Updated retrieval testing UI (#3433)

### What problem does this PR solve?



### Type of change


- [x] Documentation Update

docs/references/http_api_reference.md

@@ -1383,7 +1383,7 @@ curl --request POST \
     The maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.  
 - `"prompt"`: (*Body parameter*), `object`  
   Instructions for the LLM to follow. If it is not explicitly set, a JSON object with the following values will be generated as the default. A `prompt` JSON object contains the following attributes:  
-  - `"similarity_threshold"`: `float` RAGFlow uses a hybrid of weighted keyword similarity and vector cosine similarity during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
+  - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted reranking score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
   - `"keywords_similarity_weight"`: `float` This argument sets the weight of keyword similarity in the hybrid similarity score with vector cosine similarity or reranking model similarity. By adjusting this weight, you can control the influence of keyword similarity in relation to other similarity measures. The default value is `0.7`.
   - `"top_n"`: `int` This argument specifies the number of top chunks with similarity scores above the `similarity_threshold` that are fed to the LLM. The LLM will *only* access these 'top N' chunks.  The default value is `8`.
   - `"variables"`: `object[]` This argument lists the variables to use in the 'System' field of **Chat Configurations**. Note that:  
@@ -1518,7 +1518,7 @@ curl --request PUT \
     The maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.  
 - `"prompt"`: (*Body parameter*), `object`  
   Instructions for the LLM to follow.  A `prompt` object contains the following attributes:  
-  - `"similarity_threshold"`: `float` RAGFlow uses a hybrid of weighted keyword similarity and vector cosine similarity during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
+  - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted rerank score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
   - `"keywords_similarity_weight"`: `float` This argument sets the weight of keyword similarity in the hybrid similarity score with vector cosine similarity or reranking model similarity. By adjusting this weight, you can control the influence of keyword similarity in relation to other similarity measures. The default value is `0.7`.
   - `"top_n"`: `int` This argument specifies the number of top chunks with similarity scores above the `similarity_threshold` that are fed to the LLM. The LLM will *only* access these 'top N' chunks.  The default value is `8`.
   - `"variables"`: `object[]` This argument lists the variables to use in the 'System' field of **Chat Configurations**. Note that:  

docs/references/python_api_reference.md

@@ -957,7 +957,7 @@ The LLM settings for the chat assistant to create. Defaults to `None`. When the
 
 Instructions for the LLM to follow.  A `Prompt` object contains the following attributes:
 
-- `similarity_threshold`: `float` RAGFlow uses a hybrid of weighted keyword similarity and vector cosine similarity during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
+- `similarity_threshold`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted reranking score during retrieval. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
 - `keywords_similarity_weight`: `float` This argument sets the weight of keyword similarity in the hybrid similarity score with vector cosine similarity or reranking model similarity. By adjusting this weight, you can control the influence of keyword similarity in relation to other similarity measures. The default value is `0.7`.
 - `top_n`: `int` This argument specifies the number of top chunks with similarity scores above the `similarity_threshold` that are fed to the LLM. The LLM will *only* access these 'top N' chunks.  The default value is `8`.
 - `variables`: `list[dict[]]` This argument lists the variables to use in the 'System' field of **Chat Configurations**. Note that:
@@ -1015,7 +1015,7 @@ A dictionary representing the attributes to update, with the following keys:
   - `"frequency penalty"`, `float` Similar to presence penalty, this reduces the model’s tendency to repeat the same words.
   - `"max_token"`, `int` The maximum length of the model’s output, measured in the number of tokens (words or pieces of words).
 - `"prompt"` : Instructions for the LLM to follow.
-  - `"similarity_threshold"`: `float` RAGFlow uses a hybrid of weighted keyword similarity and vector cosine similarity during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
+  - `"similarity_threshold"`: `float` RAGFlow employs either a combination of weighted keyword similarity and weighted vector cosine similarity, or a combination of weighted keyword similarity and weighted rerank score during retrieval. This argument sets the threshold for similarities between the user query and chunks. If a similarity score falls below this threshold, the corresponding chunk will be excluded from the results. The default value is `0.2`.
   - `"keywords_similarity_weight"`: `float` This argument sets the weight of keyword similarity in the hybrid similarity score with vector cosine similarity or reranking model similarity. By adjusting this weight, you can control the influence of keyword similarity in relation to other similarity measures. The default value is `0.7`.
   - `"top_n"`: `int` This argument specifies the number of top chunks with similarity scores above the `similarity_threshold` that are fed to the LLM. The LLM will *only* access these 'top N' chunks.  The default value is `8`.
   - `"variables"`: `list[dict[]]`  This argument lists the variables to use in the 'System' field of **Chat Configurations**. Note that: