Move all templates from str to jinja2 files

src/distilabel/steps/tasks/templates/improving_text_embeddings/bitext-retrieval.jinja2

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+Write a {{ unit }} triple with one {{ unit }} in {{ source_language }} and two {{ unit }}s in {{ target_language }} with varying translation qualities in JSON format.
+
+The triple is denotes as ("S1", "S2", "S3"). The translation quality score ranges from 1 to 5, with higher scores are better.
+
+Please adhere to the following guidelines:
+ - The values of "S1" is a string in {{ source_language }}, the value of "S2" and "S3" are strings in {{ target_language }}.
+ - There should be some word overlaps between "S2" and "S3".
+ - The translation quality score of "S2" with respect to "S1" should be {{ high_score }}.
+ - The translation quality score of "S3" with respect to "S1" should be {{ low_score }}.
+ - "S3" should be grammatical and fluent, but contain some keyword or number translation errors, or miss some information, or contain some redundant information.
+ - "S1" requires {{ difficulty }} level education to understand and should be diverse in terms of topic and length.
+
+Your output must always be a JSON object only with three keys "S1", "S2" and "S3", do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/brainstorming/text-classification.jinja2

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+Brainstorm a list of potentially useful text classification tasks.
+
+Please adhere to the following guidelines:
+ - Tasks should cover a diverse range of domains and task types.
+
+Your output must always be a python list of strings only, with about 20 elements, and each element corresponds to a distinct text classification task in one sentence. Do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/brainstorming/text-matching-long.jinja2

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+Brainstorm a list of text matching tasks where the queries are long documents.
+
+Here are a few examples:
+ - Given a document that supports a debatable argument, find another document that contains opposite arguments.
+ - Provided a lengthy business proposal, retrieve competitive business strategies in the same industry.
+
+Your output must always be a python list of strings only, with about 20 elements, and each element corresponds to a distinct task in one sentence. Do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/brainstorming/text-matching-short.jinja2

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+Brainstorm a list of text matching tasks where both the queries and the groundtruth documents are very short (one or two sentences, even a short phrase).
+
+Here are a few examples:
+ - Given a scientific paper title, retrieve the title of papers that cite the given paper.
+ - Match a word with its definition.
+ - Provided a notable person's name, identify their occupation or achievement.
+
+Your output must always be a python list of strings only, with about 20 elements, and each element corresponds to a distinct task in one sentence. Do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/brainstorming/text-retrieval.jinja2

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+Brainstorm a list of potentially useful text retrieval tasks.
+
+Here are a few examples for your reference:
+ - Provided a scientific claim as query, retrieve documents that help verify or refute the claim.
+ - Search for documents that answers a FAQ-style query on children's nutrition.
+
+Please adhere to the following guidelines:
+ - Specify what the query is, and what the desired documents are.
+ - Each retrieval task should cover a wide range of queries, and should not be too specific.
+
+Your output should always be a python list of strings only, with about 20 elements, and each element corresponds to a distinct retrieval task in one sentence. Do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/long-text-matching.jinja2

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+You have been assigned a text matching task: {{ task }}
+
+Your mission is to write one example for this task in JSON format. The JSON object must contain the following keys:
+ - "input": a string, a random input specified by the task.
+ - "positive_document": a string, a relevant document for the "input" according to the task.
+
+Please adhere to the following guidelines:
+ - The values of all fields should be in {{ language }}.
+ - Both the "input" and "positive_document" should be long documents (at least 300 words), avoid substantial word overlaps, otherwise the task would be too easy.
+ - The "input" and "positive_document" should be independent of each other.
+
+Your output must always be a JSON object only, do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/monolingual-triplet.jinja2

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+Write a {{ unit }} triple with varying semantic similarity scores in JSON format. The semantic similarity score ranges from 1 to 5, with 1 denotes least similar and 5 denotes most similar.
+
+Please adhere to the following guidelines:
+ - The keys in JSON are "S1", "S2", and "S3", the values are all strings in {{ language }}, do not add any other keys.
+ - There should be some word overlaps between all three {{ unit }}s.
+ - The similarity score between S1 and S2 should be {{ high_score }}.
+ - The similarity score between S1 and S3 should be {{ low_score }}.
+ - The {{ unit }}s require {{ difficulty }} level education to understand and should be diverse in terms of topic and length.
+
+Your output must always be a JSON object only with three keys "S1", "S2" and "S3", do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/short-text-matching.jinja2

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+You have been assigned a text matching task: {{ task }}
+
+Your mission is to write one example for this task in JSON format. The JSON object must contain the following keys:
+ - "input": a string, a random input specified by the task.
+ - "positive_document": a string, a relevant document for the "input" according to the task.
+
+Please adhere to the following guidelines:
+ - The values of all fields should be in {{ language }}.
+ - Both the "input" and "positive_document" should be very short (a sentence or a phrase), avoid substantial word overlaps, otherwise the task would be too easy.
+ - The "input" and "positive_document" should be independent of each other.
+
+Your output must always be a JSON object only, do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/text-classification.jinja2

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+You have been assigned a text classification task: {{ task }}
+
+Your mission is to write one text classification example for this task in JSON format. The JSON object must contain the following keys:
+ - "input_text": a string, the input text specified by the classification task.
+ - "label": a string, the correct label of the input text.
+ - "misleading_label": a string, an incorrect label that is related to the task.
+
+Please adhere to the following guidelines:
+ - The "input_text" should be diverse in expression.
+ - The "misleading_label" must be a valid label for the given task, but not as appropriate as the "label" for the "input_text".
+ - The values for all fields should be in {{ language }}.
+ - Avoid including the values of the "label" and "misleading_label" fields in the "input_text", that would make the task too easy.
+ - The "input_text" is {{ clarity }} and requires {{ difficulty }} level education to comprehend.
+
+Your output must always be a JSON object only, do not explain yourself or output anything else. Be creative!

src/distilabel/steps/tasks/templates/improving_text_embeddings/text-retrieval.jinja2

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+You have been assigned a retrieval task: {{ task }}
+
+Your mission is to write one text retrieval example for this task in JSON format. The JSON object must contain the following keys:
+ - "user_query": a string, a random user search query specified by the retrieval task.
+ - "positive_document": a string, a relevant document for the user query.
+ - "hard_negative_document": a string, a hard negative document that only appears relevant to the query.
+
+Please adhere to the following guidelines:
+ - The "user_query" should be {{ query_type }}, {{ query_length }}, {{ clarity }}, and diverse in topic.
+ - All documents must be created independent of the query. Avoid copying the query verbatim. It's acceptable if some parts of the "positive_document" are not topically related to the query.
+ - All documents should be at least {{ num_words}} words long.
+ - The "hard_negative_document" contains some useful information, but it should be less useful or comprehensive compared to the "positive_document".
+ - Both the query and documents should be in {{ language }}.
+ - Do not provide any explanation in any document on why it is relevant or not relevant to the query.
+ - Both the query and documents require {{ difficulty }} level education to understand.
+
+Your output must always be a JSON object only, do not explain yourself or output anything else. Be creative!