import os from omegaconf import OmegaConf import requests from typing import Tuple from bs4 import BeautifulSoup from dotenv import load_dotenv load_dotenv(override=True) from pydantic import Field, BaseModel from vectara_agent.agent import Agent from vectara_agent.tools import ToolsFactory, VectaraToolFactory from vectara_agent.tools_catalog import summarize_text initial_prompt = "How can I help you today?" get_headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:98.0) Gecko/20100101 Firefox/98.0", "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8", "Accept-Language": "en-US,en;q=0.5", "Accept-Encoding": "gzip, deflate", "Connection": "keep-alive", } def create_assistant_tools(cfg): class QueryHackerNews(BaseModel): query: str = Field(..., description="The user query.") vec_factory = VectaraToolFactory(vectara_api_key=cfg.api_key, vectara_customer_id=cfg.customer_id, vectara_corpus_id=cfg.corpus_id) tools_factory = ToolsFactory() ask_hackernews = vec_factory.create_rag_tool( tool_name = "ask_hackernews", tool_description = """ Responds to query based on information and stories in hacker news from the last 6-9 months. """, tool_args_schema = QueryHackerNews, reranker = "multilingual_reranker_v1", rerank_k = 100, n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005, summary_num_results = 10, vectara_summarizer = 'vectara-summary-ext-24-05-med-omni', include_citations = True, ) def get_top_stories( n_stories: int = Field(default=10, description="The number of top stories to return.") ) -> list[str]: """ Get the top stories from hacker news. Returns a list of story IDS for the top stories right now. These are the top stories on hacker news. """ db_url = 'https://hacker-news.firebaseio.com/v0/' top_stories = requests.get(f"{db_url}topstories.json").json() return top_stories[:n_stories] def get_show_stories( n_stories: int = Field(default=10, description="The number of top SHOW HN stories to return.") ) -> list[str]: """ Get the top SHOW HN stories from hacker news. Returns a list of story IDS for the top SHOW HN stories right now. These are stories where users show their projects. """ db_url = 'https://hacker-news.firebaseio.com/v0/' top_stories = requests.get(f"{db_url}showstories.json").json() return top_stories[:n_stories] def get_ask_stories( n_stories: int = Field(default=10, description="The number of top ASK HN stories to return.") ) -> list[str]: """ Get the top ASK HN stories from hacker news. Returns a list of story IDS for the top ASK HN stories right now. These are stories where users ask questions to the community. """ db_url = 'https://hacker-news.firebaseio.com/v0/' top_stories = requests.get(f"{db_url}askstories.json").json() return top_stories[:n_stories] def get_story_details( story_id: str = Field(..., description="The story ID.") ) -> Tuple[str, str]: """ Get the title of a story from hacker news. Returns: - The title of the story (str) - The main URL of the story (str) - The external link pointed to in the story (str) """ db_url = 'https://hacker-news.firebaseio.com/v0/' story = requests.get(f"{db_url}item/{story_id}.json").json() story_url = f'https://news.ycombinator.com/item?id={story_id}' return story['title'], story_url, story['url'], def get_story_text( story_id: str = Field(..., description="The story ID.") ) -> str: """ Get the text of the story from hacker news (original text + all comments) Returns the extracted text of the story as a string. """ url = f'https://news.ycombinator.com/item?id={story_id}' html = requests.get(url, headers=get_headers).text soup = BeautifulSoup(html, 'html5lib') for element in soup.find_all(['script', 'style']): element.decompose() text = soup.get_text(" ", strip=True).replace('\n', ' ') return text def whats_new( n_stories: int = Field(default=10, description="The number of new stories to return.") ) -> list[str]: """ Provides a succint summary of what is new in the hackernews community by summarizing the content and comments of top stories. Returns a string with the summary. """ stories = get_top_stories(n_stories) texts = [get_story_text(story_id) for story_id in stories[:n_stories]] all_stories = '---------\n\n'.join(texts) return summarize_text(all_stories) return ( [tools_factory.create_tool(tool) for tool in [ get_top_stories, get_show_stories, get_ask_stories, get_story_details, get_story_text, whats_new, ] ] + tools_factory.get_llama_index_tools("tavily_research", "TavilyToolSpec", api_key=cfg.tavily_api_key) + tools_factory.standard_tools() + tools_factory.guardrail_tools() + [ask_hackernews] ) def initialize_agent(_cfg, update_func = None): bot_instructions = """ - You are a helpful assistant, with expertise in answering user questions based on Hacker News stories and comments. - Give slight preference to newer stories when answering questions. - Use the ask_hackernews tool to find relevant Hacker News stories and respond to user queries based on that information. - when you include links to Hacker News stories, use the actual title of the story as the link's displayed text. Don't use text like "Source" which doesn't tell the user what the link is about. - Don't include external links in your responses unless the user asks for them. - The Tavily tools are available to help you find information on the web, but only use them with user request - don't lose your focus on HackerNews as a source. """ agent = Agent( tools=create_assistant_tools(_cfg), topic="hacker news", custom_instructions=bot_instructions, update_func=update_func ) agent.report() return agent def get_agent_config() -> OmegaConf: cfg = OmegaConf.create({ 'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']), 'corpus_id': str(os.environ['VECTARA_CORPUS_ID']), 'api_key': str(os.environ['VECTARA_API_KEY']), 'examples': os.environ.get('QUERY_EXAMPLES', None), 'demo_welcome': "Welcome to the Hacker News Assistant demo.", 'demo_description': "This demo can be used to ask about Hacker News.", 'tavily_api_key': str(os.environ['TAVILY_API_KEY']), }) return cfg