diff --git a/server_executor_cleaned.py b/server_executor_cleaned.py
index 579ea94d..2c2e54a3 100644
--- a/server_executor_cleaned.py
+++ b/server_executor_cleaned.py
@@ -14,7 +14,7 @@ from gpt4all import GPT4All
 from loguru import logger
 from whisper_jax import FlaxWhisperPipline
 
-from utils.run_utils import run_in_executor
+from utils.run_utils import run_in_executor, config
 
 pcs = set()
 relay = MediaRelay()
@@ -28,7 +28,8 @@ RATE = 48000
 audio_buffer = AudioFifo()
 executor = ThreadPoolExecutor()
 transcription_text = ""
-llm = GPT4All("/Users/gokulmohanarangan/Library/Application Support/nomic.ai/GPT4All/ggml-vicuna-13b-1.1-q4_2.bin")
+# Load your locally downloaded Vicuna model and load it here. Set this path in the config.ini file
+llm = GPT4All(config["DEFAULT"]["LLM_PATH"])
 
 
 def get_title_and_summary():
diff --git a/utils/config.ini b/utils/config.ini
new file mode 100644
index 00000000..976f4a32
--- /dev/null
+++ b/utils/config.ini
@@ -0,0 +1,24 @@
+[DEFAULT]
+#SetexceptionruleforOpenMPerrortoallowduplicatelibinitialization
+KMP_DUPLICATE_LIB_OK=TRUE
+#ExportOpenAIAPIKey
+OPENAI_APIKEY=
+#ExportWhisperModelSize
+WHISPER_MODEL_SIZE=tiny
+WHISPER_REAL_TIME_MODEL_SIZE=tiny
+#AWSconfig
+AWS_ACCESS_KEY=***REMOVED***
+AWS_SECRET_KEY=***REMOVED***
+BUCKET_NAME=reflector-bucket
+#Summarizerconfig
+SUMMARY_MODEL=facebook/bart-large-cnn
+INPUT_ENCODING_MAX_LENGTH=1024
+MAX_LENGTH=2048
+BEAM_SIZE=6
+MAX_CHUNK_LENGTH=1024
+SUMMARIZE_USING_CHUNKS=YES
+#Audiodevice
+BLACKHOLE_INPUT_AGGREGATOR_DEVICE_NAME=aggregator
+AV_FOUNDATION_DEVICE_ID=1
+# LLM PATH
+LLM_PATH=