Create app.py

app.py

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+import discord
+# from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
+# from transformers import pipeline
+import os
+from dotenv import load_dotenv
+
+# Lite mode
+# from transformers import AutoTokenizer, AutoModelForQuestionAnswering
+# model_name = "deepset/roberta-base-squad2"
+# nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
+# tokenizer = AutoTokenizer.from_pretrained(name,)
+
+# model = AutoModelForQuestionAnswering.from_pretrained(name)
+
+# nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
+
+
+#load_dotenv()
+
+# TODO
+# Add chat history to DialoGPT for context
+
+## Initialize models
+
+# Question Answering
+# model_name = "deepset/roberta-base-squad2"
+# nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+
+# Conversational
+convo_tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
+convo_model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
+
+# Summarizer
+# summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+print('Models and tokenizers successfully loaded')
+
+# Get Discord client
+client = discord.Client()
+
+## Event Handlers
+
+@client.event
+async def on_ready():
+    print('We have logged in as {0.user}'.format(client))
+    status = "We have logged in"
+
+@client.event
+async def on_message(message):
+    if message.author == client.user:
+        return
+
+    if message.content.startswith('$ping'):
+        await message.channel.send('pong')
+        print(message.author)
+        print(message.author.name)
+        print(message.author.avatar)
+    
+    if message.content.startswith('$help'):
+        await message.channel.send('List of stable commands: ')
+        await message.channel.send('COMMANDS')
+        await message.channel.send('List of nightly commands: ')
+        await message.channel.send('COMMANDS')
+
+        if message.content.startswith('$q'):
+            question = message.content[4::]
+            if(len(question) == 0):
+                await message.channel.send("I didn't get that.")
+                return
+            else:
+                print(question)
+            QA_input = {
+                'question': 'Why is model conversion important?',
+                'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+            }
+            res = nlp(QA_input)
+            ans = res['answer']
+            score = res['score']
+            await message.channel.send(ans)
+            await message.channel.send('score: ' + score)
+
+    # if message.content.startswith('$q'):
+    #     question = message.content[4::]
+    #     if(len(question) == 0):
+    #         await message.channel.send("I didn't get that.")
+    #         return
+    #     else:
+    #         print(question)
+    #     QA_input = {
+    #         'question': 'Why is model conversion important?',
+    #         'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+    #     }
+    #     res = nlp(QA_input)
+    #     ans = res['answer']
+    #     score = res['score']
+    #     await message.channel.send(ans)
+    #     await message.channel.send('score: ' + score)
+
+    # if message.content.startswith('$TLDR'):
+    #     query = message.content[6::]
+
+    #     if(len(query) < 2):
+    #         messages = [message.content async for message in message.channel.history(limit=30)]
+    #         messages_str = ".".join(messages)
+    #         summary = summarizer(messages_str, max_length=130, min_length=30, do_sample=False)
+    #         await message.channel.send('Summary: ' + summary[0]['summary_text'])
+    #     elif(len(query) < 35):
+    #         await message.channel.send('Too short to summarize.')
+    #     else:
+    #         summary = summarizer(query, max_length=130, min_length=30, do_sample=False)
+    #         await message.channel.send('Summary: ' + summary[0]['summary_text'])
+
+    # if message.content.startswith('$talk'):
+    #     chat = message.content[6::]
+    #     if(len(chat) == 0):
+    #         await message.channel.send("I didn't get that.")
+    #         return
+    #     else:
+    #         print(chat)
+        
+    #     input_ids = convo_tokenizer.encode(chat + convo_tokenizer.eos_token, return_tensors='pt')
+    #     return_ids = convo_model.generate(input_ids, max_length=1000, pad_token_id=convo_tokenizer.eos_token_id)
+    #     response = "{}".format(convo_tokenizer.decode(return_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True))
+
+    #     await message.channel.send(response)
+
+client.run(str(os.environ.get('TOKEN')))
+# client.run(str(os.getenv('TOKEN')))