add support for GROQ models

open_notebook/models/__init__.py

@@ -10,6 +10,7 @@ from open_notebook.models.embedding_models import (
 from open_notebook.models.llms import (
     AnthropicLanguageModel,
     GeminiLanguageModel,
+    GroqLanguageModel,
     LanguageModel,
     LiteLLMLanguageModel,
     OllamaLanguageModel,
@@ -20,6 +21,7 @@ from open_notebook.models.llms import (
     XAILanguageModel,
 )
 from open_notebook.models.speech_to_text_models import (
+    GroqSpeechToTextModel,
     OpenAISpeechToTextModel,
     SpeechToTextModel,
 )
@@ -46,6 +48,7 @@ MODEL_CLASS_MAP: Dict[str, ProviderMap] = {
         "openai": OpenAILanguageModel,
         "gemini": GeminiLanguageModel,
         "xai": XAILanguageModel,
+        "groq": GroqLanguageModel,
     },
     "embedding": {
         "openai": OpenAIEmbeddingModel,
@@ -55,6 +58,7 @@ MODEL_CLASS_MAP: Dict[str, ProviderMap] = {
     },
     "speech_to_text": {
         "openai": OpenAISpeechToTextModel,
+        "groq": GroqSpeechToTextModel,
     },
     "text_to_speech": {
         "openai": OpenAITextToSpeechModel,

open_notebook/models/llms.py

@@ -13,6 +13,7 @@ from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_vertexai.model_garden import ChatAnthropicVertex
+from langchain_groq.chat_models import ChatGroq
 from langchain_ollama.chat_models import ChatOllama
 from langchain_openai.chat_models import ChatOpenAI
 from pydantic import SecretStr
@@ -191,6 +192,30 @@ class OpenRouterLanguageModel(LanguageModel):
         )
 
 
+@dataclass
+class GroqLanguageModel(LanguageModel):
+    """
+    Language model that uses the Groq chat model.
+    """
+
+    model_name: str
+
+    def to_langchain(self) -> ChatGroq:
+        """
+        Convert the language model to a LangChain chat model for Groq.
+        """
+        kwargs = self.kwargs
+        kwargs["top_p"] = self.top_p
+
+        return ChatGroq(
+            model=self.model_name,
+            temperature=self.temperature or 0.5,
+            max_tokens=self.max_tokens,
+            model_kwargs=kwargs,
+            stop_sequences=None,
+        )
+
+
 @dataclass
 class XAILanguageModel(LanguageModel):
     """

open_notebook/models/speech_to_text_models.py

@@ -40,3 +40,22 @@ class OpenAISpeechToTextModel(SpeechToTextModel):
                 model=self.model_name, file=audio
             )
             return transcription.text
+
+
+@dataclass
+class GroqSpeechToTextModel(SpeechToTextModel):
+    model_name: str
+
+    def transcribe(self, audio_file_path: str) -> str:
+        """
+        Transcribes an audio file into text
+        """
+        from groq import Groq
+
+        # todo: make this Singleton
+        client = Groq()
+        with open(audio_file_path, "rb") as audio:
+            transcription = client.audio.transcriptions.create(
+                model=self.model_name, file=audio
+            )
+            return transcription.text