Spaces:
Sleeping
Sleeping
EtienneB
commited on
Commit
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30b4543
1
Parent(s):
374dd02
updates
Browse files
agent.py
CHANGED
@@ -5,14 +5,13 @@ import re
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from dotenv import load_dotenv
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from langchain_core.messages import (AIMessage, HumanMessage, SystemMessage,
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ToolMessage)
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from langchain_huggingface import
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HuggingFaceEndpoint)
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from langgraph.graph import START, MessagesState, StateGraph
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from langgraph.prebuilt import ToolNode, tools_condition
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from tools import (absolute, add, analyze_csv_file, analyze_excel_file,
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arvix_search, audio_transcription, compound_interest,
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convert_temperature, divide, exponential,
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extract_text_from_image, factorial, floor_divide,
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get_current_time_in_timezone, greatest_common_divisor,
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is_prime, least_common_multiple, logarithm, modulus,
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@@ -35,6 +34,7 @@ tools = [
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wiki_search, analyze_excel_file, arvix_search,
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audio_transcription, python_code_parser, analyze_csv_file,
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extract_text_from_image, reverse_sentence, web_content_extract,
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]
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# Updated system prompt for cleaner output
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@@ -42,7 +42,9 @@ system_prompt = """
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You are a helpful AI assistant. When asked a question, think through it step by step and provide only the final answer.
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CRITICAL INSTRUCTIONS:
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- Use available tools when needed to gather information or perform calculations
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- After using tools and analyzing the information, provide ONLY the final answer
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- Do not include explanations, reasoning, or extra text in your final response
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- If the answer is a number, provide just the number (no units unless specifically requested)
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@@ -190,5 +192,4 @@ if __name__ == "__main__":
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else:
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print("❌ Output is NOT in the correct format!")
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except Exception as e:
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print("❌ Output is NOT in the correct format!", e)
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-
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from dotenv import load_dotenv
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from langchain_core.messages import (AIMessage, HumanMessage, SystemMessage,
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ToolMessage)
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from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
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from langgraph.graph import START, MessagesState, StateGraph
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from langgraph.prebuilt import ToolNode, tools_condition
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from tools import (absolute, add, analyze_csv_file, analyze_excel_file,
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arvix_search, audio_transcription, compound_interest,
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convert_temperature, divide, download_file, exponential,
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extract_text_from_image, factorial, floor_divide,
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get_current_time_in_timezone, greatest_common_divisor,
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is_prime, least_common_multiple, logarithm, modulus,
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wiki_search, analyze_excel_file, arvix_search,
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audio_transcription, python_code_parser, analyze_csv_file,
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extract_text_from_image, reverse_sentence, web_content_extract,
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download_file,
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]
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# Updated system prompt for cleaner output
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You are a helpful AI assistant. When asked a question, think through it step by step and provide only the final answer.
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CRITICAL INSTRUCTIONS:
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- If the question mentions attachments, files, images, documents, or URLs, use the download_file tool FIRST to download them
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- Use available tools when needed to gather information or perform calculations
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- For file analysis, use appropriate tools (analyze_csv_file, analyze_excel_file, extract_text_from_image, etc.)
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- After using tools and analyzing the information, provide ONLY the final answer
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- Do not include explanations, reasoning, or extra text in your final response
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- If the answer is a number, provide just the number (no units unless specifically requested)
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else:
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print("❌ Output is NOT in the correct format!")
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except Exception as e:
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print("❌ Output is NOT in the correct format!", e)
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tools.py
CHANGED
@@ -2,10 +2,13 @@ import base64
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import datetime
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import math
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import os
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from typing import Dict, Union
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import pandas
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import pytz
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from bs4 import BeautifulSoup
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from langchain_community.document_loaders import (
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ArxivLoader, AssemblyAIAudioTranscriptLoader, WikipediaLoader)
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@@ -13,11 +16,83 @@ from langchain_community.document_loaders.generic import GenericLoader
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from langchain_community.document_loaders.parsers import LanguageParser
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from langchain_core.messages import HumanMessage
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# from langchain_community.tools import DuckDuckGoSearchRun
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from langchain_core.tools import tool
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_tavily import TavilySearch
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@tool
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def multiply(a: Union[int, float], b: Union[int, float]) -> Union[int, float]:
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"""Multiplies two numbers and returns the product.
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import datetime
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import math
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import os
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import urllib.parse
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from pathlib import Path
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from typing import Dict, Union
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import pandas
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import pytz
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import requests
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from bs4 import BeautifulSoup
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from langchain_community.document_loaders import (
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ArxivLoader, AssemblyAIAudioTranscriptLoader, WikipediaLoader)
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from langchain_community.document_loaders.parsers import LanguageParser
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from langchain_core.messages import HumanMessage
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# from langchain_community.tools import DuckDuckGoSearchRun
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# from langchain_community.tools import DuckDuckGoSearchRun
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from langchain_core.tools import tool
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_tavily import TavilySearch
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@tool
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def download_file(url: str, filename: str = None) -> str:
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"""
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Download a file from a URL and save it locally for analysis.
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Args:
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url: The URL of the file to download
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filename: Optional custom filename. If not provided, will extract from URL
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Returns:
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The local file path where the file was saved
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"""
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try:
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# Clean and validate URL
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url = url.strip()
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if not url.startswith(('http://', 'https://')):
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return f"Error: Invalid URL format: {url}"
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# Create downloads directory if it doesn't exist
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download_dir = Path("downloads")
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download_dir.mkdir(exist_ok=True)
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# Determine filename
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if not filename:
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# Extract filename from URL
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parsed_url = urllib.parse.urlparse(url)
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filename = os.path.basename(parsed_url.path)
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# If no filename in URL, create one based on URL hash
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if not filename or '.' not in filename:
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url_hash = str(hash(url))[-8:] # Last 8 characters of hash
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filename = f"downloaded_file_{url_hash}"
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# Ensure filename has proper extension if we can detect content type
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filepath = download_dir / filename
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# Download the file
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headers = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
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}
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print(f"Downloading file from: {url}")
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response = requests.get(url, headers=headers, timeout=30, stream=True)
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response.raise_for_status()
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# Try to get better filename from Content-Disposition header
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if 'content-disposition' in response.headers:
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import re
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cd = response.headers['content-disposition']
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filename_match = re.findall('filename=(.+)', cd)
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if filename_match:
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suggested_filename = filename_match[0].strip('"')
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if suggested_filename:
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filepath = download_dir / suggested_filename
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# Write file to disk
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with open(filepath, 'wb') as f:
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for chunk in response.iter_content(chunk_size=8192):
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f.write(chunk)
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file_size = os.path.getsize(filepath)
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print(f"Successfully downloaded {filename} ({file_size} bytes)")
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return str(filepath)
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except requests.exceptions.RequestException as e:
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return f"Error downloading file: {str(e)}"
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except Exception as e:
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return f"Error saving file: {str(e)}"
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@tool
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def multiply(a: Union[int, float], b: Union[int, float]) -> Union[int, float]:
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"""Multiplies two numbers and returns the product.
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