mirror of
https://github.com/tcsenpai/agenticSeek.git
synced 2025-06-06 11:05:26 +00:00
223 lines
9.3 KiB
Python
223 lines
9.3 KiB
Python
import re
|
||
import time
|
||
|
||
from sources.utility import pretty_print, animate_thinking
|
||
from sources.agents.agent import Agent
|
||
from sources.tools.searxSearch import searxSearch
|
||
from sources.browser import Browser
|
||
from datetime import date
|
||
|
||
class BrowserAgent(Agent):
|
||
def __init__(self, model, name, prompt_path, provider):
|
||
"""
|
||
The Browser agent is an agent that navigate the web autonomously in search of answer
|
||
"""
|
||
super().__init__(model, name, prompt_path, provider)
|
||
self.tools = {
|
||
"web_search": searxSearch(),
|
||
}
|
||
self.role = "web search, internet browsing, news"
|
||
self.browser = Browser()
|
||
self.search_history = []
|
||
self.navigable_links = []
|
||
self.notes = []
|
||
self.date = self.get_today_date()
|
||
|
||
def get_today_date(self) -> str:
|
||
date_time = date.today()
|
||
return date_time.strftime("%B %d, %Y")
|
||
|
||
def extract_links(self, search_result: str):
|
||
pattern = r'(https?://\S+|www\.\S+)'
|
||
matches = re.findall(pattern, search_result)
|
||
trailing_punct = ".,!?;:"
|
||
cleaned_links = [link.rstrip(trailing_punct) for link in matches]
|
||
return self.clean_links(cleaned_links)
|
||
|
||
def clean_links(self, links: list):
|
||
links_clean = []
|
||
for link in links:
|
||
link = link.strip()
|
||
if link[-1] == '.':
|
||
links_clean.append(link[:-1])
|
||
else:
|
||
links_clean.append(link)
|
||
return links_clean
|
||
|
||
def get_unvisited_links(self):
|
||
return "\n".join([f"[{i}] {link}" for i, link in enumerate(self.navigable_links) if link not in self.search_history])
|
||
|
||
def make_newsearch_prompt(self, user_prompt: str, search_result: dict):
|
||
search_choice = self.stringify_search_results(search_result)
|
||
return f"""
|
||
Based on the search result:
|
||
{search_choice}
|
||
Your goal is to find accurate and complete information to satisfy the user’s request.
|
||
User request: {user_prompt}
|
||
To proceed, choose a relevant link from the search results. Announce your choice by saying: "I want to navigate to <link>"
|
||
Do not explain your choice.
|
||
"""
|
||
|
||
def make_navigation_prompt(self, user_prompt: str, page_text: str):
|
||
remaining_links = self.get_unvisited_links()
|
||
remaining_links_text = remaining_links if remaining_links is not None else "No links remaining, proceed with a new search."
|
||
return f"""
|
||
You are a web browser.
|
||
You are currently on this webpage:
|
||
{page_text}
|
||
|
||
You can navigate to these navigation links:
|
||
{remaining_links}
|
||
|
||
Your task:
|
||
1. Decide if the current page answers the user’s query: {user_prompt}
|
||
- If it does, take notes of the useful information, write down source, link or reference, then move to a new page.
|
||
- If it does and you are 100% certain that it provide a definive answer, say REQUEST_EXIT
|
||
- If it doesn’t, say: Error: This page does not answer the user’s query then go back or navigate to another link.
|
||
2. Navigate by either:
|
||
- Navigate to a navigation links (write the full URL, e.g., www.example.com/cats).
|
||
- If no link seems helpful, say: GO_BACK.
|
||
|
||
Recap of note taking:
|
||
If useful -> Note: [Briefly summarize the key information that answers the user’s query.]
|
||
Do not write "The page talk about ...", write your finding on the page and how they contribute to an answer.
|
||
If not useful -> Error: [Explain why the page doesn’t help.]
|
||
|
||
Example 1 (useful page, no need of going futher):
|
||
Note: According to karpathy site (https://karpathy.github.io/) LeCun net is the earliest real-world application of a neural net"
|
||
No link seem useful to provide futher information. GO_BACK
|
||
|
||
Example 2 (not useful, but related link):
|
||
Error: This forum reddit.com/welcome does not discuss anything related to the user’s query.
|
||
There is a link that could lead to the information, I want to navigate to http://reddit.com/r/locallama
|
||
|
||
Example 3 (not useful, no related links):
|
||
Error: x.com does not discuss anything related to the user’s query and no navigation link are usefull
|
||
GO_BACK
|
||
|
||
Example 3 (query answer found):
|
||
Note: I found on github.com that agenticSeek is Fosowl.
|
||
Given this information, given this I should exit the web browser. REQUEST_EXIT
|
||
|
||
Current date: {self.date}
|
||
Remember, the user asked: {user_prompt}
|
||
Do not exit until you found information the user seek or accomplished the task.
|
||
"""
|
||
|
||
def llm_decide(self, prompt):
|
||
animate_thinking("Thinking...", color="status")
|
||
self.memory.push('user', prompt)
|
||
answer, reasoning = self.llm_request()
|
||
pretty_print("-"*100)
|
||
pretty_print(answer, color="output")
|
||
pretty_print("-"*100)
|
||
return answer, reasoning
|
||
|
||
def select_unvisited(self, search_result):
|
||
results_unvisited = []
|
||
for res in search_result:
|
||
if res["link"] not in self.search_history:
|
||
results_unvisited.append(res)
|
||
return results_unvisited
|
||
|
||
def jsonify_search_results(self, results_string):
|
||
result_blocks = results_string.split("\n\n")
|
||
parsed_results = []
|
||
for block in result_blocks:
|
||
if not block.strip():
|
||
continue
|
||
lines = block.split("\n")
|
||
result_dict = {}
|
||
for line in lines:
|
||
if line.startswith("Title:"):
|
||
result_dict["title"] = line.replace("Title:", "").strip()
|
||
elif line.startswith("Snippet:"):
|
||
result_dict["snippet"] = line.replace("Snippet:", "").strip()
|
||
elif line.startswith("Link:"):
|
||
result_dict["link"] = line.replace("Link:", "").strip()
|
||
if result_dict:
|
||
parsed_results.append(result_dict)
|
||
return parsed_results
|
||
|
||
def stringify_search_results(self, results_arr):
|
||
return '\n\n'.join([f"Link: {res['link']}" for res in results_arr])
|
||
|
||
def save_notes(self, text):
|
||
lines = text.split('\n')
|
||
for line in lines:
|
||
if "note" in line.lower():
|
||
self.notes.append(line)
|
||
|
||
def conclude_prompt(self, user_query):
|
||
annotated_notes = [f"{i+1}: {note.lower().replace('note:', '')}" for i, note in enumerate(self.notes)]
|
||
search_note = '\n'.join(annotated_notes)
|
||
print("AI research notes:\n", search_note)
|
||
return f"""
|
||
Following a human request:
|
||
{user_query}
|
||
A web AI made the following finding across different pages:
|
||
{search_note}
|
||
|
||
Summarize the finding, and provide a conclusion that answer the request.
|
||
"""
|
||
|
||
def search_prompt(self, user_prompt):
|
||
return f"""
|
||
Current date: {self.date}
|
||
Make a efficient search engine query to help users with their request:
|
||
{user_prompt}
|
||
Example:
|
||
User: "search: hey jarvis i want you to login to my twitter and say hello everyone "
|
||
You: Twitter
|
||
|
||
User: "I need info on the best laptops for AI this year."
|
||
You: "search: best laptops 2025 to run Machine Learning model, reviews"
|
||
|
||
User: "Search for recent news about space missions."
|
||
You: "search: Recent space missions news, {self.date}"
|
||
|
||
Do not explain, do not write anything beside the search query.
|
||
"""
|
||
|
||
def process(self, user_prompt, speech_module) -> str:
|
||
complete = False
|
||
|
||
animate_thinking(f"Searching...", color="status")
|
||
self.memory.push('user', self.search_prompt(user_prompt))
|
||
ai_prompt, _ = self.llm_request()
|
||
search_result_raw = self.tools["web_search"].execute([ai_prompt], False)
|
||
search_result = self.jsonify_search_results(search_result_raw)[:7] # until futher improvement
|
||
prompt = self.make_newsearch_prompt(user_prompt, search_result)
|
||
unvisited = [None]
|
||
while not complete:
|
||
answer, reasoning = self.llm_decide(prompt)
|
||
self.save_notes(answer)
|
||
if "REQUEST_EXIT" in answer:
|
||
complete = True
|
||
break
|
||
links = self.extract_links(answer)
|
||
if len(unvisited) == 0:
|
||
break
|
||
if len(links) == 0 or "GO_BACK" in answer:
|
||
unvisited = self.select_unvisited(search_result)
|
||
prompt = self.make_newsearch_prompt(user_prompt, unvisited)
|
||
pretty_print(f"Going back to results. Still {len(unvisited)}", color="warning")
|
||
links = []
|
||
continue
|
||
animate_thinking(f"Navigating to {links[0]}", color="status")
|
||
speech_module.speak(f"Navigating to {links[0]}")
|
||
self.browser.go_to(links[0])
|
||
self.search_history.append(links[0])
|
||
page_text = self.browser.get_text()
|
||
self.navigable_links = self.browser.get_navigable()
|
||
prompt = self.make_navigation_prompt(user_prompt, page_text)
|
||
|
||
self.browser.close()
|
||
prompt = self.conclude_prompt(user_prompt)
|
||
self.memory.push('user', prompt)
|
||
answer, reasoning = self.llm_request()
|
||
pretty_print(answer, color="output")
|
||
return answer, reasoning
|
||
|
||
if __name__ == "__main__":
|
||
browser = Browser() |