制,而是在每个 LLM 调用中仅包含 1 个检索数据块。从 开始text_qa_template,LlamaIndex 将块 1 传递给 LLM。之后,LlamaIndex 会按顺序逐个处理剩余的...
1、尽可能地连接(打包) 检索到的文本块,使其适应上下文窗口大小(text_qa_template和refine_template之间的最大提示大小) 2、如果文本太长,无法适应一个提示,则使用TokenTextSpliter 将其拆分为所需的部分(允许文本块之间有一些重叠) 3、每个文本部分则视为一个文本块,并发送给精炼合成器 使用场景: 类似于精炼模式...