From 2a73121fcf848b1dff8d335f7896f8aebb61b1dd Mon Sep 17 00:00:00 2001
From: Ivan Ogasawara <ivan.ogasawara@gmail.com>
Date: Wed, 30 Oct 2024 23:52:53 -0400
Subject: [PATCH] refactor: Refactor bases classes for generation and retrieval
 (#15)

---
 .env.tpl                                      |    3 -
 poetry.lock                                   | 1105 ++++++++---------
 pyproject.toml                                |    2 +-
 src/rago/augmented/__init__.py                |    4 +-
 src/rago/augmented/base.py                    |   58 +-
 .../augmented/{gemini_aug.py => gemini.py}    |   27 +-
 src/rago/augmented/hugging_face.py            |   34 +-
 src/rago/augmented/openai.py                  |   48 +
 src/rago/augmented/openai_aug.py              |   35 -
 src/rago/generation/__init__.py               |    8 +-
 src/rago/generation/base.py                   |   38 +-
 src/rago/generation/gemini.py                 |   32 +
 src/rago/generation/gemini_ai.py              |   48 -
 src/rago/generation/hugging_face.py           |   38 +-
 src/rago/generation/llama.py                  |    6 +-
 .../generation/{openai_gpt.py => openai.py}   |   33 +-
 tests/.env.tpl                                |    3 +
 ...st_gemini_generation.py => test_gemini.py} |   18 +-
 tests/test_hugging_face.py                    |    2 +-
 tests/test_llama.py                           |    2 +-
 tests/{test_openai_gpt.py => test_openai.py}  |   18 +-
 21 files changed, 745 insertions(+), 817 deletions(-)
 delete mode 100644 .env.tpl
 rename src/rago/augmented/{gemini_aug.py => gemini.py} (57%)
 create mode 100644 src/rago/augmented/openai.py
 delete mode 100644 src/rago/augmented/openai_aug.py
 create mode 100644 src/rago/generation/gemini.py
 delete mode 100644 src/rago/generation/gemini_ai.py
 rename src/rago/generation/{openai_gpt.py => openai.py} (50%)
 rename tests/{test_gemini_generation.py => test_gemini.py} (78%)
 rename tests/{test_openai_gpt.py => test_openai.py} (70%)

diff --git a/.env.tpl b/.env.tpl
deleted file mode 100644
index 0ec5aa8..0000000
--- a/.env.tpl
+++ /dev/null
@@ -1,3 +0,0 @@
-HF_TOKEN=${HF_TOKEN}
-OPENAI_API_KEY=${OPENAI_API_KEY}
-GEMINI_API_KEY=${GEMINI_API_KEY}
diff --git a/poetry.lock b/poetry.lock
index 1453f0d..97656c6 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,152 +1,37 @@
 # This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
-name = "aiohappyeyeballs"
-version = "2.4.3"
-description = "Happy Eyeballs for asyncio"
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
 [[package]]
-name = "aiohttp"
-version = "3.10.10"
-description = "Async http client/server framework (asyncio)"
+name = "anyio"
+version = "4.6.2.post1"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
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 [package.extras]
-speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
-
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+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "appnope"
@@ -159,17 +44,6 @@ files = [
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@@ -261,21 +135,20 @@ lxml = ["lxml"]
 
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+version = "6.2.0"
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-python-versions = ">=3.8"
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 [package.extras]
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+css = ["tinycss2 (>=1.1.0,<1.5)"]
 
 [[package]]
 name = "cachetools"
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+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
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 grpcio = ">=1.67.1"
 protobuf = ">=5.26.1,<6.0dev"
 
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+python-versions = ">=3.7"
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+
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+optional = false
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+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<1.0)"]
+
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 version = "0.22.0"
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+
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+zstd = ["zstandard (>=0.18.0)"]
+
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 version = "0.26.2"
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 [package.extras]
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-
 [[package]]
 name = "proto-plus"
 version = "1.25.0"
@@ -3092,13 +2960,13 @@ windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "pymdown-extensions"
-version = "10.11.2"
+version = "10.12"
 description = "Extension pack for Python Markdown."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3146,17 +3014,17 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments
 
 [[package]]
 name = "pytest-cov"
-version = "5.0.0"
+version = "6.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
-coverage = {version = ">=5.2.1", extras = ["toml"]}
+coverage = {version = ">=7.5", extras = ["toml"]}
 pytest = ">=4.6"
 
 [package.extras]
@@ -4154,23 +4022,23 @@ files = [
 
 [[package]]
 name = "setuptools"
-version = "75.2.0"
+version = "75.3.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
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 python-versions = ">=3.8"
 files = [
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 [package.extras]
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+core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.collections", "jaraco.functools", "jaraco.text (>=3.7)", "more-itertools", "more-itertools (>=8.8)", "packaging", "packaging (>=24)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
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+test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test (>=5.5)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
+type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.12.*)", "pytest-mypy"]
 
 [[package]]
 name = "sh"
@@ -4205,6 +4073,17 @@ files = [
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 ]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
 [[package]]
 name = "soupsieve"
 version = "2.6"
@@ -4420,20 +4299,72 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.5.0+cpu"
+version = "2.5.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.8.0"
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+
+[[package]]
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+optional = false
+python-versions = ">=3.8.0"
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 ]
 
 [package.dependencies]
@@ -4456,25 +4387,59 @@ reference = "pytorch-cpu"
 
 [[package]]
 name = "torchvision"
-version = "0.20.0+cpu"
+version = "0.20.1"
+description = "image and video datasets and models for torch deep learning"
+optional = true
+python-versions = ">=3.8"
+files = [
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-    {file = "yarl-1.17.0-cp39-cp39-win_amd64.whl", hash = "sha256:6af417ca2c7349b101d3fd557ad96b4cd439fdb6ab0d288e3f64a068eea394d0"},
-    {file = "yarl-1.17.0-py3-none-any.whl", hash = "sha256:62dd42bb0e49423f4dd58836a04fcf09c80237836796025211bbe913f1524993"},
-    {file = "yarl-1.17.0.tar.gz", hash = "sha256:d3f13583f378930377e02002b4085a3d025b00402d5a80911726d43a67911cd9"},
-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-propcache = ">=0.2.0"
-
 [[package]]
 name = "zipp"
 version = "3.20.2"
@@ -4933,4 +4824,4 @@ gpu = ["torch", "torch", "torchvision", "torchvision"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4"
-content-hash = "5ff4a9941080c9d4d0f50f4d6c3a042df0d0286b454c23edd7fa2195eea74d1d"
+content-hash = "e4581087b3eb741d099039752ad011dc93691796aba185d9bc16853d2fde171a"
diff --git a/pyproject.toml b/pyproject.toml
index 1da4eed..288814b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,7 +36,7 @@ torchvision = [
   {version = ">=0.20.0", markers="extra=='gpu' and extra!='cpu'"},
 ]
 langdetect = ">=1"
-openai = "0.28"
+openai = "^1.52.2"
 google-generativeai = "^0.8.3"
 
 [tool.poetry.extras]
diff --git a/src/rago/augmented/__init__.py b/src/rago/augmented/__init__.py
index ed7d0d8..1ca79d7 100644
--- a/src/rago/augmented/__init__.py
+++ b/src/rago/augmented/__init__.py
@@ -3,9 +3,9 @@
 from __future__ import annotations
 
 from rago.augmented.base import AugmentedBase
-from rago.augmented.gemini_aug import GeminiAug
+from rago.augmented.gemini import GeminiAug
 from rago.augmented.hugging_face import HuggingFaceAug
-from rago.augmented.openai_aug import OpenAIAug
+from rago.augmented.openai import OpenAIAug
 
 __all__ = [
     'AugmentedBase',
diff --git a/src/rago/augmented/base.py b/src/rago/augmented/base.py
index 7947cb0..587700c 100644
--- a/src/rago/augmented/base.py
+++ b/src/rago/augmented/base.py
@@ -14,29 +14,73 @@
 class AugmentedBase:
     """Define the base structure for Augmented classes."""
 
+    api_key: str = ''
     model: Optional[Any]
+    model_name: str = ''
     db: Any
-    k: int = -1
-    documents: list[str]
+    k: int = 0
+    temperature: float = 0.5
+    prompt_template: str = ''
+    result_separator = '\n'
+    output_max_length: int = 500
+
+    # default values to be overwritten by the derived classes
+    default_model_name: str = ''
+    default_k: int = 0
+    default_temperature: float = 0.5
+    default_prompt_template: str = (
+        'Retrieve {k} entries from the context that better answer the '
+        'following query:\n```\n{query}\n```\n\ncontext:\n```\n{context}\n```'
+    )
+    default_result_separator = '\n'
+    default_output_max_length: int = 500
 
     @abstractmethod
     def __init__(
         self,
-        documents: list[str] = [],
+        model_name: str = '',
+        api_key: str = '',
         db: DBBase = FaissDB(),
-        k: int = -1,
+        k: int = 0,
+        temperature: float = 0.5,
+        prompt_template: str = '',
+        result_separator: str = '\n',
+        output_max_length: int = 500,
     ) -> None:
         """Initialize AugmentedBase."""
-        self.k = k
-        self.documents = documents
         self.db = db
+        self.api_key = api_key
+
+        self.k = k or self.default_k
+        self.model_name = model_name or self.default_model_name
+        self.temperature = temperature or self.default_temperature
+        self.result_separator = (
+            result_separator or self.default_result_separator
+        )
+        self.prompt_template = prompt_template or self.default_prompt_template
+        self.output_max_length = (
+            output_max_length or self.default_output_max_length
+        )
+
+        self.model = None
+
+        self._validate()
+        self._setup()
+
+    def _validate(self) -> None:
+        """Raise an error if the initial parameters are not valid."""
+        return
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        return
 
     @abstractmethod
     def search(
         self,
         query: str,
         documents: Any,
-        k: int = -1,
+        k: int = 0,
     ) -> list[str]:
         """Search an encoded query into vector database."""
         ...
diff --git a/src/rago/augmented/gemini_aug.py b/src/rago/augmented/gemini.py
similarity index 57%
rename from src/rago/augmented/gemini_aug.py
rename to src/rago/augmented/gemini.py
index cc51c77..bdba0b6 100644
--- a/src/rago/augmented/gemini_aug.py
+++ b/src/rago/augmented/gemini.py
@@ -13,30 +13,29 @@
 class GeminiAug(AugmentedBase):
     """GeminiAug class for query augmentation using Gemini API."""
 
-    def __init__(
-        self,
-        model_name: str = 'gemini-1.5-flash',
-        k: int = 1,
-        api_key: str = '',
-    ) -> None:
-        """Initialize the GeminiAug class."""
-        self.model_name = model_name
-        self.k = k
-        genai.configure(api_key=api_key)
+    default_model_name: str = 'gemini-1.5-flash'
+    default_k: int = 1
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        genai.configure(api_key=self.api_key)
 
     def search(
-        self, query: str, documents: list[str], k: int = 1
+        self, query: str, documents: list[str], k: int = 0
     ) -> list[str]:
         """Augment the query by expanding or rephrasing it using Gemini."""
-        prompt = f"Retrieval: '{query}'\nContext: {' '.join(documents)}"
+        k = k or self.k
+        prompt = self.prompt_template.format(
+            query=query, context=' '.join(documents), k=k
+        )
 
         response = genai.GenerativeModel(self.model_name).generate_content(
             prompt
         )
 
-        augmented_query = (
+        augmented_query = str(
             response.text.strip()
             if hasattr(response, 'text')
             else response[0].text.strip()
         )
-        return [augmented_query] * self.k
+        return augmented_query.split(self.result_separator)[:k]
diff --git a/src/rago/augmented/hugging_face.py b/src/rago/augmented/hugging_face.py
index 1a3ace6..6b4f1b6 100644
--- a/src/rago/augmented/hugging_face.py
+++ b/src/rago/augmented/hugging_face.py
@@ -8,36 +8,24 @@
 from typeguard import typechecked
 
 from rago.augmented.base import AugmentedBase
-from rago.db import DBBase, FaissDB
 
 
 @typechecked
 class HuggingFaceAug(AugmentedBase):
     """Class for augmentation with Hugging Face."""
 
-    model: Any
-    k: int = -1
-    db: DBBase
-
-    def __init__(
-        self,
-        name: str = 'paraphrase',
-        db: DBBase = FaissDB(),
-        k: int = -1,
-    ) -> None:
-        """Initialize HuggingFaceAug."""
-        if name == 'paraphrase':
-            self.model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
-        else:
-            raise Exception(
-                'The Augmented class name {name} is not supported.'
-            )
-
-        self.db = db
-        self.k = k
-
-    def search(self, query: str, documents: Any, k: int = -1) -> list[str]:
+    default_model_name = 'paraphrase-MiniLM-L6-v2'
+    default_k = 2
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        self.model = SentenceTransformer(self.model_name)
+
+    def search(self, query: str, documents: Any, k: int = 0) -> list[str]:
         """Search an encoded query into vector database."""
+        if not self.model:
+            raise Exception('The model was not created.')
+
         document_encoded = self.model.encode(documents)
         query_encoded = self.model.encode([query])
         k = k if k > 0 else self.k
diff --git a/src/rago/augmented/openai.py b/src/rago/augmented/openai.py
new file mode 100644
index 0000000..f3d1805
--- /dev/null
+++ b/src/rago/augmented/openai.py
@@ -0,0 +1,48 @@
+"""OpenAIAug class for query augmentation using OpenAI API."""
+
+from __future__ import annotations
+
+from typing import cast
+
+import openai
+
+from typeguard import typechecked
+
+from rago.augmented.base import AugmentedBase
+
+
+@typechecked
+class OpenAIAug(AugmentedBase):
+    """OpenAIAug class for query augmentation using OpenAI API."""
+
+    default_model_name = 'gpt-3.5-turbo'
+    default_k = 2
+    default_result_separator = '\n'
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        self.model = openai.OpenAI(api_key=self.api_key)
+
+    def search(
+        self, query: str, documents: list[str], k: int = 0
+    ) -> list[str]:
+        """Augment the query by expanding or rephrasing it using OpenAI."""
+        k = k or self.k
+        prompt = self.prompt_template.format(
+            query=query, context=' '.join(documents), k=k
+        )
+
+        if not self.model:
+            raise Exception('The model was not created.')
+
+        response = self.model.chat.completions.create(
+            model=self.model_name,
+            messages=[{'role': 'user', 'content': prompt}],
+            max_tokens=self.output_max_length,
+            temperature=self.temperature,
+        )
+
+        augmented_query = cast(
+            str, response.choices[0].message.content.strip()
+        )
+        return augmented_query.split(self.result_separator)[:k]
diff --git a/src/rago/augmented/openai_aug.py b/src/rago/augmented/openai_aug.py
deleted file mode 100644
index b0646a2..0000000
--- a/src/rago/augmented/openai_aug.py
+++ /dev/null
@@ -1,35 +0,0 @@
-"""OpenAIAug class for query augmentation using OpenAI API."""
-
-from __future__ import annotations
-
-import openai
-
-from typeguard import typechecked
-
-from rago.augmented.base import AugmentedBase
-
-
-@typechecked
-class OpenAIAug(AugmentedBase):
-    """OpenAIAug class for query augmentation using OpenAI API."""
-
-    def __init__(self, model_name: str = 'gpt-4', k: int = 1) -> None:
-        """Initialize the OpenAIAug class."""
-        self.model_name = model_name
-        self.k = k
-
-    def search(
-        self, query: str, documents: list[str], k: int = 1
-    ) -> list[str]:
-        """Augment the query by expanding or rephrasing it using OpenAI."""
-        prompt = f"Retrieval: '{query}'\nContext: {' '.join(documents)}"
-
-        response = openai.Completion.create(  # type: ignore[no-untyped-call]
-            model=self.model_name,
-            messages=[{'role': 'user', 'content': prompt}],
-            max_tokens=50,
-            temperature=0.5,
-        )
-
-        augmented_query = response.choices[0]['message']['content'].strip()
-        return [augmented_query] * self.k
diff --git a/src/rago/generation/__init__.py b/src/rago/generation/__init__.py
index 148e53e..d30e649 100644
--- a/src/rago/generation/__init__.py
+++ b/src/rago/generation/__init__.py
@@ -3,15 +3,15 @@
 from __future__ import annotations
 
 from rago.generation.base import GenerationBase
-from rago.generation.gemini_ai import GeminiAIGen
+from rago.generation.gemini import GeminiGen
 from rago.generation.hugging_face import HuggingFaceGen
 from rago.generation.llama import LlamaGen
-from rago.generation.openai_gpt import OpenAIGPTGen
+from rago.generation.openai import OpenAIGen
 
 __all__ = [
     'GenerationBase',
     'HuggingFaceGen',
     'LlamaGen',
-    'OpenAIGPTGen',
-    'GeminiAIGen',
+    'OpenAIGen',
+    'GeminiGen',
 ]
diff --git a/src/rago/generation/base.py b/src/rago/generation/base.py
index f49d0ae..44543d7 100644
--- a/src/rago/generation/base.py
+++ b/src/rago/generation/base.py
@@ -18,9 +18,22 @@ class GenerationBase:
     device_name: str = 'cpu'
     device: torch.device
     model: Any
+    model_name: str = ''
     tokenizer: Any
     temperature: float = 0.5
     output_max_length: int = 500
+    prompt_template: str = (
+        'question: \n```\n{query}\n```\ncontext: ```\n{context}\n```'
+    )
+
+    # default parameters that can be overwritten by the derived class
+    default_device_name: str = 'cpu'
+    default_model_name: str = ''
+    default_temperature: float = 0.5
+    default_output_max_length: int = 500
+    default_prompt_template: str = (
+        'question: \n```\n{query}\n```\ncontext: ```\n{context}\n```'
+    )
 
     @abstractmethod
     def __init__(
@@ -28,10 +41,11 @@ def __init__(
         model_name: str = '',
         api_key: str = '',
         temperature: float = 0.5,
+        prompt_template: str = '',
         output_max_length: int = 500,
         device: str = 'auto',
     ) -> None:
-        """Initialize GenerationBase.
+        """Initialize Generation class.
 
         Parameters
         ----------
@@ -39,14 +53,19 @@ def __init__(
             The name of the model to use.
         api_key : str
         temperature : float
+        prompt_template: str
         output_max_length : int
             Maximum length of the generated output.
         device: str (default=auto)
         """
         self.api_key = api_key
-        self.model_name = model_name
-        self.output_max_length = output_max_length
-        self.temperature = temperature
+        self.model_name = model_name or self.default_model_name
+        self.output_max_length = (
+            output_max_length or self.default_output_max_length
+        )
+        self.temperature = temperature or self.default_temperature
+
+        self.prompt_template = prompt_template or self.default_prompt_template
 
         if self.device_name not in ['cpu', 'cuda', 'auto']:
             raise Exception(
@@ -60,6 +79,17 @@ def __init__(
         )
         self.device = torch.device(self.device_name)
 
+        self._validate()
+        self._setup()
+
+    def _validate(self) -> None:
+        """Raise an error if the initial parameters are not valid."""
+        return
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        return
+
     @abstractmethod
     def generate(
         self,
diff --git a/src/rago/generation/gemini.py b/src/rago/generation/gemini.py
new file mode 100644
index 0000000..1607a35
--- /dev/null
+++ b/src/rago/generation/gemini.py
@@ -0,0 +1,32 @@
+"""GeminiGen class for text generation using Google's Gemini model."""
+
+from __future__ import annotations
+
+from typing import cast
+
+import google.generativeai as genai
+
+from typeguard import typechecked
+
+from rago.generation.base import GenerationBase
+
+
+@typechecked
+class GeminiGen(GenerationBase):
+    """Gemini generation model for text generation."""
+
+    default_model_name: str = 'gemini-1.5-flash'
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        genai.configure(api_key=self.api_key)
+        self.model = genai.GenerativeModel(self.model_name)
+
+    def generate(self, query: str, context: list[str]) -> str:
+        """Generate text using Gemini model support."""
+        input_text = self.prompt_template.format(
+            query=query, context=' '.join(context)
+        )
+
+        response = self.model.generate_content(input_text)
+        return cast(str, response.text.strip())
diff --git a/src/rago/generation/gemini_ai.py b/src/rago/generation/gemini_ai.py
deleted file mode 100644
index 4874b14..0000000
--- a/src/rago/generation/gemini_ai.py
+++ /dev/null
@@ -1,48 +0,0 @@
-"""GeminiAIGen class for text generation using Google's Gemini model."""
-
-from __future__ import annotations
-
-from typing import cast
-
-import google.generativeai as genai
-
-from typeguard import typechecked
-
-from rago.generation.base import GenerationBase
-
-
-@typechecked
-class GeminiAIGen(GenerationBase):
-    """Gemini generation model for text generation."""
-
-    def __init__(
-        self,
-        model_name: str = 'gemini-1.5-flash',
-        output_max_length: int = 500,
-        api_key: str = '',
-    ) -> None:
-        """Initialize GeminiAIGen class with Google's Gemini model."""
-        super().__init__(
-            model_name=model_name, output_max_length=output_max_length
-        )
-        genai.configure(api_key=api_key)
-        self.model = genai.GenerativeModel(model_name)
-
-    def generate(
-        self, query: str, context: list[str], language: str = 'en'
-    ) -> str:
-        """
-        Generate text using Google's Generative AI with Gemini model support.
-
-        Returns
-        -------
-        str
-            The generated response.
-        """
-        input_text = (
-            f"Question: {query}\nContext: {' '.join(context)}\n"
-            f"Answer in {language}:"
-        )
-
-        response = self.model.generate_content(input_text)  # Simplified call
-        return cast(str, response['text'].strip())
diff --git a/src/rago/generation/hugging_face.py b/src/rago/generation/hugging_face.py
index 8ba6548..1517610 100644
--- a/src/rago/generation/hugging_face.py
+++ b/src/rago/generation/hugging_face.py
@@ -14,38 +14,28 @@
 class HuggingFaceGen(GenerationBase):
     """HuggingFaceGen."""
 
-    def __init__(
-        self,
-        model_name: str = 't5-small',
-        api_key: str = '',
-        temperature: float = 0.5,
-        output_max_length: int = 500,
-        device: str = 'auto',
-    ) -> None:
-        """Initialize HuggingFaceGen."""
-        if model_name != 't5-small':
-            raise Exception(f'The given model {model_name} is not supported.')
+    default_model_name = 't5-small'
 
-        super().__init__(
-            model_name=model_name,
-            api_key=api_key,
-            temperature=temperature,
-            output_max_length=output_max_length,
-            device=device,
-        )
-
-        self._set_t5_small_models()
+    def _validate(self) -> None:
+        if self.model_name != 't5-small':
+            raise Exception(
+                f'The given model {self.model_name} is not supported.'
+            )
 
-    def _set_t5_small_models(self) -> None:
+    def _setup(self) -> None:
         """Set models to t5-small models."""
-        self.tokenizer = T5Tokenizer.from_pretrained('t5-small')
-        self.model = T5ForConditionalGeneration.from_pretrained('t5-small')
+        self.tokenizer = T5Tokenizer.from_pretrained(self.model_name)
+        self.model = T5ForConditionalGeneration.from_pretrained(
+            self.model_name
+        )
         self.model = self.model.to(self.device)
 
     def generate(self, query: str, context: list[str]) -> str:
         """Generate the text from the query and augmented context."""
         with torch.no_grad():
-            input_text = f"Question: {query} Context: {' '.join(context)}"
+            input_text = self.prompt_template.format(
+                query=query, context=' '.join(context)
+            )
             input_ids = self.tokenizer.encode(
                 input_text,
                 return_tensors='pt',
diff --git a/src/rago/generation/llama.py b/src/rago/generation/llama.py
index 5376141..3ec1595 100644
--- a/src/rago/generation/llama.py
+++ b/src/rago/generation/llama.py
@@ -58,10 +58,8 @@ def __init__(
 
     def generate(self, query: str, context: list[str]) -> str:
         """Generate text using Llama model with language support."""
-        # Craft the input prompt with a clear instruction for the model
-        input_text = (
-            f"Answer the following question briefly and directly.\n"
-            f"Question: {query}\nContext: {' '.join(context)}\nAnswer:"
+        input_text = self.prompt_template.format(
+            query=query, context=' '.join(context)
         )
 
         # Detect and set the language code for multilingual models (optional)
diff --git a/src/rago/generation/openai_gpt.py b/src/rago/generation/openai.py
similarity index 50%
rename from src/rago/generation/openai_gpt.py
rename to src/rago/generation/openai.py
index ddbedfa..45e7872 100644
--- a/src/rago/generation/openai_gpt.py
+++ b/src/rago/generation/openai.py
@@ -12,41 +12,36 @@
 
 
 @typechecked
-class OpenAIGPTGen(GenerationBase):
+class OpenAIGen(GenerationBase):
     """OpenAI generation model for text generation."""
 
-    def __init__(
-        self,
-        model_name: str = 'gpt-4',
-        output_max_tokens: int = 500,
-        api_key: str = '',
-    ) -> None:
-        """Initialize OpenAIGenerationModel with OpenAI's model."""
-        super().__init__(
-            model_name=model_name, output_max_length=output_max_tokens
-        )
-        openai.api_key = api_key
+    default_model_name = 'gpt-3.5-turbo'
+
+    def _setup(self) -> None:
+        """Set up the object with the initial parameters."""
+        self.model = openai.OpenAI(api_key=self.api_key)
 
     def generate(
         self,
         query: str,
         context: list[str],
-        language: str = 'en',
     ) -> str:
         """Generate text using OpenAI's API with dynamic model support."""
-        input_text = (
-            f"Question: {query}\nContext: {' '.join(context)}\n"
-            f"Answer in {language}:"
+        input_text = self.prompt_template.format(
+            query=query, context=' '.join(context)
         )
 
-        response = openai.Completion.create(  # type: ignore[no-untyped-call]
+        if not self.model:
+            raise Exception('The model was not created.')
+
+        response = self.model.chat.completions.create(
             model=self.model_name,
             messages=[{'role': 'user', 'content': input_text}],
             max_tokens=self.output_max_length,
-            temperature=0.7,
+            temperature=self.temperature,
             top_p=0.9,
             frequency_penalty=0.5,
             presence_penalty=0.3,
         )
 
-        return cast(str, response['choices'][0]['message']['content'].strip())
+        return cast(str, response.choices[0].message.content.strip())
diff --git a/tests/.env.tpl b/tests/.env.tpl
index 3a7e935..689c851 100644
--- a/tests/.env.tpl
+++ b/tests/.env.tpl
@@ -1 +1,4 @@
 HF_TOKEN=${HF_TOKEN}
+OPENAI_API_KEY=${OPENAI_API_KEY}
+GEMINI_API_KEY=${GEMINI_API_KEY}
+TOKENIZERS_PARALLELISM=false
diff --git a/tests/test_gemini_generation.py b/tests/test_gemini.py
similarity index 78%
rename from tests/test_gemini_generation.py
rename to tests/test_gemini.py
index 6a556ac..34561f3 100644
--- a/tests/test_gemini_generation.py
+++ b/tests/test_gemini.py
@@ -1,12 +1,14 @@
 """Tests for Rago package using Google's Gemini Model."""
 
+import os
+
 from pathlib import Path
 
 import pytest
 
 from rago import Rago
 from rago.augmented import GeminiAug
-from rago.generation.gemini_ai import GeminiAIGen
+from rago.generation import GeminiGen
 from rago.retrieval import StringRet
 
 
@@ -20,9 +22,9 @@ def animals_data() -> list[str]:
 
 
 @pytest.fixture
-def gemini_api_key() -> str:
+def api_key(env) -> str:
     """Fixture for Gemini API key from environment."""
-    api_key = 'AIzaSyDl6-k1hPjrgWR71Qia47F6z5dSylYJGpg'
+    api_key = os.getenv('GEMINI_API_KEY')
     if not api_key:
         raise EnvironmentError(
             'Please set the GEMINI_API_KEY environment variable.'
@@ -31,9 +33,7 @@ def gemini_api_key() -> str:
 
 
 @pytest.mark.skip_on_ci
-def test_gemini_generation(
-    animals_data: list[str], gemini_api_key: str
-) -> None:
+def test_gemini_generation(animals_data: list[str], api_key: str) -> None:
     """Test RAG pipeline with Gemini model for text generation."""
     # Instantiate Rago with the Gemini model
     rag = Rago(
@@ -41,9 +41,7 @@ def test_gemini_generation(
         augmented=GeminiAug(
             k=3
         ),  # Update if using a specific augmentation class for Gemini
-        generation=GeminiAIGen(
-            api_key=gemini_api_key, model_name='gemini-1.5-flash'
-        ),
+        generation=GeminiGen(api_key=api_key, model_name='gemini-1.5-flash'),
     )
 
     query = 'Is there any animal larger than a dinosaur?'
@@ -51,5 +49,5 @@ def test_gemini_generation(
 
     # Verify the result contains relevant information, e.g., "Blue Whale"
     assert (
-        'Blue Whale' in result
+        'blue whale' in result.lower()
     ), 'Expected response to mention Blue Whale as a larger animal.'
diff --git a/tests/test_hugging_face.py b/tests/test_hugging_face.py
index d70a0ff..d5b7331 100644
--- a/tests/test_hugging_face.py
+++ b/tests/test_hugging_face.py
@@ -29,4 +29,4 @@ def test_hugging_face(animals_data: list[str]) -> None:
 
     query = 'Is there any animals larger than a dinosaur?'
     result = rag.prompt(query)
-    assert 'Blue Whale' in result
+    assert 'blue whale' in result.lower()
diff --git a/tests/test_llama.py b/tests/test_llama.py
index 67daa97..218fbe3 100644
--- a/tests/test_llama.py
+++ b/tests/test_llama.py
@@ -34,4 +34,4 @@ def test_llama(env, animals_data: list[str], device: str = 'auto') -> None:
 
     query = 'Is there any animals larger than a dinosaur?'
     result = rag.prompt(query)
-    assert 'Blue Whale' in result
+    assert 'blue whale' in result.lower()
diff --git a/tests/test_openai_gpt.py b/tests/test_openai.py
similarity index 70%
rename from tests/test_openai_gpt.py
rename to tests/test_openai.py
index 3e7104f..15fa653 100644
--- a/tests/test_openai_gpt.py
+++ b/tests/test_openai.py
@@ -1,4 +1,4 @@
-"""Tests for Rago package using OpenAI GPT-4."""
+"""Tests for Rago package using OpenAI GPT."""
 
 import os
 
@@ -8,9 +8,7 @@
 
 from rago import Rago
 from rago.augmented import OpenAIAug
-from rago.generation.openai_gpt import (
-    OpenAIGPTGen,
-)
+from rago.generation import OpenAIGen
 from rago.retrieval import StringRet
 
 
@@ -24,7 +22,7 @@ def animals_data() -> list[str]:
 
 
 @pytest.fixture
-def openai_api_key() -> str:
+def api_key(env) -> str:
     """Fixture for OpenAI API key from environment."""
     api_key = os.getenv('OPENAI_API_KEY')
     if not api_key:
@@ -35,17 +33,17 @@ def openai_api_key() -> str:
 
 
 @pytest.mark.skip_on_ci
-def test_openai_gpt4(animals_data: list[str], openai_api_key: str) -> None:
-    """Test RAG pipeline with OpenAI's GPT-4."""
+def test_openai_gpt4(animals_data: list[str], api_key: str) -> None:
+    """Test RAG pipeline with OpenAI's GPT."""
     rag = Rago(
         retrieval=StringRet(animals_data),
-        augmented=OpenAIAug(k=3),
-        generation=OpenAIGPTGen(api_key=openai_api_key, model_name='gpt-4'),
+        augmented=OpenAIAug(api_key=api_key, k=3),
+        generation=OpenAIGen(api_key=api_key, model_name='gpt-3.5-turbo'),
     )
 
     query = 'Is there any animal larger than a dinosaur?'
     result = rag.prompt(query)
 
     assert (
-        'Blue Whale' in result
+        'blue whale' in result.lower()
     ), 'Expected response to mention Blue Whale as a larger animal.'