diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..6cd2d96
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,13 @@
+repos:
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.9.0
+    hooks:
+      - id: ruff
+        args: [ --fix ]
+      - id: ruff-format
+
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.14.0
+    hooks:
+      - id: mypy
+        additional_dependencies: [pydantic>=2.13.0]
diff --git a/Makefile b/Makefile
index 47aee0b..6a8aedf 100644
--- a/Makefile
+++ b/Makefile
@@ -2,7 +2,25 @@
 IMAGE_NAME = extractor-agent
 PORT = 3000
 
-.PHONY: build run stop clean test start shell logs
+.PHONY: build run stop clean test start shell logs lint format lint-fix typecheck install-hooks
+
+# Pre-commit hooks
+install-hooks:
+	uv run pre-commit install
+
+# Linting and Formatting
+lint:
+	uv run ruff check .
+
+format:
+	uv run ruff format .
+
+lint-fix:
+	uv run ruff check --fix .
+	uv run ruff format .
+
+typecheck:
+	uv run mypy .
 
 # Build and run the container
 start: build run
diff --git a/README.md b/README.md
index b99bea7..0687f03 100644
--- a/README.md
+++ b/README.md
@@ -61,6 +61,35 @@ docker run -p 3000:3000 -t govuk-ai-graph-tools-app
 ---
 
 
+---
+
+## Development and Code Quality
+
+### 1. Manual Checks
+You can run the full suite of checks using the `Makefile`:
+
+```bash
+# Run all checks
+make lint && make format && make typecheck
+
+# Run individual checks
+make lint
+make format
+make typecheck
+```
+
+### 2. Pre-commit Hooks
+The project is configured with `pre-commit` to automatically run these checks before every `git commit`. 
+
+To install the hooks in your local repository:
+```bash
+make install-hooks
+```
+
+Once installed, your code will be automatically linted and type-checked whenever you commit. If you need to skip the hooks (e.g., for an urgent WIP commit), you can use `git commit --no-verify`.
+
+---
+
 ## Tests
 
 ```bash
diff --git a/app.py b/app.py
index 924b00c..010095c 100644
--- a/app.py
+++ b/app.py
@@ -1,25 +1,27 @@
 import asyncio
-import fsspec
-import json
 import logging
 import os
-import re
 import time
-import uuid
+
 from asgiref.wsgi import WsgiToAsgi
 from dotenv import load_dotenv
-from flask import Flask, request, jsonify, render_template
-from src.visualiser_graph_generator import generate_graph, generate_output_path
-from src.visualiser_graph_loader import load_json_file, extract_path_parts, visualiser_graph_file_path
+from flask import Flask, jsonify, render_template, request
+from werkzeug.exceptions import BadRequest
+
 from src.utils import (
-    update_job_status, 
-    read_job_status, 
-    get_job_id_for_path,
-    get_active_job_status,
     background_run_extraction,
-    resume_interrupted_jobs
+    get_active_job_status,
+    get_job_id_for_path,
+    read_job_status,
+    resume_interrupted_jobs,
+    update_job_status,
+)
+from src.visualiser_graph_generator import generate_output_path
+from src.visualiser_graph_loader import (
+    extract_path_parts,
+    load_json_file,
+    visualiser_graph_file_path,
 )
-from werkzeug.exceptions import BadRequest
 
 
 load_dotenv()
@@ -27,93 +29,102 @@
 # Configure logging
 logging.basicConfig(
     level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[
-        logging.StreamHandler()
-    ]
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    handlers=[logging.StreamHandler()],
 )
 logger = logging.getLogger(__name__)
 
+
 def create_app():
     app = Flask(__name__)
 
-    @app.route('/graph', methods=['GET'])
+    @app.route("/graph", methods=["GET"])
     def graph_page():
         """Serve the Cytoscape graph viewer page."""
-        source_path_param = request.args.get('source_path')
+        source_path_param = request.args.get("source_path")
 
         # Validate the source_path format
         if source_path_param:
             extract_path_parts(source_path_param)
 
-        return render_template('graph.html', source_path=source_path_param or '')
+        return render_template("graph.html", source_path=source_path_param or "")
 
-    @app.route('/graph-viewmodel', methods=['GET'])
+    @app.route("/graph-viewmodel", methods=["GET"])
     async def graph_viewmodel():
         """Serve the graph data as JSON for the frontend."""
         try:
-            source_path_param = request.args.get('source_path')
-            
+            source_path_param = request.args.get("source_path")
+
             graph_filepath = visualiser_graph_file_path(source_path_param)
 
             graph_data = load_json_file(graph_filepath)
 
-            logger.info('Graph data loaded successfully.')
+            logger.info("Graph data loaded successfully.")
             return jsonify(graph_data), 200
         except Exception as e:
             app.logger.error(f"Error loading graph data: {str(e)}")
             return jsonify({"error": "Error loading graph data."}), 500
 
-    @app.route('/healthcheck/ready', methods=['GET'])
+    @app.route("/healthcheck/ready", methods=["GET"])
     def health_check():
         """Simple health check endpoint."""
         return "Application OK", 200
 
-    @app.route('/extract', methods=['GET'])
+    @app.route("/extract", methods=["GET"])
     async def extract_quotes():
         """
         Endpoint that runs the Cytoscape graph generation logic based on graph.json.
         """
         try:
-            source_path = request.args.get('source_path')
+            source_path = request.args.get("source_path")
             if not source_path:
                 return jsonify({"error": "Missing 'source_path' query parameter"}), 400
 
             input_path, output_path = generate_output_path(source_path)
             job_id = get_job_id_for_path(source_path)
-            
+
             active_status = get_active_job_status(job_id)
             if active_status:
-                logger.info(f"Duplicate request for {source_path}. Job {job_id} is already in progress.")
-                return jsonify({
-                    'job_id': job_id,
-                    'status': 'already_running',
-                    'message': f'A graph generation job is already in progress for {source_path}',
-                    'output_path': output_path
-                }), 202
+                logger.info(
+                    f"Duplicate request for {source_path}. Job {job_id} is already in progress."
+                )
+                return jsonify(
+                    {
+                        "job_id": job_id,
+                        "status": "already_running",
+                        "message": (
+                            f"A graph generation job is already in progress for {source_path}"
+                        ),
+                        "output_path": output_path,
+                    }
+                ), 202
 
             initial_status = {
                 "job_id": job_id,
                 "status": "pending",
                 "source_path": source_path,
-                "created_at": time.time()
+                "created_at": time.time(),
             }
             update_job_status(job_id, initial_status)
 
-            asyncio.create_task(background_run_extraction(job_id, input_path, output_path, initial_status))
+            asyncio.create_task(
+                background_run_extraction(job_id, input_path, output_path, initial_status)
+            )
 
-            return jsonify({
-                'job_id': job_id,
-                'status': 'accepted',
-                'message': f'Graph generation started in background for {source_path}',
-                'output_path': output_path
-            }), 202
+            return jsonify(
+                {
+                    "job_id": job_id,
+                    "status": "accepted",
+                    "message": f"Graph generation started in background for {source_path}",
+                    "output_path": output_path,
+                }
+            ), 202
 
         except Exception as e:
             app.logger.error(f"Error starting background task: {str(e)}")
             return jsonify({"error": str(e)}), 500
 
-    @app.route('/status/<job_id>', methods=['GET'])
+    @app.route("/status/<job_id>", methods=["GET"])
     def get_status(job_id):
         """Check the status of a background job from S3."""
         status_info = read_job_status(job_id)
@@ -127,8 +138,10 @@ def handle_bad_request(e):
 
     return app
 
+
 class LifespanMiddleware:
     """ASGI middleware to handle startup and shutdown events."""
+
     def __init__(self, app):
         self.app = app
 
@@ -146,14 +159,17 @@ async def __call__(self, scope, receive, send):
                     return
         return await self.app(scope, receive, send)
 
+
 def create_asgi_app():
     flask_app = create_app()
     asgi_app = WsgiToAsgi(flask_app)
     return LifespanMiddleware(asgi_app)
 
+
 if __name__ == "__main__":
     asgi_app = create_asgi_app()
     import uvicorn
+
     port = int(os.getenv("PORT", 3000))
     logger.info(f"Starting Uvicorn server on port {port}...")
-    uvicorn.run(asgi_app, host='0.0.0.0', port=port)
+    uvicorn.run(asgi_app, host="0.0.0.0", port=port)
diff --git a/pyproject.toml b/pyproject.toml
index db4eec3..7ec0102 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,4 +22,34 @@ dev = [
     "pytest>=9.0.3",
     "pytest-asyncio>=1.3.0",
     "pytest-mock>=3.15.1",
+    "ruff>=0.9.0",
+    "mypy>=1.14.0",
+    "pre-commit>=4.0.0",
 ]
+
+[tool.mypy]
+plugins = ["pydantic.mypy"]
+follow_imports = "silent"
+warn_redundant_casts = true
+warn_unused_ignores = true
+disallow_any_generics = false
+check_untyped_defs = true
+no_implicit_reexport = true
+ignore_missing_imports = true
+
+[tool.pydantic-mypy]
+init_forbid_extra = true
+init_typed = true
+warn_required_dynamic_aliases = true
+
+[tool.ruff]
+line-length = 100
+target-version = "py312"
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "W"]
+ignore = []
+
+[tool.ruff.lint.isort]
+combine-as-imports = true
+lines-after-imports = 2
diff --git a/src/content_extractor/base.py b/src/content_extractor/base.py
index 8fcb160..41bf48e 100644
--- a/src/content_extractor/base.py
+++ b/src/content_extractor/base.py
@@ -1,56 +1,75 @@
-import os
-import boto3
 import json
-from typing import List, Dict, Optional, Any
+import os
 from dataclasses import dataclass, field
 from pprint import pprint
-from pydantic import BaseModel, Field, RootModel
+from typing import Dict, List, Optional
+
+import boto3
+from pydantic import BaseModel, Field
 from pydantic_ai import Agent
 from pydantic_ai.models.bedrock import BedrockConverseModel
 from pydantic_ai.providers.bedrock import BedrockProvider
 
+
 # --- Shared Models ---
 
+
 class AgentQuote(BaseModel):
     """Simple quote model for the agent to return."""
+
     content: str = Field(description="The exact sentence or phrase found in the document.")
     keyword_matched: str = Field(description="The keyword or phrase that triggered this match.")
 
+
 class AgentQuoteExtraction(BaseModel):
     """Collection of quotes returned by the agent for a single document."""
+
     quotes: List[AgentQuote]
 
+
 class Finding(BaseModel):
     """A single unique finding within a keyword group."""
+
     content: str
     source_documents: List[str]
 
-class FinalQuoteExtraction(BaseModel): # Changed to BaseModel as RootModel is often unnecessary for simple dict roots
+
+class FinalQuoteExtraction(
+    BaseModel
+):  # Changed to BaseModel as RootModel is often unnecessary for simple dict roots
     """The final collection of quotes as a dictionary of keyword -> list of findings."""
+
     root: Dict[str, List[Finding]]
 
+
 # --- Shared Configuration ---
 
+
 @dataclass
 class BaseExtractorConfig:
     keywords: List[str]
     s3_documents: List[str]
     model_id: str = "eu.anthropic.claude-sonnet-4-6"
-    region: str = field(default_factory=lambda: os.getenv("AWS_REGION", os.getenv("AWS_DEFAULT_REGION", "eu-west-2")))
+    region: str = field(
+        default_factory=lambda: os.getenv(
+            "AWS_REGION", os.getenv("AWS_DEFAULT_REGION", "eu-west-2")
+        )
+    )
     chunk_max_chars: int = 6000
     secret_id: Optional[str] = None
 
+
 # --- Base Extractor Class ---
 
+
 class BaseQuoteExtractor:
     def __init__(self, config: BaseExtractorConfig):
         self.config = config
         self.s3_client = boto3.client("s3", region_name=self.config.region)
-        
+
         # Initialize Bedrock Agent
         model = BedrockConverseModel(
-            self.config.model_id, 
-            provider=BedrockProvider(region_name=self.config.region)
+            self.config.model_id, provider=BedrockProvider(region_name=self.config.region)
         )
         self.agent = Agent(
             model,
@@ -62,16 +81,18 @@ def __init__(self, config: BaseExtractorConfig):
                 "For each match, return:\n"
                 "1. the EXACT sentence as 'content' (do not paraphrase)\n"
                 "2. the keyword that was matched as 'keyword_matched'\n\n"
-                "If a keyword appears multiple times in different sentences, extract each unique sentence. "
+                "If a keyword appears multiple times in different sentences, "
+                "extract each unique sentence. "
                 "If no matches are found, return an empty list of quotes.\n"
-               """IMPORTANT: The source is a Markdown file. You MUST return 'content' that matches the RENDERED text, not the raw source. "
-                Apply these cleaning rules to every extracted quote:
-                - Remove Markdown link syntax: change [link text](url) to just link text.
-                - Strip formatting: remove all **, *, __, _, and ` symbols.
-                - Strip list markers: remove leading '* ', '- ', '+ ', or '1. ' types of bullet points.
-                - Strip headers: remove leading '#' symbols."""
-                
-            )
+                "IMPORTANT: The source is a Markdown file. You MUST return 'content' that "
+                "matches the RENDERED text, not the raw source. "
+                "Apply these cleaning rules to every extracted quote:\n"
+                "- Remove Markdown link syntax: change [link text](url) to just link text.\n"
+                "- Strip formatting: remove all **, *, __, _, and ` symbols.\n"
+                "- Strip list markers: remove leading '* ', '- ', '+ ', or '1. ' "
+                "types of bullet points.\n"
+                "- Strip headers: remove leading '#' symbols."
+            ),
         )
 
     def get_aws_secret(self, secret_id: str) -> dict:
@@ -92,7 +113,7 @@ def fetch_s3_content(self, s3_uri: str) -> str:
         try:
             if not s3_uri.startswith("s3://"):
                 raise ValueError(f"Invalid S3 URI: {s3_uri}")
-            
+
             parts = s3_uri.replace("s3://", "").split("/", 1)
             bucket, key = parts
             response = self.s3_client.get_object(Bucket=bucket, Key=key)
@@ -105,11 +126,12 @@ def chunk_content(self, text: str) -> List[str]:
         """Splits text into chunks respecting paragraph boundaries."""
         if not text:
             return []
-        
+
         paragraphs = text.split("\n\n")
-        chunks, current_chunk = [], []
+        chunks: List[str] = []
+        current_chunk: List[str] = []
         current_length = 0
-        
+
         for para in paragraphs:
             para_len = len(para)
             if current_length + para_len > self.config.chunk_max_chars and current_chunk:
@@ -117,8 +139,8 @@ def chunk_content(self, text: str) -> List[str]:
                 current_chunk, current_length = [para], para_len
             else:
                 current_chunk.append(para)
-                current_length += para_len + 2 # +2 for \n\n separators
-                
+                current_length += para_len + 2  # +2 for \n\n separators
+
         if current_chunk:
             chunks.append("\n\n".join(current_chunk))
         return chunks
diff --git a/src/content_extractor/highlighter.py b/src/content_extractor/highlighter.py
index 2007b72..49f1386 100644
--- a/src/content_extractor/highlighter.py
+++ b/src/content_extractor/highlighter.py
@@ -1,13 +1,14 @@
 import re
 
+
 def highlight_occurrence(text: str, keyword: str) -> str:
     if not keyword or not text:
         return text
-    
+
     escaped_keyword = re.escape(keyword)
-    
+
     pattern = re.compile(f"({escaped_keyword})", re.IGNORECASE)
-    
+
     highlighted = pattern.sub(r'<span class="occurrence">\1</span>', text, count=1)
-    
+
     return highlighted
diff --git a/src/content_extractor/opensearch.py b/src/content_extractor/opensearch.py
index 496f156..2450573 100644
--- a/src/content_extractor/opensearch.py
+++ b/src/content_extractor/opensearch.py
@@ -1,13 +1,15 @@
-import asyncio
-from typing import List
 from dataclasses import dataclass
-from .base import BaseQuoteExtractor, BaseExtractorConfig
+
+from .base import BaseExtractorConfig, BaseQuoteExtractor
+
 
 # --- Configuration ---
 
+
 @dataclass
 class OpenSearchConfig(BaseExtractorConfig):
     """Placeholder for OpenSearch specialized configuration."""
+
     index_name: str = "document_chunks"
 
 
@@ -17,5 +19,7 @@ def __init__(self, config: OpenSearchConfig):
         super().__init__(config)
         self.config = config
 
-    async def run(self, perform_indexing: bool = False, output_file: str = "outputs/extracted_quotes_os.json"):
+    async def run(
+        self, perform_indexing: bool = False, output_file: str = "outputs/extracted_quotes_os.json"
+    ):
         return None
diff --git a/src/content_extractor/s3_sequential.py b/src/content_extractor/s3_sequential.py
index fb09284..2bc448d 100644
--- a/src/content_extractor/s3_sequential.py
+++ b/src/content_extractor/s3_sequential.py
@@ -1,17 +1,25 @@
 import asyncio
-import logging
 import json
-from typing import List, Dict, Any
+import logging
 from collections import defaultdict
-from .base import BaseQuoteExtractor, Finding, FinalQuoteExtraction, BaseExtractorConfig
+from typing import Any, Dict, List, Optional, Set
+
 from src.url.generator import generate_url_fragement, s3_to_govuk_url
 
+from .base import (
+    BaseExtractorConfig,
+    BaseQuoteExtractor,
+    FinalQuoteExtraction,
+    Finding,
+)
+
+
 logger = logging.getLogger(__name__)
 
 
 class S3QuoteExtractor(BaseQuoteExtractor):
     """Processes documents sequentially by fetching from S3 and chunking."""
-    
+
     def __init__(self, config: BaseExtractorConfig):
         super().__init__(config)
         self.url_map: Dict[str, str] = {}
@@ -28,7 +36,7 @@ def _fetch_url_map(self, s3_uris: List[str]):
         for uri in s3_uris:
             if uri in self.url_map:
                 continue
-                
+
             if "/input/" in uri:
                 sources_uri = uri.split("/input/")[0] + "/input/sources.json"
             else:
@@ -37,7 +45,7 @@ def _fetch_url_map(self, s3_uris: List[str]):
 
         for sources_uri in sources_locations:
             logger.info(f"Attempting to fetch sources map from {sources_uri}...")
-            content = self.fetch_s3_content(sources_uri)
+            content: Optional[str] = self.fetch_s3_content(sources_uri)
             if content:
                 try:
                     new_map = json.loads(content)
@@ -47,7 +55,7 @@ def _fetch_url_map(self, s3_uris: List[str]):
                     logger.error(f"Failed to parse {sources_uri}: {e}")
             else:
                 logger.warning(f"No sources.json found at {sources_uri}.")
-        
+
         if self.url_map:
             logger.info(f"Total URL mappings loaded: {len(self.url_map)}")
         else:
@@ -56,7 +64,8 @@ def _fetch_url_map(self, s3_uris: List[str]):
     async def process_document(self, s3_uri: str, keywords: List[str], results_list: list):
         """Processes a single document for a specific set of keywords."""
         content = self.fetch_s3_content(s3_uri)
-        if not content: return
+        if not content:
+            return
 
         chunks = self.chunk_content(content)
         if len(chunks) > 1:
@@ -66,29 +75,30 @@ async def process_document(self, s3_uri: str, keywords: List[str], results_list:
 
         for i, chunk in enumerate(chunks, 1):
             prompt = (
-                f"Keywords: {', '.join(keywords)}\n\n"
-                f"Content (Chunk {i}/{len(chunks)}):\n{chunk}"
+                f"Keywords: {', '.join(keywords)}\n\nContent (Chunk {i}/{len(chunks)}):\n{chunk}"
             )
             try:
                 result = await self.agent.run(prompt)
                 for q in result.output.quotes:
-                    results_list.append({
-                        "content": q.content,
-                        "keyword_matched": q.keyword_matched,
-                        "source": s3_uri,
-                        "link": generate_url_fragement(base_govuk_url, q.content)
-                    })
+                    results_list.append(
+                        {
+                            "content": q.content,
+                            "keyword_matched": q.keyword_matched,
+                            "source": s3_uri,
+                            "link": generate_url_fragement(base_govuk_url, q.content),
+                        }
+                    )
             except Exception as e:
                 logger.error(f"  Error in {s3_uri} chunk {i}: {e}")
 
     async def run_mapping(self, doc_to_keywords: Dict[str, List[str]]):
         """Processes documents based on a mapping of {s3_uri: [keywords]}."""
-        raw_findings = []
-        
+        raw_findings: List[Dict[str, Any]] = []
+
         self._fetch_url_map(list(doc_to_keywords.keys()))
-        
+
         tasks = [
-            self.process_document(uri, keywords, raw_findings) 
+            self.process_document(uri, keywords, raw_findings)
             for uri, keywords in doc_to_keywords.items()
         ]
         await asyncio.gather(*tasks)
@@ -99,15 +109,17 @@ async def run(self):
         doc_to_keywords = {uri: self.config.keywords for uri in self.config.s3_documents}
         raw_findings = await self.run_mapping(doc_to_keywords)
 
-        keyword_map = defaultdict(lambda: defaultdict(set))
+        keyword_map: Dict[str, Dict[str, Set[str]]] = defaultdict(lambda: defaultdict(set))
         for f in raw_findings:
             keyword_map[f["keyword_matched"]][f["content"]].add(f["source"])
 
         final_data = {
-            kw: [Finding(content=txt, source_documents=sorted(list(srcs))) 
-                 for txt, srcs in content_map.items()]
+            kw: [
+                Finding(content=txt, source_documents=sorted(list(srcs)))
+                for txt, srcs in content_map.items()
+            ]
             for kw, content_map in keyword_map.items()
         }
 
         extraction = FinalQuoteExtraction(root=final_data)
-        return extraction
\ No newline at end of file
+        return extraction
diff --git a/src/models/graph_models.py b/src/models/graph_models.py
index c6d15c7..475e8f1 100644
--- a/src/models/graph_models.py
+++ b/src/models/graph_models.py
@@ -1,10 +1,13 @@
-from pydantic import BaseModel, Field, ConfigDict
-from typing import List, Optional, Dict, Union, Any, Literal
+from typing import Any, Dict, List, Literal, Optional
+
+from pydantic import BaseModel, ConfigDict, Field
+
 
 class Alias(BaseModel):
     name: str
     source_files: List[str] = Field(default_factory=list)
 
+
 class Entity(BaseModel):
     id: str
     canonical_key: str
@@ -16,32 +19,39 @@ class Entity(BaseModel):
 
     model_config = ConfigDict(extra="allow")
 
+
 class GraphInput(BaseModel):
     entities: List[Entity]
-    
+
     model_config = ConfigDict(extra="allow")
 
+
 class Occurrence(BaseModel):
     link: str
     context: str
 
+
 class NodeData(BaseModel):
     id: str
     label: str
     type: Literal["entity", "alias"]
     occurrences: Optional[List[Occurrence]] = None
 
+
 class Node(BaseModel):
     data: NodeData
 
+
 class EdgeData(BaseModel):
     source: str
     target: str
     label: str
 
+
 class Edge(BaseModel):
     data: EdgeData
 
+
 class GraphOutput(BaseModel):
     nodes: List[Node]
     edges: List[Edge]
diff --git a/src/url/generator.py b/src/url/generator.py
index 92a21ce..6cf106f 100644
--- a/src/url/generator.py
+++ b/src/url/generator.py
@@ -1,22 +1,24 @@
 import urllib.parse
 from typing import Optional
 
-def convert_string_to_url_query_format(text: str)-> str:
-    quoted = urllib.parse.quote(text, safe='')
-    quoted= (quoted
-            .replace('-', '%2D')
-            .replace('.', '%2E')
-            .replace('~', '%7E')
-            .replace('_', '%5F'))
+
+def convert_string_to_url_query_format(text: str) -> str:
+    quoted = urllib.parse.quote(text, safe="")
+    quoted = quoted.replace("-", "%2D").replace(".", "%2E").replace("~", "%7E").replace("_", "%5F")
     return quoted
 
+
 def generate_url_fragement(base_url: str, content: str):
     encoded_content = convert_string_to_url_query_format(content)
     url = f"{base_url}#:~:text={encoded_content}"
     return url
 
+
 def s3_to_govuk_url(s3_uri: str, url_map: Optional[dict] = None) -> str:
-    """Derives a GOV.UK URL from an S3 URI, using url_map if provided, otherwise using fallback logic."""
+    """
+    Derives a GOV.UK URL from an S3 URI, using url_map if provided,
+    otherwise using fallback logic.
+    """
     if url_map and s3_uri in url_map:
         return url_map[s3_uri]
 
@@ -24,8 +26,6 @@ def s3_to_govuk_url(s3_uri: str, url_map: Optional[dict] = None) -> str:
         path = s3_uri.split("/input/")[-1]
     else:
         path = s3_uri.split("/")[-1]
-        
+
     path = path.replace(".md", "")
     return f"https://www.gov.uk/{path}"
-
-    
diff --git a/src/utils/__init__.py b/src/utils/__init__.py
index a6e051a..c66bc8c 100644
--- a/src/utils/__init__.py
+++ b/src/utils/__init__.py
@@ -1,9 +1,20 @@
 from .job_tracker import (
-    update_job_status, 
-    read_job_status, 
-    get_status_path,
-    get_job_id_for_path,
-    get_active_job_status,
     background_run_extraction,
-    resume_interrupted_jobs
+    get_active_job_status,
+    get_job_id_for_path,
+    get_status_path,
+    read_job_status,
+    resume_interrupted_jobs,
+    update_job_status,
 )
+
+
+__all__ = [
+    "background_run_extraction",
+    "get_active_job_status",
+    "get_job_id_for_path",
+    "get_status_path",
+    "read_job_status",
+    "resume_interrupted_jobs",
+    "update_job_status",
+]
diff --git a/src/utils/job_tracker.py b/src/utils/job_tracker.py
index c2b107a..ae4f6fe 100644
--- a/src/utils/job_tracker.py
+++ b/src/utils/job_tracker.py
@@ -1,20 +1,25 @@
+import asyncio
+import hashlib
 import json
 import logging
-import fsspec
-import hashlib
 import time
-import asyncio
 from typing import Optional
+
+import fsspec
+
 from src.visualiser_graph_generator import generate_graph, generate_output_path
 
+
 logger = logging.getLogger(__name__)
 
 STATUS_ROOT = "s3://govuk-ai-accelerator-data-integration/graph_tools/job_statuses"
 
+
 def get_status_path(job_id: str) -> str:
     """Returns the S3 path for a given job ID."""
     return f"{STATUS_ROOT}/{job_id}.json"
 
+
 def update_job_status(job_id: str, status_data: dict):
     """Updates the job status in S3."""
     path = get_status_path(job_id)
@@ -26,7 +31,8 @@ def update_job_status(job_id: str, status_data: dict):
     except Exception as e:
         logger.error(f"Failed to update job status in S3 for job {job_id}: {str(e)}")
 
-def read_job_status(job_id: str) -> dict| None:
+
+def read_job_status(job_id: str) -> dict | None:
     """Reads the job status from S3."""
     path = get_status_path(job_id)
     fs = fsspec.filesystem("s3")
@@ -43,72 +49,78 @@ def read_job_status(job_id: str) -> dict| None:
         logger.error(f"Failed to read job status from S3 for job {job_id}: {str(e)}")
         return None
 
+
 def get_job_id_for_path(source_path: str) -> str:
     """Generates a predictable job_id based on a hash of the source_path."""
     return hashlib.sha256(source_path.encode()).hexdigest()
 
+
 def get_active_job_status(job_id: str, timeout_hours: int = 24) -> Optional[dict]:
     """
-    Returns the job status ONLY if it is currently active (pending/running) 
+    Returns the job status ONLY if it is currently active (pending/running)
     and has not exceeded the timeout. Returns None if the job is stale or not active.
     """
     status = read_job_status(job_id)
     if not status:
         return None
-        
+
     if status.get("status") in ["pending", "running"]:
         created_at = status.get("created_at", 0)
         is_stale = (time.time() - created_at) > (timeout_hours * 3600)
-        
+
         if not is_stale:
             return status
-            
+
     return None
 
+
 async def background_run_extraction(job_id: str, input_path: str, output_path: str, status: dict):
     """Background task for graph generation and status tracking."""
     try:
-        logger.info(f'Starting background graph generation for {input_path} (Job: {job_id})...')
+        logger.info(f"Starting background graph generation for {input_path} (Job: {job_id})...")
         status["status"] = "running"
         update_job_status(job_id, status)
-        
+
         await generate_graph(input_path, output_path)
-        
+
         status["status"] = "completed"
         status["output_path"] = output_path
         status["completed_at"] = time.time()
         update_job_status(job_id, status)
-        logger.info(f'Graph generation completed successfully for {output_path}')
+        logger.info(f"Graph generation completed successfully for {output_path}")
     except Exception as e:
         logger.error(f"Background graph generation failed for job {job_id}: {str(e)}")
         status["status"] = "failed"
         status["error"] = str(e)
         update_job_status(job_id, status)
 
+
 async def resume_interrupted_jobs():
     """Scans for jobs stuck in 'running' state and restarts them if they are fresh (<24h)."""
     logger.info("Scanning for interrupted jobs to resume...")
     fs = fsspec.filesystem("s3")
-    
+
     try:
         # List all status files
         status_files = fs.glob(f"{STATUS_ROOT}/*.json")
-        
+
         for file_path in status_files:
             job_id = file_path.split("/")[-1].replace(".json", "")
             status = read_job_status(job_id)
-            
+
             if status and status.get("status") == "running":
                 created_at = status.get("created_at", 0)
                 is_fresh = (time.time() - created_at) < (24 * 3600)
-                
+
                 if is_fresh:
                     source_path = status.get("source_path")
                     if source_path:
                         try:
                             input_path, output_path = generate_output_path(source_path)
                             logger.info(f"Resuming interrupted job {job_id} for {source_path}")
-                            asyncio.create_task(background_run_extraction(job_id, input_path, output_path, status))
+                            asyncio.create_task(
+                                background_run_extraction(job_id, input_path, output_path, status)
+                            )
                         except Exception as e:
                             logger.error(f"Failed to prepare resumption for job {job_id}: {str(e)}")
                 else:
diff --git a/src/visualiser_graph_generator.py b/src/visualiser_graph_generator.py
index 0110c2a..f5949d6 100644
--- a/src/visualiser_graph_generator.py
+++ b/src/visualiser_graph_generator.py
@@ -1,31 +1,41 @@
-import json
 import asyncio
-import os
-import re
+import json
 import logging
-from typing import List, Dict, Any, Set, Tuple, Optional, Union
+import re
 from collections import defaultdict
-from src.content_extractor.s3_sequential import S3QuoteExtractor
+from typing import Any, Dict, List, Optional, Tuple, Union
+
+import fsspec
+
 from src.content_extractor.base import BaseExtractorConfig
 from src.content_extractor.highlighter import highlight_occurrence
-import fsspec
+from src.content_extractor.s3_sequential import S3QuoteExtractor
 from src.models.graph_models import (
-    GraphInput, GraphOutput, Node, NodeData, Edge, EdgeData, Occurrence, Entity
+    Edge,
+    EdgeData,
+    Entity,
+    GraphInput,
+    GraphOutput,
+    Node,
+    NodeData,
+    Occurrence,
 )
 
 
 logger = logging.getLogger(__name__)
 
+
 def slugify(text: str) -> str:
     """Simple slugify for node IDs."""
     text = text.lower()
-    text = re.sub(r'[^a-z0-9]+', '_', text)
-    return text.strip('_')
+    text = re.sub(r"[^a-z0-9]+", "_", text)
+    return text.strip("_")
+
 
 def build_registries(entities: List[Entity]) -> Dict[str, Any]:
     """Parses entities to map s3_uris to keywords and metadata based on structured aliases."""
-    registry = defaultdict(lambda: {"keywords": set(), "entities": []})
-    
+    registry: Dict[str, Dict[str, Any]] = defaultdict(lambda: {"keywords": set(), "entities": []})
+
     for ent in entities:
         for alias in ent.aliases:
             for uri in alias.source_files:
@@ -35,20 +45,19 @@ def build_registries(entities: List[Entity]) -> Dict[str, Any]:
                 # Ensure each entity is only added once per unique URI
                 if ent not in registry[uri]["entities"]:
                     registry[uri]["entities"].append(ent)
-            
+
     return registry
 
+
 async def fetch_extraction_findings(registry: Dict[str, Any]) -> List[Dict[str, Any]]:
     """Runs the extractor over unique S3 documents."""
     config = BaseExtractorConfig(keywords=[], s3_documents=[])
     extractor = S3QuoteExtractor(config)
 
-    doc_to_keywords = {
-        uri: list(data["keywords"]) 
-        for uri, data in registry.items() 
-        if data["keywords"]
+    doc_to_keywords: Dict[str, List[str]] = {
+        uri: list(data["keywords"]) for uri, data in registry.items() if data["keywords"]
     }
-    
+
     if not doc_to_keywords:
         logger.warning("No documents or aliases found to extract.")
         return []
@@ -56,26 +65,30 @@ async def fetch_extraction_findings(registry: Dict[str, Any]) -> List[Dict[str,
     logger.info(f"Starting extraction for {len(doc_to_keywords)} documents...")
     return await extractor.run_mapping(doc_to_keywords)
 
-def map_findings_to_entities(raw_findings: List[Dict[str, Any]], registry: Dict[str, Any]) -> Dict[str, Any]:
+
+def map_findings_to_entities(
+    raw_findings: List[Dict[str, Any]], registry: Dict[str, Any]
+) -> Dict[str, Dict[str, List[Occurrence]]]:
     """Groups findings by entity and alias with highlighting and links."""
-    results = defaultdict(lambda: defaultdict(list))
-    
+    results: Dict[str, Dict[str, List[Occurrence]]] = defaultdict(lambda: defaultdict(list))
+
     for finding in raw_findings:
         uri = finding["source"]
         keyword = finding["keyword_matched"]
         content = finding["content"]
-        link = finding["link"] 
-        
-        for ent in registry[uri]["entities"]:
-            if any(a.name == keyword for a in ent.aliases):
-                occurrence = Occurrence(
-                    link=link,
-                    context=highlight_occurrence(content, keyword)
-                )
-                results[ent.canonical_key][keyword].append(occurrence)
-                
+        link = finding["link"]
+
+        if uri in registry:
+            for ent in registry[uri]["entities"]:
+                if any(a.name == keyword for a in ent.aliases):
+                    occurrence = Occurrence(
+                        link=link, context=highlight_occurrence(content, keyword)
+                    )
+                    results[ent.canonical_key][keyword].append(occurrence)
+
     return results
 
+
 def build_node_structure(entities: List[Entity], entity_results: Dict[str, Any]) -> GraphOutput:
     """Constructs the final list of nodes and edges."""
     nodes, edges = [], []
@@ -84,45 +97,46 @@ def build_node_structure(entities: List[Entity], entity_results: Dict[str, Any])
         ent_id = ent.canonical_key
         human_label = ent.label or ent_id.replace("_", " ").title()
         nodes.append(Node(data=NodeData(id=ent_id, label=human_label, type="entity")))
-        
+
         # Use a dict to accumulate alias nodes by their slugified ID to avoid duplicates
         alias_map = {}
-        
+
         for alias_obj in ent.aliases:
             alias = alias_obj.name
             occurrences = entity_results[ent_id].get(alias, [])
             alias_id = f"{ent_id}__{slugify(alias)}"
-            
+
             if alias_id not in alias_map:
                 alias_map[alias_id] = NodeData(
-                    id=alias_id,
-                    label=alias,
-                    type="alias",
-                    occurrences=[]
+                    id=alias_id, label=alias, type="alias", occurrences=[]
                 )
-            
-            if occurrences:
-                alias_map[alias_id].occurrences.extend(occurrences)
-        
+
+            occ = alias_map[alias_id].occurrences
+            if occurrences and occ is not None:
+                occ.extend(occurrences)
+
         # Add the deduplicated alias nodes and their edges
         for alias_id, node_data in alias_map.items():
             # If no occurrences, clear the list (Pydantic will handle Optional)
             if not node_data.occurrences:
                 node_data.occurrences = None
-            
+
             nodes.append(Node(data=node_data))
-            
+
             count = len(node_data.occurrences) if node_data.occurrences else 0
-            edges.append(Edge(
-                data=EdgeData(
-                    source=ent_id,
-                    target=alias_id,
-                    label=f"Alias ({count})" if count > 0 else "Alias"
+            edges.append(
+                Edge(
+                    data=EdgeData(
+                        source=ent_id,
+                        target=alias_id,
+                        label=f"Alias ({count})" if count > 0 else "Alias",
+                    )
                 )
-            ))
+            )
 
     return GraphOutput(nodes=nodes, edges=edges)
 
+
 async def generate_graph(input_data: Union[str, Dict[str, Any]], output_path: Optional[str] = None):
     """Main orchestration function. Can take a file path (str) or a dictionary."""
     if isinstance(input_data, str):
@@ -134,7 +148,7 @@ async def generate_graph(input_data: Union[str, Dict[str, Any]], output_path: Op
             raise
     else:
         graph_data = input_data
-    
+
     # Validate input
     try:
         validated_input = GraphInput.model_validate(graph_data)
@@ -144,38 +158,37 @@ async def generate_graph(input_data: Union[str, Dict[str, Any]], output_path: Op
         raise
 
     registry = build_registries(entities)
-    
+
     raw_findings = await fetch_extraction_findings(registry)
     entity_results = map_findings_to_entities(raw_findings, registry)
-    
+
     cy_graph = build_node_structure(entities, entity_results)
     cy_json = cy_graph.model_dump(exclude_none=True)
-    
+
     if output_path:
         with fsspec.open(output_path, "w", auto_mkdir=True) as f:
             json.dump(cy_json, f, indent=4)
         logger.info(f"Graph saved to {output_path}")
-    
-    return cy_json
 
+    return cy_json
 
 
 def generate_output_path(source_path: str) -> Tuple[str, str]:
     """Generates the output path for the graph JSON file."""
-    
-    #TODO: make input from user be relative without the bucketname applied
-    match = re.search(r'(?P<domain_name>[^/]+)/(?P<run>run-\d+-\d+)', source_path)
-    s3_bucket_uri = 's3://govuk-ai-accelerator-data-integration'
+
+    # TODO: make input from user be relative without the bucketname applied
+    match = re.search(r"(?P<domain_name>[^/]+)/(?P<run>run-\d+-\d+)", source_path)
+    s3_bucket_uri = "s3://govuk-ai-accelerator-data-integration"
     if match:
-        domain_name = match.group('domain_name')
-        run_id = match.group('run')
-        output_path =f"{s3_bucket_uri}/graph_tools/{domain_name}/{run_id}/graphNode.json"
-        input_path= f"{s3_bucket_uri}/{source_path}"
+        domain_name = match.group("domain_name")
+        run_id = match.group("run")
+        output_path = f"{s3_bucket_uri}/graph_tools/{domain_name}/{run_id}/graphNode.json"
+        input_path = f"{s3_bucket_uri}/{source_path}"
         return input_path, output_path
     else:
         logger.error(f"Invalid input path: {source_path}")
         raise ValueError(f"Invalid input path: {source_path}")
-    
-  
+
+
 if __name__ == "__main__":
     asyncio.run(generate_graph("graph.json", "outputs/graphNode.json"))
diff --git a/src/visualiser_graph_loader.py b/src/visualiser_graph_loader.py
index f98efde..957ed12 100644
--- a/src/visualiser_graph_loader.py
+++ b/src/visualiser_graph_loader.py
@@ -1,20 +1,23 @@
-import fsspec
 import json
 import logging
-import os
 import re
-from typing import Dict, Any
+from typing import Any, Dict
+
+import fsspec
 from werkzeug.exceptions import BadRequest
 
+
 logger = logging.getLogger(__name__)
 
-ONTOLOGY_RUN_PATH_PATTERN = r'(?P<domain_name>[a-zA-Z0-9_-]+)/(?P<run>run-\d+-\d+)'
+ONTOLOGY_RUN_PATH_PATTERN = r"(?P<domain_name>[a-zA-Z0-9_-]+)/(?P<run>run-\d+-\d+)"
 S3_BUCKET_NAME = "govuk-ai-accelerator-data-integration"
 
+
 def load_json_file(file_path: str) -> Dict[str, Any]:
     with fsspec.open(file_path, "r") as f:
         return json.load(f)
 
+
 def visualiser_graph_file_path(source_path: str | None) -> str:
     if source_path:
         domain_name, run_id = extract_path_parts(source_path)
@@ -22,15 +25,16 @@ def visualiser_graph_file_path(source_path: str | None) -> str:
         logger.info(f"Loading graph data from: '{filename}'")
     else:
         filename = "graph-viewmodel.json"
-        logger.info('Loading default example graph data for viewmodel endpoint...')
+        logger.info("Loading default example graph data for viewmodel endpoint...")
     return filename
 
+
 def extract_path_parts(path: str) -> tuple[str, str]:
     match = re.fullmatch(ONTOLOGY_RUN_PATH_PATTERN, path)
     if not match:
         logger.warning(f"Invalid 'source_path' format: '{path}'")
         raise BadRequest(f"Invalid 'source_path' format: '{path}'")
 
-    domain_name = match.group('domain_name')
-    run_id = match.group('run')
+    domain_name = match.group("domain_name")
+    run_id = match.group("run")
     return domain_name, run_id
diff --git a/tests/test_graph_validation.py b/tests/test_graph_validation.py
index 5377dcf..fc0f838 100644
--- a/tests/test_graph_validation.py
+++ b/tests/test_graph_validation.py
@@ -1,7 +1,9 @@
 import pytest
+
 from src.models.graph_models import GraphInput, GraphOutput
 from src.visualiser_graph_generator import slugify
 
+
 def test_graph_input_validation():
     data = {
         "entities": [
@@ -10,7 +12,7 @@ def test_graph_input_validation():
                 "canonical_key": "test_entity",
                 "label": "Test Entity",
                 "aliases": [{"name": "alias1"}, {"name": "alias2"}],
-                "properties": {"sourceUrls": "s3://bucket/key"}
+                "properties": {"sourceUrls": "s3://bucket/key"},
             }
         ]
     }
@@ -18,43 +20,30 @@ def test_graph_input_validation():
     assert len(validated.entities) == 1
     assert validated.entities[0].id == "e1"
 
+
 def test_graph_input_invalid():
     data = {
         "entities": [
             {
                 "id": "e1",
                 # missing canonical_key
-                "label": "Test Entity"
+                "label": "Test Entity",
             }
         ]
     }
     with pytest.raises(Exception):
         GraphInput.model_validate(data)
 
+
 def test_slugify():
     assert slugify("Hello World!") == "hello_world"
     assert slugify("Test-123") == "test_123"
 
+
 def test_graph_output_validation():
     data = {
-        "nodes": [
-            {
-                "data": {
-                    "id": "e1",
-                    "label": "Entity 1",
-                    "type": "entity"
-                }
-            }
-        ],
-        "edges": [
-            {
-                "data": {
-                    "source": "e1",
-                    "target": "a1",
-                    "label": "Alias"
-                }
-            }
-        ]
+        "nodes": [{"data": {"id": "e1", "label": "Entity 1", "type": "entity"}}],
+        "edges": [{"data": {"source": "e1", "target": "a1", "label": "Alias"}}],
     }
     validated = GraphOutput.model_validate(data)
     assert len(validated.nodes) == 1
diff --git a/tests/test_routes.py b/tests/test_routes.py
index 354e41c..cc38306 100644
--- a/tests/test_routes.py
+++ b/tests/test_routes.py
@@ -1,9 +1,9 @@
-import pytest
 import importlib
-import sys
+
 from werkzeug.test import Client
 from werkzeug.wrappers import Response
 
+
 def _app_module():
     return importlib.import_module("app")
 
@@ -11,9 +11,10 @@ def _app_module():
 def _client():
     return Client(_app_module().create_app(), Response)
 
+
 def test_healthcheck_ready_route():
     response = _client().get("/healthcheck/ready")
 
     assert response.status_code == 200
     body = response.get_data(as_text=True)
-    assert 'Application OK' in body
+    assert "Application OK" in body
diff --git a/uv.lock b/uv.lock
index b978467..c2c6e5b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,6 +1,10 @@
 version = 1
 revision = 3
 requires-python = ">=3.12"
+resolution-markers = [
+    "python_full_version >= '3.15'",
+    "python_full_version < '3.15'",
+]
 
 [[package]]
 name = "aiobotocore"
@@ -222,6 +226,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/9a/3c/c17fb3ca2d9c3acff52e30b309f538586f9f5b9c9cf454f3845fc9af4881/certifi-2026.2.25-py3-none-any.whl", hash = "sha256:027692e4402ad994f1c42e52a4997a9763c646b73e4096e4d5d6db8af1d6f0fa", size = 153684, upload-time = "2026-02-25T02:54:15.766Z" },
 ]
 
+[[package]]
+name = "cfgv"
+version = "3.5.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/4e/b5/721b8799b04bf9afe054a3899c6cf4e880fcf8563cc71c15610242490a0c/cfgv-3.5.0.tar.gz", hash = "sha256:d5b1034354820651caa73ede66a6294d6e95c1b00acc5e9b098e917404669132", size = 7334, upload-time = "2025-11-19T20:55:51.612Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/db/3c/33bac158f8ab7f89b2e59426d5fe2e4f63f7ed25df84c036890172b412b5/cfgv-3.5.0-py2.py3-none-any.whl", hash = "sha256:a8dc6b26ad22ff227d2634a65cb388215ce6cc96bbcc5cfde7641ae87e8dacc0", size = 7445, upload-time = "2025-11-19T20:55:50.744Z" },
+]
+
 [[package]]
 name = "charset-normalizer"
 version = "3.4.7"
@@ -316,6 +329,15 @@ wheels = [
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