Prasanthkumar commited on
Commit
88c9b9b
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verified ·
1 Parent(s): e2d148b

Update agent/agent.py

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  1. agent/agent.py +6 -6
agent/agent.py CHANGED
@@ -17,11 +17,11 @@ from langchain_core.tools import tool
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  from langchain.tools.retriever import create_retriever_tool
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  from supabase.client import Client, create_client
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- from tools.basic_calculator import add, count_substring, divide, modulus, multiply, power, square_root, subtract
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- from tools.code_interpreter import execute_code_multilang
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- from tools.document_processing import save_and_read_file,download_file_from_url, extract_text_from_image, analyze_csv_file, analyze_excel_file
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  from tools.image_processing import analyze_image, transform_image, draw_on_image, generate_simple_image, combine_images
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- from tools.web_search import arxiv_search, similar_question_search, wiki_search, web_search
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  load_dotenv() # load environment variables
@@ -36,11 +36,11 @@ sys_msg = SystemMessage(content=system_prompt)
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  # build a retriever
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  embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") # set the model to generate embeddings; dim=768
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- supabase:Client = create_client(os.environ.get("SUPABASE_URL"), os.environ.get("SUPABASE_SERVICE_KEY"))
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  vector_store = SupabaseVectorStore(client=supabase, embedding= embeddings, table_name="documents", query_name="match_documents_langchain")
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  create_retriever_tool = create_retriever_tool(retriever=vector_store.as_retriever(), name="Question Retriever", description="A tool to retrieve similar questions from a vector store.")
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- tools = [web_search, wiki_search, similar_question_search, arxiv_search, multiply, add, subtract, divide, modulus, power, square_root, count_substring, save_and_read_file, download_file_from_url, extract_text_from_image, analyze_csv_file, analyze_excel_file, execute_code_multilang, analyze_image, transform_image, draw_on_image, generate_simple_image, combine_images]
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  # Build the agent graph
 
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  from langchain.tools.retriever import create_retriever_tool
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  from supabase.client import Client, create_client
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+ from tools.calculator import add, sub, mul, div, floor_div, square, mod, pow, square_root, absolute, gcd, lcm, factorial
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+ from tools.code_interpreter_tools import execute_code_multilang
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+ from tools.document_parser import save_and_read_file,download_file_from_url, extract_text_from_image, analyze_csv_file, analyze_excel_file
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  from tools.image_processing import analyze_image, transform_image, draw_on_image, generate_simple_image, combine_images
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+ from tools.web_search_tools import arxiv_search, similar_question_search, wiki_search, web_search
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  load_dotenv() # load environment variables
 
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  # build a retriever
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  embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") # set the model to generate embeddings; dim=768
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+ supabase:Client = create_client(os.environ.get("SUPABASE_URL"), os.environ.get("SUPABASE_KEY"))
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  vector_store = SupabaseVectorStore(client=supabase, embedding= embeddings, table_name="documents", query_name="match_documents_langchain")
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  create_retriever_tool = create_retriever_tool(retriever=vector_store.as_retriever(), name="Question Retriever", description="A tool to retrieve similar questions from a vector store.")
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+ tools = [web_search, wiki_search, similar_question_search, arxiv_search, add, sub, mul, div, floor_div, square, mod, pow, square_root, absolute, gcd, lcm, factorial, save_and_read_file, download_file_from_url, extract_text_from_image, analyze_csv_file, analyze_excel_file, execute_code_multilang, analyze_image, transform_image, draw_on_image, generate_simple_image, combine_images]
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  # Build the agent graph