venv uvicorn python 虚拟服务器外网无法访问

python -m venv .venv
source ./.venv/bin/activate
pip install -r requirements.txt
./run.sh

source ./.venv/bin/activate
uvicorn main:app --reload

虚拟web服务器外网访问控制台启动命令用以下代码启动
uvicorn main:app --host 0.0.0.0 --port 8501 --reload
启动到后台

nohup uvicorn main:app --host 0.0.0.0 --port 8501 --reload &

main.py

import xmltodict
import anthropic
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse, StreamingResponsefrom prompt_constructors import *from claude import ClaudeLlm  # claude.py から ClaudeLlm クラスをインポート
import os
import base64app = FastAPI()
api_key = "your key"
client = anthropic.Anthropic(api_key=api_key)# @app.middleware("http")
# async def log_body(request: Request, call_next):
#     body = await request.body()
#     print("HTTP REQUEST BODY: ", body)
#     return await call_next(request)# The anthropic API does not have a method to list models, so we are hard coding the models here
@app.get("/models")
async def list_models() -> JSONResponse:return JSONResponse(content={"data": [{"id": "claude-3-sonnet-20240229", "name": "Anthropic Claude 3 Sonnet"},{"id": "anthropic.claude-3-sonnet-20240229-v1:0", "name": "AWS Bedrock Anthropic Claude 3 Sonnet"},{"id": "claude-3-opus-20240229", "name": "Anthropic Claude 3 Opus"},]})def map_req(req: dict) -> dict:messages = req["messages"]mapped_req = {"messages": messages,}return mapped_req@app.post("/chat/completions")
async def completions(request: Request) -> StreamingResponse:data = await request.body()req = map_req(json.loads(data))messages=req["messages"]claude = ClaudeLlm(client, messages)resp = claude.generate_responses("claude-3-opus-20240229")return StreamingResponse(resp, media_type="application/x-ndjson")def map_resp(response) -> str:data = json.loads(response)finish_reason = Noneparsed_tool_calls = []for message in data["content"]:if 'text' in message.keys() and message["text"].startswith("<function_calls>"):xml_tool_calls = message["text"] + "</function_calls>"tool_calls = xmltodict.parse(xml_tool_calls)if tool_calls["function_calls"]["invoke"] is list:for key, value in tool_calls["function_calls"]["invoke"].items():parsed_tool_calls.append({"index": 0,"id": value['tool_name'],"type": "function","function": {"name": value["tool_name"],"arguments": str(value["parameters"]),},})else:parsed_tool_calls.append({"index": 0,"id": tool_calls["function_calls"]["invoke"]["tool_name"],"type": "function","function": {"name": tool_calls["function_calls"]["invoke"]["tool_name"],"arguments": json.dumps(tool_calls["function_calls"]["invoke"]["parameters"]),},})message.pop("text", None)message.pop("type", None)message["tool_calls"] = parsed_tool_callsmessage["content"] = Nonemessage["role"] = "assistant"if 'text' in message.keys():message["content"] = message["text"]if "stop_reason" in data.keys() and data["stop_reason"] == "stop_sequence":finish_reason = "tool_calls"if "stop_reason" in data.keys() and data["stop_reason"] == "end_turn":finish_reason = "stop"translated = {"id": data["id"],"object": "chat.completion.chunk","created": 0,"model": data["model"],"system_fingerprint": "TEMP","choices": [{"index": 0,"delta": data["content"][0],},],"finish_reason": finish_reason,}return json.dumps(translated)

claude.py

import pandas as pd
from forex_python.converter import CurrencyRates
import time
import anthropic
from anthropic.types.message_stream_event import MessageStartEvent, MessageDeltaEvent, ContentBlockDeltaEventclass ClaudeLlm:def __init__(self, client, user_input):self.client = clientself.user_input = user_inputself.cost_df = pd.DataFrame(columns=["Model", "Input Tokens", "Output Tokens", "Input Cost", "Output Cost", "Total Cost", "総計_円換算", "処理時間"])def convert_usd_to_jpy(self, usd_amount):c = CurrencyRates()try:rate = c.get_rate('USD', 'JPY')jpy_rate = (f"為替レート: {rate:.2f}円/ドル")return usd_amount * rate, jpy_rateexcept Exception as e:rate = 150  # フォールバックとして使用する為替レートjpy_rate = (f"為替レート: {rate:.2f}円/ドル想定")return usd_amount * rate, jpy_ratedef calculate_cost(self, model, input_tokens, output_tokens):token_costs = {"claude-3-opus-20240229": {"input": 0.000015, "output": 0.000075},"claude-3-sonnet-20240229": {"input": 0.000003, "output": 0.000015},}model_costs = token_costs[model]input_cost = input_tokens * model_costs["input"]output_cost = output_tokens * model_costs["output"]total_cost = input_cost + output_costreturn input_cost, output_cost, total_costdef generate_responses(self, model_name):start_time = time.time()input_tokens = 0output_tokens = 0try:with self.client.messages.stream(model=model_name,max_tokens=1024,messages=[{"role": "user", "content": self.user_input}],) as stream:for event in stream:if isinstance(event, MessageStartEvent):usage_info = event.message.usageinput_tokens = usage_info.input_tokenselif isinstance(event, MessageDeltaEvent):output_tokens = event.usage.output_tokenselif isinstance(event, ContentBlockDeltaEvent):return_text = event.delta.textyield return_textexcept anthropic.APIStatusError as e:error_response = e.response.json()if 'error' in error_response and error_response['error'].get('type') == 'overloaded_error':return "APIが過負荷状態です。しばらくしてから再試行してください。"input_cost, output_cost, total_cost = self.calculate_cost(model_name, input_tokens, output_tokens)jpy_total_cost, _ = self.convert_usd_to_jpy(total_cost)end_time = time.time()response_time = end_time - start_timenew_row = {"Model": model_name,"Input Tokens": input_tokens,"Output Tokens": output_tokens,"Input Cost": f"${input_cost:.6f}","Output Cost": f"${output_cost:.6f}","Total Cost": f"${total_cost:.6f}","総計_円換算": f"¥{jpy_total_cost:.3f}","処理時間": f"{response_time:.2f}秒"}new_row_df = pd.DataFrame([new_row])self.cost_df = pd.concat([self.cost_df, new_row_df], ignore_index=True)return self.cost_df