Delete utils.py

utils.py

@@ -1,105 +0,0 @@
-import json
-import uuid
-import time
-import tiktoken
-from constants import CHAT_COMPLETION_CHUNK, CONTENT_TYPE_EVENT_STREAM
-from flask import jsonify
-
-def generate_system_fingerprint():
-    """生成并返回唯一的系统指纹。"""
-    return f"fp_{uuid.uuid4().hex[:10]}"
-
-def create_openai_chunk(content, model, finish_reason=None, usage=None):
-    """创建格式化的 OpenAI 响应块。"""
-    chunk = {
-        "id": f"chatcmpl-{uuid.uuid4()}",
-        "object": CHAT_COMPLETION_CHUNK,
-        "created": int(time.time()),
-        "model": model,
-        "system_fingerprint": generate_system_fingerprint(),
-        "choices": [
-            {
-                "index": 0,
-                "delta": {"content": content} if content else {},
-                "logprobs": None,
-                "finish_reason": finish_reason
-            }
-        ]
-    }
-    if usage is not None:
-        chunk["usage"] = usage
-    return chunk
-
-def count_tokens(text, model="gpt-3.5-turbo-0301"):
-    """计算给定文本的令牌数量。"""
-    try:
-        return len(tiktoken.encoding_for_model(model).encode(text))
-    except KeyError:
-        return len(tiktoken.get_encoding("cl100k_base").encode(text))
-
-def count_message_tokens(messages, model="gpt-3.5-turbo-0301"):
-    """计算消息列表中的总令牌数量。"""
-    return sum(count_tokens(str(message), model) for message in messages)
-
-def stream_notdiamond_response(response, model):
-    """流式处理 notdiamond API 响应。"""
-    buffer = ""
-
-    for chunk in response.iter_content(1024):
-        if chunk:
-            buffer = chunk.decode('utf-8')
-            yield create_openai_chunk(buffer, model)
-    
-    yield create_openai_chunk('', model, 'stop')
-
-def handle_non_stream_response(response, model, prompt_tokens):
-    """处理非流式 API 响应并构建最终 JSON。"""
-    full_content = ""
-    
-    for chunk in stream_notdiamond_response(response, model):
-        if chunk['choices'][0]['delta'].get('content'):
-            full_content += chunk['choices'][0]['delta']['content']
-
-    completion_tokens = count_tokens(full_content, model)
-    total_tokens = prompt_tokens + completion_tokens
-
-    return jsonify({
-        "id": f"chatcmpl-{uuid.uuid4()}",
-        "object": "chat.completion",
-        "created": int(time.time()),
-        "model": model,
-        "system_fingerprint": generate_system_fingerprint(),
-        "choices": [
-            {
-                "index": 0,
-                "message": {
-                    "role": "assistant",
-                    "content": full_content
-                },
-                "finish_reason": "stop"
-            }
-        ],
-        "usage": {
-            "prompt_tokens": prompt_tokens,
-            "completion_tokens": completion_tokens,
-            "total_tokens": total_tokens
-        }
-    })
-
-def generate_stream_response(response, model, prompt_tokens):
-    """生成流式 HTTP 响应。"""
-    total_completion_tokens = 0
-    
-    for chunk in stream_notdiamond_response(response, model):
-        content = chunk['choices'][0]['delta'].get('content', '')
-        total_completion_tokens += count_tokens(content, model)
-        
-        chunk['usage'] = {
-            "prompt_tokens": prompt_tokens,
-            "completion_tokens": total_completion_tokens,
-            "total_tokens": prompt_tokens + total_completion_tokens
-        }
-        
-        yield f"data: {json.dumps(chunk)}\n\n"
-    
-    yield "data: [DONE]\n\n"