switched over to prompting to multiple models at once

main.py

 import os
 import subprocess
 from pathlib import Path
-
+# enables counting list items
+from operator import length_hint
 # .env parser
 from dotenv import load_dotenv
 # colored print
@@ -9,6 +10,8 @@ from colorist import Color, BrightColor, bright_yellow, magenta, red, green
 # langchain stuff
 from langchain_community.llms import Ollama
 from langchain.prompts import PromptTemplate
+from langchain.model_laboratory import ModelLaboratory
+
 
 ##################################################
 ### PREPARING & STARTING
@@ -24,34 +27,31 @@ if not os.path.isfile('./.env'):
 load_dotenv()
 
 ##########
-# INSTALLING LLM
+# INSTALLING LLMS
 ##########
-print(f"installing llm <{os.environ['llmName']}>. This can take a while, depending on size and if already installed.")
-
-# create download folder
-Path(os.environ['OLLAMA_MODELS']).mkdir(parents=True, exist_ok=True)
-
-process = subprocess.run(["ollama","pull" , f"{os.environ['llmName']}"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+# split llm names into array
+llmNames = os.environ['LLM_NAMES'].split(',')
+green(f'Installing {length_hint(llmNames)} LLMs. This can take a while, depending on installation status, size and bandwith.')
+# loop trhough llm names
+for idx, llmName in enumerate(llmNames):
+  print(f"{idx+1}/{length_hint(llmNames)}: {llmName}")
+  # install
+  process = subprocess.run(["ollama","pull" , f"{llmName}"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
   # on error
   if process.returncode != 0:
-  magenta(process.stderr.decode('utf8'))
-  red(f"ABORTING: Unable to install the requested LLM")
-  os._exit(1)
-
-print(process.stdout.decode('UTF8'))
+    red(process.stderr.decode('utf8'))
+    # remove name from array
+    llmNames.pop(idx)
 
-llm = Ollama(
-    model=os.environ['llmName'], 
-    temperature=0,
-    # callback_manager=CallbackManager([StreamingStdOutCallbackHandler()])
-)
-# write down the question to ask
-question="What tall is the tallest pyramid in egypt and what's it called?"
+# exit if no LLM could be loaded
+if length_hint(llmNames) == 0:
+  red(f"ABORTING: Unable to install even one of the requested LLMs")
+  os._exit(1)
 
 ##################################################
-### ASK THE LLM
+### DEFINING THE PROMPT
 ##################################################
-green('prompting')
+green('preparing the prompt specifications')
 # define template
 prompt_template = PromptTemplate(
   input_variables=['question'],
@@ -63,9 +63,18 @@ prompt_template = PromptTemplate(
   ---------------------
   """
 )
-# create prompt by injecting the question
-prompt = prompt_template.format(question=question)
-# run the query
-response = llm.invoke(prompt)
-# return the response
-print(f"Question: {Color.MAGENTA}{question}{Color.OFF}\nAnswer: {BrightColor.MAGENTA}{response}{Color.OFF}\n")
+
+##################################################
+### RUNNING THE TEST
+##################################################
+# define LLMs to run with their specs
+localLLMs = []
+for idx, llmName in enumerate(llmNames):
+  localLLMs.append(Ollama(
+    model=llmName,
+    temperature=os.environ['OVERAL_TEMPERATURE']
+  ))
+# setup 'laboratory'
+lab = ModelLaboratory.from_llms(localLLMs, prompt=prompt_template)
+# run prompt through all llms
+lab.compare(os.environ['QUESTION'])
\ No newline at end of file