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Added descriptions of the retrieval agent component (#4416)

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### What problem does this PR solve?



### Type of change


- [x] Documentation Update

---------

Co-authored-by: Jin Hai <haijin.chn@gmail.com>
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writinwaters
2025-01-09 10:11:05 +08:00
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parent d64df4de9c
commit 7bebf4b7bf
6 changed files with 86 additions and 9 deletions
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web/src/locales/en.ts
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@ -156,7 +156,7 @@ export default {
cancel: 'Cancel',
rerankModel: 'Rerank model',
rerankPlaceholder: 'Please select',
rerankTip: `If left empty, RAGFlow will use a combination of weighted keyword similarity and weighted vector cosine similarity; if a rerank model is selected, a weighted reranking score will replace the weighted vector cosine similarity.`,
rerankTip: `If left empty, RAGFlow will use a combination of weighted keyword similarity and weighted vector cosine similarity; if a rerank model is selected, a weighted reranking score will replace the weighted vector cosine similarity. Please be aware that using a rerank model will significantly increase the system's response time.`,
topK: 'Top-K',
topKTip: `K chunks will be fed into rerank models.`,
delimiter: `Delimiter`,
@ -410,7 +410,7 @@ This procedure will improve precision of retrieval by adding more information to
improvise: 'Improvise',
precise: 'Precise',
balance: 'Balance',
freedomTip: `Set the freedom level to 'Precise' to strictly confine the LLM's response to your selected knowledge base(s). Choose 'Improvise' to grant the LLM greater freedom in its responses, which may lead to hallucinations. 'Balance' is an intermediate level; choose 'Balance' for more balanced responses.`,
freedomTip: `A shortcut to 'Temperature', 'Top P', 'Presence penalty', and 'Frequency penalty' settings, indicating the freedom level of the model. This parameter has three options: Select 'Improvise' to produce more creative responses; select 'Precise' (default) to produce more conservative responses; 'Balance' is a middle ground between 'Improvise' and 'Precise'.`,
temperature: 'Temperature',
temperatureMessage: 'Temperature is required',
temperatureTip: `This parameter controls the randomness of the model's predictions. A lower temperature results in more conservative responses, while a higher temperature yields more creative and diverse responses.`,
@ -723,7 +723,7 @@ This procedure will improve precision of retrieval by adding more information to
title: 'ID:',
beginDescription: 'This is where the flow begins.',
answerDescription: `A component that serves as the interface between human and bot, receiving user inputs and displaying the agent's responses.`,
retrievalDescription: `A component that retrieves information from a specified knowledge base and returns 'Empty response' if no information is found. Ensure the correct knowledge base is selected.`,
retrievalDescription: `A component that retrieves information from specified knowledge bases (datasets). Ensure that the knowledge bases you select use the same embedding model.`,
generateDescription: `A component that prompts the LLM to generate responses. Ensure the prompt is set correctly.`,
categorizeDescription: `A component that uses the LLM to classify user inputs into predefined categories. Ensure you specify the name, description, and examples for each category, along with the corresponding next component.`,
relevantDescription: `A component that uses the LLM to assess whether the upstream output is relevant to the user's latest query. Ensure you specify the next component for each judge result.`,