feat: Groq as LLM provider

README.md

@@ -9,7 +9,10 @@ Welcome to a LLM Response Analysis Framework! This tool is designed to dive deep
 ## Features
 
 - **Dynamic LLM Integration**
-Seamlessly connect with various LLM providers and models to fetch responses using a flexible architecture.
+Seamlessly connect with various LLM providers and models to fetch responses using a flexible architecture. Following integrations are available.
+   - Openai
+   - Groq
+   - Ollama
 
 - **LangChain Structured Output Chain Analysis**
 Seamlessly connect with a LangChain Structured Output and check for the consistency of responses. [See this documentation for further information.](docs/check_chain/README.md)
@@ -92,6 +95,11 @@ Before using `det`, configure your LLM and embeddings provider API keys
 
 `export OPENAI_API_KEY=sk-makeSureThisIsaRealKey`
 
+for groq to configure groq client API key. 
+
+`export GROQ_API_KEY=gsk-DUMMYKEYISTHIS`
+
+
 ### Basic Usage
 
 To get a list of all the arguments and their descriptions, use:
@@ -109,6 +117,10 @@ det check-responses \
   --embeddings-model text-embedding-ada-002
 ```
 
+for `Groq` use --llm-provider as `Groq`
+for `Ollama` use --llm-provider as `Ollama`
+
+
 ### LangChain Structured Output Chains
 
 a LangChain Structured Output example

det/embeddings/generator.py

@@ -5,7 +5,7 @@
 import logging
 
 from openai import OpenAI
-
+import openai
 
 logger = logging.getLogger(__name__)
 
@@ -65,6 +65,18 @@ def _instantiate_openai_client(self, api_key: str):
             else:
                 self.client = OpenAI()
                 logger.info("OpenAI client instantiated successfully without api_key.")
+            self.client.models.list()
+        except openai.APIConnectionError as e:
+            logger.error("The server could not be reached")
+            logger.error(e.__cause__)  # The original exception
+        except openai.RateLimitError as e:
+            logger.error(
+                f"A 429 status code was received; we should back off a bit.{e}"
+            )
+        except openai.APIStatusError as e:
+            logger.error(f"Another non-200-range status code was received: {e}")
+            logger.error(e.status_code)
+            logger.error(e.response)
         except Exception as e:
             logger.error(f"Error instantiating OpenAI client: {str(e)}")
             self.client = None

det/llm/llm_groq.py

@@ -0,0 +1,72 @@
+"""
+# llm/llm_groq.py
+
+This module defines the GroqClient class, an implementation of the BaseLLMClient for generating
+text responses using Groq's API. It abstracts the details of API interaction, allowing for easy
+generation of text completions with various configurations.
+
+The client utilizes environment variables for API authentication, ensuring secure access without
+hard-coding sensitive information. It supports specifying a model at initialization for all
+subsequent requests, with the option to override default parameters per request.
+
+Example:
+--------
+    llm_client = GroqClient(model="llama3-8b-8192")
+    prompt = "Explain the significance of abstract classes in object-oriented programming."
+    response = llm_client.generate_response(prompt, temperature=0.5, max_tokens=100)
+    print(response)
+
+This setup facilitates seamless integration with different Large Language Models by adhering to the
+BaseLLMClient interface, promoting a plug-and-play architecture for text generation tasks.
+"""
+
+from groq import Groq
+import groq
+import logging
+
+from det.llm.base import LLMGeneratorInterface
+
+logger = logging.getLogger(__name__)
+
+
+class GroqClient(LLMGeneratorInterface):
+    """
+    Example:
+    --------
+        llm_client = GroqClient(model="llama3-8b-8192", api_key="your_api_key_here")
+        prompt = "Explain the significance of abstract classes in object-oriented programming."
+        response = llm_client.generate_response(prompt, temperature=0.5, max_tokens=100)
+        print(response)
+    """
+
+    def __init__(self, model: str = "llama3-8b-8192", api_key: str = None):
+        try:
+            if api_key:
+                self.client = Groq(api_key=api_key)
+            else:
+                self.client = Groq()
+            self.model = model
+            self.client.models.list()
+        except groq.APIConnectionError as e:
+            logger.error(f"The server could not be reached: {e}")
+        except groq.RateLimitError as e:
+            logger.error(
+                f"A 429 status code was received; we should back off a bit: {e}"
+            )
+        except groq.APIStatusError as e:
+            logger.error(f"Another non-200-range status code was received: {e}")
+        except Exception as e:
+            logger.error(f"Error instantiating Groq client: {str(e)}")
+            self.client = None
+
+    def generate_response(self, prompt: str, **kwargs):
+        try:
+            response = self.client.chat.completions.create(
+                model=self.model,  # Use the model specified during initialization
+                messages=[{"role": "user", "content": prompt}],
+                **kwargs,
+            )
+            return response.choices[0].message.content
+        except Exception as e:
+            print(f"An error occurred: {e}")
+            return None

det/llm/llm_openai.py

@@ -21,9 +21,13 @@
 """
 
 from openai import OpenAI
+import openai
+import logging
 
 from det.llm.base import LLMGeneratorInterface
 
+logger = logging.getLogger(__name__)
+
 
 class OpenAIClient(LLMGeneratorInterface):
     """
@@ -36,11 +40,29 @@ class OpenAIClient(LLMGeneratorInterface):
     """
 
     def __init__(self, model: str = "gpt-3.5-turbo", api_key: str = None):
-        if api_key:
-            self.client = OpenAI(api_key=api_key)
-        else:
-            self.client = OpenAI()
-        self.model = model
+        try:
+            if api_key:
+                self.client = OpenAI(api_key=api_key)
+                logger.info("OpenAI client instantiated successfully using api_key.")
+            else:
+                self.client = OpenAI()
+                logger.info("OpenAI client instantiated successfully without api_key.")
+            self.model = model
+            self.client.models.list()
+        except openai.APIConnectionError as e:
+            logger.error("The server could not be reached")
+            logger.error(e.__cause__)  # The original exception
+        except openai.RateLimitError as e:
+            logger.error(
+                f"A 429 status code was received; we should back off a bit:{e}"
+            )
+        except openai.APIStatusError as e:
+            logger.error("Another non-200-range status code was received")
+            logger.error(e.status_code)
+            logger.error(e.response)
+        except Exception as e:
+            logger.error(f"Error instantiating OpenAI client: {str(e)}")
+            self.client = None
 
     def generate_response(self, prompt: str, **kwargs):
         try:

pyproject.toml

@@ -19,6 +19,7 @@ langchain = "^0.1.12"
 langchain-community = "^0.0.29"
 langchain-openai = "^0.1.1"
 deepdiff = "^6.7.1"
+groq = "^0.11.0"
 
 [tool.poetry.group.dev.dependencies]
 pre-commit = "^3.6.2"