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proxyless-llm-websearch

⭐ 122 stars Dutch by itshyao

🌐 Taal

🧠 Proxyloze LLM Webzoekmachine

Een proxyloze multi-zoekmachine LLM-web retrieval tool, ondersteunt URL-inhoudsanalyse en webpagina crawling, combineert LangGraph en LangGraph-MCP voor modulaire agent-chaining. Speciaal ontworpen voor externe kennisoproep door grote taalmodellen, ondersteunt Playwright + Crawl4AI voor webpagina-ophaling en -analyse, ondersteunt asynchrone parallelle verwerking, inhoudssnijden en herordening/filtering.

🚀 Changelog

✨ Overzicht van functies

workflow

framework

⚡ Snel aan de slag

Repository klonen

git clone https://github.com/itshyao/proxyless-llm-websearch.git
cd proxyless-llm-websearch

Installatie van afhankelijkheden

pip install -r requirements.txt
python -m playwright install

Configuratie van omgevingsvariabelen

# 百炼llm
OPENAI_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
OPENAI_API_KEY=sk-xxx
MODEL_NAME=qwen-plus-latest

百炼embedding

EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1 EMBEDDING_API_KEY=sk-xxx EMBEDDING_MODEL_NAME=text-embedding-v4

百炼reranker

RERANK_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1 RERANK_API_KEY=sk-xxx RERANK_MODEL=gte-rerank-v2

Langgraph-Agent

#### DEMONSTRATIE

python agent/demo.py

#### API SERVEREN

python agent/api_serve.py

import requests

url = "http://localhost:8800/search"

data = { "question": "广州今日天气", "engine": "bing", "split": { "chunk_size": 512, "chunk_overlap": 128 }, "rerank": { "top_k": 5 } }

try: response = requests.post( url, json=data )

if response.status_code == 200: print("✅ 请求成功!") print("响应内容:", response.json()) else: print(f"❌ 请求失败,状态码:{response.status_code}") print("错误信息:", response.text)

except requests.exceptions.RequestException as e: print(f"⚠️ 请求异常:{str(e)}")

#### Gradio

python agent/gradio_demo.py

gradio

gradio

#### docker

docker-compose -f docker-compose-ag.yml up -d --build

Langgrph-MCP

#### Start MCP-service

python mcp/websearch.py

#### DEMONSTRATIE

python mcp/demo.py

#### API SERVEREN

python mcp/api_serve.py

import requests

url = "http://localhost:8800/search"

data = { "question": "广州今日天气" }

try: response = requests.post( url, json=data )

if response.status_code == 200: print("✅ 请求成功!") print("响应内容:", response.json()) else: print(f"❌ 请求失败,状态码:{response.status_code}") print("错误信息:", response.text)

except requests.exceptions.RequestException as e: print(f"⚠️ 请求异常:{str(e)}")

#### docker

docker-compose -f docker-compose-mcp.yml up -d --build

Aangepaste module

#### Aangepaste blokverdeling

from typing import Optional, List

class YourSplitter: def __init__(self, text: str, chunk_size: int = 512, chunk_overlap: int = 128): self.text = text self.chunk_size = chunk_size self.chunk_overlap = chunk_overlap

def split_text(self, text: Optional[str] = None) -> List: # TODO: implement splitting logic return ["your chunk"]

#### Aangepaste herschikking

from typing import List, Union, Tuple

class YourReranker: async def get_reranked_documents( self, query: Union[str, List[str]], documents: List[str], ) -> Union[ Tuple[List[str]], Tuple[List[int]], ]: return ["your chunk"], ["chunk index"]

🔍 Vergelijking met online netwerkzoektests

We vergelijken het project met enkele toonaangevende online API's en beoordelen hun prestaties bij complexe vraagstukken.

🔥 Dataset

🧑‍🏫 Vergelijkingsresultaten

| Zoekmachine/Systeem | ✅ Correct | ❌ Incorrect | ⚠️ Gedeeltelijk correct | | ------------------- | ---------- | ------------ | ----------------------- | | Volcano Ark | 5,00% | 72,21% | 22,79% | | Bailian | 9,85% | 62,79% | 27,35% | | Onze | 19,85% | 47,94% | 32,06% |

🙏 Dankwoord

Enkele functies van dit project zijn mogelijk gemaakt en geïnspireerd door de volgende open source projecten. Onze oprechte dank:

--- Tranlated By Open Ai Tx | Last indexed: 2025-09-08 ---