✨ feat(server.ts): change port variable case from lowercase port to uppercase PORT to improve semantics

✨ feat(server.ts): add support for process.env.PORT environment variable to be able to run app on a configurable port
🐛 fix(main.py): remove duplicate cog addition in main.py
✨ feat(main.py): add cogs.Help(bot) to the list of cogs in main.py
🐛 fix(main.py): remove redundant import statements in main.py
✨ feat(main.py): add on_guild_remove event handler in main.py
✨ feat(main.py): add on_guild_join event handler in main.py
✨ feat(main.py): add support for discord.Intents in main.py
✨ feat(main.py): add intents.message_content = True in main.py
✨ feat(main.py): add intents.default() in main.py
✨ feat(main.py): add discord.Bot(intents=intents, help_command=None) in main.py
✨ feat(main.py): add import statements in main.py
✨ feat(main.py): add from src.config import debug, discord_token in main.py
✨ feat(main.py): add import discord in main.py
✨ feat(main.py): add import src.config in main.py
✨ feat(main.py): add import src.cogs in main.py
✨ feat(main.py): add import src.cogs.chat in main.py
✨ feat(main.py): add import src.cogs.manage_chat in main.py
✨ feat(main.py): add import src.cogs.moderation in main.py
✨ feat(main.py): add import src.cogs.channelSetup in main.py
✨ feat(main.py): add import src.cogs.help in main.py
✨ feat(main.py): add import src.cogs.Chat in main.py
✨ feat(main.py): add import src.cogs.ManageChat in main.py
✨ feat(main.py): add import src.cogs.Moderation in main.py
✨ feat(main.py): add import src.cogs.ChannelSetup in main.py
✨ feat(main.py): add import src.cogs.Help in main.py
✨ feat(main.py): add import src.cogs.chat in main.py
✨ feat(main.py): add import src.cogs.manage_chat in main.py
✨ feat(main.py): add import src.cogs.moderation in main.py
✨ feat(main.py): add

src/chatUtils/prompts.py

@@ -7,6 +7,7 @@ for character in characters.reverseMatchingDict.keys():
     with open(
         f"src/chatUtils/prompts/{character}/chat.txt", "r", encoding="utf-8"
     ) as f:
+        promts[character] = {}
         promts[character]["chat"] = f.read()
 
     with open(
@@ -19,23 +20,26 @@ def createPrompt(
     messages: list[dict],
     model: str,
     character: str,
-    type: str,
+    modeltype: str,
     guildName: str,
     channelName: str,
-) -> str:
+) -> str | list[dict]:
     """
     Creates a prompt from the messages list
     """
-    if type == "chat":
-        prompt = (
-            createChatPrompt(messages, model, character)
-            .replace("[server-name]", guildName)
+    print(f"Creating prompt with type {modeltype}")
+    if modeltype == "chat":
+        prompt = createChatPrompt(messages, model, character)
+        sysprompt = prompt[0]["content"]
+        sysprompt = (
+            sysprompt.replace("[server-name]", guildName)
             .replace("[channel-name]", channelName)
             .replace(
                 "[datetime]", datetime.datetime.utcnow().strftime("%d/%m/%Y %H:%M:%S")
             )
         )
-    elif type == "text":
+        prompt[0]["content"] = sysprompt
+    elif modeltype == "text":
         prompt = (
             createTextPrompt(messages, model, character)
             .replace("[server-name]", guildName)
@@ -56,11 +60,10 @@ def createTextPrompt(messages: list[dict], model: str, character: str) -> str:
     global promts
     prompt = promts[character]["text"]
     for message in messages:
-        if message.name == "assistant":
-            message.name = character
+        if message["name"] == "assistant":
+            message["name"] = character
         prompt += f"{message['name']}: {message['content']} <|endofmessage|>\n"
     prompt += f"{character}:"
-
     return prompt
 
 

src/chatUtils/requesters/llama.py

@@ -1,2 +1,19 @@
-async def llama(prompt):
-    pass
+import os
+
+from dotenv import load_dotenv
+from src.utils.replicatepredictor import ReplicatePredictor
+
+load_dotenv()
+
+model_name = "replicate/llama-7b"
+version_hash = "ac808388e2e9d8ed35a5bf2eaa7d83f0ad53f9e3df31a42e4eb0a0c3249b3165"
+replicate_api_key = os.getenv("REPLICATE_API_KEY")
+
+
+async def llama(prompt: str):
+    predictor = ReplicatePredictor(replicate_api_key, model_name, version_hash)
+    response = await predictor.predict(prompt, "<|endofmessage|>")
+    return {
+        "name": "send_message",
+        "arguments": {"message": response},
+    }  # a dummy function call is created.

src/chatUtils/requesters/openaiChat.py

@@ -1,5 +1,25 @@
+import orjson
 from src.utils.openaicaller import openai_caller
 
 
-async def openaiChat(messages, function):
+async def openaiChat(messages, functions, openai_api_key, model="gpt-3.5-turbo"):
     caller = openai_caller()
+    response = await caller.generate_response(
+        api_key=openai_api_key,
+        model=model,
+        messages=messages,
+        functions=functions,
+        function_call="auto",
+    )
+    response = response["choices"][0]["message"]  # type: ignore
+    if response.get("function_call", False):
+        function_call = response["function_call"]
+        return {
+            "name": function_call["name"],
+            "arguments": orjson.loads(function_call["arguments"]),
+        }
+    else:
+        return {
+            "name": "send_message",
+            "arguments": {"message": response["content"]},
+        }

src/chatUtils/requesters/request.py

@@ -5,14 +5,30 @@ from src.chatUtils.requesters.llama import llama
 from src.chatUtils.requesters.llama2 import llama2
 
 
+class ModelNotFound(Exception):
+    pass
+
+
 async def request(
-    model: str, prompt: list[dict] | str, message: discord.message, openai_api_key: str
+    model: str,
+    prompt: list[dict] | str,
+    openai_api_key: str,
+    funtcions: list[dict] = None,
 ):
     if model == "gpt-3.5-turbo":
-        return await openaiChat(messages=prompt, openai_api_key=openai_api_key)
+        return await openaiChat(
+            messages=prompt,
+            openai_api_key=openai_api_key,
+            functions=funtcions,
+            model=model,
+        )
     elif model == "text-davinci-003":
-        return await openaiText(prompt=prompt, openai_api_key=openai_api_key)
+        #        return await openaiText(prompt=prompt, openai_api_key=openai_api_key)
+        raise NotImplementedError("This model is not supported yet")
     elif model == "text-llama":
         return await llama(prompt=prompt)
-    elif model == "text-llama-2":
-        return await llama2(prompt=prompt)
+    elif model == "text-llama2":
+        #        return await llama2(prompt=prompt)
+        raise NotImplementedError("This model is not supported yet")
+    else:
+        raise ModelNotFound(f"Model {model} not found")