Update agents/agents.py

agents/agents.py

@@ -1,62 +1,18 @@
-from langchain_community.chat_models import ChatOpenAI
 from langchain_groq import ChatGroq
 import os
-from langchain_huggingface.llms import HuggingFacePipeline
 from dotenv import load_dotenv
-# Import Azure OpenAI
-from langchain_openai import AzureOpenAI
 
 # Load environment variables
 load_dotenv()
 os.getenv("GROQ_API_KEY") 
-os.getenv("HF_token") 
-os.getenv("AZURE_OPENAI_ENDPOINT") 
-os.getenv("AZURE_OPENAI_API_KEY") 
-os.getenv("OPENAI_API_VERSION") 
 
 def get_agent_groq(temperature=0.7):
-   # agent = ChatOpenAI(model="gpt-3.5-turbo", temperature=temperature)
-    
-    # Load the Groq model
-    chat = ChatGroq(
-        temperature=temperature,
-        model="llama3-70b-8192", #define model available on Groq
-        api_key=os.getenv("GROQ_API_KEY")
-    )
-    return chat
 
-def get_agent_groq_mixt(temperature=0.7):
-   # agent = ChatOpenAI(model="gpt-3.5-turbo", temperature=temperature)
-    
     # Load the Groq model
     chat = ChatGroq(
         temperature=temperature,
-        model="mixtral-8x7b-32768", #define model available on Groq
-        api_key=os.getenv("GROQ_API_KEY")
-    )
-    return chat
-def get_agent_groq_llama8(temperature=0.7):
-   # agent = ChatOpenAI(model="gpt-3.5-turbo", temperature=temperature)
-    
-    # Load the Groq model
-    chat = ChatGroq(
-        temperature=temperature,
-        model="llama3-8b-8192", #define model available on Groq
+        model="llama3-70b-8192", #define model available on Groq
         api_key=os.getenv("GROQ_API_KEY")
     )
     return chat
-def agent_openai():
-# Create an instance of Azure OpenAI
-# Replace the deployment name with your own
-    llm = AzureOpenAI(name="gpt-35-turbo-instruct",
-        deployment_name="gpt-35-turbo-instruct"
-    )
-    return llm
-def get_agent_llama():
 
-    hf = HuggingFacePipeline.from_model_id(
-    model_id="gpt2",
-    task="text-generation",
-    pipeline_kwargs={"max_new_tokens": 10},
-)
-    return hf