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03cd67b 8abd124 c984898 03cd67b 820aa0b 04e04c8 03cd67b efdee21 03cd67b c984898 03cd67b 3c965e9 8abd124 e93d4ea 8abd124 3c965e9 03cd67b 8abd124 28040a7 03cd67b 8abd124 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 | import os
from typing import TypedDict, List, Dict, Any, Optional
from langchain.agents import create_tool_calling_agent, AgentExecutor
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.tools import tool
from langchain_core.messages import HumanMessage
from langchain_core.prompts import ChatPromptTemplate
# 1. Web Browsing
from langchain_community.tools import DuckDuckGoSearchRun
from langchain_community.document_loaders import ImageCaptionLoader
import requests
import pandas as pd
from pypdf import PdfReader
@tool
def web_search(query: str) -> str:
"""Allows search through DuckDuckGo.
Args:
query: what you want to search
"""
search = DuckDuckGoSearchRun()
results = search.invoke(query)
return "\n".join(results)
@tool
def visit_webpage(url: str) -> str:
"""Fetches raw HTML content of a web page.
Args:
url: the webpage url
"""
try:
response = requests.get(url, timeout=5)
return response.text
except Exception as e:
return f"[ERROR fetching {url}]: {str(e)}"
# 4. File Reading
@tool
def read_file(dir: str) -> str:
"""Read the content of the provided file
Args:
dir: the filepath
"""
extension = dir.split['.'][-1]
if extension == 'xlsx':
dataframe = pd.read_excel(dir)
return dataframe.to_string()
elif extension == 'pdf':
reader = PdfReader(dir)
contents = [p.extract_text() for p in reader.pages]
return "\n".join(contents)
else:
with open(dir) as f:
return f.read()
# 5. Image Open
@tool
def image_caption(dir: str) -> str:
"""Understand the content of the provided image
Args:
dir: the image url link
"""
loader = ImageCaptionLoader(images=[dir])
metadata = loader.load()
return metadata[0].page_content
# 2. Coding
# 3. Multi-Modality
# ("human", f"Question: {question}\nReport to validate: {final_answer}")
class BasicAgent:
def __init__(self):
self.model = ChatGoogleGenerativeAI(
model="gemini-2.0-flash",
temperature=0,
max_tokens=1024,
timeout=None,
max_retries=2,
google_api_key="AIzaSyAxVUPaGJIgdxB46ZR0RWPKSjB9a63Z80o",
# other params...
)
# System Prompt for few shot prompting
self.sys_prompt = """"
You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER].
YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separared list of numbers and/or strings.
If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise.
If you are asked for a string, don't use articles, neither abbreviations (eg. for cities), and write the digits in plain text unless specified otherwise.
If you are asked for a comma separated list, apply the above rules depending of whether the element to put in the list is a number or a string.
There are few tools provided: web_search, visit_webpage, read_file and image_caption.
Here are few examples demonstrating how to call and use the tools.
"""
self.tools = [web_search, visit_webpage, read_file, image_caption]
self.prompt = ChatPromptTemplate.from_messages([
("system", self.sys_prompt),
("human", "{input}"),
("placeholder", "{agent_scratchpad}")
])
self.agent = create_tool_calling_agent(self.model, self.tools, self.prompt)
self.agent_exe = AgentExecutor(agent=self.agent, tools=self.tools, verbose=True)
print("BasicAgent initialized.")
def __call__(self, question: str) -> str:
print(f"Agent received question (first 50 chars): {question[:50]}...")
response = self.agent_exe.invoke({"input": question})
fixed_answer = response['message'][-1].content
# fixed_answer = "This is a default answer."
print(f"Agent returning fixed answer: {fixed_answer}")
return fixed_answer |