diff --git a/docs/examples/distributed/LLM_inference/client.py b/docs/examples/distributed/LLM_inference/client.py
index 1c6ee6c9..fc07b8d2 100644
--- a/docs/examples/distributed/LLM_inference/client.py
+++ b/docs/examples/distributed/LLM_inference/client.py
@@ -9,11 +9,99 @@
 import time
 
 
+def _fetch_job_info(name):
+    # Mock this for testing
+    command = ["squeue", "-h", f"--name={name}", "--format=\"%A %j %T %P %U %k %N\""]
+    return subprocess.check_output(command, text=True)
+
+
+def get_slurm_job_by_name(name):
+    """Retrieve a list of jobs that match a given job name"""
+
+    output =_fetch_job_info(name)
+    jobs = []
+
+    def parse_meta(comment):
+        data = dict()
+        if comment != "(null)":
+            items = comment.split('|')
+            for kv in items:
+                try:
+                    k, v = kv.split('=', maxsplit=1)
+                    data[k] = v
+                except: 
+                    pass
+
+        return data
+
+    for line in output.splitlines():
+        job_id, job_name, status, partition, user, comment, nodes = line.split(' ')
+
+        jobs.append({
+            "job_id":job_id, 
+            "job_name":job_name, 
+            "status":status,
+            "partition":partition, 
+            "user":user,
+            "comment": parse_meta(comment),
+            "nodes": nodes
+        })
+
+    return jobs
+
+
+def find_suitable_inference_server(jobs, model):
+    """Select suitable jobs from a list, looking for a specific model"""
+    selected = []
+    
+    def is_shared(job):
+        return job["comment"].get("shared", 'y') == 'y'
+    
+    def is_running(job):
+        return job['status'] == "RUNNING"
+    
+    def has_model(job, model):
+        if model is None:
+            return True
+        
+        # FIXME: 
+        #   /network/weights/llama.var/llama2/Llama-2-7b-hf != meta-llama/Llama-2-7b-hf
+        #
+        return job['comment']['model'] == model
+    
+    def select(job):
+        selected.append({
+            "model": job['comment']["model"],
+            "host": job["comment"]["host"],
+            "port": job["comment"]["port"],
+        })
+            
+    for job in jobs:
+        if is_shared(job) and is_running(job) and has_model(job, model):
+            select(job)
+                
+    return selected
+
+
+def get_inference_server(model=None):
+    """Retrieve an inference server from slurm jobs"""
+    jobs = get_slurm_job_by_name('inference_server_SHARED.sh')
+
+    servers = find_suitable_inference_server(jobs, model)
+
+    try:
+        return random.choice(servers)
+    except IndexError:
+        return None
+
+
 def get_server_url_and_port() -> tuple[str, int]:
-    with open("server.txt") as f:
-        server_url_and_port = f.read().strip()
-    server_url, _, port = server_url_and_port.partition(":")
-    return server_url, int(port)
+    server = get_inference_server(model)
+
+    if server is None:
+        return None
+    
+    return server['host'], int(server['port'])
 
 
 def debug():
@@ -21,6 +109,7 @@ def debug():
     while not Path("server.txt").exists():
         time.sleep(1)
         print(f"Waiting for server to start...")
+
     server_url, port = get_server_url_and_port()
     print(f"Found server at {server_url}:{port}")
     response = requests.get(