File size: 1,532 Bytes
715a633 ebafaef 715a633 ebafaef 4135762 6b5e0d9 ebafaef 6c44e19 331400f 715a633 67905b1 715a633 758564e 67905b1 715a633 758564e af3a044 758564e af3a044 715a633 |
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 |
from langchain_openai import ChatOpenAI
from src.tools.tools import *
from src.tools.code_interpreter import safe_code_run
from langgraph.prebuilt import ToolNode
from src.schemas import PlannerPlan
from src.tools.youtube_transcript import extract_youtube_transcript
from src.tools.video_analyzer import video_qa_gemma
from src.utils.utils import log_stage
from langchain_core.messages import HumanMessage, SystemMessage, AIMessage, ToolMessage
from dotenv import load_dotenv
load_dotenv()
config = {"configurable": {"thread_id": "1"}, "recursion_limit" : 50}
TOOLS = [video_qa_gemma, download_file_from_url, web_search,
arxiv_search, wiki_search, add, subtract, multiply, divide,
power, analyze_excel_file, analyze_csv_file, analyze_docx_file,
analyze_pdf_file, analyze_txt_file,
vision_qa_gemma, safe_code_run, web_extract, transcribe_audio] #extract_youtube_transcript
TOOL_NODE = ToolNode(TOOLS)
DEBUGGING_TOOL_NODE = TOOL_NODE
llm = ChatOpenAI(model="gpt-4o-mini", temperature=0.7) #default 0.25
llm_deterministic = ChatOpenAI(model="gpt-5-mini", temperature=0.05)
planner_llm = ChatOpenAI(model="gpt-4o-mini", temperature=0.1).with_structured_output(PlannerPlan)
llm_criticist = ChatOpenAI(model="gpt-4o-mini", temperature=0.1)
llm_with_tools = llm_deterministic.bind_tools(TOOLS)
llm_reasoning = ChatOpenAI(model="gpt-5-mini", temperature=0.3)
llm_simple_executor = ChatOpenAI(model="gpt-5-mini", temperature=0.3)
llm_simple_with_tools = llm_simple_executor.bind_tools(TOOLS)
|