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import asyncio |
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import json |
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import random |
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import re |
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import string |
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import time |
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import uuid |
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from datetime import datetime, timezone |
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from typing import Any, Dict, List, Optional |
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|
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import boto3 |
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import httpx |
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import tiktoken |
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import platform |
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import hashlib |
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from fastapi import HTTPException |
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from api.config import ( |
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MODEL_MAPPING, |
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get_headers_api_chat, |
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get_headers_chat, |
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BASE_URL, |
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AGENT_MODE, |
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TRENDING_AGENT_MODE, |
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MODEL_PREFIXES |
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) |
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from api.logger import setup_logger |
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from api.models import ChatRequest |
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from api.validate import getHid |
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logger = setup_logger(__name__) |
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R2_ACCESS_KEY_ID = "df9c9eb87e850a8eb27afd3968077b42" |
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R2_SECRET_ACCESS_KEY = "14b08b0855263bb63d2618da3a6537e1b0446d89d51da03a568620b1e5342ea8" |
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R2_ENDPOINT_URL = "https://f2f92ac53fae792c4155f6e93a514989.r2.cloudflarestorage.com" |
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R2_BUCKET_NAME = "snapzion" |
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R2_REPLACED_URLS_KEY = "snapzion.txt" |
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s3 = boto3.client( |
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"s3", |
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endpoint_url=R2_ENDPOINT_URL, |
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aws_access_key_id=R2_ACCESS_KEY_ID, |
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aws_secret_access_key=R2_SECRET_ACCESS_KEY, |
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) |
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BLOCKED_MESSAGE = ( |
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"Generated by BLACKBOX.AI, try unlimited chat https://www.blackbox.ai " |
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"and for API requests replace https://www.blackbox.ai with https://api.blackbox.ai" |
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) |
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def get_random_name_email_customer(): |
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""" |
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Generate a random name, email, and customer ID. |
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The customer ID keeps the same length format as 'cus_Rldf7IKdNhdhiw'. |
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""" |
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first_names = ["Alice", "Bob", "Carol", "David", "Evelyn", "Frank", "Grace", "Hector", "Ivy", "Jackie"] |
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last_names = ["Smith", "Johnson", "Davis", "Miller", "Thompson", "Garcia", "Brown", "Wilson", "Martin", "Clark"] |
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random_name = f"{random.choice(first_names)} {random.choice(last_names)}" |
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email_username = ''.join(random.choices(string.ascii_lowercase + string.digits, k=8)) |
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random_email = f"{email_username}@gmail.com" |
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suffix_length = len("Rldf7IKdNhdhiw") |
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suffix_chars = string.ascii_letters + string.digits |
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random_suffix = ''.join(random.choice(suffix_chars) for _ in range(suffix_length)) |
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random_customer_id = f"cus_{random_suffix}" |
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return random_name, random_email, random_customer_id |
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def generate_system_fingerprint() -> str: |
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raw_data = f"{platform.node()}-{time.time()}-{uuid.uuid4()}" |
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short_hash = hashlib.md5(raw_data.encode()).hexdigest()[:12] |
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return f"fp_{short_hash}" |
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|
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def get_last_user_prompt(messages: List[Any]) -> str: |
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for msg in reversed(messages): |
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if msg.role == "user": |
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if isinstance(msg.content, str): |
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return msg.content.strip() |
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elif isinstance(msg.content, list): |
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for item in msg.content: |
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if item.get("type") == "text": |
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return item.get("text", "").strip() |
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return "" |
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|
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def upload_replaced_urls_to_r2(urls: List[str], alt_text: str = "") -> None: |
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if not urls: |
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logger.info("No replaced or final Snapzion URLs to store. Skipping snapzion.txt update.") |
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return |
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existing_data = "" |
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try: |
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response = s3.get_object(Bucket=R2_BUCKET_NAME, Key=R2_REPLACED_URLS_KEY) |
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existing_data = response['Body'].read().decode('utf-8') |
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logger.info("Successfully read existing snapzion.txt from R2.") |
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except s3.exceptions.NoSuchKey: |
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logger.info("snapzion.txt does not exist yet. Will create a new one.") |
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except Exception as e: |
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logger.error(f"Error reading snapzion.txt from R2: {e}") |
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alt_text = alt_text.strip() |
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markdown_lines = [f"" for url in urls] |
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to_append = "\n".join(markdown_lines) |
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if existing_data.strip(): |
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updated_content = existing_data + "\n" + to_append |
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else: |
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updated_content = to_append |
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try: |
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s3.put_object( |
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Bucket=R2_BUCKET_NAME, |
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Key=R2_REPLACED_URLS_KEY, |
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Body=updated_content.encode("utf-8"), |
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ContentType="text/plain", |
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) |
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logger.info(f"Appended {len(urls)} new URLs to snapzion.txt in R2 (in Markdown format).") |
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except Exception as e: |
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logger.error(f"Failed to upload replaced URLs to R2: {e}") |
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|
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def calculate_tokens(text: str, model: str) -> int: |
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try: |
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encoding = tiktoken.encoding_for_model(model) |
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tokens = encoding.encode(text) |
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return len(tokens) |
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except KeyError: |
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logger.warning(f"Model '{model}' not supported by tiktoken for token counting. Using a generic method.") |
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return len(text.split()) |
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|
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def create_chat_completion_data( |
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content: str, |
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model: str, |
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timestamp: int, |
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request_id: str, |
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system_fingerprint: str, |
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prompt_tokens: int = 0, |
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completion_tokens: int = 0, |
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finish_reason: Optional[str] = None, |
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function_call: Optional[Dict] = None, |
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) -> Dict[str, Any]: |
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usage = None |
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if finish_reason == "stop": |
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usage = { |
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"prompt_tokens": prompt_tokens, |
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"completion_tokens": completion_tokens, |
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"total_tokens": prompt_tokens + completion_tokens, |
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} |
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return { |
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"id": request_id, |
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"object": "chat.completion.chunk", |
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"created": timestamp, |
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"model": model, |
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"system_fingerprint": system_fingerprint, |
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"choices": [{ |
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"index": 0, |
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"delta": { |
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"content": content if not function_call else None, |
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"role": "assistant", |
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"function_call": function_call |
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}, |
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"finish_reason": finish_reason |
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}], |
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"usage": usage, |
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} |
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def message_to_dict(message, model_prefix: Optional[str] = None, tools: Optional[List[Dict]] = None) -> Dict[str, Any]: |
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""" |
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Convert a ChatRequest message to a dict for the request payload. |
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Supports function calling, images, and model prefixes. |
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""" |
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content = "" |
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images_data = [] |
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image_urls = [] |
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|
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if isinstance(message.content, list): |
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for item in message.content: |
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if item.get("type") == "text": |
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content = item.get("text", "").strip() |
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elif item.get("type") == "image_url" and len(images_data) < 3: |
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image_url = item.get("image_url", {}).get("url", "") |
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if image_url: |
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|
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file_path = f"MultipleFiles/{uuid.uuid4().hex}.jpg" |
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images_data.append({"filePath": file_path, "contents": image_url}) |
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image_urls.append({"image_url": {"url": image_url}}) |
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elif isinstance(message.content, str): |
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content = message.content.strip() |
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if model_prefix and content: |
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content = f"{model_prefix} {content}" |
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base_message = {"role": message.role, "content": content} |
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if images_data: |
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base_message["data"] = { |
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"imageBase64": images_data[0]["contents"] if images_data else "", |
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"fileText": "", |
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"title": "snapshot", |
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"imagesData": images_data |
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} |
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for img in image_urls[1:]: |
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base_message["content"] = base_message.get("content", "") |
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base_message.setdefault("content", []).append(img) |
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return base_message if images_data else {"role": message.role, "content": content} |
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def strip_model_prefix(content: str, model_prefix: Optional[str] = None) -> str: |
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if model_prefix and content.startswith(model_prefix): |
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logger.debug(f"Stripping prefix '{model_prefix}' from content.") |
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return content[len(model_prefix):].strip() |
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return content |
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async def process_streaming_response(request: ChatRequest): |
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system_fingerprint = generate_system_fingerprint() |
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random_name, random_email, random_customer_id = get_random_name_email_customer() |
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|
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request_id = f"chatcmpl-{uuid.uuid4()}" |
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logger.info(f"Processing request (stream) {request_id} - Model: {request.model}") |
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agent_mode = AGENT_MODE.get(request.model, {}) |
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trending_agent_mode = TRENDING_AGENT_MODE.get(request.model, {}) |
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model_prefix = MODEL_PREFIXES.get(request.model, "") |
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headers_api_chat = get_headers_api_chat(BASE_URL) |
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if request.model == "o1-preview": |
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delay_seconds = random.randint(1, 60) |
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logger.info(f"Delay {delay_seconds}s for model 'o1-preview' (Request: {request_id})") |
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await asyncio.sleep(delay_seconds) |
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h_value = await getHid() |
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if not h_value: |
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logger.error("No h-value for validation.") |
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raise HTTPException(status_code=500, detail="Missing h-value.") |
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messages = [message_to_dict(msg, model_prefix=model_prefix, tools=request.tools) for msg in request.messages] |
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json_data = { |
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"agentMode": agent_mode, |
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"clickedAnswer2": False, |
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"clickedAnswer3": False, |
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"clickedForceWebSearch": False, |
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"codeInterpreterMode": False, |
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"codeModelMode": True, |
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"githubToken": "", |
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"deepSearchMode": False, |
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"domains": None, |
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"id": request_id, |
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"imageGenerationMode": False, |
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"isChromeExt": False, |
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"isMicMode": False, |
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"isPremium": True, |
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"isMemoryEnabled": False, |
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"maxTokens": request.max_tokens, |
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"messages": messages, |
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"mobileClient": False, |
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"playgroundTemperature": request.temperature, |
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"playgroundTopP": request.top_p, |
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"previewToken": None, |
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"trendingAgentMode": trending_agent_mode, |
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"userId": None, |
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"userSelectedModel": MODEL_MAPPING.get(request.model, request.model), |
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"userSystemPrompt": None, |
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"validated": h_value, |
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"visitFromDelta": False, |
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"webSearchModePrompt": False, |
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"vscodeClient": False, |
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"customProfile": {"name": "", "occupation": "", "traits": [], "additionalInfo": "", "enableNewChats": False}, |
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"webSearchModeOption": {"autoMode": False, "webMode": False, "offlineMode": True}, |
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"session": { |
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"user": {"name": random_name, "email": random_email, "image": "https://lh3.googleusercontent.com/a/...=s96-c", "subscriptionStatus": "PREMIUM"}, |
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"expires": datetime.now(timezone.utc).isoformat(timespec='milliseconds').replace('+00:00', 'Z'), |
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"subscriptionCache": {"customerId": random_customer_id, "status": "PREMIUM", "isTrialSubscription": "False", "expiryTimestamp": 1744652408, "lastChecked": int(time.time() * 1000)}, |
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"beastMode": False, |
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"reasoningMode": False, |
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"designerMode": False, |
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"workspaceId": "", |
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}, |
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} |
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|
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prompt_tokens = 0 |
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for msg in messages: |
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if "content" in msg: |
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prompt_tokens += calculate_tokens(msg["content"], request.model) |
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if "data" in msg and "imagesData" in msg["data"]: |
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for image_data in msg["data"]["imagesData"]: |
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prompt_tokens += calculate_tokens(image_data["contents"], request.model) |
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|
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completion_tokens = 0 |
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final_snapzion_links = [] |
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|
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async with httpx.AsyncClient() as client: |
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try: |
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async with client.stream("POST", f"{BASE_URL}/api/chat", headers=headers_api_chat, json=json_data, timeout=100) as response: |
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response.raise_for_status() |
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async for chunk in response.aiter_text(): |
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timestamp = int(datetime.now().timestamp()) |
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if not chunk: |
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continue |
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if chunk.startswith("$@$v=undefined-rv1$@$"): |
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chunk = chunk[21:] |
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if BLOCKED_MESSAGE in chunk: |
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logger.info(f"Blocked message found in chunk (Request: {request_id}).") |
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chunk = chunk.replace(BLOCKED_MESSAGE, "").strip() |
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if not chunk: |
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continue |
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if "https://storage.googleapis.com" in chunk: |
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chunk = chunk.replace("https://storage.googleapis.com", "https://cdn.snapzion.com") |
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snapzion_urls = re.findall(r"(https://cdn\.snapzion\.com[^\s\)]+)", chunk) |
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if snapzion_urls: |
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final_snapzion_links.extend(snapzion_urls) |
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cleaned_content = strip_model_prefix(chunk, model_prefix) |
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completion_tokens += calculate_tokens(cleaned_content, request.model) |
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|
|
|
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function_call = None |
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if cleaned_content and cleaned_content.startswith("{"): |
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try: |
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function_call = json.loads(cleaned_content) |
|
cleaned_content = None |
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except json.JSONDecodeError: |
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pass |
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|
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yield "data: " + json.dumps(create_chat_completion_data( |
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cleaned_content, |
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request.model, |
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timestamp, |
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request_id, |
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system_fingerprint, |
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prompt_tokens, |
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completion_tokens, |
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finish_reason=None, |
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function_call=function_call |
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)) + "\n\n" |
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yield "data: " + json.dumps(create_chat_completion_data("", request.model, timestamp, request_id, system_fingerprint, prompt_tokens, completion_tokens, "stop")) + "\n\n" |
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yield "data: [DONE]\n\n" |
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except httpx.HTTPStatusError as e: |
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logger.error(f"HTTP error (stream) {request_id}: {e}") |
|
error_message = f"HTTP error occurred: {e}" |
|
try: |
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error_details = e.response.json() |
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error_message += f" Details: {error_details}" |
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except ValueError: |
|
error_message += f" Response body: {e.response.text}" |
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yield "data: " + json.dumps(create_chat_completion_data(error_message, request.model, int(datetime.now().timestamp()), request_id, system_fingerprint, prompt_tokens, completion_tokens, "error")) + "\n\n" |
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yield "data: [DONE]\n\n" |
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except httpx.RequestError as e: |
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logger.error(f"Request error (stream) {request_id}: {e}") |
|
error_message = f"Request error occurred: {e}" |
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yield "data: " + json.dumps(create_chat_completion_data(error_message, request.model, int(datetime.now().timestamp()), request_id, system_fingerprint, prompt_tokens, completion_tokens, "error")) + "\n\n" |
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yield "data: [DONE]\n\n" |
|
except Exception as e: |
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logger.error(f"Unhandled error (stream) {request_id}: {e}") |
|
error_message = f"An unexpected error occurred: {e}" |
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yield "data: " + json.dumps(create_chat_completion_data(error_message, request.model, int(datetime.now().timestamp()), request_id, system_fingerprint, prompt_tokens, completion_tokens, "error")) + "\n\n" |
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yield "data: [DONE]\n\n" |
|
|
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last_user_prompt = get_last_user_prompt(request.messages) |
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upload_replaced_urls_to_r2(final_snapzion_links, alt_text=last_user_prompt) |
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|
|
|
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|
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async def process_non_streaming_response(request: ChatRequest): |
|
system_fingerprint = generate_system_fingerprint() |
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random_name, random_email, random_customer_id = get_random_name_email_customer() |
|
|
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request_id = f"chatcmpl-{uuid.uuid4()}" |
|
logger.info(f"Processing request (non-stream) {request_id} - Model: {request.model}") |
|
|
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agent_mode = AGENT_MODE.get(request.model, {}) |
|
trending_agent_mode = TRENDING_AGENT_MODE.get(request.model, {}) |
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model_prefix = MODEL_PREFIXES.get(request.model, "") |
|
|
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headers_api_chat = get_headers_api_chat(BASE_URL) |
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headers_chat = get_headers_chat(BASE_URL, next_action=str(uuid.uuid4()), next_router_state_tree=json.dumps([""])) |
|
|
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if request.model == "o1-preview": |
|
delay_seconds = random.randint(20, 60) |
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logger.info(f"Delay {delay_seconds}s for 'o1-preview' (Request: {request_id})") |
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await asyncio.sleep(delay_seconds) |
|
|
|
h_value = "00f37b34-a166-4efb-bce5-1312d87f2f94" |
|
if not h_value: |
|
logger.error("Failed to retrieve h-value.") |
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raise HTTPException(status_code=500, detail="Missing h-value.") |
|
|
|
messages = [message_to_dict(msg, model_prefix=model_prefix, tools=request.tools) for msg in request.messages] |
|
|
|
json_data = { |
|
"agentMode": agent_mode, |
|
"clickedAnswer2": False, |
|
"clickedAnswer3": False, |
|
"clickedForceWebSearch": False, |
|
"codeInterpreterMode": False, |
|
"codeModelMode": True, |
|
"githubToken": "", |
|
"deepSearchMode": False, |
|
"domains": None, |
|
"id": request_id, |
|
"imageGenerationMode": False, |
|
"isChromeExt": False, |
|
"isMicMode": False, |
|
"isPremium": True, |
|
"isMemoryEnabled": False, |
|
"maxTokens": request.max_tokens, |
|
"messages": messages, |
|
"mobileClient": False, |
|
"playgroundTemperature": request.temperature, |
|
"playgroundTopP": request.top_p, |
|
"previewToken": None, |
|
"trendingAgentMode": trending_agent_mode, |
|
"userId": None, |
|
"userSelectedModel": MODEL_MAPPING.get(request.model, request.model), |
|
"userSystemPrompt": None, |
|
"validated": h_value, |
|
"visitFromDelta": False, |
|
"webSearchModePrompt": False, |
|
"vscodeClient": False, |
|
"customProfile": {"name": "", "occupation": "", "traits": [], "additionalInfo": "", "enableNewChats": False}, |
|
"webSearchModeOption": {"autoMode": False, "webMode": False, "offlineMode": True}, |
|
"session": { |
|
"user": {"name": random_name, "email": random_email, "image": "https://lh3.googleusercontent.com/a/...=s96-c", "subscriptionStatus": "PREMIUM"}, |
|
"expires": datetime.now(timezone.utc).isoformat(timespec='milliseconds').replace('+00:00', 'Z'), |
|
"subscriptionCache": {"customerId": random_customer_id, "status": "PREMIUM", "isTrialSubscription": "False", "expiryTimestamp": 1744652408, "lastChecked": int(time.time() * 1000)}, |
|
"beastMode": False, |
|
"reasoningMode": False, |
|
"designerMode": False, |
|
"workspaceId": "", |
|
}, |
|
} |
|
|
|
prompt_tokens = 0 |
|
for msg in messages: |
|
if "content" in msg: |
|
prompt_tokens += calculate_tokens(msg["content"], request.model) |
|
if "data" in msg and "imagesData" in msg["data"]: |
|
for image_data in msg["data"]["imagesData"]: |
|
prompt_tokens += calculate_tokens(image_data["contents"], request.model) |
|
|
|
full_response = "" |
|
final_snapzion_links = [] |
|
|
|
async with httpx.AsyncClient() as client: |
|
try: |
|
async with client.stream("POST", f"{BASE_URL}/api/chat", headers=headers_api_chat, json=json_data) as response: |
|
response.raise_for_status() |
|
async for chunk in response.aiter_text(): |
|
full_response += chunk |
|
except httpx.HTTPStatusError as e: |
|
logger.error(f"HTTP error (non-stream) {request_id}: {e}") |
|
error_message = f"HTTP error occurred: {e}" |
|
try: |
|
error_details = e.response.json() |
|
error_message += f" Details: {error_details}" |
|
except ValueError: |
|
error_message += f" Response body: {e.response.text}" |
|
return { |
|
"id": request_id, |
|
"object": "chat.completion", |
|
"created": int(datetime.now().timestamp()), |
|
"model": request.model, |
|
"system_fingerprint": system_fingerprint, |
|
"choices": [{"index": 0, "message": {"role": "assistant", "content": error_message}, "finish_reason": "error"}], |
|
"usage": {"prompt_tokens": prompt_tokens, "completion_tokens": 0, "total_tokens": prompt_tokens}, |
|
} |
|
except httpx.RequestError as e: |
|
logger.error(f"Request error (non-stream) {request_id}: {e}") |
|
error_message = f"Request error occurred: {e}" |
|
return { |
|
"id": request_id, |
|
"object": "chat.completion", |
|
"created": int(datetime.now().timestamp()), |
|
"model": request.model, |
|
"system_fingerprint": system_fingerprint, |
|
"choices": [{"index": 0, "message": {"role": "assistant", "content": error_message}, "finish_reason": "error"}], |
|
"usage": {"prompt_tokens": prompt_tokens, "completion_tokens": 0, "total_tokens": prompt_tokens}, |
|
} |
|
except Exception as e: |
|
logger.error(f"Unexpected error (non-stream) {request_id}: {e}") |
|
error_message = f"An unexpected error occurred: {e}" |
|
return { |
|
"id": request_id, |
|
"object": "chat.completion", |
|
"created": int(datetime.now().timestamp()), |
|
"model": request.model, |
|
"system_fingerprint": system_fingerprint, |
|
"choices": [{"index": 0, "message": {"role": "assistant", "content": error_message}, "finish_reason": "error"}], |
|
"usage": {"prompt_tokens": prompt_tokens, "completion_tokens": 0, "total_tokens": prompt_tokens}, |
|
} |
|
|
|
if full_response.startswith("$@$v=undefined-rv1$@$"): |
|
full_response = full_response[21:] |
|
if BLOCKED_MESSAGE in full_response: |
|
full_response = full_response.replace(BLOCKED_MESSAGE, "").strip() |
|
if not full_response: |
|
raise HTTPException(status_code=500, detail="Blocked message in response.") |
|
if "https://storage.googleapis.com" in full_response: |
|
full_response = full_response.replace("https://storage.googleapis.com", "https://cdn.snapzion.com") |
|
snapzion_urls = re.findall(r"(https://cdn\.snapzion\.com[^\s\)]+)", full_response) |
|
for link in snapzion_urls: |
|
final_snapzion_links.append(link) |
|
cleaned_full_response = strip_model_prefix(full_response, model_prefix) |
|
completion_tokens = calculate_tokens(cleaned_full_response, request.model) |
|
last_user_prompt = get_last_user_prompt(request.messages) |
|
upload_replaced_urls_to_r2(final_snapzion_links, alt_text=last_user_prompt) |
|
|
|
return { |
|
"id": request_id, |
|
"object": "chat.completion", |
|
"created": int(datetime.now().timestamp()), |
|
"model": request.model, |
|
"system_fingerprint": system_fingerprint, |
|
"choices": [{"index": 0, "message": {"role": "assistant", "content": cleaned_full_response}, "finish_reason": "stop"}], |
|
"usage": {"prompt_tokens": prompt_tokens, "completion_tokens": completion_tokens, "total_tokens": prompt_tokens + completion_tokens}, |
|
} |
|
|