diff --git a/autointent/_dataset/_dataset.py b/autointent/_dataset/_dataset.py
index 774773b2..d15ca8ae 100644
--- a/autointent/_dataset/_dataset.py
+++ b/autointent/_dataset/_dataset.py
@@ -100,13 +100,14 @@ def from_hub(cls, repo_id: str) -> "Dataset":
         :param repo_id: ID of the Hugging Face repository.
         :return: Initialized Dataset object.
         """
-        splits, intents = load_dataset(repo_id), []
+        from ._reader import DictReader
+
+        splits = load_dataset(repo_id)
+        mapping = dict(**splits)
         if Split.INTENTS in get_dataset_config_names(repo_id):
-            intents = load_dataset(repo_id, Split.INTENTS)[Split.INTENTS].to_list()
-        return cls(
-            splits.items(),
-            intents=[Intent.model_validate(intent) for intent in intents],
-        )
+            mapping["intents"] = load_dataset(repo_id, Split.INTENTS)[Split.INTENTS].to_list()
+
+        return DictReader().read(mapping)
 
     def to_multilabel(self) -> "Dataset":
         """
diff --git a/autointent/generation/utterances/__init__.py b/autointent/generation/utterances/__init__.py
index e69de29b..db54310e 100644
--- a/autointent/generation/utterances/__init__.py
+++ b/autointent/generation/utterances/__init__.py
@@ -0,0 +1,14 @@
+from .basic import SynthesizerChatTemplate, UtteranceGenerator
+from .evolution import AbstractEvolution, ConcreteEvolution, EvolutionChatTemplate, ReasoningEvolution, UtteranceEvolver
+from .generator import Generator
+
+__all__ = [
+    "AbstractEvolution",
+    "ConcreteEvolution",
+    "EvolutionChatTemplate",
+    "Generator",
+    "ReasoningEvolution",
+    "SynthesizerChatTemplate",
+    "UtteranceEvolver",
+    "UtteranceGenerator",
+]
diff --git a/autointent/generation/utterances/basic/__init__.py b/autointent/generation/utterances/basic/__init__.py
index e69de29b..5ae1c024 100644
--- a/autointent/generation/utterances/basic/__init__.py
+++ b/autointent/generation/utterances/basic/__init__.py
@@ -0,0 +1,4 @@
+from .chat_template import SynthesizerChatTemplate
+from .utterance_generator import UtteranceGenerator
+
+__all__ = ["SynthesizerChatTemplate", "UtteranceGenerator"]
diff --git a/autointent/generation/utterances/basic/chat_template.py b/autointent/generation/utterances/basic/chat_template.py
new file mode 100644
index 00000000..98b52aae
--- /dev/null
+++ b/autointent/generation/utterances/basic/chat_template.py
@@ -0,0 +1,134 @@
+"""Chat template for evolution augmentation via abstractization."""
+
+import random
+from abc import ABC, abstractmethod
+from copy import deepcopy
+from typing import ClassVar
+
+from autointent import Dataset
+from autointent.generation.utterances.schemas import Message, Role
+from autointent.schemas import Intent
+
+
+class BaseSynthesizer(ABC):
+    """Base class."""
+
+    @abstractmethod
+    def __call__(self, intent_data: Intent, n_examples: int) -> list[Message]:
+        """Generate examples for this intent."""
+
+
+class SynthesizerChatTemplate(BaseSynthesizer):
+    """Chat template for generating additional examples for a given intent class."""
+
+    __messages: ClassVar[list[Message]] = [
+        Message(
+            role=Role.USER,
+            content=(
+                "You will be provided with a set of example utterances and the name "
+                "of the common topic (intent name) of these utterances. "
+                "Your task is to generate more examples that fit within the same intent name.\n\n"
+                "Note:\n"
+                "- You can generate similar utterances with only slot values changed\n"
+                "- You can generate completely different utterance from the same intent name\n"
+                "- Intent name can be missed, then you should infer from example utterances only\n"
+                "- Example utterances can be missed, then you should infer from intent name only\n"
+                "{extra_instructions}\n\n"
+                "Intent name: ordering_pizza\n\n"
+                "Example Utterances:\n"
+                "1. I want to order a large pepperoni pizza.\n"
+                "2. Can I get a medium cheese pizza with extra olives?\n"
+                "3. Please deliver a small veggie pizza to my address.\n\n"
+                "Please generate 3 more examples for the provided intent name."
+            ),
+        ),
+        Message(
+            role=Role.ASSISTANT,
+            content=(
+                "1. I'd like to order a large margherita pizza.\n"
+                "2. Can you deliver a medium Hawaiian pizza with extra pineapple?\n"
+                "3. Please send a small BBQ chicken pizza to my home."
+            ),
+        ),
+        Message(
+            role=Role.USER,
+            content=(
+                "Intent name: booking a hotel\n\n"
+                "Example Utterances:\n"
+                "1. I need to book a room for two nights in New York.\n\n"
+                "Please generate 2 more examples for the provided intent name."
+            ),
+        ),
+        Message(
+            role=Role.ASSISTANT,
+            content=(
+                "1. Can you reserve a deluxe room for my trip to Tokyo?\n"
+                "2. I need to book a hotel room with a mountain view in Denver."
+            ),
+        ),
+        Message(
+            role=Role.USER,
+            content=(
+                "Intent name:\n\n"
+                "Example Utterances:\n"
+                "1. What is the weather like today?\n\n"
+                "Please generate 2 more examples for the provided intent class."
+            ),
+        ),
+        Message(
+            role=Role.ASSISTANT,
+            content=("1. Can you tell me the forecast for tomorrow?\n" "2. Is it going to rain this weekend?"),
+        ),
+        Message(
+            role=Role.USER,
+            content=(
+                "Intent name: Scheduling a Meeting\n\n"
+                "Example Utterances:\n\n"
+                "Please generate 3 more examples for the provided intent class."
+            ),
+        ),
+        Message(
+            role=Role.ASSISTANT,
+            content=(
+                "1. I need to schedule a meeting for next Tuesday.\n"
+                "2. Can you set up a conference call for tomorrow afternoon?\n"
+                "3. Please arrange a meeting with the marketing team next week."
+            ),
+        ),
+    ]
+
+    def __init__(
+        self,
+        dataset: Dataset,
+        split: str,
+        extra_instructions: str | None = None,
+        max_sample_utterances: int | None = None,
+    ) -> None:
+        """Initialize."""
+        if extra_instructions is None:
+            extra_instructions = ""
+
+        self._messages = deepcopy(self.__messages)
+
+        msg = self._messages[0]
+        msg["content"] = msg["content"].format(extra_instructions=extra_instructions)
+
+        self.dataset = dataset
+        self.split = split
+        self.max_sample_utterances = max_sample_utterances
+
+    def __call__(self, intent_data: Intent, n_examples: int) -> list[Message]:
+        """Generate additional examples for the provided intent class."""
+        filtered_split = self.dataset[self.split].filter(lambda sample: sample[Dataset.label_feature] == intent_data.id)
+        sample_utterances = filtered_split[Dataset.utterance_feature]
+        if self.max_sample_utterances is not None:
+            sample_utterances = random.sample(sample_utterances, k=self.max_sample_utterances)
+        return [
+            *self._messages,
+            Message(
+                role=Role.USER,
+                content=f"Intent name: {intent_data.name}\n\n"
+                f"Example Utterances:\n{sample_utterances}\n\n"
+                f"Please generate {n_examples} more examples for the provided intent class.\n",
+            ),
+        ]
diff --git a/autointent/generation/utterances/basic/chat_template.yaml b/autointent/generation/utterances/basic/chat_template.yaml
deleted file mode 100644
index 9d512a11..00000000
--- a/autointent/generation/utterances/basic/chat_template.yaml
+++ /dev/null
@@ -1,119 +0,0 @@
-- role: system
-  content: |
-    You will be provided with a set of example utterances and the name of the common topic (intent class) of these utterances. Your task is to generate more examples that fit within the same intent class.
-
-    Note:
-    - You can generate similar utterances with only slot values changed
-    - You can generate completely different utterance from the same intent class
-    - Intent name can be missed, then you should infer from example utterances only
-    - Example utterances can be missed, then you should infer from intent name only
-    {extra_instructions}
-- role: user
-  content: |
-    Intent Class: ordering_pizza
-
-    Example Utterances:
-    1. I want to order a large pepperoni pizza.
-    2. Can I get a medium cheese pizza with extra olives?
-    3. Please deliver a small veggie pizza to my address.
-
-    Please generate 3 more examples for the provided intent class.
-- role: assistant
-  content: |
-    1. I'd like to order a large margherita pizza.
-    2. Can you deliver a medium Hawaiian pizza with extra pineapple?
-    3. Please send a small BBQ chicken pizza to my home.
-- role: user
-  content: |
-    Intent Class: booking a hotel
-
-    Example Utterances:
-    1. I need to book a room for two nights in New York.
-
-    Please generate 2 more examples for the provided intent class.
-- role: assistant
-  content: |
-    1. Can you reserve a deluxe room for my trip to Tokyo?
-    2. I need to book a hotel room with a mountain view in Denver.
-- role: user
-  content: |
-    Intent Class:
-
-    Example Utterances:
-    1. What is the weather like today?
-
-    Please generate 2 more examples for the provided intent class.
-- role: assistant
-  content: |
-    1. Can you tell me the forecast for tomorrow?
-    2. Is it going to rain this weekend?
-- role: user
-  content: |
-    Intent Class: Scheduling a Meeting
-
-    Example Utterances:
-
-    Please generate 3 more examples for the provided intent class.
-- role: assistant
-  content: |
-    1. I need to schedule a meeting for next Tuesday.
-    2. Can you set up a conference call for tomorrow afternoon?
-    3. Please arrange a meeting with the marketing team next week.
-- role: user
-  content: |
-    Intent Class: {intent_name}
-
-    Example Utterances:
-    {example_utterances}
-
-    Please generate {n_examples} more examples for the provided intent class.
-
-# ### Intent Class: Asking for Directions
-# **Example Utterances:**
-# 1. "How do I get to the nearest coffee shop?"
-# 2. "Can you give me directions to the airport?"
-# 3. "What is the best route to the museum from here?"
-
-# ### Intent Class: Making a Restaurant Reservation
-# **Example Utterances:**
-# 1. "I want to make a reservation for dinner tonight."
-# 2. "Can you book a table for two at the Italian restaurant?"
-# 3. "Please reserve a table for four at the steakhouse for Saturday evening."
-
-# ### Intent Class: Requesting Technical Support
-# **Example Utterances:**
-# 1. "I'm having trouble with my laptop."
-# 2. "Can you help me fix my Wi-Fi connection?"
-# 3. "My software is not working properly, can you assist?"
-
-# ### Intent Class: Inquiring About Product Availability
-# **Example Utterances:**
-# 1. "Do you have the new iPhone in stock?"
-# 2. "Is the blue shirt available in size medium?"
-# 3. "Can you check if the latest book by John Doe is available?"
-
-# ### Intent Class: Requesting Account Information
-# **Example Utterances:**
-# 1. "What is my current account balance?"
-# 2. "Can you tell me my recent transactions?"
-# 3. "I need to check my account statement for last month."
-
-# ### Intent Class: Booking a Flight
-# **Example Utterances:**
-# 1. "I want to book a flight to Los Angeles."
-# 2. "Can you find me a flight to Paris next week?"
-# 3. "Please book a round-trip flight to New York for next month."
-
-# ### Intent Class: Requesting Movie Recommendations
-# **Example Utterances:**
-# 1. "Can you recommend a good action movie?"
-# 2. "What are some highly rated comedies?"
-# 3. "I'm in the mood for a romantic film, any suggestions?"
-
-# ### Intent Class: Ordering Groceries
-# **Example Utterances:**
-# 1. "I need to order some milk and bread."
-# 2. "Can you add apples and bananas to my grocery list?"
-# 3. "Please order a dozen eggs and a pack of butter."
-
-# You can use these intent names and example utterances to further train or test your language model for generating more examples within each intent class.
diff --git a/autointent/generation/utterances/basic/cli.py b/autointent/generation/utterances/basic/cli.py
index 782776f8..baa6968c 100644
--- a/autointent/generation/utterances/basic/cli.py
+++ b/autointent/generation/utterances/basic/cli.py
@@ -1,11 +1,17 @@
 """CLI for basic utterance generator."""
 
+import logging
 from argparse import ArgumentParser
 
 from autointent import load_dataset
-from autointent.generation.utterances.basic.utterance_generator import LengthType, StyleType, UtteranceGenerator
+from autointent.generation.utterances.basic.utterance_generator import UtteranceGenerator
 from autointent.generation.utterances.generator import Generator
 
+from .chat_template import SynthesizerChatTemplate
+
+logging.basicConfig(level="INFO")
+logger = logging.getLogger(__name__)
+
 
 def main() -> None:
     """ClI endpoint."""
@@ -28,6 +34,7 @@ def main() -> None:
         default=None,
         help="Local path where to save result",
     )
+    parser.add_argument("--split", type=str, default="train")
     parser.add_argument("--private", action="store_true", help="Publish privately if --output-repo option is used")
     parser.add_argument(
         "--n-generations",
@@ -41,37 +48,19 @@ def main() -> None:
         default=5,
         help="Number of utterances to use as an example for augmentation",
     )
-    parser.add_argument(
-        "--custom-instruction",
-        type=str,
-        action="append",
-        help="Add extra instructions to default prompt."
-        "You can use this argument multiple times to add multiple instructions",
-    )
-    parser.add_argument(
-        "--length",
-        choices=LengthType.__args__,  # type: ignore[attr-defined]
-        default="none",
-        help="How to extend the prompt with length instruction",
-    )
-    parser.add_argument(
-        "--style",
-        choices=StyleType.__args__,  # type: ignore[attr-defined]
-        default="none",
-        help="How to extend the prompt with style instruction",
-    )
-    parser.add_argument(
-        "--same-punctuation",
-        action="store_true",
-        help="Whether to extend the prompt with punctuation instruction",
-    )
     args = parser.parse_args()
 
     dataset = load_dataset(args.input_path)
-    generator = UtteranceGenerator(
-        Generator(), args.custom_instruction or [], args.length, args.style, args.same_punctuation
-    )
-    generator.augment(dataset, n_generations=args.n_generations, max_sample_utterances=args.n_sample_utterances)
+    template = SynthesizerChatTemplate(dataset, args.split, max_sample_utterances=args.n_sample_utterances)
+    generator = UtteranceGenerator(Generator(), template)
+
+    n_before = len(dataset[args.split])
+    new_samples = generator.augment(dataset, split_name=args.split, n_generations=args.n_generations)
+    n_after = len(dataset[args.split])
+
+    logger.info("# samples before %s", n_before)
+    logger.info("# samples generated %s", len(new_samples))
+    logger.info("# samples after %s", n_after)
 
     dataset.to_json(args.output_path)
 
diff --git a/autointent/generation/utterances/basic/extra_instructions.json b/autointent/generation/utterances/basic/extra_instructions.json
deleted file mode 100644
index a17c384b..00000000
--- a/autointent/generation/utterances/basic/extra_instructions.json
+++ /dev/null
@@ -1,14 +0,0 @@
-{
-    "length": {
-        "same": "Generated utterances should have the similar length in a sense of number of words to example utterances",
-        "longer": "Generated utterances can be a little bit longer in a sense of number of words than example utterances",
-        "shorter": "Generated utterances can be a little bit shorter in a sense of number of words than example utterances"
-    },
-    "style": {
-        "same": "Generated utterances should follow the same style of conversation as example utterances",
-        "formal": "Generated utterances should follow a formal style of conversation",
-        "informal": "Generated utterances doesn't have to follow a formal style of conversation",
-        "playful": "Generated utterances can be playful and funny"
-    },
-    "punctuation": "Generated utterances should follow the same punctuation style"
-}
diff --git a/autointent/generation/utterances/basic/utterance_generator.py b/autointent/generation/utterances/basic/utterance_generator.py
index ecd22de3..1d962272 100644
--- a/autointent/generation/utterances/basic/utterance_generator.py
+++ b/autointent/generation/utterances/basic/utterance_generator.py
@@ -1,22 +1,15 @@
 """Basic generation of new utterances from existing ones."""
 
-import importlib.resources as ires
-import json
-import random
-from typing import Any, Literal
+from collections.abc import Callable
 
-import yaml
 from datasets import Dataset as HFDataset
 from datasets import concatenate_datasets
 
 from autointent import Dataset
 from autointent.custom_types import Split
 from autointent.generation.utterances.generator import Generator
-from autointent.generation.utterances.utils import safe_format  # type: ignore[attr-defined]
-from autointent.schemas import Sample
-
-LengthType = Literal["none", "same", "longer", "shorter"]
-StyleType = Literal["none", "formal", "informal", "playful"]
+from autointent.generation.utterances.schemas import Message
+from autointent.schemas import Intent, Sample
 
 
 class UtteranceGenerator:
@@ -28,34 +21,14 @@ class UtteranceGenerator:
     punctuation and length of the desired generations.
     """
 
-    def __init__(
-        self,
-        generator: Generator,
-        custom_instruction: list[str],
-        length: LengthType,
-        style: StyleType,
-        same_punctuation: bool,
-    ) -> None:
+    def __init__(self, generator: Generator, prompt_maker: Callable[[Intent, int], list[Message]]) -> None:
         """Initialize."""
         self.generator = generator
-        prompt_template_yaml = _load_prompt()
-        self.prompt_template_yaml = _add_extra_instructions(
-            prompt_template_yaml,
-            custom_instruction,
-            length,
-            style,
-            same_punctuation,
-        )
+        self.prompt_maker = prompt_maker
 
-    def __call__(self, intent_name: str, example_utterances: list[str], n_generations: int) -> list[str]:
+    def __call__(self, intent_data: Intent, n_generations: int) -> list[str]:
         """Generate new utterances."""
-        messages_yaml = safe_format(
-            self.prompt_template_yaml,
-            intent_name=intent_name,
-            example_utterances=_format_utterances(example_utterances),
-            n_examples=n_generations,
-        )
-        messages = yaml.safe_load(messages_yaml)
+        messages = self.prompt_maker(intent_data, n_generations)
         response_text = self.generator.get_chat_completion(messages)
         return _extract_utterances(response_text)
 
@@ -64,24 +37,18 @@ def augment(
         dataset: Dataset,
         split_name: str = Split.TRAIN,
         n_generations: int = 5,
-        max_sample_utterances: int = 5,
         update_split: bool = True,
     ) -> list[Sample]:
         """
         Augment some split of dataset.
 
-        Note that for now it supports only single-label datasets.
+        TODO Note that for now it supports only single-label datasets.
         """
         original_split = dataset[split_name]
         new_samples = []
         for intent in dataset.intents:
-            filtered_split = original_split.filter(lambda sample, id=intent.id: sample[Dataset.label_feature] == id)
-            sample_utterances = filtered_split[Dataset.utterance_feature]
-            if max_sample_utterances is not None:
-                sample_utterances = random.sample(sample_utterances, k=max_sample_utterances)
             generated_utterances = self(
-                intent_name=intent.name or "",
-                example_utterances=sample_utterances,
+                intent_data=intent,
                 n_generations=n_generations,
             )
             new_samples.extend(
@@ -93,54 +60,6 @@ def augment(
         return [Sample(**sample) for sample in new_samples]
 
 
-def _load_prompt() -> str:
-    with ires.files("autointent.generation.utterances.basic").joinpath("chat_template.yaml").open() as file:
-        return file.read()
-
-
-def _load_extra_instructions() -> dict[str, Any]:
-    with ires.files("autointent.generation.utterances.basic").joinpath("extra_instructions.json").open() as file:
-        return json.load(file)  # type: ignore[no-any-return]
-
-
-def _add_extra_instructions(
-    prompt_template_yaml: str,
-    custom_instruction: list[str],
-    length: LengthType,
-    style: StyleType,
-    same_punctuation: bool,
-) -> str:
-    instructions = _load_extra_instructions()
-
-    extra_instructions = []
-    if length != "none":
-        extra_instructions.append(instructions["length"][length])
-    if style != "none":
-        extra_instructions.append(instructions["style"][style])
-    if same_punctuation:
-        extra_instructions.append(instructions["punctuation"])
-
-    extra_instructions.extend(custom_instruction)
-
-    parsed_extra_instructions = "\n    ".join([f"- {s}" for s in extra_instructions])
-    return safe_format(prompt_template_yaml, extra_instructions=parsed_extra_instructions)  # type: ignore[no-any-return]
-
-
-def _format_utterances(utterances: list[str]) -> str:
-    """
-    Convert given utterances into string that is ready to insert into prompt.
-
-    Given list of utterances, the output string is returned in the following format:
-    .. code-block::
-        1. I want to order a large pepperoni pizza.
-        2. Can I get a medium cheese pizza with extra olives?
-        3. Please deliver a small veggie pizza to my address.
-
-    Note that tab is inserted before each line because of how yaml processes multi-line fields.
-    """
-    return "\n    ".join(f"{i}. {ut}" for i, ut in enumerate(utterances))
-
-
 def _extract_utterances(response_text: str) -> list[str]:
     """
     Parse LLM output.
diff --git a/autointent/generation/utterances/evolution/__init__.py b/autointent/generation/utterances/evolution/__init__.py
index e69de29b..27007e7f 100644
--- a/autointent/generation/utterances/evolution/__init__.py
+++ b/autointent/generation/utterances/evolution/__init__.py
@@ -0,0 +1,4 @@
+from .chat_templates import AbstractEvolution, ConcreteEvolution, EvolutionChatTemplate, ReasoningEvolution
+from .evolver import UtteranceEvolver
+
+__all__ = ["AbstractEvolution", "ConcreteEvolution", "EvolutionChatTemplate", "ReasoningEvolution", "UtteranceEvolver"]
diff --git a/autointent/generation/utterances/evolution/chat_templates/__init__.py b/autointent/generation/utterances/evolution/chat_templates/__init__.py
index e69de29b..8417ff1a 100644
--- a/autointent/generation/utterances/evolution/chat_templates/__init__.py
+++ b/autointent/generation/utterances/evolution/chat_templates/__init__.py
@@ -0,0 +1,6 @@
+from .abstract import AbstractEvolution
+from .base import EvolutionChatTemplate
+from .concrete import ConcreteEvolution
+from .reasoning import ReasoningEvolution
+
+__all__ = ["AbstractEvolution", "ConcreteEvolution", "EvolutionChatTemplate", "ReasoningEvolution"]
diff --git a/autointent/generation/utterances/evolution/chat_templates/abstract.py b/autointent/generation/utterances/evolution/chat_templates/abstract.py
new file mode 100644
index 00000000..4ab88c35
--- /dev/null
+++ b/autointent/generation/utterances/evolution/chat_templates/abstract.py
@@ -0,0 +1,45 @@
+"""Chat template for evolution augmentation via abstractization."""
+
+from typing import ClassVar
+
+from autointent.generation.utterances.schemas import Message, Role
+from autointent.schemas import Intent
+
+from .base import EvolutionChatTemplate
+
+
+class AbstractEvolution(EvolutionChatTemplate):
+    """Chat template for evolution augmentation via abstraction."""
+
+    _messages: ClassVar[list[Message]] = [
+        Message(
+            role=Role.USER,
+            content=(
+                "I want you to act as a rewriter. "
+                "You will be provided with an utterance and the topic (name of intent class) of the utterance. "
+                "You need to complicate the utterance using the following method:\n"
+                "1. Rewrite the utterance by removing specific inquiries or replacing with more generic.\n"
+                "2. Rewritten utterance should be concise and understandable by humans.\n"
+                "3. Rewritten utterance must be fully answerable.\n"
+                "4. Rewritten utterance should not contain more than 10 words.\n\n"
+                "Intent name: Reserve Restaurant"
+                "Utterance: I want to reserve a table for 4 persons at 9 pm."
+            ),
+        ),
+        Message(role=Role.ASSISTANT, content="Please, reserve a table for me."),
+        Message(
+            role=Role.ASSISTANT,
+            content=(
+                "Intent name: requesting technical support"
+                "Utterance: My Lenovo laptop is constantly rebooting and overheating."
+            ),
+        ),
+        Message(role=Role.ASSISTANT, content="I'm having trouble with my laptop."),
+    ]
+
+    def __call__(self, utterance: str, intent_data: Intent) -> list[Message]:
+        """Make chat to complete."""
+        return [
+            *self._messages,
+            Message(role=Role.USER, content=f"Intent name: {intent_data.name or ''}\nUtterance: {utterance}"),
+        ]
diff --git a/autointent/generation/utterances/evolution/chat_templates/abstract.yaml b/autointent/generation/utterances/evolution/chat_templates/abstract.yaml
deleted file mode 100644
index 37ddc558..00000000
--- a/autointent/generation/utterances/evolution/chat_templates/abstract.yaml
+++ /dev/null
@@ -1,33 +0,0 @@
-- role: user
-  content: |
-    {base_instruction}
-    1. Rewrite the utterance by removing specific inquiries or replacing with more generic.
-    2. Rewritten utterance should be concise and understandable by humans.
-    3. Rewritten utterance must be fully answerable.
-    4. Rewritten utterance should not contain more than 10 words.
-
-    Intent Class:
-    Reserve Restaurant
-
-    Utterance:
-    I want to reserve a table for 4 persons at 9 pm.
-- role: assistant
-  content: |
-    Please, reserve a table for be.
-- role: user
-  content: |
-    Intent Class:
-    requesting technical support
-
-    Utterance:
-    My Lenovo laptop is constantly rebooting and overheating.
-- role: assistant
-  content: |
-    I'm having trouble with my laptop.
-- role: user
-  content: |
-    Intent Class:
-    {intent_name}
-
-    Utterance:
-    {utterance}
diff --git a/autointent/generation/utterances/evolution/chat_templates/base.py b/autointent/generation/utterances/evolution/chat_templates/base.py
new file mode 100644
index 00000000..cb119d1b
--- /dev/null
+++ b/autointent/generation/utterances/evolution/chat_templates/base.py
@@ -0,0 +1,14 @@
+"""Base class for chat templates for evolution augmentation."""
+
+from abc import ABC, abstractmethod
+
+from autointent.generation.utterances.schemas import Message
+from autointent.schemas import Intent
+
+
+class EvolutionChatTemplate(ABC):
+    """Base class for chat templates for evolution augmentation."""
+
+    @abstractmethod
+    def __call__(self, utterance: str, intent_data: Intent) -> list[Message]:
+        """Make a chat to complete by LLM."""
diff --git a/autointent/generation/utterances/evolution/chat_templates/base_instruction.txt b/autointent/generation/utterances/evolution/chat_templates/base_instruction.txt
deleted file mode 100644
index e2b498a3..00000000
--- a/autointent/generation/utterances/evolution/chat_templates/base_instruction.txt
+++ /dev/null
@@ -1,3 +0,0 @@
-I want you to act as a rewriter.
-    You will be provided with an utterance and the topic (name of intent class) of the utterance.
-    You need to complicate the utterance using the following method:
diff --git a/autointent/generation/utterances/evolution/chat_templates/concrete.py b/autointent/generation/utterances/evolution/chat_templates/concrete.py
new file mode 100644
index 00000000..dcca78ba
--- /dev/null
+++ b/autointent/generation/utterances/evolution/chat_templates/concrete.py
@@ -0,0 +1,42 @@
+"""Chat template for evolution augmentation via concretizing."""
+
+from typing import ClassVar
+
+from autointent.generation.utterances.schemas import Message, Role
+from autointent.schemas import Intent
+
+from .base import EvolutionChatTemplate
+
+
+class ConcreteEvolution(EvolutionChatTemplate):
+    """Chat template for evolution augmentation via concretizing."""
+
+    _messages: ClassVar[list[Message]] = [
+        Message(
+            role=Role.USER,
+            content=(
+                "I want you to act as a rewriter. "
+                "You will be provided with an utterance and the topic (name of intent class) of the utterance. "
+                "You need to complicate the utterance using the following method:\n"
+                "1. Rewrite the utterance by removing specific inquiries or replacing with more generic.\n"
+                "2. Rewritten utterance should be concise and understandable by humans.\n"
+                "3. Rewritten utterance must be fully answerable.\n"
+                "4. Rewritten utterance should not contain more than 10 words.\n\n"
+                "Intent name: Reserve Restaurant\n"
+                "Utterance: I want to make a reservation for dinner tonight."
+            ),
+        ),
+        Message(role=Role.ASSISTANT, content="I want to reserve a table for 4 persons at 9 pm."),
+        Message(
+            role=Role.USER,
+            content=("Intent name: requesting technical support\n" "Utterance: I'm having trouble with my laptop."),
+        ),
+        Message(role=Role.ASSISTANT, content="My laptop is constantly rebooting and overheating."),
+    ]
+
+    def __call__(self, utterance: str, intent_data: Intent) -> list[Message]:
+        """Make chat to complete."""
+        return [
+            *self._messages,
+            Message(role=Role.USER, content=f"Intent name: {intent_data.name or ''}\nUtterance: {utterance}"),
+        ]
diff --git a/autointent/generation/utterances/evolution/chat_templates/concretizing.yaml b/autointent/generation/utterances/evolution/chat_templates/concretizing.yaml
deleted file mode 100644
index 67037448..00000000
--- a/autointent/generation/utterances/evolution/chat_templates/concretizing.yaml
+++ /dev/null
@@ -1,33 +0,0 @@
-- role: user
-  content: |
-    {base_instruction}
-    1. Rewrite the utterance by removing specific inquiries or replacing with more generic.
-    2. Rewritten utterance should be concise and understandable by humans.
-    3. Rewritten utterance must be fully answerable.
-    4. Rewritten utterance should not contain more than 10 words.
-
-    Intent Class:
-    Reserve Restaurant
-
-    Utterance:
-    I want to make a reservation for dinner tonight.
-- role: assistant
-  content: |
-    I want to reserve a table for 4 persons at 9 pm.
-- role: user
-  content: |
-    Intent Class:
-    requesting technical support
-
-    Utterance:
-    I'm having trouble with my laptop.
-- role: assistant
-  content: |
-    My laptop is constantly rebooting and overheating.
-- role: user
-  content: |
-    Intent Class:
-    {intent_name}
-
-    Utterance:
-    {utterance}
diff --git a/autointent/generation/utterances/evolution/chat_templates/reasoning.py b/autointent/generation/utterances/evolution/chat_templates/reasoning.py
new file mode 100644
index 00000000..39791acc
--- /dev/null
+++ b/autointent/generation/utterances/evolution/chat_templates/reasoning.py
@@ -0,0 +1,45 @@
+"""Chat template for evolution augmentation via reasoning."""
+
+from typing import ClassVar
+
+from autointent.generation.utterances.schemas import Message, Role
+from autointent.schemas import Intent
+
+from .base import EvolutionChatTemplate
+
+
+class ReasoningEvolution(EvolutionChatTemplate):
+    """Chat template for evolution augmentation via reasoning."""
+
+    _messages: ClassVar[list[Message]] = [
+        Message(
+            role=Role.USER,
+            content=(
+                "I want you to act as a rewriter. "
+                "You will be provided with an utterance and the topic (name of intent class) of the utterance. "
+                "You need to complicate the utterance using the following method:\n"
+                "1. Rewrite the utterance by removing specific inquiries or replacing with more generic.\n"
+                "2. Rewritten utterance should be concise and understandable by humans.\n"
+                "3. Rewritten utterance must be fully answerable.\n"
+                "4. Rewritten utterance should not contain more than 10 words.\n\n"
+                "Intent name: Asking for Directions\n"
+                "Utterance: How do I get to the nearest coffee shop?"
+            ),
+        ),
+        Message(role=Role.ASSISTANT, content="If there are some place where I can buy a coffee, how can I get there?"),
+        Message(
+            role=Role.USER,
+            content=(
+                "Intent name: requesting technical support\n"
+                "Utterance: I want to get help from technical support for my laptop."
+            ),
+        ),
+        Message(role=Role.ASSISTANT, content="I don't know what's happening with my laptop."),
+    ]
+
+    def __call__(self, utterance: str, intent_data: Intent) -> list[Message]:
+        """Make chat to complete."""
+        return [
+            *self._messages,
+            Message(role=Role.USER, content=f"Intent name: {intent_data.name or ''}\nUtterance: {utterance}"),
+        ]
diff --git a/autointent/generation/utterances/evolution/chat_templates/reasoning.yaml b/autointent/generation/utterances/evolution/chat_templates/reasoning.yaml
deleted file mode 100644
index 02c3eb88..00000000
--- a/autointent/generation/utterances/evolution/chat_templates/reasoning.yaml
+++ /dev/null
@@ -1,33 +0,0 @@
-- role: user
-  content: |
-    {base_instruction}
-    1. Rewrite the utterance by removing specific inquiries or replacing with more generic.
-    2. Rewritten utterance should be concise and understandable by humans.
-    3. Rewritten utterance must be fully answerable.
-    4. Rewritten utterance should not contain more than 10 words.
-
-    Intent Class:
-    Asking for Directions
-
-    Utterance:
-    How do I get to the nearest coffee shop?
-- role: assistant
-  content: |
-    If there are some place where I can buy a coffee, how can I get there?
-- role: user
-  content: |
-    Intent Class:
-    requesting technical support
-
-    Utterance:
-    I want to get help from technical support for my laptop.
-- role: assistant
-  content: |
-    I don't know what's happening with my laptop.
-- role: user
-  content: |
-    Intent Class:
-    {intent_name}
-
-    Utterance:
-    {utterance}
diff --git a/autointent/generation/utterances/evolution/cli.py b/autointent/generation/utterances/evolution/cli.py
index be04e11e..f05991ed 100644
--- a/autointent/generation/utterances/evolution/cli.py
+++ b/autointent/generation/utterances/evolution/cli.py
@@ -1,14 +1,16 @@
 """CLI for evolutionary augmenter."""
 
+import logging
 from argparse import ArgumentParser
-from typing import TYPE_CHECKING
 
 from autointent import load_dataset
 from autointent.generation.utterances.evolution.evolver import UtteranceEvolver
 from autointent.generation.utterances.generator import Generator
 
-if TYPE_CHECKING:
-    from .evolver import EvolutionType
+from .chat_templates import AbstractEvolution, ConcreteEvolution, EvolutionChatTemplate, ReasoningEvolution
+
+logging.basicConfig(level="INFO")
+logger = logging.getLogger(__name__)
 
 
 def main() -> None:
@@ -20,6 +22,7 @@ def main() -> None:
         required=True,
         help="Path to json or hugging face repo with dataset",
     )
+    parser.add_argument("--split", type=str, default="train")
     parser.add_argument(
         "--output-path",
         type=str,
@@ -37,33 +40,27 @@ def main() -> None:
     parser.add_argument("--reasoning", action="store_true", help="Whether to use `Reasoning` evolution")
     parser.add_argument("--concretizing", action="store_true", help="Whether to use `Concretizing` evolution")
     parser.add_argument("--abstract", action="store_true", help="Whether to use `Abstract` evolution")
-    parser.add_argument("--formal", action="store_true", help="Whether to use `Formal` evolution")
-    parser.add_argument("--informal", action="store_true", help="Whether to use `Informal` evolution")
-    parser.add_argument("--funny", action="store_true", help="Whether to use `Funny` evolution")
-    parser.add_argument("--goofy", action="store_true", help="Whether to use `Goofy` evolution")
     parser.add_argument("--seed", type=int, default=0)
     args = parser.parse_args()
 
-    evolutions: list[EvolutionType] = []
+    evolutions: list[EvolutionChatTemplate] = []
     if args.reasoning:
-        evolutions.append("reasoning")
+        evolutions.append(ReasoningEvolution())
     if args.concretizing:
-        evolutions.append("concretizing")
+        evolutions.append(ConcreteEvolution())
     if args.abstract:
-        evolutions.append("abstract")
-    if args.formal:
-        evolutions.append("formal")
-    if args.informal:
-        evolutions.append("informal")
-    if args.funny:
-        evolutions.append("funny")
-    if args.goofy:
-        evolutions.append("goofy")
+        evolutions.append(AbstractEvolution())
 
     dataset = load_dataset(args.input_path)
+    n_before = len(dataset[args.split])
 
     generator = UtteranceEvolver(Generator(), evolutions, args.seed)
-    generator.augment(dataset, n_evolutions=args.n_evolutions)
+    new_samples = generator.augment(dataset, split_name=args.split, n_evolutions=args.n_evolutions)
+    n_after = len(dataset[args.split])
+
+    logger.info("# samples before %s", n_before)
+    logger.info("# samples generated %s", len(new_samples))
+    logger.info("# samples after %s", n_after)
 
     dataset.to_json(args.output_path)
 
diff --git a/autointent/generation/utterances/evolution/evolver.py b/autointent/generation/utterances/evolution/evolver.py
index 690afd23..bdcf1069 100644
--- a/autointent/generation/utterances/evolution/evolver.py
+++ b/autointent/generation/utterances/evolution/evolver.py
@@ -4,21 +4,17 @@
 Deeply inspired by DeepEval evolutions.
 """
 
-import importlib.resources as ires
 import random
-from typing import Literal
+from collections.abc import Callable, Sequence
 
-import yaml
 from datasets import Dataset as HFDataset
 from datasets import concatenate_datasets
 
 from autointent import Dataset
 from autointent.custom_types import Split
 from autointent.generation.utterances.generator import Generator
-from autointent.generation.utterances.utils import safe_format  # type: ignore[attr-defined]
-from autointent.schemas import Sample
-
-EvolutionType = Literal["reasoning", "concretizing", "abstract", "formal", "informal", "funny", "goofy"]
+from autointent.generation.utterances.schemas import Message
+from autointent.schemas import Intent, Sample
 
 
 class UtteranceEvolver:
@@ -29,31 +25,23 @@ class UtteranceEvolver:
     to change it in a specific way.
     """
 
-    def __init__(self, generator: Generator, evolutions: list[EvolutionType], seed: int = 0) -> None:
+    def __init__(
+        self, generator: Generator, prompt_makers: Sequence[Callable[[str, Intent], list[Message]]], seed: int = 0
+    ) -> None:
         """Initialize."""
         self.generator = generator
-        self.evolutions = evolutions
-        self.prompts = _load_prompts()
+        self.prompt_makers = prompt_makers
         random.seed(seed)
 
-    def _evolve(self, utterance: str, intent_name: str, evolution: EvolutionType) -> str:
+    def _evolve(self, utterance: str, intent_data: Intent) -> str:
         """Apply evolutions single time."""
-        messages_yaml = safe_format(
-            self.prompts[evolution],
-            base_instruction=self.prompts["base_instruction"],
-            utterance=utterance,
-            intent_name=intent_name,
-        )
-        messages = yaml.safe_load(messages_yaml)
-        return self.generator.get_chat_completion(messages)
+        maker = random.choice(self.prompt_makers)
+        chat = maker(utterance, intent_data)
+        return self.generator.get_chat_completion(chat)
 
-    def __call__(self, utterance: str, intent_name: str, n_evolutions: int = 1) -> list[str]:
+    def __call__(self, utterance: str, intent_data: Intent, n_evolutions: int = 1) -> list[str]:
         """Apply evolutions mupltiple times."""
-        res = []
-        for _ in range(n_evolutions):
-            evolution = random.choice(self.evolutions)
-            res.append(self._evolve(utterance, intent_name, evolution))
-        return res
+        return [self._evolve(utterance, intent_data) for _ in range(n_evolutions)]
 
     def augment(
         self, dataset: Dataset, split_name: str = Split.TRAIN, n_evolutions: int = 1, update_split: bool = True
@@ -68,25 +56,12 @@ def augment(
         for sample in original_split:
             utterance = sample[Dataset.utterance_feature]
             label = sample[Dataset.label_feature]
-            intent_info = next(intent for intent in dataset.intents if intent.id == label)
-            generated_utterances = self(
-                utterance=utterance, intent_name=intent_info.name or "", n_evolutions=n_evolutions
-            )
+            intent_data = next(intent for intent in dataset.intents if intent.id == label)
+            generated_utterances = self(utterance=utterance, intent_data=intent_data, n_evolutions=n_evolutions)
             new_samples.extend(
-                [{Dataset.label_feature: intent_info.id, Dataset.utterance_feature: ut} for ut in generated_utterances]
+                [{Dataset.label_feature: intent_data.id, Dataset.utterance_feature: ut} for ut in generated_utterances]
             )
         if update_split:
             generated_split = HFDataset.from_list(new_samples)
             dataset[split_name] = concatenate_datasets([original_split, generated_split])
         return [Sample(**sample) for sample in new_samples]
-
-
-def _load_prompts() -> dict[str, str]:
-    files = ires.files("autointent.generation.utterances.evolution.chat_templates")
-
-    res = {}
-    for file_name in ["reasoning.yaml", "concretizing.yaml", "abstract.yaml", "base_instruction.txt"]:
-        with files.joinpath(file_name).open() as file:
-            res[file_name.split(".")[0]] = file.read()
-
-    return res
diff --git a/autointent/generation/utterances/generator.py b/autointent/generation/utterances/generator.py
index 69672278..dfc9ec86 100644
--- a/autointent/generation/utterances/generator.py
+++ b/autointent/generation/utterances/generator.py
@@ -5,6 +5,8 @@
 import openai
 from dotenv import load_dotenv
 
+from .schemas import Message
+
 
 class Generator:
     """Wrapper class for accessing OpenAI API."""
@@ -15,7 +17,7 @@ def __init__(self) -> None:
         self.client = openai.OpenAI(base_url=os.environ["OPENAI_BASE_URL"], api_key=os.environ["OPENAI_API_KEY"])
         self.model_name = os.environ["OPENAI_MODEL_NAME"]
 
-    def get_chat_completion(self, messages: list[dict[str, str]]) -> str:
+    def get_chat_completion(self, messages: list[Message]) -> str:
         """Prompt LLM and return its answer."""
         response = self.client.chat.completions.create(
             messages=messages,  # type: ignore[arg-type]
diff --git a/autointent/generation/utterances/schemas.py b/autointent/generation/utterances/schemas.py
new file mode 100644
index 00000000..e296f6cd
--- /dev/null
+++ b/autointent/generation/utterances/schemas.py
@@ -0,0 +1,18 @@
+"""Schemas that are useful for working with prompts."""
+
+from typing import TypedDict
+
+
+class Message(TypedDict):
+    """Schema for message to LLM."""
+
+    role: str
+    content: str
+
+
+class Role:
+    """Roles in a chat with LLM."""
+
+    SYSTEM = "system"
+    USER = "user"
+    ASSISTANT = "assistant"
diff --git a/autointent/generation/utterances/utils.py b/autointent/generation/utterances/utils.py
deleted file mode 100644
index 7742ea1f..00000000
--- a/autointent/generation/utterances/utils.py
+++ /dev/null
@@ -1,27 +0,0 @@
-# type: ignore  # noqa: PGH003
-
-import string
-from typing import Any
-
-
-class SafeFormatter(string.Formatter):
-    """Utility class for loading prompt templates."""
-
-    def get_value(self, key, args, kwargs) -> Any:  # noqa: ANN001, ANN401
-        """Overloaded."""
-        if isinstance(key, str):
-            return kwargs.get(key, "{" + key + "}")
-        return super().get_value(key, args, kwargs)
-
-    def parse(self, format_string):  # noqa: ANN001, ANN201
-        """Overloaded."""
-        try:
-            return super().parse(format_string)
-        except ValueError:
-            return [(format_string, None, None, None)]
-
-
-def safe_format(format_string: str, *args: tuple[str], **kwargs: dict[str, str]) -> str:
-    """Format chat template."""
-    formatter = SafeFormatter()
-    return formatter.format(format_string, *args, **kwargs)
diff --git a/autointent/modules/scoring/_knn/knn.py b/autointent/modules/scoring/_knn/knn.py
index 6de4d162..cda70bd9 100644
--- a/autointent/modules/scoring/_knn/knn.py
+++ b/autointent/modules/scoring/_knn/knn.py
@@ -43,7 +43,7 @@ class KNNScorer(ScoringModule):
     .. testoutput::
 
         [[0.67297815 0.32702185]
-         [0.44031678 0.55968322]]
+         [0.44031667 0.55968333]]
 
     """
 
diff --git a/tests/generation/test_basic_synthesizer.py b/tests/generation/test_basic_synthesizer.py
new file mode 100644
index 00000000..674b3535
--- /dev/null
+++ b/tests/generation/test_basic_synthesizer.py
@@ -0,0 +1,52 @@
+from unittest.mock import Mock
+
+from autointent.generation.utterances import SynthesizerChatTemplate, UtteranceGenerator
+
+
+def has_unfilled_fields(template):
+    try:
+        # Attempt to format the string with empty values
+        template.format(**{})  # noqa: PIE804
+        return False  # No unfilled fields  # noqa: TRY300
+    except KeyError:
+        return True  # Unfilled fields detected
+
+
+def test_default_chat_template(dataset):
+    template = SynthesizerChatTemplate(dataset, split="train_0")
+    prompt = template(dataset.intents[0], n_examples=1)
+    for msg in prompt:
+        assert not has_unfilled_fields(msg["content"])
+    assert "extra_instructions" not in prompt
+
+
+def test_extra_instructions(dataset):
+    template = SynthesizerChatTemplate(dataset, split="train_0", extra_instructions="football")
+    prompt = template(dataset.intents[0], n_examples=1)[0]["content"]
+    assert "extra_instructions" not in prompt
+    assert "football" in prompt
+
+
+def test_on_dataset(dataset):
+    mock_llm = Mock()
+    mock_llm.get_chat_completion.return_value = "1. LLM answer"
+
+    split_name = "train_0"
+
+    template = SynthesizerChatTemplate(dataset, split=split_name)
+    augmenter = UtteranceGenerator(mock_llm, template)
+
+    n_before = len(dataset[split_name])
+    new_samples = augmenter.augment(dataset, split_name=split_name, update_split=False)
+    n_after = len(dataset[split_name])
+
+    assert n_before == n_after
+    assert len(new_samples) == len(dataset.intents)
+    assert all(sample.utterance == "LLM answer" for sample in new_samples)
+
+    n_before = len(dataset[split_name])
+    new_samples = augmenter.augment(dataset, split_name=split_name, update_split=True)
+    n_after = len(dataset[split_name])
+
+    assert n_before + len(new_samples) == n_after
+    assert len(new_samples) == len(dataset.intents)
diff --git a/tests/generation/test_evolver.py b/tests/generation/test_evolver.py
new file mode 100644
index 00000000..c95c9def
--- /dev/null
+++ b/tests/generation/test_evolver.py
@@ -0,0 +1,34 @@
+from unittest.mock import Mock
+
+from autointent.generation.utterances import AbstractEvolution, UtteranceEvolver
+
+
+def test_default_chat_template(dataset):
+    template = AbstractEvolution()
+    prompt = template("some utterance", dataset.intents[0])
+    assert "some utterance" in prompt[-1]["content"]
+
+
+def test_on_dataset(dataset):
+    mock_llm = Mock()
+    mock_llm.get_chat_completion.return_value = "LLM answer"
+
+    split_name = "train_0"
+
+    template = AbstractEvolution()
+    augmenter = UtteranceEvolver(mock_llm, [template])
+
+    n_before = len(dataset[split_name])
+    new_samples = augmenter.augment(dataset, split_name=split_name, n_evolutions=1, update_split=False)
+    n_after = len(dataset[split_name])
+
+    assert n_before == n_after
+    assert len(new_samples) == n_before
+    assert all(sample.utterance == "LLM answer" for sample in new_samples)
+
+    n_before = len(dataset[split_name])
+    new_samples = augmenter.augment(dataset, split_name=split_name, n_evolutions=1, update_split=True)
+    n_after = len(dataset[split_name])
+
+    assert n_before + len(new_samples) == n_after
+    assert len(new_samples) == n_before