Database scripts and files

Database/report_type_update3+.py

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+import os
+import time
+from langchain_community.document_loaders import PyMuPDFLoader
+from langchain_community.embeddings import AnyscaleEmbeddings
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Pinecone as PineconeStore
+from langchain_community.chat_models import ChatAnyscale
+from langchain.chains import create_retrieval_chain
+from langchain.chains.combine_documents import create_stuff_documents_chain
+from langchain_core.prompts import ChatPromptTemplate
+from sqlalchemy import create_engine, Column, Integer, String
+from sqlalchemy.orm import declarative_base, sessionmaker
+import pinecone
+
+# Set API keys and environment variables
+os.environ["ANYSCALE_API_KEY"] = ""
+os.environ["PINECONE_API_KEY"] = ""
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = ""
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+# Connect to the SQLite database
+engine = create_engine('sqlite:///C:/Users/MI/Sqlite/med_assist.db', echo=True)
+Base = declarative_base()
+
+# Define the report_type table
+class ReportType(Base):
+    __tablename__ = 'report_type'
+    report_type_id = Column(Integer, primary_key=True, autoincrement=True)
+    report_type_name = Column(String, nullable=False)
+
+Session = sessionmaker(bind=engine)
+session = Session()
+
+# Load data 
+pdf_loader = PyMuPDFLoader('Blood report.pdf')
+Blood_reports = pdf_loader.load()
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)
+pdf_doc = text_splitter.split_documents(Blood_reports)
+
+# Initialize a LangChain embedding object
+api_key = os.getenv("ANYSCALE_API_KEY")
+embeddings = AnyscaleEmbeddings(
+    anyscale_api_key=api_key, model="thenlper/gte-large"
+)
+
+# Initialize Pinecone
+pc = pinecone.Pinecone(api_key=os.getenv("PINECONE_API_KEY"))
+
+# Create index if it doesn't exist
+index_name = "pp"
+if index_name not in pc.list_indexes().names():
+    pc.create_index(
+        name=index_name,
+        dimension=1024,
+        metric="cosine",
+        spec=pinecone.ServerlessSpec(
+            cloud="aws",
+            region="us-east-1"
+        )
+    )
+
+# Initialize Pinecone index
+index = pc.Index(index_name)
+
+# Embed each chunk and upsert the embeddings into a distinct namespace
+namespace = "pp1"
+pineconeVector = PineconeStore.from_documents(
+    documents=pdf_doc,
+    index_name=index_name,
+    embedding=embeddings,
+    namespace=namespace
+)
+
+time.sleep(1)
+
+# Initialize the language model with Anyscale
+llm = ChatAnyscale(anyscale_api_key=os.getenv('ANYSCALE_API_KEY'), model='meta-llama/Meta-Llama-3-8B-Instruct')
+
+# Initialize the Pinecone retriever
+retriever = pineconeVector.as_retriever()
+docs = retriever.invoke("what information is contained in the document")
+
+# Define the system prompt
+system_prompt = (
+    "Use the given context to answer the question. "
+    "If you don't know the answer, say you don't know. "
+    "Use three sentences maximum and keep the answer concise. "
+    "Context: {context}"
+)
+
+# Create the prompt template
+prompt = ChatPromptTemplate.from_messages(
+    [
+        ("system", system_prompt),
+        ("human", "{input}"),
+    ]
+)
+# Create the question-answer chain
+question_answer_chain = create_stuff_documents_chain(llm, prompt)
+# Create the retrieval chain
+chain = create_retrieval_chain(retriever, question_answer_chain)
+
+#Query input
+query = "What kind of report is this? Blood, urine, or other type?"
+
+# Invoke the chain with the query
+response = chain.invoke({"input": query})
+
+# Extract the answer from the response
+answer = response['answer']
+
+print(answer)
+
+# Extract the report type from the answer
+if "blood" in answer.lower():
+    report_type = "Blood report"
+elif "urine" in answer.lower():
+    report_type = "Urinalysis"
+else:
+    report_type = "Other report"
+
+# Perform the query and update the database
+query_vector = embeddings.embed_query(query)
+results = index.query(vector=query_vector, top_k=10, namespace=namespace)  
+
+for match in results['matches']:
+    matched_id = match['id']
+
+    # Check if the record already exists
+    existing_record = session.query(ReportType).filter_by(report_type_name=report_type).first()
+    if existing_record:
+        print(f"Record with report_type_name '{report_type}' already exists.")
+    else:
+        # Insert a new record
+        new_report_type = ReportType(
+            report_type_name=report_type
+        )
+        session.add(new_report_type)
+
+# Commit changes to the database
+session.commit()
+session.close()

UI/desktop_app/desktop_app/asgi.py

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+"""
+ASGI config for desktop_app project.
+
+It exposes the ASGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/howto/deployment/asgi/
+"""
+
+import os
+
+from django.core.asgi import get_asgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'desktop_app.settings')
+
+application = get_asgi_application()

UI/desktop_app/desktop_app/settings.py

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+"""
+Django settings for desktop_app project.
+
+Generated by 'django-admin startproject' using Django 5.0.6.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/topics/settings/
+
+For the full list of settings and their values, see
+https://docs.djangoproject.com/en/5.0/ref/settings/
+"""
+import os
+from pathlib import Path
+
+# Build paths inside the project like this: BASE_DIR / 'subdir'.
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+
+# Quick-start development settings - unsuitable for production
+# See https://docs.djangoproject.com/en/5.0/howto/deployment/checklist/
+
+# SECURITY WARNING: keep the secret key used in production secret!
+SECRET_KEY = 'django-insecure-jwnz+2p7%6-ywxxl4m&&biho7^m+20c7wmqccb2hs_@)ak-s6t'
+
+# SECURITY WARNING: don't run with debug turned on in production!
+DEBUG = True
+
+ALLOWED_HOSTS = []
+
+
+# Application definition
+
+INSTALLED_APPS = [
+    'django.contrib.admin',
+    'django.contrib.auth',
+    'django.contrib.contenttypes',
+    'django.contrib.sessions',
+    'django.contrib.messages',
+    'django.contrib.staticfiles',
+    'ui',
+    'ui.DB_query'
+]
+
+MIDDLEWARE = [
+    'django.middleware.security.SecurityMiddleware',
+    'django.contrib.sessions.middleware.SessionMiddleware',
+    'django.middleware.common.CommonMiddleware',
+    'django.middleware.csrf.CsrfViewMiddleware',
+    'django.contrib.auth.middleware.AuthenticationMiddleware',
+    'django.contrib.messages.middleware.MessageMiddleware',
+    'django.middleware.clickjacking.XFrameOptionsMiddleware',
+]
+
+ROOT_URLCONF = 'desktop_app.urls'
+
+TEMPLATES = [
+    {
+        'BACKEND': 'django.template.backends.django.DjangoTemplates',
+        'DIRS': [],
+        'APP_DIRS': True,
+        'OPTIONS': {
+            'context_processors': [
+                'django.template.context_processors.debug',
+                'django.template.context_processors.request',
+                'django.contrib.auth.context_processors.auth',
+                'django.contrib.messages.context_processors.messages',
+            ],
+        },
+    },
+]
+
+WSGI_APPLICATION = 'desktop_app.wsgi.application'
+
+
+# Database
+# https://docs.djangoproject.com/en/5.0/ref/settings/#databases
+
+DATABASES = {
+    'default': {
+        'ENGINE': 'django.db.backends.sqlite3',
+        'NAME': BASE_DIR / 'db.sqlite3',
+    }
+}
+
+
+# Password validation
+# https://docs.djangoproject.com/en/5.0/ref/settings/#auth-password-validators
+
+AUTH_PASSWORD_VALIDATORS = [
+    {
+        'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
+    },
+]
+
+
+# Internationalization
+# https://docs.djangoproject.com/en/5.0/topics/i18n/
+
+LANGUAGE_CODE = 'en-us'
+
+TIME_ZONE = 'UTC'
+
+USE_I18N = True
+
+USE_TZ = True
+
+
+# Static files (CSS, JavaScript, Images)
+# https://docs.djangoproject.com/en/5.0/howto/static-files/
+
+STATIC_URL = '/static/'
+
+STATICFILES_DIRS = [
+    BASE_DIR / "ui/static",
+]
+
+# Default primary key field type
+# https://docs.djangoproject.com/en/5.0/ref/settings/#default-auto-field
+
+DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'
+

UI/desktop_app/desktop_app/urls.py

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+from django.contrib import admin
+from django.urls import path, include
+
+urlpatterns = [
+    path('admin/', admin.site.urls),
+    path('', include('ui.urls')),
+]

UI/desktop_app/desktop_app/wsgi.py

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+"""
+WSGI config for desktop_app project.
+
+It exposes the WSGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/5.0/howto/deployment/wsgi/
+"""
+
+import os
+
+from django.core.wsgi import get_wsgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'desktop_app.settings')
+
+application = get_wsgi_application()

UI/desktop_app/manage

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+

UI/desktop_app/manage.py

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+#!/usr/bin/env python
+"""Django's command-line utility for administrative tasks."""
+import os
+import sys
+
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+
+def main():
+    """Run administrative tasks."""
+    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'desktop_app.settings')
+    try:
+        from django.core.management import execute_from_command_line
+    except ImportError as exc:
+        raise ImportError(
+            "Couldn't import Django. Are you sure it's installed and "
+            "available on your PYTHONPATH environment variable? Did you "
+            "forget to activate a virtual environment?"
+        ) from exc
+    execute_from_command_line(sys.argv)
+
+
+if __name__ == '__main__':
+    main()

UI/desktop_app/ui/DB_query/AnyScaleLLM.py

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+from langchain_core.runnables.base import Runnable
+import openai
+import logging
+
+# Set up logging
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+class AnyScaleLLM():
+    def __init__(self, model_name, api_key, base_url="https://api.endpoints.anyscale.com/v1"):
+        self.base_url = base_url
+        self.api_key = api_key
+        self.model_name = model_name
+
+    def chat_completion(self, prompt, question):
+        client = openai.OpenAI(
+            base_url=self.base_url,
+            api_key=self.api_key
+        )
+
+        messages = [
+            {"role": "system", "content": prompt},
+            {"role": "user", "content": question}
+        ]
+
+        try:
+            chat_completion = client.chat.completions.create(
+                model=self.model_name,
+                messages=messages,
+                temperature=0.1
+            )
+
+            response = chat_completion.choices[0].message.content
+            logger.debug(f"API Response: {response}")
+
+            return response
+        except Exception as e:
+            logger.error(f"Error during chat completion: {e}")
+            return "An error occurred while processing your request."