Upload 3 files

context.py

@@ -0,0 +1,36 @@
+contexts = {}
+
+def update_context(user_id, message, role):
+    if user_id not in contexts:
+        contexts[user_id] = []
+
+    if message.author.id == user_id:
+        role = "user"
+    else:
+        role = "assistant"
+
+    new_context_entry = {"role": role, "content": message.content}
+    contexts[user_id].append(new_context_entry)
+
+    if len(contexts[user_id]) > 5:
+        contexts[user_id] = contexts[user_id][-5:]
+
+    return contexts[user_id]
+
+def format_prompt(context):
+    prompt = "Привет! Меня зовут Хелпер, и я ваш дружелюбный дроид-путеводитель по миру Звездных войн. Задавайте свои вопросы на русском языке, и я постараюсь помочь вам, используя свои знания из этой захватывающей вселенной. Я буду стараться отвечать на все ваши запросы максимально точно и полезно."
+    messages = [{"role": "system", "content": prompt}]
+    messages.extend(context)
+
+    return messages
+
+def filter_response(response):
+    unwanted_phrases = ["unwanted_phrase1", "unwanted_phrase2"]
+    for phrase in unwanted_phrases:
+        if phrase in response:
+            return "I'm sorry, I can't provide an answer to that question."
+    return response
+
+def post_process(response):
+    # Add your post-processing logic here
+    return response

discord_api.py

@@ -0,0 +1,64 @@
+import discord
+import traceback
+
+DISCORD_TOKEN = 'указать токен'
+
+class MyClient(discord.Client):
+    def __init__(self, *args, **kwargs):
+        intents = discord.Intents.default()
+        intents.message_content = True
+        super().__init__(intents=intents, *args, **kwargs)
+
+    async def on_message(self, message):
+        print("Received message:", message.content)
+        try:
+            if message.author.id == self.user.id:
+                return
+
+            context = update_context(message.author.id, message, "user")
+            print("Updated context:", context)
+
+            messages = format_prompt(context)
+            print("Formatted prompt:", messages)
+
+            response = await call_huggingface_api(messages)
+            print("Received response:", response)
+
+            if response is not None and 'generated_text' in response[0]:
+                response_text = response[0]['generated_text']
+                print("Filtered response:", response_text)
+
+                response_text = filter_response(response_text)
+                print("Post-processed response:", response_text)
+
+                # Check if the response contains the user's question
+                if context[-1]["content"].lower() not in response_text.lower():
+                    # If the response does not contain the user's question, clear the context and generate a new response
+                    contexts[message.author.id] = []
+                    context = update_context(message.author.id, message, "user")
+                    messages = format_prompt(context)
+                    response = await call_huggingface_api(messages)
+                    response_text = response[0]['generated_text']
+                    response_text = filter_response(response_text)
+                    response_text = post_process(response_text)
+
+                last_bot_response = response_text.split("user:")[-1].strip()
+                print("Sending response:", last_bot_response)
+
+                if len(last_bot_response) > 2000:
+                    chunks = [last_bot_response[i:i+2000] for i in range(0, len(last_bot_response), 2000)]
+                    for chunk in chunks:
+                        await message.channel.send(chunk)
+                else:
+                    await message.channel.send(last_bot_response)
+            else:
+                print("Error generating text.")
+                await message.channel.send("Error generating text.")
+        except Exception as e:
+            print(f"Error in on_message: {e}")
+            print(traceback.format_exc())
+            await message.channel.send("An error occurred while processing your message. Please try again later.")
+
+async def main():
+    client = MyClient()
+    await client.start(DISCORD_TOKEN)

zefir7b_api.py

@@ -0,0 +1,40 @@
+import aiohttp
+import json
+import traceback
+
+HUGGINGFACE_TOKEN = 'указать токен'
+MODEL = "HuggingFaceH4/zephyr-7b-beta"
+
+async def call_huggingface_api(messages, temperature=0.95, top_k=50, top_p=0.9, num_return_sequences=1000):
+    url = f"https://api-inference.huggingface.co/models/{MODEL}"
+    headers = {"Authorization": f"Bearer {HUGGINGFACE_TOKEN}"}
+    data = {
+        "inputs": "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages]),
+        "options": {
+            "temperature": temperature,
+            "top_k": top_k,
+            "top_p": top_p,
+            "max_length": 1000,
+            "no_repeat_ngram_size": 3,
+            "do_sample": True,
+            "num_return_sequences": num_return_sequences,
+            "no_repeat_ngram_size": 3,
+            "repetition_penalty": 1.2,
+            "length_penalty": 1.0,
+            "early_stopping": True,
+        }
+    }
+
+    try:
+        async with aiohttp.ClientSession() as session:
+            async with session.post(url, headers=headers, json=data) as resp:
+                if resp.status == 200:
+                    response = await resp.json()
+                    return response
+                else:
+                    print(f"Error calling Hugging Face API: {resp.status}, {await resp.text()}")
+                    return None
+    except Exception as e:
+        print(f"Error calling Hugging Face API: {e}")
+        print(traceback.format_exc())
+        return None