make the /gpt function useable

app/cogs/gpt.py

@@ -1,3 +1,4 @@
+import discord
 from discord import option
 from discord.ext import commands
 
@@ -7,24 +8,59 @@ class Gpt(commands.Cog):
         self.bot: commands.Bot = bot
 
     @commands.slash_command(
-        guild_ids=None,
+        guld_ids=None,
         name="gpt",
-        description="Ask dalebot a question, he'll do his best to answer",
+        description="Talk to an LLM",
     )
+    @option(name="question", description="The question to ask", required=True)
     @option(
-        name="prompt",
-        description="What you want to ask dale-bot",
-        required=True,
+        name="temperature", description="I dunno", min_value=0, max_value=1, default=0.1
     )
-    async def gpt(self, ctx: commands.Context, prompt):
-        import gpt
+    @option(name="top_p", description="I dunno", min_value=0, max_value=1, default=0.75)
+    @option(name="top_k", description="I dunno", min_value=0, max_value=100, default=40)
+    @option(name="beams", description="I dunno", min_value=0, max_value=4, default=4)
+    @option(
+        name="tokens", description="I dunno", min_value=1, max_value=512, default=128
+    )
+    async def gpt(
+        self,
+        ctx,
+        question: str,
+        temperature: int,
+        top_p: int,
+        top_k: int,
+        beams: int,
+        tokens: int,
+    ):
+        import requests
 
-        # try:
         await ctx.defer()
-        embed = gpt.answer_question(prompt, user=ctx.author.name)
-        await ctx.send_followup(embed=embed)
-        # except Exception as e:
-        #     await ctx.send(e)
+        response = requests.post(
+            "https://tloen-alpaca-lora.hf.space/run/predict",
+            json={
+                "data": [
+                    question,
+                    "You live in California in Silicon valley. You are a computer program that is running in a kubernetes cluster. The cluster is comprised of 3 Thinkcentre M92p tiny computers. Your hobbies include racing cars, eating ice cream, and petting dogs.",
+                    float(temperature),
+                    float(top_p),
+                    float(top_k),
+                    int(beams),
+                    int(tokens),
+                ]
+            },
+        ).json()
+
+        data = response["data"][0]
+
+        embed = discord.Embed(
+            description=data,
+            color=discord.Color.green(),
+            type="rich",
+        )
+
+        embed.set_author(name="You asked me: %s" % question)
+
+        await ctx.followup.send(embed=embed)
 
 
 def setup(bot):

app/gpt.py

@@ -1,16 +0,0 @@
-import discord
-import os
-
-import openai
-
-
-def answer_question(prompt, user):
-    bots_context = "You are located in zipcode 94549. You are a chatbot written in python and you are answering questions for me"
-
-    openai.api_key = os.getenv("OPENAI_API_KEY")
-
-    completion = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo", messages=[{"role": user, "content": prompt}]
-    )
-
-    return completion.choices[0].message

argocd-application.yaml

@@ -1,26 +0,0 @@
-apiVersion: argoproj.io/v1alpha1
-kind: Application
-metadata:
-  name: dragon-bot
-  namespace: argocd
-spec:
-  project: default
-  source:
-    repoURL: git@git.luker.fr:ldooks/dragon-bot.git
-    targetRevision: HEAD
-    path: helm
-  destination:
-    server: https://kubernetes.default.svc
-    namespace: default
-  syncPolicy:
-    automated:
-      prune: true
-      selfHeal: true
-    retry:
-      limit: 2
-      backoff:
-        duration: 5s
-        factor: 2
-        maxDuration: 3m0s
-    syncOptions:
-      - PruneLast=true