Create release_checklist_code.py

Tests new features, code in docs.

release_checklist_code.py

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+"""
+This code is used to test various aspects of PhaseLLM. We recommend running this on a P3 EC2 instance with Ubuntu 22.04 installed. To get this up and running, run the following code:
+
+sudo apt-get update
+sudo apt-get upgrade
+sudo apt-get install xorg
+sudo apt-get install nvidia-driver-460
+sudo reboot
+
+Run `nvidia-smi` to ensure you have GPU devices with CUDA installed.
+
+"""
+
+##########################################################################################
+# GPU SETUP
+#
+
+import torch
+
+# Confirm GPUs are installed and usable.
+print(torch.cuda.is_available())
+print(torch.cuda.current_device())
+
+##########################################################################################
+# ENVIRONMENT VARIABLES
+#
+
+# Load all environment variables and API keys
+
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+openai_api_key = os.getenv("OPENAI_API_KEY")
+anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+cohere_api_key = os.getenv("COHERE_API_KEY")
+hugging_face_api_key = os.getenv("HUGGING_FACE_API_KEY")
+
+##########################################################################################
+# GPT-3.5 EVALUATOR WITH COHERE AND CLAUDE COMPARISONS
+#
+
+# Run GPT-3.5 evaluator
+
+from phasellm.eval import GPT35Evaluator
+
+# We'll use GPT-3.5 as the evaluator.
+e = GPT35Evaluator(openai_api_key)
+
+# Our objective.
+objective = "We're building a chatbot to discuss a user's travel preferences and provide advice."
+
+# Chats that have been launched by users.
+travel_chat_starts = [
+    "I'm planning to visit Poland in spring.",
+    "I'm looking for the cheapest flight to Europe next week.",
+    "I am trying to decide between Prague and Paris for a 5-day trip",
+    "I want to visit Europe but can't decide if spring, summer, or fall would be better.",
+    "I'm unsure I should visit Spain by flying via the UK or via France."
+]
+
+from phasellm.llms import CohereWrapper, ClaudeWrapper
+cohere_model = CohereWrapper(cohere_api_key)
+claude_model = ClaudeWrapper(anthropic_api_key)
+
+print("Running test. 1 = Cohere, and 2 = Claude.")
+for tcs in travel_chat_starts:
+
+    messages = [{"role":"system", "content":objective},
+            {"role":"user", "content":tcs}]
+
+    response_cohere = cohere_model.complete_chat(messages, "assistant")
+    response_claude = claude_model.complete_chat(messages, "assistant")
+
+    pref = e.choose(objective, tcs, response_cohere, response_claude)
+    print(f"{pref}")
+
+##########################################################################################
+# DOLLY TESTS
+#
+
+from phasellm.llms import DollyWrapper
+dw = DollyWrapper()
+
+# Testing chat capability.
+messages = [{"role":"user", "content":"What should I eat for lunch today?"}]
+dw.complete_chat(messages, 'assistant')
+
+# Run a text completion.
+dw.text_completion("The capital of Poland is")
+
+##########################################################################################
+# GPT-3.5 EVALUATOR WITH COHERE AND DOLLY COMPARISONS
+#
+
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+openai_api_key = os.getenv("OPENAI_API_KEY")
+anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+cohere_api_key = os.getenv("COHERE_API_KEY")
+
+from phasellm.eval import GPT35Evaluator
+
+# We'll use GPT-3.5 as the evaluator.
+e = GPT35Evaluator(openai_api_key)
+
+# Our objective.
+objective = "We're building a chatbot to discuss a user's travel preferences and provide advice."
+
+# Chats that have been launched by users.
+travel_chat_starts = [
+    "I'm planning to visit Poland in spring.",
+    "I'm looking for the cheapest flight to Europe next week.",
+    "I am trying to decide between Prague and Paris for a 5-day trip",
+    "I want to visit Europe but can't decide if spring, summer, or fall would be better.",
+    "I'm unsure I should visit Spain by flying via the UK or via France."
+]
+
+from phasellm.llms import CohereWrapper
+from phasellm.llms import DollyWrapper # NEW: importing the DollyWrapper...
+dwl = DollyWrapper() # NEW: ... and instantiating it.
+
+cohere_model = CohereWrapper(cohere_api_key)
+
+print("Running test. 1 = Cohere, and 2 = Dolly.")
+for tcs in travel_chat_starts:
+    messages = [{"role":"system", "content":objective},
+                {"role":"user", "content":tcs}]
+    response_cohere = cohere_model.complete_chat(messages, "assistant")
+    response_dw = dw.complete_chat(messages, "assistant") # NEW: minor change to variable name
+    pref = e.choose(objective, tcs, response_cohere, response_dw)
+    print(f"{pref}")
+
+##########################################################################################
+# BLOOM TESTS
+#
+
+from phasellm.llms import BloomWrapper
+bw = BloomWrapper(hugging_face_api_key)
+
+# Testing chat capability.
+messages = [{"role":"user", "content":"What should I eat for lunch today?"}]
+bw.complete_chat(messages, 'assistant')
+
+# Run a text completion.
+bw.text_completion("The capital of Poland is")