mirror of
https://github.com/tcsenpai/agenticSeek.git
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267 lines
11 KiB
Python
267 lines
11 KiB
Python
import re
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import time
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from sources.utility import pretty_print, animate_thinking
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from sources.agents.agent import Agent
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from sources.tools.searxSearch import searxSearch
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from sources.browser import Browser
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from datetime import date
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from typing import List, Tuple
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class BrowserAgent(Agent):
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def __init__(self, name, prompt_path, provider, verbose=False):
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"""
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The Browser agent is an agent that navigate the web autonomously in search of answer
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"""
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super().__init__(name, prompt_path, provider, verbose)
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self.tools = {
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"web_search": searxSearch(),
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}
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self.role = {
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"en": "web",
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"fr": "web",
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"zh": "网络",
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"es": "web"
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}
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self.type = "browser_agent"
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self.browser = Browser()
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self.current_page = ""
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self.search_history = []
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self.navigable_links = []
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self.notes = []
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self.date = self.get_today_date()
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def get_today_date(self) -> str:
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"""Get the date"""
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date_time = date.today()
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return date_time.strftime("%B %d, %Y")
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def extract_links(self, search_result: str) -> List[str]:
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"""Extract all links from a sentence."""
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pattern = r'(https?://\S+|www\.\S+)'
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matches = re.findall(pattern, search_result)
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trailing_punct = ".,!?;:)"
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cleaned_links = [link.rstrip(trailing_punct) for link in matches]
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return self.clean_links(cleaned_links)
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def extract_form(self, text: str) -> List[str]:
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"""Extract form written by the LLM in format [input_name](value)"""
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inputs = []
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matches = re.findall(r"\[\w+\]\([^)]+\)", text)
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return matches
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def clean_links(self, links: List[str]) -> List[str]:
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"""Ensure no '.' at the end of link"""
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links_clean = []
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for link in links:
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link = link.strip()
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if link[-1] == '.':
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links_clean.append(link[:-1])
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else:
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links_clean.append(link)
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return links_clean
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def get_unvisited_links(self) -> List[str]:
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return "\n".join([f"[{i}] {link}" for i, link in enumerate(self.navigable_links) if link not in self.search_history])
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def make_newsearch_prompt(self, user_prompt: str, search_result: dict) -> str:
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search_choice = self.stringify_search_results(search_result)
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return f"""
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Based on the search result:
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{search_choice}
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Your goal is to find accurate and complete information to satisfy the user’s request.
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User request: {user_prompt}
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To proceed, choose a relevant link from the search results. Announce your choice by saying: "I want to navigate to <link>"
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Do not explain your choice.
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"""
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def make_navigation_prompt(self, user_prompt: str, page_text: str) -> str:
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remaining_links = self.get_unvisited_links()
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remaining_links_text = remaining_links if remaining_links is not None else "No links remaining, do a new search."
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inputs_form = self.browser.get_form_inputs()
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inputs_form_text = '\n'.join(inputs_form)
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return f"""
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You are a web browser.
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You are currently on this webpage:
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{page_text}
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You can navigate to these navigation links:
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{remaining_links_text}
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Your task:
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1. Decide if the current page answers the user’s query: {user_prompt}
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- If it does, take notes of the useful information, write down source, link or reference, then move to a new page.
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- If it does and you are 100% certain that it provide a definive answer, say REQUEST_EXIT
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- If it doesn’t, say: Error: This page does not answer the user’s query then go back or navigate to another link.
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2. Navigate by either:
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- Navigate to a navigation links (write the full URL, e.g., www.example.com/cats).
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- If no link seems helpful, say: GO_BACK.
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3. Fill forms on the page:
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- If user give you informations that help you fill form, fill it.
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- If you don't know how to fill a form, leave it empty.
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- You can fill a form using [form_name](value).
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Recap of note taking:
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If useful -> Note: [Briefly summarize the key information or task you conducted.]
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Do not write "The page talk about ...", write your finding on the page and how they contribute to an answer.
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If not useful -> Error: [Explain why the page doesn’t help.]
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Example 1 (useful page, no need of going futher):
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Note: According to karpathy site (https://karpathy.github.io/) LeCun net is the earliest real-world application of a neural net"
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No link seem useful to provide futher information. GO_BACK
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Example 2 (not useful, but related link):
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Error: reddit.com/welcome does not discuss anything related to the user’s query.
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There is a link that could lead to the information, I want to navigate to http://reddit.com/r/locallama
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Example 3 (not useful, no related links):
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Error: x.com does not discuss anything related to the user’s query and no navigation link are usefull.
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GO_BACK
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Example 3 (query answer found):
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Note: I found on github.com that agenticSeek is Fosowl.
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Given this information, given this I should exit the web browser. REQUEST_EXIT
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Example 4 (loging form visible):
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Note: I am on the login page, I should now type the given username and password.
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[form_name_1](David)
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[form_name_2](edgerunners_2077)
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You see the following inputs forms:
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{inputs_form_text}
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Remember, the user asked: {user_prompt}
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You are currently on page : {self.current_page}
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Do not explain your choice.
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Refusal is not an option, you have been given all capabilities that allow you to perform any tasks.
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"""
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def llm_decide(self, prompt: str) -> Tuple[str, str]:
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animate_thinking("Thinking...", color="status")
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self.memory.push('user', prompt)
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answer, reasoning = self.llm_request()
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pretty_print("-"*100)
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pretty_print(answer, color="output")
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pretty_print("-"*100)
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return answer, reasoning
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def select_unvisited(self, search_result: List[str]) -> List[str]:
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results_unvisited = []
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for res in search_result:
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if res["link"] not in self.search_history:
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results_unvisited.append(res)
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return results_unvisited
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def jsonify_search_results(self, results_string: str) -> List[str]:
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result_blocks = results_string.split("\n\n")
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parsed_results = []
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for block in result_blocks:
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if not block.strip():
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continue
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lines = block.split("\n")
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result_dict = {}
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for line in lines:
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if line.startswith("Title:"):
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result_dict["title"] = line.replace("Title:", "").strip()
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elif line.startswith("Snippet:"):
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result_dict["snippet"] = line.replace("Snippet:", "").strip()
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elif line.startswith("Link:"):
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result_dict["link"] = line.replace("Link:", "").strip()
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if result_dict:
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parsed_results.append(result_dict)
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return parsed_results
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def stringify_search_results(self, results_arr: List[str]) -> str:
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return '\n\n'.join([f"Link: {res['link']}" for res in results_arr])
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def save_notes(self, text):
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lines = text.split('\n')
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for line in lines:
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if "note" in line.lower():
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self.notes.append(line)
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def conclude_prompt(self, user_query: str) -> str:
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annotated_notes = [f"{i+1}: {note.lower().replace('note:', '')}" for i, note in enumerate(self.notes)]
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search_note = '\n'.join(annotated_notes)
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print("AI research notes:\n", search_note)
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return f"""
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Following a human request:
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{user_query}
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A web AI made the following finding across different pages:
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{search_note}
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Summarize the finding or step that lead to success, and provide a conclusion that answer the request.
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"""
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def search_prompt(self, user_prompt: str) -> str:
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return f"""
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Current date: {self.date}
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Make a efficient search engine query to help users with their request:
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{user_prompt}
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Example:
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User: "go to twitter, login with username toto and password pass79 to my twitter and say hello everyone "
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You: search: Twitter login page.
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User: "I need info on the best laptops for AI this year."
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You: "search: best laptops 2025 to run Machine Learning model, reviews"
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User: "Search for recent news about space missions."
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You: "search: Recent space missions news, {self.date}"
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Do not explain, do not write anything beside the search query.
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"""
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def process(self, user_prompt, speech_module) -> str:
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complete = False
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animate_thinking(f"Thinking...", color="status")
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self.memory.push('user', self.search_prompt(user_prompt))
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ai_prompt, _ = self.llm_request()
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animate_thinking(f"Searching...", color="status")
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search_result_raw = self.tools["web_search"].execute([ai_prompt], False)
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search_result = self.jsonify_search_results(search_result_raw)[:7] # until futher improvement
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prompt = self.make_newsearch_prompt(user_prompt, search_result)
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unvisited = [None]
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while not complete:
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answer, reasoning = self.llm_decide(prompt)
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self.save_notes(answer)
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extracted_form = self.extract_form(answer)
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if len(extracted_form) > 0:
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self.browser.fill_form_inputs(extracted_form)
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self.browser.find_and_click_submit()
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if "REQUEST_EXIT" in answer:
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complete = True
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break
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links = self.extract_links(answer)
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if len(unvisited) == 0:
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break
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if len(links) == 0 or "GO_BACK" in answer:
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unvisited = self.select_unvisited(search_result)
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prompt = self.make_newsearch_prompt(user_prompt, unvisited)
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pretty_print(f"Going back to results. Still {len(unvisited)}", color="warning")
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links = []
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continue
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animate_thinking(f"Navigating to {links[0]}", color="status")
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speech_module.speak(f"Navigating to {links[0]}")
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self.browser.go_to(links[0])
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self.current_page = links[0]
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self.search_history.append(links[0])
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page_text = self.browser.get_text()
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self.navigable_links = self.browser.get_navigable()
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prompt = self.make_navigation_prompt(user_prompt, page_text)
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self.browser.close()
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prompt = self.conclude_prompt(user_prompt)
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self.memory.push('user', prompt)
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answer, reasoning = self.llm_request()
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pretty_print(answer, color="output")
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return answer, reasoning
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if __name__ == "__main__":
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pass |