first commit

bot/utils/ai_utils.py

@@ -0,0 +1,153 @@
+import aiohttp
+import io
+import time
+import os
+import random
+import json
+from langdetect import detect
+from gtts import gTTS
+from urllib.parse import quote
+from utils.config_loader import load_current_language, config
+from openai import AsyncOpenAI
+from duckduckgo_search import AsyncDDGS
+from dotenv import load_dotenv
+
+load_dotenv()
+
+current_language = load_current_language()
+internet_access = config['INTERNET_ACCESS']
+
+client = AsyncOpenAI(
+    base_url=config['API_BASE_URL'],
+    api_key="nah-ha",
+)
+
+async def generate_response(instructions, history):
+    messages = [
+            {"role": "system", "name": "instructions", "content": instructions},
+            *history,
+        ]
+
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "searchtool",
+                "description": "Searches the internet.",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "query": {
+                            "type": "string",
+                            "description": "The query for search engine",
+                        }
+                    },
+                    "required": ["query"],
+                },
+            },
+        }
+    ]
+    response = await client.chat.completions.create(
+        model=config['MODEL_ID'],
+        messages=messages,        
+        tools=tools,
+        tool_choice="auto",
+    )
+    response_message = response.choices[0].message
+    tool_calls = response_message.tool_calls
+
+    if tool_calls:
+        available_functions = {
+            "searchtool": duckduckgotool,
+        }
+        messages.append(response_message)
+
+        for tool_call in tool_calls:
+            function_name = tool_call.function.name
+            function_to_call = available_functions[function_name]
+            function_args = json.loads(tool_call.function.arguments)
+            function_response = await function_to_call(
+                query=function_args.get("query")
+            )
+            messages.append(
+                {
+                    "tool_call_id": tool_call.id,
+                    "role": "tool",
+                    "name": function_name,
+                    "content": function_response,
+                }
+            )
+        second_response = await client.chat.completions.create(
+            model=config['MODEL_ID'],
+            messages=messages
+        ) 
+        return second_response.choices[0].message.content
+    return response_message.content
+
+async def duckduckgotool(query) -> str:
+    if config['INTERNET_ACCESS']:
+        return "internet access has been disabled by user"
+    blob = ''
+    results = await AsyncDDGS(proxy=None).text(query, max_results=6)
+    try:
+        for index, result in enumerate(results[:6]):  # Limiting to 6 results
+            blob += f'[{index}] Title : {result["title"]}\nSnippet : {result["body"]}\n\n\n Provide a cohesive response base on provided Search results'
+    except Exception as e:
+        blob += f"Search error: {e}\n"
+    return blob
+
+
+async def poly_image_gen(session, prompt):
+    seed = random.randint(1, 100000)
+    image_url = f"https://image.pollinations.ai/prompt/{prompt}?seed={seed}"
+    async with session.get(image_url) as response:
+        image_data = await response.read()
+        return io.BytesIO(image_data)
+
+async def generate_image_prodia(prompt, model, sampler, seed, neg):
+    print("\033[1;32m(Prodia) Creating image for :\033[0m", prompt)
+    start_time = time.time()
+    async def create_job(prompt, model, sampler, seed, neg):
+        url = 'https://api.prodia.com/generate'
+        params = {
+            'new': 'true',
+            'prompt': f'{quote(prompt)}',
+            'model': model,
+            'steps': '100',
+            'cfg': '9.5',
+            'seed': f'{seed}',
+            'sampler': sampler,
+            'upscale': 'True',
+            'aspect_ratio': 'square'
+        }
+        async with aiohttp.ClientSession() as session:
+            async with session.get(url, params=params) as response:
+                data = await response.json()
+                return data['job']
+
+    job_id = await create_job(prompt, model, sampler, seed, neg)
+    url = f'https://api.prodia.com/job/{job_id}'
+    headers = {
+        'authority': 'api.prodia.com',
+        'accept': '*/*',
+    }
+
+    async with aiohttp.ClientSession() as session:
+        while True:
+            async with session.get(url, headers=headers) as response:
+                json = await response.json()
+                if json['status'] == 'succeeded':
+                    async with session.get(f'https://images.prodia.xyz/{job_id}.png?download=1', headers=headers) as response:
+                        content = await response.content.read()
+                        img_file_obj = io.BytesIO(content)
+                        duration = time.time() - start_time
+                        print(f"\033[1;34m(Prodia) Finished image creation\n\033[0mJob id : {job_id}  Prompt : ", prompt, "in", duration, "seconds.")
+                        return img_file_obj
+
+async def text_to_speech(text):
+    bytes_obj = io.BytesIO()
+    detected_language = detect(text)
+    tts = gTTS(text=text, lang=detected_language)
+    tts.write_to_fp(bytes_obj)
+    bytes_obj.seek(0)
+    return bytes_obj