Create agents/agents.py

agents/agents.py

@@ -0,0 +1,62 @@
+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
+        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