feat(generation): add backend support for Groq

src/rago/generation/__init__.py

@@ -7,6 +7,7 @@
 from rago.generation.deepseek import DeepSeekGen
 from rago.generation.fireworks import FireworksGen
 from rago.generation.gemini import GeminiGen
+from rago.generation.groq import GroqGen
 from rago.generation.hugging_face import HuggingFaceGen
 from rago.generation.hugging_face_inf import HuggingFaceInfGen
 from rago.generation.llama import LlamaGen
@@ -19,6 +20,7 @@
     'FireworksGen',
     'GeminiGen',
     'GenerationBase',
+    'GroqGen',
     'HuggingFaceGen',
     'HuggingFaceInfGen',
     'LlamaGen',

src/rago/generation/groq.py

@@ -0,0 +1,82 @@
+"""Groq class for text generation."""
+
+from __future__ import annotations
+
+from typing import cast
+
+import instructor
+import openai
+
+from pydantic import BaseModel
+from typeguard import typechecked
+
+from rago.generation.base import GenerationBase
+
+
+@typechecked
+class GroqGen(GenerationBase):
+    """Groq generation model for text generation."""
+
+    default_model_name = 'gemma2-9b-it'
+    default_api_params = {  # noqa: RUF012
+        'top_p': 1.0,
+    }
+
+    def _setup(self) -> None:
+        """Set up the Groq client."""
+        groq_api_key = self.api_key
+        if not groq_api_key:
+            raise Exception('GROQ_API_KEY environment variable is not set')
+
+        # Can use Groq client as well.
+        groq_client = openai.OpenAI(
+            base_url='https://api.groq.com/openai/v1', api_key=groq_api_key
+        )
+
+        # Optionally use instructor if structured output is needed
+        self.model = (
+            instructor.from_openai(groq_client)
+            if self.structured_output
+            else groq_client
+        )
+
+    def generate(
+        self,
+        query: str,
+        context: list[str],
+    ) -> str | BaseModel:
+        """Generate text using the Groq AP."""
+        input_text = self.prompt_template.format(
+            query=query, context=' '.join(context)
+        )
+
+        if not self.model:
+            raise Exception('The model was not created.')
+
+        api_params = (
+            self.api_params if self.api_params else self.default_api_params
+        )
+
+        messages = []
+        if self.system_message:
+            messages.append({'role': 'system', 'content': self.system_message})
+        messages.append({'role': 'user', 'content': input_text})
+
+        model_params = dict(
+            model=self.model_name,
+            messages=messages,
+            max_completion_tokens=self.output_max_length,
+            temperature=self.temperature,
+            **api_params,
+        )
+
+        if self.structured_output:
+            model_params['response_model'] = self.structured_output
+
+        response = self.model.chat.completions.create(**model_params)
+        self.logs['model_params'] = model_params
+
+        if hasattr(response, 'choices') and isinstance(response.choices, list):
+            return cast(str, response.choices[0].message.content.strip())
+
+        return cast(BaseModel, response)

tests/.env.tpl

@@ -5,3 +5,4 @@ TOKENIZERS_PARALLELISM=false
 COHERE_API_KEY=${COHERE_API_KEY}
 FIREWORKS_API_KEY=${FIREWORKS_API_KEY}
 TOGETHER_API_KEY=${TOGETHER_API_KEY}
+GROQ_API_KEY=${GROQ_API_KEY}

tests/conftest.py

@@ -94,3 +94,14 @@ def api_key_together(env) -> str:
             'Please set the TOGETHER_API_KEY environment variable.'
         )
     return key
+
+
+@pytest.fixture
+def api_key_groq(env) -> str:
+    """Fixture for GROQ API key from environment."""
+    key = os.getenv('GROQ_API_KEY')
+    if not key:
+        raise EnvironmentError(
+            'Please set the GROQ_API_KEY environment variable.'
+        )
+    return key

tests/test_generation.py

@@ -10,6 +10,7 @@
     DeepSeekGen,
     FireworksGen,
     GeminiGen,
+    GroqGen,
     HuggingFaceGen,
     HuggingFaceInfGen,
     LlamaGen,
@@ -32,6 +33,7 @@
     CohereGen: 'api_key_cohere',
     FireworksGen: 'api_key_fireworks',
     TogetherGen: 'api_key_together',
+    GroqGen: 'api_key_groq',
 }
 
 gen_models = [
@@ -85,6 +87,10 @@
     partial(
         HuggingFaceInfGen,
     ),
+    # model 9
+    partial(
+        GroqGen,
+    ),
 ]
 
 
@@ -98,6 +104,7 @@ def test_generation_simple_output(
     api_key_gemini: str,
     api_key_together: str,
     api_key_hugging_face: str,
+    api_key_groq: str,
     partial_model: partial,
 ) -> None:
     """Test RAG pipeline with model generation."""
@@ -150,6 +157,7 @@ def test_generation_structure_output(
     api_key_gemini: str,
     api_key_together: str,
     api_key_hugging_face: str,
+    api_key_groq: str,
     animals_data: list[str],
     question: str,
     partial_model: partial,