added llm calls to ai

src/game_utils.py

@@ -38,14 +38,20 @@ WIN CONDITION:
 '''
 
 herd_animal = """\
-You are a {animal}. In 10 words or less give a description of yourself starting with "I". The description should not give away too much information about the {animal} as you do not want the Chameleon to be able to guess what animal you are. Do not repeat responses from other players.
+You are a {animal}, keep this a secret at all costs. 
+In 10 words or less give a description of yourself starting with "I". The description should not give away too much information about the {animal} as you do not want the Chameleon to be able to guess what animal you are. Do not repeat responses from other players.
+If the Chameleon can guess what animal you really are you will LOSE.
 Previously Mentioned Descriptions: 
 {player_responses}
 Your Response:
 """
 
 chameleon_animal = """\
-You are the Chameleon. Initially, you don't know what animal the other players are, your goal is to deduce . Using the context that they have provided, In 10 words or less give a description of yourself starting with "I". If no one else has said anything try to say something generic that could be true of any animals. 
+You are the Chameleon, keep this a secret at all costs. 
+You don't know what animal the other players are, your goal is to deduce it using the context they provide.
+Starting with "I" describe yourself in 10 words or less as if you are the same animal as the other players. 
+If no one else has said anything try to say something generic that could be true of any animals. 
+If the other players realize you are the Chameleon you will LOSE. 
 Previously Mentioned Descriptions:
 {player_responses}
 Your Response:
@@ -65,7 +71,6 @@ chameleon_prompt = """\
 You are the Chameleon, vote for someone else to remove suspicion from yourself.
 """
 
-
 prompts = {
     "herd_animal": game_rules + herd_animal,
     "chameleon_animal": game_rules + chameleon_animal,

src/player.py

@@ -1,4 +1,19 @@
-from game_utils import fetch_prompt
+import os
+import openai
+
+# Using TGI Inference Endpoints from Hugging Face
+# api_type = "tgi"
+api_type = "openai"
+
+if api_type == "tgi":
+    model_name = "tgi"
+    client = openai.Client(
+        base_url=os.environ['HF_ENDPOINT_URL'] + "/v1/",
+        api_key=os.environ['HF_API_TOKEN']
+    )
+else:
+    model_name = "gpt-3.5-turbo"
+    client = openai.Client()
 
 class Player:
     def __init__(self, name: str, controller: str, role: str):
@@ -9,9 +24,9 @@ class Player:
 
     def collect_input(self, prompt: str) -> str:
         """Store the input and output in the messages list. Return the output."""
-        self.messages.append(prompt)
+        self.messages.append({"role": "user", "content": prompt})
         output = self.respond(prompt)
-        self.messages.append(output)
+        self.messages.append({"role": "assistant", "content": output})
         return output
 
     def respond(self, prompt: str) -> str:
@@ -20,11 +35,18 @@ class Player:
             return input()
 
         elif self.controller == "ai":
-            return "I am an AI and I am responding to the prompt."
+            chat_completion = client.chat.completions.create(
+                model=model_name,
+                messages=self.messages,
+                stream=False,
+            )
+
+            return chat_completion.choices[0].message.content
+
 
     def add_message(self, message: str):
         """Add a message to the messages list. No response required."""
-        self.messages.append(message)
+        self.messages.append({"role": "user", "content": message})