> ## Documentation Index
> Fetch the complete documentation index at: https://ultrarag.openbmb.cn/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompt

## QA Prompts

### `qa_boxed`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,template->prompt_ls")
def qa_boxed(
    q_ls: List[str], 
    template: str | Path
) -> List[PromptMessage]
```

**Function**

Basic Q\&A Prompt.

Loads specified Jinja2 template, renders each question in the question list into a Prompt.

Template Variable: `{{ question }}`

### `qa_boxed_multiple_choice`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,choices_ls,template->prompt_ls")
def qa_boxed_multiple_choice(
    q_ls: List[str],
    choices_ls: List[List[str]],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Multiple Choice Q\&A Prompt.

Automatically formats choice list into "A: ..., B: ..." form and injects into template.

Template Variables: `{{ question }}`, `{{ choices }}`

### `qa_rag_boxed`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,ret_psg,template->prompt_ls")
def qa_rag_boxed(
    q_ls: List[str], 
    ret_psg: List[str | Any], 
    template: str | Path
) -> list[PromptMessage]
```

**Function**

Standard RAG Prompt.

Concatenates retrieved passage lists and injects into template.

Template Variables: `{{ question }}`, `{{ documents }}`

### `qa_rag_boxed_multiple_choice`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,choices_ls,ret_psg,template->prompt_ls")
def qa_rag_boxed_multiple_choice(
    q_ls: List[str],
    choices_ls: List[List[str]],
    ret_psg: List[List[str]],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Multiple Choice Q\&A Prompt with Retrieval Context.

Template Variables: `{{ question }}`, `{{ documents }}`, `{{ choices }}`

***

## RankCoT Prompts

### `RankCoT_kr`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,ret_psg,kr_template->prompt_ls")
def RankCoT_kr(
    q_ls: List[str],
    ret_psg: List[str | Any],
    template: str | Path,
) -> list[PromptMessage]
```

**Function**

RankCoT Phase 1: Knowledge Retrieval Prompt.

Template Variables: `{{ question }}`, `{{ documents }}`

### `RankCoT_qa`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,kr_ls,qa_template->prompt_ls")
def RankCoT_qa(
    q_ls: List[str],
    kr_ls: List[str],
    template: str | Path,
) -> list[PromptMessage]
```

**Function**

RankCoT Phase 2: Chain-of-Thought based Q\&A Prompt.

Template Variables: `{{ question }}`, `{{ CoT }}` (Here CoT is usually knowledge generated in the previous phase)

***

## IRCoT Prompts

### `ircot_next_prompt`

**Signature**

```python theme={null}
@app.prompt(output="memory_q_ls,memory_ret_psg,template->prompt_ls")
def ircot_next_prompt(
    memory_q_ls: List[List[str | None]],
    memory_ret_psg: List[List[List[str]] | None],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

IRCoT (Interleaved Retrieval CoT) Iterative Prompt Generation.

Constructs next round's Prompt based on historical retrieval results and chain of thought. Supports single-turn and multi-turn history concatenation.

Template Variables: `{{ documents }}`, `{{ question }}`, `{{ cur_answer }}`

***

## WebNote Prompts

### `webnote_init_page`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,plan_ls,webnote_init_page_template->prompt_ls")
def webnote_init_page(
    q_ls: List[str],
    plan_ls: List[str],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

WebNote Agent: Initialize note page.

Template Variables: `{{ question }}`, `{{ plan }}`

### `webnote_gen_plan`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,webnote_gen_plan_template->prompt_ls")
def webnote_gen_plan(
    q_ls: List[str],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

WebNote Agent: Generate search plan.

Template Variable: `{{ question }}`

### `webnote_gen_subq`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,plan_ls,page_ls,webnote_gen_subq_template->prompt_ls")
def webnote_gen_subq(
    q_ls: List[str],
    plan_ls: List[str],
    page_ls: List[str],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

WebNote Agent: Generate sub-questions.

Template Variables: `{{ question }}`, `{{ plan }}`, `{{ page }}`

### `webnote_fill_page`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,plan_ls,page_ls,subq_ls,psg_ls,webnote_fill_page_template->prompt_ls")
def webnote_fill_page(
    q_ls: List[str],
    plan_ls: List[str],
    page_ls: List[str],
    subq_ls: List[str],
    psg_ls: List[Any],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

WebNote Agent: Fill notes based on retrieval results.

Template Variables: `{{ question }}`, `{{ plan }}`, `{{ sub_question }}`, `{{ docs_text }}`, `{{ page }}`

### `webnote_gen_answer`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,page_ls,webnote_gen_answer_template->prompt_ls")
def webnote_gen_answer(
    q_ls: List[str],
    page_ls: List[str],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

WebNote Agent: Generate final answer based on notes.

Template Variables: `{{ question }}`, `{{ page }}`

***

## Search-R1 & R1-Searcher

### `search_r1_gen`

**Signature**

```python theme={null}
@app.prompt(output="prompt_ls,ans_ls,ret_psg,search_r1_gen_template->prompt_ls")
def search_r1_gen(
    prompt_ls: List[PromptMessage],
    ans_ls: List[str],
    ret_psg: List[str | Any],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Generation Prompt suitable for R1 style.

Truncates Top-3 retrieval passages and injects into context.

Template Variables: `{{ history }}`, `{{ answer }}`, `{{ passages }}`

### `r1_searcher_gen`

**Signature**

```python theme={null}
@app.prompt(output="prompt_ls,ans_ls,ret_psg,r1_searcher_gen_template->prompt_ls")
def r1_searcher_gen(
    prompt_ls: List[PromptMessage],
    ans_ls: List[str],
    ret_psg: List[str | Any],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Generation Prompt suitable for R1 Searcher.

Truncates Top-5 retrieval passages.

Template Variables: `{{ history }}`, `{{ answer }}`, `{{ passages }}`

***

## Search-o1 Prompts

### `search_o1_init`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,searcho1_reasoning_template->prompt_ls")
def search_o1_init(
    q_ls: List[str],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Search-O1 Initial Reasoning Prompt.

Template Variable: `{{ question }}`

### `search_o1_reasoning_indocument`

**Signature**

```python theme={null}
@app.prompt(output="extract_query_list,ret_psg,total_reason_list,searcho1_refine_template->prompt_ls")
def search_o1_reasoning_indocument(
    extract_query_list: List[str], 
    ret_psg: List[List[str]],       
    total_reason_list: List[List[str]], 
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Search-O1 Reasoning Refinement Prompt.

Merges historical reasoning steps (first + last 3 steps) with current retrieved documents for next step reasoning.

Template Variables: `{{ prev_reasoning }}`, `{{ search_query }}`, `{{ document }}`

### `search_o1_insert`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,total_subq_list,total_final_info_list,searcho1_reasoning_template->prompt_ls") 
def search_o1_insert(
    q_ls: List[str],
    total_subq_list: List[List[str]], 
    total_final_info_list: List[List[str]],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Search-O1 Formatted Insertion Prompt.

Explicitly inserts `<|begin_search_query|>` and search result tags into Prompt to construct complete chain-of-thought context.

***

## EVisRAG & Multi-branch Prompts

### `gen_subq`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,ret_psg,gen_subq_template->prompt_ls")
def gen_subq(
    q_ls: List[str],
    ret_psg: List[str | Any],
    template: str | Path,
) -> List[PromptMessage]
```

**Function**

Loop/Branch Demo: Generate sub-questions based on documents.

Template Variables: `{{ question }}`, `{{ documents }}`

### `evisrag_vqa`

**Signature**

```python theme={null}
@app.prompt(output="q_ls,ret_psg,evisrag_template->prompt_ls")
def evisrag_vqa(
    q_ls: List[str], 
    ret_psg: List[str | Any], 
    template: str | Path
) -> list[PromptMessage]
```

**Function**

Multimodal VQA RAG Prompt.

Automatically repeatedly inserts `<image>` Token into Prompt according to the number of retrieved images.

Template Variable: `{{ question }}` (contains automatically injected image tokens)

***

## SurveyCPM Prompts

### `surveycpm_search`

**Signature**

```python theme={null}
@app.prompt(output="instruction_ls,survey_ls,cursor_ls,surveycpm_search_template->prompt_ls")
def surveycpm_search(
    instruction_ls: List[str],
    survey_ls: List[str],
    cursor_ls: List[str | None],
    surveycpm_search_template: str | Path,
) -> List[PromptMessage]
```

**Function**

Survey Agent: Decide next search content.

Parses JSON format outline, generates text description of current outline.

Template Variables: `{{ user_query }}`, `{{ current_outline }}`, `{{ current_instruction }}`

### `surveycpm_init_plan`

**Signature**

```python theme={null}
@app.prompt(output="instruction_ls,retrieved_info_ls,surveycpm_init_plan_template->prompt_ls")
def surveycpm_init_plan(
    instruction_ls: List[str],
    retrieved_info_ls: List[str],
    surveycpm_init_plan_template: str | Path,
) -> List[PromptMessage]
```

**Function**

Survey Agent: Initialize outline plan.

Template Variables: `{{ user_query }}`, `{{ current_information }}`

### `surveycpm_write`

**Signature**

```python theme={null}
@app.prompt(output="instruction_ls,survey_ls,cursor_ls,retrieved_info_ls,surveycpm_write_template->prompt_ls")
def surveycpm_write(
    instruction_ls: List[str],
    survey_ls: List[str],
    cursor_ls: List[str | None],
    retrieved_info_ls: List[str],
    surveycpm_write_template: str | Path,
) -> List[PromptMessage]
```

**Function**

Survey Agent: Write specific section content.

Template Variables: `{{ user_query }}`, `{{ current_survey }}`, `{{ current_instruction }}`, `{{ current_information }}`

### `surveycpm_extend_plan`

**Signature**

```python theme={null}
@app.prompt(output="instruction_ls,survey_ls,surveycpm_extend_plan_template->prompt_ls")
def surveycpm_extend_plan(
    instruction_ls: List[str],
    survey_ls: List[str],
    surveycpm_extend_plan_template: str | Path,
) -> List[PromptMessage]
```

**Function**

Survey Agent: Extend or modify outline plan.

Template Variables: `{{ user_query }}`, `{{ current_survey }}`

***

## Configuration

```yaml servers/prompt/parameter.yaml icon="https://mintcdn.com/ultrarag/T7GffHzZitf6TThi/images/yaml.svg?fit=max&auto=format&n=T7GffHzZitf6TThi&q=85&s=69b41e79144bc908039c2ee3abbb1c3b" theme={null}
# QA
template: prompt/qa_boxed.jinja

# RankCoT
kr_template: prompt/RankCoT_knowledge_refinement.jinja
qa_template: prompt/RankCoT_question_answering.jinja

# Search-R1
search_r1_gen_template: prompt/search_r1_append.jinja

# R1-Searcher
r1_searcher_gen_template: prompt/r1_searcher_append.jinja

# Search-o1
searcho1_reasoning_template: prompt/search_o1_reasoning.jinja
searcho1_refine_template: prompt/search_o1_refinement.jinja


# For other prompts, please add parameters here as needed

# Take webnote as an example:
webnote_gen_plan_template: prompt/webnote_gen_plan.jinja
webnote_init_page_template: prompt/webnote_init_page.jinja
webnote_gen_subq_template: prompt/webnote_gen_subq.jinja
webnote_fill_page_template: prompt/webnote_fill_page.jinja
webnote_gen_answer_template: prompt/webnote_gen_answer.jinja

# SurveyCPM
surveycpm_search_template: prompt/surveycpm_search.jinja
surveycpm_init_plan_template: prompt/surveycpm_init_plan.jinja
surveycpm_write_template: prompt/surveycpm_write.jinja
surveycpm_extend_plan_template: prompt/surveycpm_extend_plan.jinja
```

| Parameter     | Description                                                     |
| ------------- | --------------------------------------------------------------- |
| `template`    | Basic QA template path                                          |
| `kr_template` | RankCoT knowledge refinement template path                      |
| `qa_template` | RankCoT Q\&A template path                                      |
| `*_template`  | Jinja2 template file path corresponding to each module function |