diff options
Diffstat (limited to 'autoAidModules/search_funcs.py')
| -rw-r--r-- | autoAidModules/search_funcs.py | 35 |
1 files changed, 30 insertions, 5 deletions
diff --git a/autoAidModules/search_funcs.py b/autoAidModules/search_funcs.py index 241872e..e69ed47 100644 --- a/autoAidModules/search_funcs.py +++ b/autoAidModules/search_funcs.py @@ -1,16 +1,22 @@ +import os + from serpapi import GoogleSearch from .sample_res import res from boilerpy3 import extractors from fake_useragent import UserAgent +from langchain.llms import Bedrock +from langchain.prompts.prompt import PromptTemplate import requests extractor = extractors.ArticleExtractor() preferred_forums = { - "BMW": ["bimmerforums.com"] + "BMW": ["bimmerforums.com"], + "Subaru": ["nasioc.com"] } +llm = Bedrock(model_id="anthropic.claude-instant-v1") ua = UserAgent() """ @@ -29,7 +35,12 @@ Website data: def find_preferred_forums(make): if make not in preferred_forums: - return None + template = "Human: If BMW: bimmerforums.com, Subaru: nasioc.com, Mazda: forum.miata.net What is the best forum for {make}? No more explanation\n\nAssistant: Then {make}:" + prompt = PromptTemplate(input_variables=["make"], template=template) + pred = llm.predict(prompt.format(make=make), max_tokens_to_sample=30, temperature=1,top_k=250, top_p=0.999) + make_url = pred.strip().split()[0] + print(f"Found {make_url} for {make}") + preferred_forums[make] = [make_url] return preferred_forums[make] def get_preferred_forums(make): @@ -41,6 +52,20 @@ def parse_page(url): content = extractor.get_content_from_url(url) return content +def get_tasks_from_pages(pages: list = [], query: str = "", details: str = ""): + template = "Human: You are an beginner mechanic. You are trying to solve the problem of {query} and have a {details}.\n Generate simple tasks from the following pages:\n {pages}\n\nAssistant: I would try all of the following, one by one:\n\n- Have you tried turning your car on and off?\n- " + prompt_template = PromptTemplate(input_variables=["query", "details", "pages"], template=template) + + + pred = llm.predict( + prompt_template.format( + query=query, details=details, pages=pages + ), max_tokens_to_sample=501, temperature=1,top_k=250, top_p=0.999 + ) + pred = "- " + pred + print(pred) + return pred + def search_on_forum(forum, query, max_results: int = 5): params = { @@ -49,12 +74,12 @@ def search_on_forum(forum, query, max_results: int = 5): "hl": "en", "gl": "us", "google_domain": "google.com", - "api_key": "KEY" + "api_key": os.environ.get("SERP_API_KEY", "demo") } #search = GoogleSearch(params) #results = search.get_dict() - results = res + results = res # Debugging Data if results["search_metadata"]['status'] == "Success": data = [] for idx, result in enumerate(results["organic_results"]): @@ -73,4 +98,4 @@ def search_on_forum(forum, query, max_results: int = 5): data.append(new_dict) return data else: - return []
\ No newline at end of file + return [] |