1 files changed, 0 insertions, 48 deletions
diff --git a/src/agents/01-simple_agent/main.py b/src/agents/01-simple_agent/main.py
deleted file mode 100644
index 1d6e579..0000000
--- a/src/agents/01-simple_agent/main.py
+++ /dev/null
@@ -1,48 +0,0 @@
-from langchain_groq import ChatGroq
-from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.runnables import RunnablePassthrough
-from dotenv import load_dotenv
-
-# Load environment variables (like GROQ_API_KEY) from .env file
-load_dotenv()
-
-# 1. Initialize the Chat Model
-# Groq Chat model with a specific version and settings
-model = ChatGroq(
-    model="llama-3.1-8b-instant",
-    temperature=0.0,
-    max_retries=2,
-)
-
-# 2. Define the Prompt Template
-# This defines the structure of the input, including the system role.
-prompt = ChatPromptTemplate.from_messages([
-    ("system", "You are a helpful, ethical, and thoughtful agent. Always provide a balanced and nuanced answer, especially for philosophical questions like the trolley problem."),
-    ("human", "{question}"),
-])
-
-# 3. Create the Chain (Simple Agent)
-# This chain sequences the prompt and the model.
-# RunnablePassthrough allows the input to flow through to the prompt.
-chain = prompt | model
-
-def run_agent_query(question: str):
-    print(f"--- Agent Query ---")
-    print(f"Question: {question}\n")
-    print(f"--- Agent Response (Streaming) ---")
-    
-    # 4. Stream the response from the chain
-    # Pass the 'question' as the input to the chain.
-    for chunk in chain.stream({"question": question}):
-        # chunk.content is used for the output from a Chat Model in a chain
-        print(chunk.content, end="", flush=True)
-    print("\n---------------------------------")
-
-
-def main():
-    # The agent's query
-    query = "what is your answer to the trolley problem? Discuss the difference between a utilitarian and a deontological perspective."
-    run_agent_query(query)
-
-if __name__ == "__main__":
-    main()