feat: Integrate environment configuration and initialize chat model with embeddings

test_env.py

@@ -1,5 +1,22 @@
 import gradio as gr
-from dotenv 
+from dotenv import dotenv_values, load_dotenv
+from langchain.chat_models import init_chat_model
+from langchain_huggingface import HuggingFaceEmbeddings
+from langchain_chroma import Chroma
+
+
+load_dotenv()
+config = dotenv_values()
+FIREWORKS_API_KEY = config.get("FIREWORKS_API_KEY")
+LANGSMITH_API_KEY = config.get("LANGSMITH_API_KEY")
+
+llm = init_chat_model("accounts/fireworks/models/llama-v3p1-70b-instruct", model_provider="fireworks")
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+vector_store = Chroma(
+    collection_name="example_collection",
+    embedding_function=embeddings,
+    persist_directory="./chroma_langchain_db",  # Where to save data locally, remove if not necessary
+)
 
 
 def chat_interface(message, chat_history):