Prompt Templates
以下是参考提示模板。
我们首先显示默认提示的链接。
然后，我们显示基本提示类， 派生自`Langchain <https://langchain.readthedocs.io/en/latest/modules/prompt.html>`。
默认提示
默认提示列表可以在`这里找到 <https://github.com/jerryjliu/llama_index/blob/main/llama_index/prompts/default_prompts.py>`。
注意：我们还为ChatGPT用例策划了一组精炼提示。 ChatGPT精炼提示列表可以在`这里找到 <https://github.com/jerryjliu/llama_index/blob/main/llama_index/prompts/chat_prompts.py>`。
Prompts
Subclasses from base prompt.
- llama_index.prompts.prompts.KeywordExtractPrompt
Query keyword extract prompt.
Prompt to extract keywords from a query query_str with a maximum of max_keywords keywords.
Required template variables: query_str, max_keywords
- llama_index.prompts.prompts.KnowledgeGraphPrompt
Simple Input prompt.
Required template variables: query_str.
- llama_index.prompts.prompts.QueryKeywordExtractPrompt
Schema extract prompt.
Prompt to extract schema from unstructured text text.
Required template variables: text, schema
- llama_index.prompts.prompts.QuestionAnswerPrompt
Keyword extract prompt.
Prompt to extract keywords from a text text with a maximum of max_keywords keywords.
Required template variables: text, max_keywords
- llama_index.prompts.prompts.RefinePrompt
Question Answer prompt.
Prompt to answer a question query_str given a context context_str.
Required template variables: context_str, query_str
- llama_index.prompts.prompts.RefineTableContextPrompt
Define the knowledge graph triplet extraction prompt.
- llama_index.prompts.prompts.SchemaExtractPrompt
Text to SQL prompt.
Prompt to translate a natural language query into SQL in the dialect dialect given a schema schema.
Required template variables: query_str, schema, dialect
- llama_index.prompts.prompts.SimpleInputPrompt
Pandas prompt. Convert query to python code.
Required template variables: query_str, df_str, instruction_str.
- llama_index.prompts.prompts.SummaryPrompt
Tree Insert prompt.
Prompt to insert a new chunk of text new_chunk_text into the tree index. More specifically, this prompt has the LLM select the relevant candidate child node to continue tree traversal.
Required template variables: num_chunks, context_list, new_chunk_text
- llama_index.prompts.prompts.TableContextPrompt
Refine Table context prompt.
Prompt to refine a table context given a table schema schema, as well as unstructured text context context_msg, and a task query_str. This includes both a high-level description of the table as well as a description of each column in the table.
- llama_index.prompts.prompts.TextToSQLPrompt
Table context prompt.
Prompt to generate a table context given a table schema schema, as well as unstructured text context context_str, and a task query_str. This includes both a high-level description of the table as well as a description of each column in the table.
- llama_index.prompts.prompts.TreeInsertPrompt
Tree select prompt.
Prompt to select a candidate child node out of all child nodes provided in context_list, given a query query_str. num_chunks is the number of child nodes in context_list.
Required template variables: num_chunks, context_list, query_str
- llama_index.prompts.prompts.TreeSelectMultiplePrompt
Refine prompt.
Prompt to refine an existing answer existing_answer given a context context_msg, and a query query_str.
Required template variables: query_str, existing_answer, context_msg
- llama_index.prompts.prompts.TreeSelectPrompt
Tree select multiple prompt.
Prompt to select multiple candidate child nodes out of all child nodes provided in context_list, given a query query_str. branching_factor refers to the number of child nodes to select, and num_chunks is the number of child nodes in context_list.
- Required template variables: num_chunks, context_list, query_str,
branching_factor
基本提示类
Prompt class.
- class llama_index.prompts.Prompt(template: Optional[str] = None, langchain_prompt: Optional[BasePromptTemplate] = None, langchain_prompt_selector: Optional[ConditionalPromptSelector] = None, stop_token: Optional[str] = None, output_parser: Optional[BaseOutputParser] = None, prompt_type: str = PromptType.CUSTOM, metadata: Optional[Dict[str, Any]] = None, **prompt_kwargs: Any)
Prompt class for LlamaIndex.
- Wrapper around langchain's prompt class. Adds ability to:
enforce certain prompt types
partially fill values
define stop token
- format(llm: Optional[BaseLanguageModel] = None, **kwargs: Any) str
Format the prompt.
- classmethod from_langchain_prompt(prompt: BasePromptTemplate, **kwargs: Any) Prompt
Load prompt from LangChain prompt.
- classmethod from_langchain_prompt_selector(prompt_selector: ConditionalPromptSelector, **kwargs: Any) Prompt
Load prompt from LangChain prompt.
- classmethod from_prompt(prompt: Prompt, llm: Optional[BaseLanguageModel] = None, prompt_type: Optional[PromptType] = None) Prompt
Create a prompt from an existing prompt.
Use case: If the existing prompt is already partially filled, and the remaining fields satisfy the requirements of the prompt class, then we can create a new prompt from the existing partially filled prompt.
- get_langchain_prompt(llm: Optional[BaseLanguageModel] = None) BasePromptTemplate
Get langchain prompt.
- property original_template: str
Return the originally specified template, if supplied.