src/api/llm_api.py

from typing import List, Dict
from abc import ABC, abstractmethod
from openai import OpenAI
import logging
import httpx

class LLMInterface(ABC):
    @abstractmethod
    def generate(self, prompt: str) -> str:
        pass

class DeepseekInterface(LLMInterface):
    def __init__(self, api_key: str, base_url: str, model: str):
        self.api_key = api_key
        self.base_url = base_url
        self.model = model
        self.headers = {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        }
    
    def _build_system_prompt(self, role: str) -> str:
        """构建系统提示词"""
        roles = {
            "summarizer": "You are a professional tourism content analyst, good at extracting and summarizing key tourism-related information. Please answer in English",
            "planner": "You are a professional travel planner who is good at making detailed travel plans. Please answer in English"
        }
        return roles.get(role, "You are a professional AI assistant. Please answer in English")
    
    def generate(self, prompt: str, role: str = "planner") -> str:
        import requests
        from requests.adapters import HTTPAdapter
        from urllib3.util.retry import Retry
        
        session = requests.Session()
        retries = Retry(
            total=3,
            backoff_factor=1,
            status_forcelist=[500, 502, 503, 504]
        )
        session.mount('https://', HTTPAdapter(max_retries=retries))
        
        payload = {
            "model": self.model,
            "messages": [
                {
                    "role": "system", 
                    "content": self._build_system_prompt(role)
                },
                {
                    "role": "user", 
                    "content": prompt
                }
            ],
            "temperature": 0.7,
            "max_tokens": 2000
        }
        
        try:
            response = session.post(
                f"{self.base_url}/v1/chat/completions",
                headers=self.headers,
                json=payload,
                timeout=(10, 60)
            )
            response.raise_for_status()
            return response.json()['choices'][0]['message']['content']
        except requests.exceptions.Timeout:
            print("Deepseek API request timeout, retrying...")
            return "Sorry, due to network issues, content generation is temporarily unavailable. Please try again later."
        except requests.exceptions.RequestException as e:
            print(f"Error calling Deepseek API: {str(e)}")
            return "Sorry, an error occurred while generating content. Please try again later."

    def summarize_document(self, content: str, title: str, url: str) -> str:
        """使用 Deepseek 总结文档"""
        prompt = f"""Please analyze the following tourism web content and generate a rich summary paragraph.

Web Title: {title}
Web Link: {url}

Web Content:
{content[:4000]}

Requirements:
1. The summary should be between 300-500 words
2. Keep the most important tourism information (attractions, suggestions, tips, etc.)
3. Use an objective tone
4. Information should be accurate and practical
5. Remove marketing and advertising content
6. Maintain logical coherence

Please return the summary content directly, without any other explanation."""
        
        return self.generate(prompt, role="summarizer")

    def generate_travel_plan(self, query: str, context: List[Dict]) -> str:
        # 构建更结构化的上下文
        context_text = "\n\n".join([
            f"Source {i+1} ({doc.get('title', 'Unknown Title')}):\n{doc['passage']}" 
            for i, doc in enumerate(context)
        ])
        
        prompt = f"""As a professional travel planner, please create a detailed travel plan based on the user's needs and reference materials.

User Needs: {query}

Reference Materials:
{context_text}

Please provide the following content:
1. Itinerary Overview (Overall arrangement and key attractions)
2. Daily detailed itinerary (includes specific time, location, and transportation methods)
3. Traffic suggestions (includes practical APP recommendations)
4. Accommodation recommendations (includes specific areas and hotel suggestions)
5. Food recommendations (includes specialty restaurants and snacks)
6. Practical tips (weather, clothing, essential items, etc.)

Requirements:
1. The itinerary should be reasonable, considering the distance between attractions
2. Provide specific time points
3. Include detailed traffic guidance
4. Suggestions should be specific and practical
5. Consider actual conditions (e.g., opening hours of attractions)

Please return the travel plan content directly, without any other explanation."""

        return self.generate(prompt, role="planner")

class OllamaInterface(LLMInterface):
    def __init__(self, base_url: str, model: str):
        self.base_url = base_url.rstrip('/')
        self.model = model
        self.headers = {
            "Content-Type": "application/json"
        }
    
    def _build_system_prompt(self, role: str) -> str:
        """构建系统提示词"""
        roles = {
            "summarizer": "You are a professional tourism content analyst, good at extracting and summarizing key tourism-related information. Please answer in English",
            "planner": "You are a professional travel planner who is good at making detailed travel plans. Please answer in English"
        }
        return roles.get(role, "You are a professional AI assistant. Please answer in English")
    
    def generate(self, prompt: str, role: str = "planner") -> str:
        import requests
        
        payload = {
            "model": self.model,
            "messages": [
                {
                    "role": "system",
                    "content": self._build_system_prompt(role)
                },
                {
                    "role": "user",
                    "content": prompt
                }
            ],
            "stream": False
        }
        
        try:
            response = requests.post(
                f"{self.base_url}/api/chat",
                headers=self.headers,
                json=payload,
                timeout=(10, 60)
            )
            response.raise_for_status()
            return response.json()['message']['content']
        except Exception as e:
            print(f"Error calling Ollama API: {str(e)}")
            return "Sorry, an error occurred while generating content. Please try again later."

    def summarize_document(self, content: str, title: str, url: str) -> str:
        """使用 Ollama 总结文档"""
        prompt = f"""Please analyze the following tourism web content and generate a rich summary paragraph.

Web Title: {title}
Web Link: {url}

Web Content:
{content[:4000]}

Requirements:
1. The summary should be between 300-500 words
2. Keep the most important tourism information (attractions, suggestions, tips, etc.)
3. Use an objective tone
4. Information should be accurate and practical
5. Remove marketing and advertising content
6. Maintain logical coherence

Please return the summary content directly, without any other explanation."""
        
        return self.generate(prompt, role="summarizer")

    def generate_travel_plan(self, query: str, context: List[Dict]) -> str:
        # 构建更结构化的上下文
        context_text = "\n\n".join([
            f"来源 {i+1} ({doc.get('title', '未知标题')}):\n{doc['passage']}" 
            for i, doc in enumerate(context)
        ])
        
        prompt = f"""As a professional travel planner, please create a detailed travel plan based on the user's needs and reference materials.

User Needs: {query}

Reference Materials:
{context_text}

Please provide the following content:
1. Itinerary Overview (Overall arrangement and key attractions)
2. Daily detailed itinerary (includes specific time, location, and transportation methods)
3. Traffic suggestions (includes practical APP recommendations)
4. Accommodation recommendations (includes specific areas and hotel suggestions)
5. Food recommendations (includes specialty restaurants and snacks)
6. Practical tips (weather, clothing, essential items, etc.)

Requirements:
1. The itinerary should be reasonable, considering the distance between attractions
2. Provide specific time points
3. Include detailed traffic guidance
4. Suggestions should be specific and practical
5. Consider actual conditions (e.g., opening hours of attractions)

Please return the travel plan content directly, without any other explanation."""

        return self.generate(prompt, role="planner")

class OpenAIInterface(LLMInterface):
    def __init__(self, api_key: str, model: str = "gpt-4o", base_url: str = "https://api.feidaapi.com/v1"):
        self.api_key = api_key
        self.model = model
        self.client = OpenAI(api_key=api_key, base_url=base_url)
    
    def _build_system_prompt(self, role: str) -> str:
        """构建系统提示词"""
        roles = {
            "summarizer": "You are a professional tourism content analyst, good at extracting and summarizing key tourism-related information. Please answer in English",
            "planner": "You are a professional travel planner who is good at making detailed travel plans. Please answer in English"
        }
        return roles.get(role, "You are a professional AI assistant. Please answer in English")
    
    def generate(self, prompt: str, role: str = "planner") -> str:
        try:
            messages = [
                {"role": "system", "content": self._build_system_prompt(role)},
                {"role": "user", "content": prompt}
            ]
            
            response = self.client.chat.completions.create(
                model=self.model,
                messages=messages,
                temperature=0.7,
                max_tokens=2000
            )
            
            return response.choices[0].message.content
            
        except Exception as e:
            logging.error(f"Error calling OpenAI API: {str(e)}")
            return "Sorry, an error occurred while generating content. Please try again later."

    def summarize_document(self, content: str, title: str, url: str) -> str:
        """使用 OpenAI 总结文档"""
        prompt = f"""Please analyze the following tourism web content and generate a rich summary paragraph.

Web Title: {title}
Web Link: {url}

Web Content:
{content[:4000]}

Requirements:
1. The summary should be between 300-500 words
2. Keep the most important tourism information (attractions, suggestions, tips, etc.)
3. Use an objective tone
4. Information should be accurate and practical
5. Remove marketing and advertising content
6. Maintain logical coherence

Please return the summary content directly, without any other explanation."""
        
        return self.generate(prompt, role="summarizer")

    def generate_travel_plan(self, query: str, context: List[Dict]) -> str:
        # 构建更结构化的上下文
        context_text = "\n\n".join([
            f"Source {i+1} ({doc.get('title', 'Unknown Title')}):\n{doc['passage']}" 
            for i, doc in enumerate(context)
        ])
        
        prompt = f"""As a professional travel planner, please create a detailed travel plan based on the user's needs and reference materials.

User Needs: {query}

Reference Materials:
{context_text}

Please provide the following content:
1. Itinerary Overview (Overall arrangement and key attractions)
2. Daily detailed itinerary (includes specific time, location, and transportation methods)
3. Traffic suggestions (includes practical APP recommendations)
4. Accommodation recommendations (includes specific areas and hotel suggestions)
5. Food recommendations (includes specialty restaurants and snacks)
6. Practical tips (weather, clothing, essential items, etc.)

Requirements:
1. The itinerary should be reasonable, considering the distance between attractions
2. Provide specific time points
3. Include detailed traffic guidance
4. Suggestions should be specific and practical
5. Consider actual conditions (e.g., opening hours of attractions)

Please return the travel plan content directly, without any other explanation."""

        return self.generate(prompt, role="planner")