Revert "refactor!: Deprecate name param in PromptTemplate and int…

…roduce `template_name` instead (#4810)" (#4834)

This reverts commit f660f41.

haystack/nodes/answer_generator/openai.py

@@ -115,7 +115,7 @@ def __init__(
             stop_words = ["\n", "<|endoftext|>"]
         if prompt_template is None:
             prompt_template = PromptTemplate(
-                template_name="question-answering-with-examples",
+                name="question-answering-with-examples",
                 prompt_text="Please answer the question according to the above context."
                 "\n===\nContext: {examples_context}\n===\n{examples}\n\n"
                 "===\nContext: {context}\n===\n{query}",

haystack/nodes/prompt/prompt_node.py

@@ -97,7 +97,7 @@ def __init__(
             },
         )
         super().__init__()
-        self.prompt_templates: Dict[str, PromptTemplate] = {pt.template_name: pt for pt in get_predefined_prompt_templates()}  # type: ignore
+        self.prompt_templates: Dict[str, PromptTemplate] = {pt.name: pt for pt in get_predefined_prompt_templates()}  # type: ignore
         self.default_prompt_template: Union[str, PromptTemplate, None] = default_prompt_template
         self.output_variable: Optional[str] = output_variable
         self.model_name_or_path: Union[str, PromptModel] = model_name_or_path
@@ -193,13 +193,13 @@ def add_prompt_template(self, prompt_template: PromptTemplate) -> None:
         :param prompt_template: The PromptTemplate object to be added.
         :return: None
         """
-        if prompt_template.template_name in self.prompt_templates:
+        if prompt_template.name in self.prompt_templates:
             raise ValueError(
-                f"Prompt template {prompt_template.template_name} already exists. "
+                f"Prompt template {prompt_template.name} already exists. "
                 f"Select a different name for this prompt template."
             )
 
-        self.prompt_templates[prompt_template.template_name] = prompt_template  # type: ignore
+        self.prompt_templates[prompt_template.name] = prompt_template  # type: ignore
 
     def remove_prompt_template(self, prompt_template: str) -> PromptTemplate:
         """
@@ -244,7 +244,7 @@ def is_supported_template(self, prompt_template: Union[str, PromptTemplate]) ->
         :param prompt_template: The prompt template to be checked.
         :return: True if the prompt template is supported, False otherwise.
         """
-        template_name = prompt_template if isinstance(prompt_template, str) else prompt_template.template_name
+        template_name = prompt_template if isinstance(prompt_template, str) else prompt_template.name
         return template_name in self.prompt_templates
 
     def get_prompt_template(self, prompt_template: Union[str, PromptTemplate, None] = None) -> Optional[PromptTemplate]:
@@ -288,9 +288,7 @@ def get_prompt_template(self, prompt_template: Union[str, PromptTemplate, None]
         default_prompt_template = self.get_prompt_template()
         if default_prompt_template:
             output_parser = default_prompt_template.output_parser
-        return PromptTemplate(
-            template_name="custom-at-query-time", prompt_text=prompt_text, output_parser=output_parser
-        )
+        return PromptTemplate(name="custom-at-query-time", prompt_text=prompt_text, output_parser=output_parser)
 
     def prompt_template_params(self, prompt_template: str) -> List[str]:
         """

haystack/nodes/prompt/prompt_template.py

@@ -1,4 +1,3 @@
-import warnings
 from typing import Optional, List, Union, Tuple, Dict, Iterator, Any
 import logging
 import os
@@ -185,49 +184,22 @@ class PromptTemplate(BasePromptTemplate, ABC):
     """
 
     def __init__(
-        self,
-        prompt_text: str,
-        template_name: Optional[str] = None,
-        output_parser: Optional[Union[BaseOutputParser, Dict[str, Any]]] = None,
-        name: Optional[str] = None,
+        self, name: str, prompt_text: str, output_parser: Optional[Union[BaseOutputParser, Dict[str, Any]]] = None
     ):
         """
          Creates a PromptTemplate instance.
 
+        :param name: The name of the prompt template (for example, "sentiment-analysis", "question-generation"). You can specify your own name but it must be unique.
         :param prompt_text: The prompt text, including prompt parameters.
-        :param template_name: The name of the prompt template (for example, "sentiment-analysis", "question-generation").
-                              You can specify your own name but it must be unique.
         :param output_parser: A parser that applied to the model output.
                 For example, to convert the model output to an Answer object, you can use `AnswerParser`.
                 Instead of BaseOutputParser instances, you can also pass dictionaries defining the output parsers. For example:
                 ```
                 output_parser={"type": "AnswerParser", "params": {"pattern": "Answer: (.*)"}},
                 ```
-        :param name: This parameter is deprecated. Use `template_name` instead.
         """
         super().__init__()
 
-        if template_name is None and name is None:
-            raise ValueError("Specify the parameter `template_name`.")
-
-        if name is not None and template_name is None:
-            warnings.warn(
-                "The parameter `name` is deprecated and will be removed in Haystack 2.0. Use the parameter "
-                "`template_name` instead.",
-                category=DeprecationWarning,
-                stacklevel=2,
-            )
-            template_name = name
-
-        if name is not None and template_name is not None:
-            warnings.warn(
-                "You are using both `name` and `template_name` parameters. The parameter `name` is deprecated and will be "
-                "removed in Haystack 2.0. Use only the parameter `template_name`. "
-                f"PromptTemplate will be initialized using the parameter `template_name` ('{template_name}').",
-                category=DeprecationWarning,
-                stacklevel=2,
-            )
-
         # use case when PromptTemplate is loaded from a YAML file, we need to start and end the prompt text with quotes
         for strip in PROMPT_TEMPLATE_STRIPS:
             prompt_text = prompt_text.strip(strip)
@@ -240,16 +212,15 @@ def __init__(
 
         self._ast_expression = ast.parse(f'f"{prompt_text}"', mode="eval")
 
-        template_name = str(template_name)
-        ast_validator = _ValidationVisitor(prompt_template_name=template_name)
+        ast_validator = _ValidationVisitor(prompt_template_name=name)
         ast_validator.visit(self._ast_expression)
 
         ast_transformer = _FstringParamsTransformer()
         self._ast_expression = ast.fix_missing_locations(ast_transformer.visit(self._ast_expression))
         self._prompt_params_functions = ast_transformer.prompt_params_functions
         self._used_functions = ast_validator.used_functions
 
-        self.template_name = template_name
+        self.name = name
         self.prompt_text = prompt_text
         self.prompt_params: List[str] = sorted(
             param for param in ast_validator.prompt_params if param not in PROMPT_TEMPLATE_SPECIAL_CHAR_ALIAS
@@ -364,25 +335,25 @@ def fill(self, *args, **kwargs) -> Iterator[str]:
             yield prompt_prepared
 
     def __repr__(self):
-        return f"PromptTemplate(prompt_text={self.prompt_text}, template_name={self.template_name}, prompt_params={self.prompt_params})"
+        return f"PromptTemplate(name={self.name}, prompt_text={self.prompt_text}, prompt_params={self.prompt_params})"
 
 
 def get_predefined_prompt_templates() -> List[PromptTemplate]:
     return [
         PromptTemplate(
-            template_name="question-answering",
+            name="question-answering",
             prompt_text="Given the context please answer the question. Context: {join(documents)}; Question: "
             "{query}; Answer:",
             output_parser=AnswerParser(),
         ),
         PromptTemplate(
-            template_name="question-answering-per-document",
+            name="question-answering-per-document",
             prompt_text="Given the context please answer the question. Context: {documents}; Question: "
             "{query}; Answer:",
             output_parser=AnswerParser(),
         ),
         PromptTemplate(
-            template_name="question-answering-with-references",
+            name="question-answering-with-references",
             prompt_text="Create a concise and informative answer (no more than 50 words) for a given question "
             "based solely on the given documents. You must only use information from the given documents. "
             "Use an unbiased and journalistic tone. Do not repeat text. Cite the documents using Document[number] notation. "
@@ -392,7 +363,7 @@ def get_predefined_prompt_templates() -> List[PromptTemplate]:
             output_parser=AnswerParser(reference_pattern=r"Document\[(\d+)\]"),
         ),
         PromptTemplate(
-            template_name="question-answering-with-document-scores",
+            name="question-answering-with-document-scores",
             prompt_text="Answer the following question using the paragraphs below as sources. "
             "An answer should be short, a few words at most.\n"
             "Paragraphs:\n{documents}\n"
@@ -403,47 +374,47 @@ def get_predefined_prompt_templates() -> List[PromptTemplate]:
             "After having considered all possibilities, the final answer is:\n",
         ),
         PromptTemplate(
-            template_name="question-generation",
+            name="question-generation",
             prompt_text="Given the context please generate a question. Context: {documents}; Question:",
         ),
         PromptTemplate(
-            template_name="conditioned-question-generation",
+            name="conditioned-question-generation",
             prompt_text="Please come up with a question for the given context and the answer. "
             "Context: {documents}; Answer: {answers}; Question:",
         ),
-        PromptTemplate(template_name="summarization", prompt_text="Summarize this document: {documents} Summary:"),
+        PromptTemplate(name="summarization", prompt_text="Summarize this document: {documents} Summary:"),
         PromptTemplate(
-            template_name="question-answering-check",
+            name="question-answering-check",
             prompt_text="Does the following context contain the answer to the question? "
             "Context: {documents}; Question: {query}; Please answer yes or no! Answer:",
             output_parser=AnswerParser(),
         ),
         PromptTemplate(
-            template_name="sentiment-analysis",
+            name="sentiment-analysis",
             prompt_text="Please give a sentiment for this context. Answer with positive, "
             "negative or neutral. Context: {documents}; Answer:",
         ),
         PromptTemplate(
-            template_name="multiple-choice-question-answering",
+            name="multiple-choice-question-answering",
             prompt_text="Question:{query} ; Choose the most suitable option to answer the above question. "
             "Options: {options}; Answer:",
             output_parser=AnswerParser(),
         ),
         PromptTemplate(
-            template_name="topic-classification",
+            name="topic-classification",
             prompt_text="Categories: {options}; What category best describes: {documents}; Answer:",
         ),
         PromptTemplate(
-            template_name="language-detection",
+            name="language-detection",
             prompt_text="Detect the language in the following context and answer with the "
             "name of the language. Context: {documents}; Answer:",
         ),
         PromptTemplate(
-            template_name="translation",
+            name="translation",
             prompt_text="Translate the following context to {target_language}. Context: {documents}; Translation:",
         ),
         PromptTemplate(
-            template_name="zero-shot-react",
+            name="zero-shot-react",
             prompt_text="You are a helpful and knowledgeable agent. To achieve your goal of answering complex questions "
             "correctly, you have access to the following tools:\n\n"
             "{tool_names_with_descriptions}\n\n"

test/agents/test_agent.py

@@ -185,7 +185,7 @@ def test_tool_result_extraction(reader, retriever_with_docs):
     assert result == "Paris" or result == "Madrid"
 
     # PromptNode as a Tool
-    pt = PromptTemplate("Here is a question: {query}, Answer:", "test")
+    pt = PromptTemplate("test", "Here is a question: {query}, Answer:")
     pn = PromptNode(default_prompt_template=pt)
 
     t = Tool(name="Search", pipeline_or_node=pn, description="N/A", output_variable="results")
@@ -219,7 +219,7 @@ def test_agent_run(reader, retriever_with_docs, document_store_with_docs):
     country_finder = PromptNode(
         model_name_or_path=prompt_model,
         default_prompt_template=PromptTemplate(
-            template_name="country_finder",
+            name="country_finder",
             prompt_text="When I give you a name of the city, respond with the country where the city is located.\n"
             "City: Rome\nCountry: Italy\n"
             "City: Berlin\nCountry: Germany\n"

test/nodes/test_generator.py

@@ -158,7 +158,7 @@ def test_openai_answer_generator_custom_template(haystack_openai_config, docs):
         pytest.skip("No API key found, skipping test")
 
     lfqa_prompt = PromptTemplate(
-        template_name="lfqa",
+        name="lfqa",
         prompt_text="""
         Synthesize a comprehensive answer from your knowledge and the following topk most relevant paragraphs and the given question.
         \n===\Paragraphs: {context}\n===\n{query}""",

test/nodes/test_shaper.py

@@ -838,7 +838,7 @@ def test_strings_to_answers_after_prompt_node_yaml(tmp_path):
               - name: prompt_template_raw_qa_per_document
                 type: PromptTemplate
                 params:
-                  template_name: raw-question-answering-per-document
+                  name: raw-question-answering-per-document
                   prompt_text: 'Given the context please answer the question. Context: {{documents}}; Question: {{query}}; Answer:'
 
               - name: prompt_node_raw_qa