modify structure to read env files from .env file in same directory

Author: james-pplx

perplexity-llamaindex/memory/chat_summary_memory_buffer/scripts/chat_memory_buffer.py

@@ -1,13 +1,17 @@
 from llama_index.core.memory import ChatSummaryMemoryBuffer
-from llama_index.core.llms import ChatMessage  # Add this import
+from llama_index.core.llms import ChatMessage
 from llama_index.llms.openai import OpenAI as LlamaOpenAI
 from openai import OpenAI as PerplexityClient
+from dotenv import load_dotenv
 import os
 
+# Load environment variables from .env file
+load_dotenv()
+
 # Configure LLM for memory summarization
 llm = LlamaOpenAI(
     model="gpt-4o-2024-08-06",
-    api_key=os.environ["PERPLEXITY_API_KEY"],
+    api_key=os.getenv("PERPLEXITY_API_KEY"),
     base_url="https://api.openai.com/v1/chat/completions"
 )
 
@@ -25,36 +29,29 @@
 
 # Create API client
 sonar_client = PerplexityClient(
-    api_key=os.environ["PERPLEXITY_API_KEY"],
+    api_key=os.getenv("PERPLEXITY_API_KEY"),
     base_url="https://api.perplexity.ai"
 )
 
 def chat_with_memory(user_query: str):
-    # Store user message as ChatMessage
     memory.put(ChatMessage(role="user", content=user_query))
-    
-    # Get optimized message history
     messages = memory.get()
 
-    # Convert to Perplexity-compatible format
     messages_dict = [
         {"role": m.role, "content": m.content}
         for m in messages
     ]
 
-    # Execute API call
     response = sonar_client.chat.completions.create(
         model="sonar-pro",
         messages=messages_dict,
         temperature=0.3
     )
 
-    # Store response
     assistant_response = response.choices[0].message.content
     memory.put(ChatMessage(
         role="assistant",
         content=assistant_response
     ))
 
     return assistant_response
-