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.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+data/CRESCENDDI/Drug-to-drug[[:space:]]Negative[[:space:]]Controls.xlsx filter=lfs diff=lfs merge=lfs -text
+data/CRESCENDDI/Dug-to-drug[[:space:]]Positive[[:space:]]Controls.xlsx filter=lfs diff=lfs merge=lfs -text
+data/CRESCENDDI/Single-drug[[:space:]]adverse[[:space:]]effects,[[:space:]]indications[[:space:]]and[[:space:]]negative[[:space:]]controls.xlsx filter=lfs diff=lfs merge=lfs -text
+docs/images/logo.png filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.11
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD ["python", "interaction_db/data_loader.py"]

LICENSE

@@ -0,0 +1,201 @@
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config.py

@@ -0,0 +1,37 @@
+"""
+Centralised, cached access to runtime configuration.
+"""
+
+from functools import lru_cache
+from importlib import resources
+import json
+import os
+from pathlib import Path
+import yaml
+from dotenv import load_dotenv
+
+
+@lru_cache(maxsize=None)
+def _load_prompt_template() -> str:
+    with open("prompts/router_prompt.yml", "r") as fh:
+        return yaml.safe_load(fh)["template"]
+
+
+@lru_cache(maxsize=None)
+def _load_mcp_configs() -> dict:
+    cfg_path = Path(
+        os.getenv(
+            "MCP_CONFIG_PATH",
+            Path(__file__).resolve().parent / "settings" / "mcp_config.json",
+        )
+    )
+    with cfg_path.open() as fh:
+        return json.load(fh)["mcpServers"]
+
+
+load_dotenv()
+
+PROMPT_TEMPLATE: str = _load_prompt_template()
+MCP_CONFIGS: dict = _load_mcp_configs()
+MODEL_API_KEY: str = os.getenv("MODEL_API_KEY")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

data/CRESCENDDI/Drug-to-drug Negative Controls.xlsx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f66a06d89960f0e7cf64a12baf4bf53dbdf14d0efcd7e5b8bb15cc19a36523bf
+size 129094

data/CRESCENDDI/Dug-to-drug Positive Controls.xlsx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a6f2ab3db42e2e674cc8f9556951e1806cc87b253118c4176bc2da57dece48c
+size 393509

data/CRESCENDDI/Single-drug adverse effects, indications and negative controls.xlsx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:599315920c4e722009b9809bd6a3ac44b4cd37bd24bf0c39b2cd85644e2cea27
+size 1979074

docker-compose.yml

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+version: "3.8"
+
+services:
+  mysql:
+    image: mysql:8
+    container_name: my-mysql
+    restart: always
+    environment:
+      MYSQL_ROOT_PASSWORD: ${MYSQL_PASSWORD}
+      MYSQL_DATABASE: ${MYSQL_DATABASE}
+    ports:
+      - "3306:3306"
+    volumes:
+      - mysql_data:/var/lib/mysql
+
+  python:
+    build: .
+    container_name: data-loader
+    depends_on:
+      - mysql
+    environment:
+      MYSQL_USER: ${MYSQL_USER}
+      MYSQL_PASSWORD: ${MYSQL_PASSWORD}
+      MYSQL_HOST: mysql
+      MYSQL_PORT: 3306
+      MYSQL_DATABASE: ${MYSQL_DATABASE}
+      PYTHONPATH: /app
+    volumes:
+      - .:/app
+    command: python interaction_db/data_loader.py
+
+volumes:
+  mysql_data:

interaction_db/data_loader.py

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+import os
+import time
+import pandas as pd
+import mysql.connector
+from mysql.connector import Error
+from sqlalchemy import create_engine
+from dotenv import load_dotenv
+from interaction_db.data_sources import (
+    DRUG_TO_DRUG_POSITIVE,
+    DRUG_TO_DRUG_NEGATIVE,
+    SINGLE_DRUG_DATA,
+)
+
+load_dotenv()
+
+USER = os.getenv("MYSQL_USER")
+PASSWORD = os.getenv("MYSQL_PASSWORD")
+HOST = os.getenv("MYSQL_HOST")
+PORT = int(os.getenv("MYSQL_PORT", 3306))
+DATABASE = os.getenv("MYSQL_DATABASE")
+
+
+def wait_for_mysql(host, user, password, port, timeout=60):
+    print(f"⏳ Waiting for MySQL at {host}:{port}...")
+    start_time = time.time()
+    while True:
+        try:
+            conn = mysql.connector.connect(
+                host=host, user=user, password=password, port=port
+            )
+            conn.close()
+            print("MySQL is ready!")
+            break
+        except Error as e:
+            if time.time() - start_time > timeout:
+                raise TimeoutError("MySQL did not become ready in time.")
+            time.sleep(2)
+
+
+wait_for_mysql(HOST, USER, PASSWORD, PORT)
+
+# Create the database if it doesn't exist
+conn = mysql.connector.connect(host=HOST, user=USER, password=PASSWORD)
+cursor = conn.cursor()
+cursor.execute(f"CREATE DATABASE IF NOT EXISTS {DATABASE}")
+print(f"Database '{DATABASE}' created or already exists.")
+cursor.close()
+conn.close()
+
+# Data
+file_paths = {
+    "drug_to_drug_positive_controls": DRUG_TO_DRUG_POSITIVE,
+    "drug_to_drug_negative_controls": DRUG_TO_DRUG_NEGATIVE,
+    "single_drug_data": SINGLE_DRUG_DATA,
+}
+
+# MySQL
+engine = create_engine(
+    f"mysql+mysqlconnector://{USER}:{PASSWORD}@{HOST}:{PORT}/{DATABASE}"
+)
+
+# Process data
+for table_key, file_path in file_paths.items():
+    if not os.path.exists(file_path):
+        print(f"File not found: {file_path}")
+        continue
+
+    if table_key == "single_drug_data":
+        # Load positive and negative controls into separate tables
+        sheet_map = {
+            "Tab1 - Positive": "single_drug_positive_controls",
+            "Tab2 - Negative": "single_drug_negative_controls",
+        }
+        for sheet_name, table_name in sheet_map.items():
+            df = pd.read_excel(file_path, sheet_name=sheet_name)
+            df = df.where(pd.notnull(df), None)
+            df.to_sql(name=table_name, con=engine, if_exists="replace", index=False)
+            print(f"Uploaded sheet '{sheet_name}' to table '{table_name}'")
+    else:
+        df = pd.read_excel(file_path, sheet_name=0)
+        df = df.where(pd.notnull(df), None)
+        df.to_sql(name=table_key, con=engine, if_exists="replace", index=False)
+        print(f"Uploaded file '{file_path}' to table '{table_key}'")
+
+print("All Excel data uploaded to MySQL successfully.")

interaction_db/data_sources.py

@@ -0,0 +1,3 @@
+SINGLE_DRUG_DATA = "data/CRESCENDDI/Single-drug adverse effects, indications and negative controls.xlsx"
+DRUG_TO_DRUG_POSITIVE = "data/CRESCENDDI/Dug-to-drug Positive Controls.xlsx"
+DRUG_TO_DRUG_NEGATIVE = "data/CRESCENDDI/Drug-to-drug Negative Controls.xlsx"

prompts/drug_prompts.py

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+drug_tools_prompt = """
+            From user input, identify:
+            1. Mentioned drug(s).
+            2. Whether the user is asking about indications, adverse effects, or interactions.
+
+            Use the available tools to retrieve and summarize relevant data. If results are extensive, highlight the most critical information (e.g., severe or common effects). Do not describe tables or internal tool structure. Do not infer unknown connections. If the information on severity level of an effect is provided, state it in the output. Clearly state when no known information exists. Use both positive and negative tools when asked about adverse effects and interactions.
+            """
+
+drug_mcp_prompt = """
+            From user input, identify:
+            1. Mentioned drug(s).
+            2. Whether the user is asking about indications, adverse effects, or interactions.
+
+            Use the available mysql database to retrieve and summarize relevant data.
+
+            | drug_to_drug_negative_controls | positive interactions (EVENT_CONCEPT_NAME) with their severity levels (MICROMEDEX_SEV_LEVEL) between drugs (DRUG_1_CONCEPT_NAME, DRUG_2_CONCEPT_NAME) |
+            | drug_to_drug_positive_controls | negative interactions (EVENT_CONCEPT_NAME) between drugs (DRUG_1_CONCEPT_NAME, DRUG_2_CONCEPT_NAME) |
+            | single_drug_negative_controls  | negative effects (EVENT_CONCEPT_NAME) of a drug (DRUG_CONCEPT_NAME) |
+            | single_drug_positive_controls  | positive adverse effects (EVENT_TYPE == Adverse event) and indications (EVENT_TYPE == Indication) of a drug (DRUG_CONCEPT_NAME) |
+
+            If results are extensive, highlight the most critical information (e.g., severe or common effects).
+            Do not describe tables or internal tool structure.
+            Do not infer unknown connections.
+            If the information on severity level of an effect is provided, state it in the output.
+            Clearly state when no known information exists.
+            Use first positive controls table when asked about adverse effects and interactions between two drugs. If nothing is found, use negative drug-to-drug controls table.
+            You should first recognize entities in user input, then query databases (with lowercase or capitalized inputs; incase there are two drugs, query both columns with them), and finally provided the answer based on information retrieved.
+            """

prompts/router_prompt.yml

@@ -0,0 +1,22 @@
+# prompts/router_prompt.yml
+name: router_and_role_prompt
+description: Describes the role of an agent and healthcare-related tools
+input_variables:
+  - text
+template: |-
+  You are a Smart Healthcare Assistant whose core mission is to give users fast, reliable answers about:
+    •	Drug-drug, food-drug, and other interactions
+    •	Adverse effects and safety concerns
+    •	General medical information backed by the latest data
+
+  You have a direct integration with Whoop, enabling truly personalized guidance. Through the connector you can:
+    •	get_latest_cycle → return the user’s available cycle dates
+    •	get_sleeps → fetch detailed sleep metrics
+    •	get_workouts → retrieve workout and strain data
+    •	…and other health-tracking endpoints as needed
+
+  Available tools
+    1.	Whoop MCP Server – interface for all Whoop data functions
+    2.	Healthcare MCP Server – gateway to up-to-date clinical resources (interactions, adverse events, guidelines)
+
+  Use these tools in concert to deliver clear, actionable, and evidence-based responses tailored to each user.