Capacity Building

How do funders help scientists, patient groups and other stakeholders increase their capacity to influence, and accelerate scientific research?

Preliminaries

from alhazen.apps.chat import  AlhazenAgentChatBot
from alhazen.core import get_langchain_chatmodel, MODEL_TYPE
from alhazen.schema_sqla import *
from alhazen.tools.basic import AddCollectionFromEPMCTool, DeleteCollectionTool
from alhazen.tools.paperqa_emulation_tool import PaperQAEmulationTool
from alhazen.tools.metadata_extraction_tool import MetadataExtractionTool, MetadataExtractionWithRAGTool 
from alhazen.toolkit import AlhazenToolkit
from alhazen.utils.jats_text_extractor import NxmlDoc
from alhazen.utils.ceifns_db import Ceifns_LiteratureDb, create_ceifns_database, drop_ceifns_database

from langchain.callbacks.tracers import ConsoleCallbackHandler
from langchain.docstore.document import Document
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores.pgvector import PGVector

from bs4 import BeautifulSoup,Tag,Comment,NavigableString
from databricks import sql
from datetime import datetime
from importlib_resources import files
import os
import pandas as pd
from pathlib import Path
import re
import requests

from sqlalchemy import create_engine, exists, func
from sqlalchemy.orm import sessionmaker, aliased

from time import time,sleep
from tqdm import tqdm
from urllib.request import urlopen
from urllib.parse import quote_plus, quote, unquote
from urllib.error import URLError, HTTPError
import yaml

# Using Aliases like this massively simplifies the use of SQLAlchemy
IR = aliased(InformationResource)

SKC = aliased(ScientificKnowledgeCollection)
SKC_HM = aliased(ScientificKnowledgeCollectionHasMembers)
SKE = aliased(ScientificKnowledgeExpression)
SKE_XREF = aliased(ScientificKnowledgeExpressionXref)
SKE_IRI = aliased(ScientificKnowledgeExpressionIri)
SKE_HR = aliased(ScientificKnowledgeExpressionHasRepresentation)
SKE_MO = aliased(ScientificKnowledgeExpressionMemberOf)
SKI = aliased(ScientificKnowledgeItem)
SKI_HP = aliased(ScientificKnowledgeItemHasPart)
SKF = aliased(ScientificKnowledgeFragment)

N = aliased(Note)
NIA = aliased(NoteIsAbout)
SKC_HN = aliased(ScientificKnowledgeCollectionHasNotes)
SKE_HN = aliased(ScientificKnowledgeExpressionHasNotes)
SKI_HN = aliased(ScientificKnowledgeItemHasNotes)
SKF_HN = aliased(ScientificKnowledgeFragmentHasNotes)

Remember to set environmental variables for this code:

• ALHAZEN_DB_NAME - the name of the PostGresQL database you are storing information into
• LOCAL_FILE_PATH - the location on disk where you save temporary files, downloaded models or other data.

os.environ['ALHAZEN_DB_NAME'] = 'machine_learning_and_biology'
os.environ['LOCAL_FILE_PATH'] = '/users/gully.burns/alhazen/'

if os.path.exists(os.environ['LOCAL_FILE_PATH']) is False:
    os.makedirs(os.environ['LOCAL_FILE_PATH'])

if os.environ.get('ALHAZEN_DB_NAME') is None: 
    raise Exception('Which database do you want to use for this application?')
db_name = os.environ['ALHAZEN_DB_NAME']

if os.environ.get('LOCAL_FILE_PATH') is None: 
    raise Exception('Where are you storing your local literature database?')
loc = os.environ['LOCAL_FILE_PATH']

drop_ceifns_database(os.environ['ALHAZEN_DB_NAME'])

huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
    - Avoid using `tokenizers` before the fork if possible
    - Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Database has been backed up to /users/gully.burns/alhazen/alhazen_workbooks/backup2024-02-14-09-25-50.sql
Database has been dropped successfully !!

create_ceifns_database(os.environ['ALHAZEN_DB_NAME'])

100%|██████████| 311/311 [00:00<00:00, 2249.83it/s]

ldb = Ceifns_LiteratureDb(loc=loc, name=db_name)
llm = get_langchain_chatmodel(model_type=MODEL_TYPE.Ollama, llm_name='mixtral:instruction')
cb = AlhazenAgentChatBot()

print('AVAILABLE TOOLS')
for t in cb.tk.get_tools():
    print('\t'+type(t).__name__)

AVAILABLE TOOLS
    AddCollectionFromEPMCTool
    AddAuthorsToCollectionTool
    DescribeCollectionCompositionTool
    DeleteCollectionTool
    RetrieveFullTextTool
    RetrieveFullTextToolForACollection
    MetadataExtractionTool
    SimpleExtractionWithRAGTool
    PaperQAEmulationTool
    CheckExpressionTool
    IntrospectionTool