diff --git a/.gitignore b/.gitignore
index 2eea525..04aa24c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,65 @@
-.env
\ No newline at end of file
+COMMS.md
+# --- Byte-compiled / optimized / DLL files ---
+**/__pycache__/
+*.py[cod]
+*$py.class
+
+# --- Virtual Environments ---
+# It's best practice to keep these out of your repo
+.venv/
+venv/
+ENV/
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# --- Unit test / coverage reports ---
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.pyo
+.hypothesis/
+.pytest_cache/
+cover/
+
+# --- Jupyter Notebooks ---
+.ipynb_checkpoints
+
+# --- Environment Variables & Secrets ---
+# NEVER commit these files
+.env
+.venv
+env.ini
+.env.test
+.secrets
+
+# --- IDE Specific Files ---
+.vscode/
+.idea/
+*.swp
+*.swo
+
+# --- OS Generated Files ---
+.DS_Store
+Thumbs.db
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..8cb444e
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,39 @@
+repos:
+  # 1. Standard Hygiene
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.5.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-added-large-files
+        args: ['--maxkb=500']
+
+  # 3. Ruff: The All-in-One (Linter + Formatter + Isort)
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.1.11
+    hooks:
+      - id: ruff
+        args: [ --fix, --exit-non-zero-on-fix ]
+      - id: ruff-format
+
+  # 4. Mypy: Static Type Checking (Crucial for FastAPI/Pydantic)
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.8.0
+    hooks:
+      - id: mypy
+        additional_dependencies: [
+          "types-requests",
+          "pydantic",
+          "fastapi"
+        ]
+        args: [--ignore-missing-imports, --scripts-are-modules]
+
+  # 5. Poetry: Dependency Integrity
+  - repo: local
+    hooks:
+      - id: poetry-check
+        name: poetry check
+        entry: poetry check
+        language: system
+        pass_filenames: false
diff --git a/README_API.md b/README_API.md
new file mode 100644
index 0000000..7002a87
--- /dev/null
+++ b/README_API.md
@@ -0,0 +1,514 @@
+# ML Tech Assessment - API Documentation
+
+## Table of Contents
+- [Overview](#overview)
+- [Prerequisites](#prerequisites)
+- [Environment Setup](#environment-setup)
+- [Configuration](#configuration)
+- [Running the Application](#running-the-application)
+- [API Endpoints](#api-endpoints)
+- [Error Handling](#error-handling)
+- [Testing](#testing)
+
+## Overview
+
+This API provides LLM-powered text summarization and call-to-action (CTA) generation services. Built with FastAPI, it offers both synchronous and asynchronous endpoints for processing single and batch text summarization requests.
+
+**Key Features:**
+- Generate summaries and actionable CTAs from text
+- Retrieve previously generated summaries by ID
+- Batch processing with async support
+- In-memory storage for generated summaries
+- Built-in error handling for LLM service failures
+
+**Technology Stack:**
+- Python 3.12
+- FastAPI
+- OpenAI API
+- Poetry (dependency management)
+- Pydantic (data validation)
+
+## Prerequisites
+
+### Install Conda
+
+Conda is recommended for managing the Python environment. Choose one of the following:
+
+#### Option 1: Miniconda (Minimal installation)
+```bash
+# Linux/Mac
+wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+bash Miniconda3-latest-Linux-x86_64.sh
+
+# Follow the installation prompts
+# Restart your terminal after installation
+```
+
+#### Option 2: Anaconda (Full distribution)
+Download and install from [Anaconda's website](https://www.anaconda.com/products/distribution)
+
+Verify installation:
+```bash
+conda --version
+```
+
+## Environment Setup
+
+### 1. Create Conda Environment
+
+Create a new conda environment with Python 3.12 (matching the project requirement):
+
+```bash
+conda create -n ml-assessment python=3.12
+```
+
+**Note:** This creates an isolated Python environment. The actual project dependencies will be synced from `pyproject.toml` in the next steps.
+
+### 2. Activate Environment
+
+```bash
+conda activate ml-assessment
+```
+
+**Note:** You'll need to activate this environment every time you work on the project.
+
+### 3. Install Poetry
+
+Poetry is used for dependency management:
+
+```bash
+pip install poetry
+```
+
+### 4. Sync Project Dependencies from Configuration
+
+Poetry will read the `pyproject.toml` and `poetry.lock` files to replicate the exact environment configuration:
+
+```bash
+poetry install
+```
+
+This command **syncs your environment** with the project's dependency specifications, installing:
+- `fastapi[standard]` - Web framework with standard dependencies
+- `openai` - OpenAI API client
+- `pydantic-settings` - Settings management
+- `redis[hiredis]` - Redis client with C parser
+- `pytest` - Testing framework
+- Development dependencies (ruff, pytest-cov, pre-commit)
+
+**Important:**
+- The `poetry.lock` file ensures you get the **exact same versions** used in development
+- This replicates the working environment, not creating a new configuration from scratch
+- Poetry reads from the existing `pyproject.toml` to sync all dependencies
+
+**Verify Installation:**
+```bash
+# Check installed packages
+poetry show
+
+# Verify key packages
+poetry show fastapi openai pydantic-settings
+```
+
+## Configuration
+
+### Environment Variables
+
+Create a `.env` file in the root directory of the project with the following variables:
+
+```bash
+# Required: OpenAI API Configuration
+OPENAI_API_KEY=your_openai_api_key_here
+OPENAI_MODEL=gpt-4  # or gpt-3.5-turbo, gpt-4-turbo, etc.
+
+# Optional: API Configuration
+HOST=0.0.0.0
+PORT=8000
+```
+
+**Important:** Never commit the `.env` file to version control. It's already included in `.gitignore`.
+
+## Running the Application
+
+### Development Mode
+
+Start the FastAPI development server:
+
+```bash
+# Make sure your conda environment is activated
+conda activate ml-assessment
+
+# Run with uvicorn (included in fastapi[standard])
+uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
+```
+
+The API will be available at:
+- **API Base URL:** `http://localhost:8000`
+- **Interactive API Docs (Swagger):** `http://localhost:8000/docs`
+- **Alternative API Docs (ReDoc):** `http://localhost:8000/redoc`
+
+### Production Mode
+
+For production deployment:
+
+```bash
+uvicorn app.main:app --host 0.0.0.0 --port 8000 --workers 4
+```
+
+## API Endpoints
+
+### Base URL
+```
+http://localhost:8000
+```
+
+---
+
+### 1. Root Endpoint
+
+**GET** `/`
+
+Simple health check endpoint.
+
+**Response:**
+```json
+{
+  "Hello": "World"
+}
+```
+
+---
+
+### 2. Generate Summary and CTAs
+
+**GET** `/summary_maker/get_summary_and_ctas`
+
+Generates a summary and calls to action (CTAs) for a given text using the LLM service.
+
+**Parameters:**
+
+| Parameter | Type | Location | Required | Description |
+|-----------|------|----------|----------|-------------|
+| `text_to_summary` | string | Query | Yes | The transcript text to analyze (min 10 characters, whitespace trimmed) |
+
+**Request Example:**
+```bash
+curl -X GET "http://localhost:8000/summary_maker/get_summary_and_ctas?text_to_summary=This%20is%20a%20sample%20transcript%20discussing%20project%20goals%20and%20next%20steps"
+```
+
+**Response Example:**
+```json
+{
+  "id": "123e4567-e89b-12d3-a456-426614174000",
+  "summary": "A comprehensive summary of the provided text content",
+  "ctas": [
+    "Review and approve the project timeline",
+    "Schedule follow-up meeting with stakeholders",
+    "Document technical requirements"
+  ]
+}
+```
+
+**Response Schema:**
+- `id` (string): Unique identifier for the generated summary
+- `summary` (string): Generated summary of the input text
+- `ctas` (array of strings): List of actionable calls to action
+
+**Status Codes:**
+- `200 OK` - Successfully generated summary
+- `400 Bad Request` - Invalid input (text too short or invalid format)
+- `401 Unauthorized` - Invalid OpenAI API credentials
+- `503 Service Unavailable` - LLM service error
+
+---
+
+### 3. Retrieve Summary by ID
+
+**GET** `/summary_maker/get_summary_and_ctas_by_id`
+
+Retrieves a previously generated summary and its associated CTAs using the summary ID.
+
+**Parameters:**
+
+| Parameter | Type | Location | Required | Description |
+|-----------|------|----------|----------|-------------|
+| `id` | string | Query | Yes | The unique ID of the summary to retrieve |
+
+**Request Example:**
+```bash
+curl -X GET "http://localhost:8000/summary_maker/get_summary_and_ctas_by_id?id=123e4567-e89b-12d3-a456-426614174000"
+```
+
+**Response Example:**
+```json
+{
+  "id": "123e4567-e89b-12d3-a456-426614174000",
+  "content": "A comprehensive summary of the provided text content",
+  "ctas": [
+    "Review and approve the project timeline",
+    "Schedule follow-up meeting with stakeholders"
+  ]
+}
+```
+
+**Status Codes:**
+- `200 OK` - Successfully retrieved summary
+- `404 Not Found` - Summary with given ID does not exist
+
+---
+
+### 4. Batch Async Summary Generation
+
+**POST** `/summary_maker/async_get_summary_and_ctas`
+
+Asynchronously generates summaries and CTAs for a batch of texts. Processes multiple texts in parallel and returns results in the same order as the input.
+
+**Request Body:**
+
+Array of text strings (each min 10 characters):
+
+```json
+[
+  "First transcript text to summarize with at least 10 characters",
+  "Second transcript text to summarize with sufficient length",
+  "Third transcript text for batch processing"
+]
+```
+
+**Request Example:**
+```bash
+curl -X POST "http://localhost:8000/summary_maker/async_get_summary_and_ctas" \
+  -H "Content-Type: application/json" \
+  -d '[
+    "This is the first meeting transcript discussing quarterly goals",
+    "Second transcript about technical architecture decisions",
+    "Third transcript covering team collaboration improvements"
+  ]'
+```
+
+**Response Example:**
+```json
+{
+  "items": [
+    {
+      "summary": {
+        "id": "uuid-1",
+        "summary": "Summary of first text",
+        "ctas": ["Action 1", "Action 2"]
+      },
+      "error": null
+    },
+    {
+      "summary": {
+        "id": "uuid-2",
+        "summary": "Summary of second text",
+        "ctas": ["Action 1"]
+      },
+      "error": null
+    },
+    {
+      "summary": null,
+      "error": "Error processing this item: rate limit exceeded"
+    }
+  ]
+}
+```
+
+**Response Schema:**
+- `items` (array): Array of results, one per input text (maintains order)
+  - `summary` (object or null): Summary response object if successful
+    - `id` (string): Unique identifier
+    - `summary` (string): Generated summary
+    - `ctas` (array): List of CTAs
+  - `error` (string or null): Error message if processing failed
+
+**Status Codes:**
+- `200 OK` - Batch processing completed (check individual items for errors)
+- `400 Bad Request` - Invalid request body format
+- `401 Unauthorized` - Invalid OpenAI API credentials
+
+**Notes:**
+- Individual items can fail while others succeed
+- Results maintain the same order as input
+- All items are processed concurrently for optimal performance
+
+---
+
+### 5. List All Summary IDs
+
+**GET** `/extras/get_summaries_ids`
+
+Retrieves a list of all summary IDs that have been generated and stored in the repository.
+
+**Request Example:**
+```bash
+curl -X GET "http://localhost:8000/extras/get_summaries_ids"
+```
+
+**Response Example:**
+```json
+[
+  "123e4567-e89b-12d3-a456-426614174000",
+  "987fcdeb-51a2-43f7-b890-123456789abc",
+  "456789ab-cdef-0123-4567-89abcdef0123"
+]
+```
+
+**Response Schema:**
+- Array of strings containing all summary IDs
+
+**Status Codes:**
+- `200 OK` - Successfully retrieved list (may be empty array if no summaries exist)
+
+---
+
+## Error Handling
+
+The API includes comprehensive error handling for OpenAI service errors:
+
+### Error Response Format
+
+```json
+{
+  "detail": "Error description message"
+}
+```
+
+### Common Error Codes
+
+| Status Code | Error Type | Description | Resolution |
+|-------------|------------|-------------|------------|
+| `400` | Bad Request | Invalid request format or parameters | Check request body/query parameters |
+| `401` | Authentication Error | Invalid OpenAI API credentials | Verify `OPENAI_API_KEY` in `.env` file |
+| `404` | Not Found | Summary ID does not exist | Check the ID or use `/extras/get_summaries_ids` |
+| `503` | Service Unavailable | LLM service error (rate limits, timeouts) | Retry the request after a delay |
+
+### OpenAI-Specific Errors
+
+The API automatically catches and handles:
+- **AuthenticationError**: Invalid API key → 401 response
+- **BadRequestError**: Invalid LLM request → 400 response
+- **OpenAIError**: General service errors → 503 response
+
+## Testing
+
+### Run All Tests
+
+```bash
+# Activate environment
+conda activate ml-assessment
+
+# Run tests
+pytest
+```
+
+### Verbose Test Output
+
+```bash
+pytest -v
+```
+
+### Coverage Report
+
+```bash
+pytest --cov
+```
+
+### Test Structure
+
+Tests are located in the `tests/` directory:
+- `tests/adapters/` - Tests for OpenAI adapter
+- `tests/adapters/mock_data.py` - Mock data for testing
+
+## API Usage Examples
+
+### Python Example
+
+```python
+import requests
+
+BASE_URL = "http://localhost:8000"
+
+# Generate a summary
+response = requests.get(
+    f"{BASE_URL}/summary_maker/get_summary_and_ctas",
+    params={"text_to_summary": "Your long text content here..."}
+)
+summary_data = response.json()
+print(f"Summary ID: {summary_data['id']}")
+print(f"Summary: {summary_data['summary']}")
+print(f"CTAs: {summary_data['ctas']}")
+
+# Retrieve by ID
+response = requests.get(
+    f"{BASE_URL}/summary_maker/get_summary_and_ctas_by_id",
+    params={"id": summary_data['id']}
+)
+retrieved = response.json()
+```
+
+### JavaScript/Node.js Example
+
+```javascript
+const BASE_URL = "http://localhost:8000";
+
+// Generate a summary
+async function generateSummary(text) {
+  const response = await fetch(
+    `${BASE_URL}/summary_maker/get_summary_and_ctas?text_to_summary=${encodeURIComponent(text)}`
+  );
+  const data = await response.json();
+  return data;
+}
+
+// Batch processing
+async function batchProcess(texts) {
+  const response = await fetch(
+    `${BASE_URL}/summary_maker/async_get_summary_and_ctas`,
+    {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify(texts)
+    }
+  );
+  const data = await response.json();
+  return data;
+}
+```
+
+### cURL Examples
+
+```bash
+# Generate summary
+curl -X GET "http://localhost:8000/summary_maker/get_summary_and_ctas?text_to_summary=Your%20text%20here"
+
+# Retrieve by ID
+curl -X GET "http://localhost:8000/summary_maker/get_summary_and_ctas_by_id?id=YOUR_ID_HERE"
+
+# Batch processing
+curl -X POST "http://localhost:8000/summary_maker/async_get_summary_and_ctas" \
+  -H "Content-Type: application/json" \
+  -d '["Text one", "Text two", "Text three"]'
+
+# List all IDs
+curl -X GET "http://localhost:8000/extras/get_summaries_ids"
+```
+
+## Additional Resources
+
+- **FastAPI Documentation:** https://fastapi.tiangolo.com/
+- **OpenAI API Documentation:** https://platform.openai.com/docs/
+- **Poetry Documentation:** https://python-poetry.org/docs/
+- **Interactive API Documentation:** http://localhost:8000/docs (when server is running)
+
+## Notes
+
+- The application uses **in-memory storage** by default. All summaries are lost when the server restarts.
+- For production use, consider implementing persistent storage (database, Redis, etc.).
+- The API uses OpenAI's LLM models. Ensure you have sufficient API credits and respect rate limits.
+- All text inputs are validated (minimum 10 characters, whitespace trimmed).
+- The batch endpoint processes requests concurrently for optimal performance.
+
+## Support
+
+For issues or questions, refer to the main [README.md](./README.md) or check the interactive API documentation at http://localhost:8000/docs when the server is running.
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diff --git a/app/adapters/__pycache__/openai.cpython-312.pyc b/app/adapters/__pycache__/openai.cpython-312.pyc
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diff --git a/app/adapters/openai.py b/app/adapters/openai.py
index 700427f..0751a45 100644
--- a/app/adapters/openai.py
+++ b/app/adapters/openai.py
@@ -1,23 +1,26 @@
 import openai
 import pydantic
-from app import ports
 
+from app.ports.llm import LLm
 
-class OpenAIAdapter(ports.LLm):
+
+class OpenAIAdapter(LLm):
     def __init__(self, api_key: str, model: str) -> None:
         self._model = model
         self._client = openai.OpenAI(api_key=api_key)
         self._aclient = openai.AsyncOpenAI(api_key=api_key)
 
-    def run_completion(self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]) -> pydantic.BaseModel:
+    def run_completion(
+        self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]
+    ) -> pydantic.BaseModel:
         """
         Executes a completion request using the OpenAI API with the provided prompts and response format.
-    
+
         Args:
             system_prompt (str): The system's introductory message for the chat.
             user_prompt (str): The user input for which a response is needed.
             dto (Type[pydantic.BaseModel]): A Pydantic model class used to define the structure of the API response.
-    
+
         Returns:
             pydantic.BaseModel: An instance of the provided DTO class populated with the API response data.
             more info: https://platform.openai.com/docs/guides/structured-outputs?api-mode=chat
@@ -29,12 +32,13 @@ def run_completion(self, system_prompt: str, user_prompt: str, dto: type[pydanti
                 {"role": "system", "content": system_prompt},
                 {"role": "user", "content": user_prompt},
             ],
-            response_format=dto
+            response_format=dto,
         )
         return completion.choices[0].message.parsed
 
-    async def run_completion_async(self, system_prompt: str, user_prompt: str,
-                                   dto: type[pydantic.BaseModel]) -> pydantic.BaseModel:
+    async def run_completion_async(
+        self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]
+    ) -> pydantic.BaseModel:
         """
         Executes a completion request using the OpenAI API with the provided prompts and response format.
 
@@ -47,13 +51,13 @@ async def run_completion_async(self, system_prompt: str, user_prompt: str,
          pydantic.BaseModel: An instance of the provided DTO class populated with the API response data.
 
          more info: https://platform.openai.com/docs/guides/structured-outputs?api-mode=chat
-         """
+        """
         completion = await self._aclient.beta.chat.completions.parse(
             model=self._model,
             messages=[
                 {"role": "system", "content": system_prompt},
                 {"role": "user", "content": user_prompt},
             ],
-            response_format=dto
+            response_format=dto,
         )
         return completion.choices[0].message.parsed
diff --git a/app/configurations.py b/app/configurations.py
index 6416183..6eb8d27 100644
--- a/app/configurations.py
+++ b/app/configurations.py
@@ -2,9 +2,15 @@
 
 
 class EnvConfigs(pydantic_settings.BaseSettings):
-    model_config =pydantic_settings.SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")
+    model_config = pydantic_settings.SettingsConfigDict(
+        env_file=".env", env_file_encoding="utf-8"
+    )
 
     OPENAI_API_KEY: str
     OPENAI_MODEL: str = "gpt-4o-2024-08-06"
 
+    REDIS_HOST: str = "localhost"
+    REDIS_PORT: int = 6379
 
+
+settings = EnvConfigs()
diff --git a/app/dependencies.py b/app/dependencies.py
new file mode 100644
index 0000000..9b193f6
--- /dev/null
+++ b/app/dependencies.py
@@ -0,0 +1,24 @@
+from fastapi import HTTPException
+
+from app.adapters.openai import OpenAIAdapter
+from app.configurations import settings
+from app.ports.llm import LLm
+from app.ports.summary_repository import SummaryRepository
+
+
+def get_llm_service_openai() -> LLm:
+    return OpenAIAdapter(model=settings.OPENAI_MODEL, api_key=settings.OPENAI_API_KEY)
+
+
+_summary_repository: SummaryRepository | None = None
+
+
+def get_summary_repository() -> SummaryRepository:
+    if _summary_repository is None:
+        raise HTTPException(status_code=503, detail="Service temporarily unavailable")
+    return _summary_repository
+
+
+def set_summary_repository(repository: SummaryRepository) -> None:
+    global _summary_repository
+    _summary_repository = repository
diff --git a/app/domain/entities.py b/app/domain/entities.py
new file mode 100644
index 0000000..d70c069
--- /dev/null
+++ b/app/domain/entities.py
@@ -0,0 +1,8 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class Summary:
+    id: str
+    content: str
+    ctas: list[str]
diff --git a/app/main.py b/app/main.py
new file mode 100644
index 0000000..7406724
--- /dev/null
+++ b/app/main.py
@@ -0,0 +1,65 @@
+from contextlib import asynccontextmanager
+
+import fastapi
+from fastapi import FastAPI, Request
+from fastapi.responses import JSONResponse
+from openai import (
+    AuthenticationError,
+    BadRequestError,
+    OpenAIError,
+)
+
+from app.dependencies import set_summary_repository
+from app.repositories.in_memory import InMemorySummaryRepository
+from app.routers import extras, summary
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    repository = InMemorySummaryRepository()
+    set_summary_repository(repository)
+
+    yield
+
+
+app = fastapi.FastAPI(lifespan=lifespan)
+
+
+def _openai_error_response(
+    request: Request, status_code: int, detail: str, exception: Exception
+) -> JSONResponse:
+    return JSONResponse(
+        status_code=status_code,
+        content={"detail": detail},
+    )
+
+
+@app.exception_handler(AuthenticationError)
+async def auth_handler(request: Request, exc: AuthenticationError) -> JSONResponse:
+    return _openai_error_response(request, 401, "Invalid API credentials.", exc)
+
+
+@app.exception_handler(BadRequestError)
+async def bad_request_handler(request: Request, exc: BadRequestError) -> JSONResponse:
+    return _openai_error_response(request, 400, "Invalid request to LLM service.", exc)
+
+
+# Fallback for any other OpenAI error
+@app.exception_handler(OpenAIError)
+async def openai_error_handler(request: Request, exc: OpenAIError) -> JSONResponse:
+    return _openai_error_response(
+        request, 503, "LLM service error. Please retry later.", exc
+    )
+
+
+app.include_router(summary.router)
+app.include_router(extras.router)
+
+
+@app.get("/")
+def read_root():
+    return {"Hello": "World"}
+
+
+if __name__ == "__main__":
+    fastapi.run(app, host="[IP_ADDRESS]", port=8000)
diff --git a/app/ports/__init__.py b/app/ports/__init__.py
index d082b39..e69de29 100644
--- a/app/ports/__init__.py
+++ b/app/ports/__init__.py
@@ -1 +0,0 @@
-from app.ports.llm import LLm
\ No newline at end of file
diff --git a/app/ports/__pycache__/__init__.cpython-312.pyc b/app/ports/__pycache__/__init__.cpython-312.pyc
deleted file mode 100644
index 2931c93..0000000
Binary files a/app/ports/__pycache__/__init__.cpython-312.pyc and /dev/null differ
diff --git a/app/ports/__pycache__/llm.cpython-312.pyc b/app/ports/__pycache__/llm.cpython-312.pyc
deleted file mode 100644
index 7627420..0000000
Binary files a/app/ports/__pycache__/llm.cpython-312.pyc and /dev/null differ
diff --git a/app/ports/llm.py b/app/ports/llm.py
index 4e31ec3..40b15b4 100644
--- a/app/ports/llm.py
+++ b/app/ports/llm.py
@@ -1,8 +1,17 @@
-import pydantic
 from abc import ABC, abstractmethod
 
+import pydantic
+
 
 class LLm(ABC):
     @abstractmethod
-    def run_completion(self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]) -> pydantic.BaseModel:
+    def run_completion(
+        self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]
+    ) -> pydantic.BaseModel:
+        pass
+
+    @abstractmethod
+    async def run_completion_async(
+        self, system_prompt: str, user_prompt: str, dto: type[pydantic.BaseModel]
+    ) -> pydantic.BaseModel:
         pass
diff --git a/app/ports/summary_repository.py b/app/ports/summary_repository.py
new file mode 100644
index 0000000..b7efd56
--- /dev/null
+++ b/app/ports/summary_repository.py
@@ -0,0 +1,17 @@
+from abc import ABC, abstractmethod
+
+from app.domain.entities import Summary
+
+
+class SummaryRepository(ABC):
+    @abstractmethod
+    def save(self, summary: Summary) -> None:
+        pass
+
+    @abstractmethod
+    def get_by_id(self, id: str) -> Summary | None:
+        pass
+
+    @abstractmethod
+    def list_ids(self) -> list[str]:
+        pass
diff --git a/app/prompts.py b/app/prompts.py
index 6b5b496..f42401c 100644
--- a/app/prompts.py
+++ b/app/prompts.py
@@ -8,4 +8,3 @@
 
                     Transcript:
                     {transcript}"""
-
diff --git a/app/repositories/__init__.py b/app/repositories/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app/repositories/in_memory.py b/app/repositories/in_memory.py
new file mode 100644
index 0000000..09ddae4
--- /dev/null
+++ b/app/repositories/in_memory.py
@@ -0,0 +1,16 @@
+from app.domain.entities import Summary
+from app.ports.summary_repository import SummaryRepository
+
+
+class InMemorySummaryRepository(SummaryRepository):
+    def __init__(self) -> None:
+        self._store: dict[str, Summary] = {}
+
+    def save(self, summary: Summary) -> None:
+        self._store[str(summary.id)] = summary
+
+    def get_by_id(self, id: str) -> Summary | None:
+        return self._store.get(id)
+
+    def list_ids(self) -> list[str]:
+        return list(self._store.keys())
diff --git a/app/routers/__init__.py b/app/routers/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app/routers/extras.py b/app/routers/extras.py
new file mode 100644
index 0000000..4e393bc
--- /dev/null
+++ b/app/routers/extras.py
@@ -0,0 +1,21 @@
+from fastapi import APIRouter, Depends
+
+from app.dependencies import get_summary_repository
+from app.ports.summary_repository import SummaryRepository
+
+router = APIRouter(prefix="/extras", tags=["extras"])
+
+
+@router.get(
+    "/get_summaries_ids",
+    response_model=list[str],
+    summary="Retrieve list of all summary IDs",
+    description=(
+        "Fetches a list containing the unique IDs of all summaries that have been generated and stored "
+        "in the repository. This endpoint provides a simple way to enumerate all available summaries for later retrieval."
+    ),
+)
+async def get_summaries_ids(
+    repository: SummaryRepository = Depends(get_summary_repository),
+) -> list[str]:
+    return repository.list_ids()
diff --git a/app/routers/summary.py b/app/routers/summary.py
new file mode 100644
index 0000000..745d078
--- /dev/null
+++ b/app/routers/summary.py
@@ -0,0 +1,117 @@
+import asyncio
+from uuid import uuid4
+
+from fastapi import APIRouter, Depends, HTTPException, Query
+
+from app.dependencies import get_llm_service_openai, get_summary_repository
+from app.domain.entities import Summary
+from app.ports.llm import LLm
+from app.ports.summary_repository import SummaryRepository
+from app.prompts import RAW_USER_PROMPT, SYSTEM_PROMPT
+from app.schemas.llm_responses import SummaryLLMOutput
+from app.schemas.requests import TextToSummary
+from app.schemas.responses import (
+    BatchSummaryItem,
+    BatchSummaryResponse,
+    SummaryResponse,
+)
+
+router = APIRouter(prefix="/summary_maker", tags=["summary_maker"])
+
+
+@router.get(
+    "/get_summary_and_ctas",
+    response_model=SummaryResponse,
+    summary="Gets the summary and calls to action (CTAs) for a given text.",
+    description=(
+        "Provides a summary and actionable CTAs for a supplied text. "
+        "This endpoint accepts a text input, processes it via the LLM service, "
+        "and returns a structured response containing the generated summary and a list of CTAs. "
+        "The summary is designed to encapsulate the key ideas, while the CTAs are actionable recommendations "
+        "or next steps derived from the content."
+    ),
+)
+async def get_summary_and_ctas(
+    text_to_summary: TextToSummary = Query(
+        ...,
+        description="The transcript text to analyze",
+        example="This is a sample transcript discussing project goals...",
+    ),
+    llm: LLm = Depends(get_llm_service_openai),
+    repository: SummaryRepository = Depends(get_summary_repository),
+) -> SummaryResponse:
+    llm_result = llm.run_completion(
+        SYSTEM_PROMPT,
+        RAW_USER_PROMPT.format(transcript=str(text_to_summary)),
+        dto=SummaryLLMOutput,
+    )
+
+    summary_entity = Summary(
+        id=str(uuid4()), content=llm_result.content, ctas=llm_result.ctas
+    )
+
+    repository.save(summary_entity)
+
+    return SummaryResponse.from_entity(summary_entity)
+
+
+@router.get(
+    "/get_summary_and_ctas_by_id",
+    response_model=Summary,
+    summary="Retrieve a summary and CTAs by its unique ID.",
+    description=(
+        "Fetches a previously generated summary and its associated calls to action (CTAs) "
+        "using the provided summary ID. This endpoint allows consumers to retrieve the summary content "
+        "and actionable CTAs for a specific document or text that was processed earlier and stored in the repository."
+    ),
+)
+async def get_summary_and_ctas_by_id(
+    id: str, repository: SummaryRepository = Depends(get_summary_repository)
+) -> Summary:
+    summary = repository.get_by_id(id)
+
+    if summary is None:
+        raise HTTPException(status_code=404, detail="Summary not found")
+    return summary
+
+
+@router.post(
+    "/async_get_summary_and_ctas",
+    response_model=BatchSummaryResponse,
+    summary="Asynchronously generate summaries and CTAs for a batch of texts.",
+    description=(
+        "Accepts a list of texts and asynchronously processes each to generate a summary and actionable calls to action (CTAs) "
+        "using the LLM service. Instead of handling requests one by one, this endpoint allows multiple texts to be summarized in parallel, "
+        "returning a list of structured summary responses. Each response contains the summary and associated CTAs for the corresponding input text."
+    ),
+)
+async def async_single_get_summary_and_ctas(
+    list_of_texts_to_summarize: list[TextToSummary],
+    llm: LLm = Depends(get_llm_service_openai),
+    repository: SummaryRepository = Depends(get_summary_repository),
+) -> BatchSummaryResponse:
+    async def process_one_request(text_to_summarize: TextToSummary) -> Summary:
+        llm_result = await llm.run_completion_async(
+            SYSTEM_PROMPT,
+            RAW_USER_PROMPT.format(transcript=str(text_to_summarize)),
+            dto=SummaryLLMOutput,
+        )
+
+        summary_entity = Summary(
+            id=str(uuid4()), content=llm_result.content, ctas=llm_result.ctas
+        )
+
+        repository.save(summary_entity)
+
+        return summary_entity
+
+    tasks = [process_one_request(item) for item in list_of_texts_to_summarize]
+    raw_results = await asyncio.gather(*tasks, return_exceptions=True)
+    items: list[BatchSummaryItem] = []
+    for result in raw_results:
+        if isinstance(result, BaseException):
+            items.append(BatchSummaryItem(error=str(result)))
+        else:
+            items.append(BatchSummaryItem(summary=SummaryResponse.from_entity(result)))
+
+    return BatchSummaryResponse(items=items)
diff --git a/app/schemas/__init__.py b/app/schemas/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app/schemas/llm_responses.py b/app/schemas/llm_responses.py
new file mode 100644
index 0000000..e4233b6
--- /dev/null
+++ b/app/schemas/llm_responses.py
@@ -0,0 +1,8 @@
+from pydantic import BaseModel, Field
+
+
+class SummaryLLMOutput(BaseModel):
+    content: str = Field(examples=["Summary of the text provided"])
+    ctas: list[str] = Field(
+        examples=["1) First call to action 2) Second call to action"]
+    )
diff --git a/app/schemas/requests.py b/app/schemas/requests.py
new file mode 100644
index 0000000..b58e0dd
--- /dev/null
+++ b/app/schemas/requests.py
@@ -0,0 +1,5 @@
+from typing import Annotated
+
+from pydantic import StringConstraints
+
+TextToSummary = Annotated[str, StringConstraints(strip_whitespace=True, min_length=10)]
diff --git a/app/schemas/responses.py b/app/schemas/responses.py
new file mode 100644
index 0000000..6bd369d
--- /dev/null
+++ b/app/schemas/responses.py
@@ -0,0 +1,28 @@
+from pydantic import BaseModel, Field
+
+from app.domain.entities import Summary
+
+
+class SummaryResponse(BaseModel):
+    id: str = Field(examples=["123-abc"])
+    summary: str = Field(examples=["Summary of the text provided"])
+    ctas: list[str] = Field(
+        examples=["1) First call to action 2) Second call to action"]
+    )
+
+    @classmethod
+    def from_entity(cls, entity: Summary):
+        return cls(id=entity.id, summary=entity.content, ctas=entity.ctas)
+
+
+class BatchSummaryItem(BaseModel):
+    """Single item in a batch summary response — either success or error."""
+
+    summary: SummaryResponse | None = None
+    error: str | None = None
+
+
+class BatchSummaryResponse(BaseModel):
+    """Batch response with one entry per input, preserving order."""
+
+    items: list[BatchSummaryItem]
diff --git a/assessment.md b/assessment.md
index 948879b..d5826c7 100644
--- a/assessment.md
+++ b/assessment.md
@@ -52,4 +52,4 @@ A file defining the interface (ports) for this adapter will be provided.
 - You will find a test running openai adapter. This will be the documentation to build the prompt to analyze the transcript
 - The provided OpenAI adapter utilizes structured output, allowing you to specify a system prompt, a user prompt, and a DTO. The adapter then returns a model instance populated according to the DTO's defined structure.
 - Create a DTO that contains the requested fields.
-- Hexagonal (or clean) architecture consists of distinct layers. Consider creating a separate model layer for the LLM responses. Pay attention to avoiding layer coupling. 
+- Hexagonal (or clean) architecture consists of distinct layers. Consider creating a separate model layer for the LLM responses. Pay attention to avoiding layer coupling.
diff --git a/poetry.lock b/poetry.lock
index c70e10c..39fdcb7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,16 @@
-# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.3.1 and should not be changed by hand.
+
+[[package]]
+name = "annotated-doc"
+version = "0.0.4"
+description = "Document parameters, class attributes, return types, and variables inline, with Annotated."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "annotated_doc-0.0.4-py3-none-any.whl", hash = "sha256:571ac1dc6991c450b25a9c2d84a3705e2ae7a53467b5d111c24fa8baabbed320"},
+    {file = "annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4"},
+]
 
 [[package]]
 name = "annotated-types"
@@ -46,18 +58,162 @@ files = [
     {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"},
 ]
 
+[[package]]
+name = "cfgv"
+version = "3.5.0"
+description = "Validate configuration and produce human readable error messages."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "cfgv-3.5.0-py2.py3-none-any.whl", hash = "sha256:a8dc6b26ad22ff227d2634a65cb388215ce6cc96bbcc5cfde7641ae87e8dacc0"},
+    {file = "cfgv-3.5.0.tar.gz", hash = "sha256:d5b1034354820651caa73ede66a6294d6e95c1b00acc5e9b098e917404669132"},
+]
+
+[[package]]
+name = "click"
+version = "8.3.1"
+description = "Composable command line interface toolkit"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "click-8.3.1-py3-none-any.whl", hash = "sha256:981153a64e25f12d547d3426c367a4857371575ee7ad18df2a6183ab0545b2a6"},
+    {file = "click-8.3.1.tar.gz", hash = "sha256:12ff4785d337a1bb490bb7e9c2b1ee5da3112e94a8622f26a6c77f5d2fc6842a"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-groups = ["main"]
-markers = "platform_system == \"Windows\" or sys_platform == \"win32\""
+groups = ["main", "dev"]
 files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
+markers = {main = "platform_system == \"Windows\" or sys_platform == \"win32\"", dev = "sys_platform == \"win32\""}
+
+[[package]]
+name = "coverage"
+version = "7.13.2"
+description = "Code coverage measurement for Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "coverage-7.13.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f4af3b01763909f477ea17c962e2cca8f39b350a4e46e3a30838b2c12e31b81b"},
+    {file = "coverage-7.13.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:36393bd2841fa0b59498f75466ee9bdec4f770d3254f031f23e8fd8e140ffdd2"},
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+]
+
 [[package]]
 name = "httpcore"
 version = "1.0.9"
@@ -105,6 +668,59 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<1.0)"]
 
+[[package]]
+name = "httptools"
+version = "0.7.1"
+description = "A collection of framework independent HTTP protocol utils."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "httptools-0.7.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:aeefa0648362bb97a7d6b5ff770bfb774930a327d7f65f8208394856862de517"},
+    {file = "httptools-0.7.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0d92b10dbf0b3da4823cde6a96d18e6ae358a9daa741c71448975f6a2c339cad"},
+    {file = "httptools-0.7.1-cp39-cp39-win_amd64.whl", hash = "sha256:5ddbd045cfcb073db2449563dd479057f2c2b681ebc232380e63ef15edc9c023"},
+    {file = "httptools-0.7.1.tar.gz", hash = "sha256:abd72556974f8e7c74a259655924a717a2365b236c882c3f6f8a45fe94703ac9"},
+]
+
 [[package]]
 name = "httpx"
 version = "0.28.1"
@@ -130,6 +746,21 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "identify"
+version = "2.6.16"
+description = "File identification library for Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "identify-2.6.16-py2.py3-none-any.whl", hash = "sha256:391ee4d77741d994189522896270b787aed8670389bfd60f326d677d64a6dfb0"},
+    {file = "identify-2.6.16.tar.gz", hash = "sha256:846857203b5511bbe94d5a352a48ef2359532bc8f6727b5544077a0dcfb24980"},
+]
+
+[package.extras]
+license = ["ukkonen"]
+
 [[package]]
 name = "idna"
 version = "3.10"
@@ -151,12 +782,30 @@ version = "2.1.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760"},
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 ]
 
+[[package]]
+name = "jinja2"
+version = "3.1.6"
+description = "A very fast and expressive template engine."
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"},
+    {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
 [[package]]
 name = "jiter"
 version = "0.9.0"
@@ -243,6 +892,153 @@ files = [
     {file = "jiter-0.9.0.tar.gz", hash = "sha256:aadba0964deb424daa24492abc3d229c60c4a31bfee205aedbf1acc7639d7893"},
 ]
 
+[[package]]
+name = "markdown-it-py"
+version = "4.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "markdown-it-pyrs", "mistletoe (>=1.0,<2.0)", "mistune (>=3.0,<4.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins (>=0.5.0)"]
+profiling = ["gprof2dot"]
+rtd = ["ipykernel", "jupyter_sphinx", "mdit-py-plugins (>=0.5.0)", "myst-parser", "pyyaml", "sphinx", "sphinx-book-theme (>=1.0,<2.0)", "sphinx-copybutton", "sphinx-design"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions", "requests"]
+
+[[package]]
+name = "markupsafe"
+version = "3.0.3"
+description = "Safely add untrusted strings to HTML/XML markup."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
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+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
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+    {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
+]
+
+[[package]]
+name = "nodeenv"
+version = "1.10.0"
+description = "Node.js virtual environment builder"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+groups = ["dev"]
+files = [
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+    {file = "nodeenv-1.10.0.tar.gz", hash = "sha256:996c191ad80897d076bdfba80a41994c2b47c68e224c542b48feba42ba00f8bb"},
+]
+
 [[package]]
 name = "openai"
 version = "1.76.2"
@@ -276,19 +1072,36 @@ version = "25.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
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 ]
 
+[[package]]
+name = "platformdirs"
+version = "4.5.1"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
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+    {file = "platformdirs-4.5.1.tar.gz", hash = "sha256:61d5cdcc6065745cdd94f0f878977f8de9437be93de97c1c12f853c9c0cdcbda"},
+]
+
+[package.extras]
+docs = ["furo (>=2025.9.25)", "proselint (>=0.14)", "sphinx (>=8.2.3)", "sphinx-autodoc-typehints (>=3.2)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.4.2)", "pytest-cov (>=7)", "pytest-mock (>=3.15.1)"]
+type = ["mypy (>=1.18.2)"]
+
 [[package]]
 name = "pluggy"
 version = "1.5.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
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@@ -298,6 +1111,25 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
+[[package]]
+name = "pre-commit"
+version = "4.5.1"
+description = "A framework for managing and maintaining multi-language pre-commit hooks."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
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+    {file = "pre_commit-4.5.1.tar.gz", hash = "sha256:eb545fcff725875197837263e977ea257a402056661f09dae08e4b149b030a61"},
+]
+
+[package.dependencies]
+cfgv = ">=2.0.0"
+identify = ">=1.0.0"
+nodeenv = ">=0.11.1"
+pyyaml = ">=5.1"
+virtualenv = ">=20.10.0"
+
 [[package]]
 name = "pydantic"
 version = "2.11.4"
@@ -312,6 +1144,7 @@ files = [
 
 [package.dependencies]
 annotated-types = ">=0.6.0"
+email-validator = {version = ">=2.0.0", optional = true, markers = "extra == \"email\""}
 pydantic-core = "2.33.2"
 typing-extensions = ">=4.12.2"
 typing-inspection = ">=0.4.0"
@@ -432,6 +1265,31 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pydantic-extra-types"
+version = "2.11.0"
+description = "Extra Pydantic types."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "pydantic_extra_types-2.11.0.tar.gz", hash = "sha256:4e9991959d045b75feb775683437a97991d02c138e00b59176571db9ce634f0e"},
+]
+
+[package.dependencies]
+pydantic = ">=2.5.2"
+typing-extensions = "*"
+
+[package.extras]
+all = ["cron-converter (>=1.2.2)", "pendulum (>=3.0.0,<4.0.0)", "phonenumbers (>=8,<10)", "pycountry (>=23)", "pymongo (>=4.0.0,<5.0.0)", "python-ulid (>=1,<2) ; python_version < \"3.9\"", "python-ulid (>=1,<4) ; python_version >= \"3.9\"", "pytz (>=2024.1)", "semver (>=3.0.2)", "semver (>=3.0.2,<3.1.0)", "tzdata (>=2024.1)"]
+cron = ["cron-converter (>=1.2.2)"]
+pendulum = ["pendulum (>=3.0.0,<4.0.0)"]
+phonenumbers = ["phonenumbers (>=8,<10)"]
+pycountry = ["pycountry (>=23)"]
+python-ulid = ["python-ulid (>=1,<2) ; python_version < \"3.9\"", "python-ulid (>=1,<4) ; python_version >= \"3.9\""]
+semver = ["semver (>=3.0.2)"]
+
 [[package]]
 name = "pydantic-settings"
 version = "2.9.1"
@@ -456,13 +1314,28 @@ gcp-secret-manager = ["google-cloud-secret-manager (>=2.23.1)"]
 toml = ["tomli (>=2.0.1)"]
 yaml = ["pyyaml (>=6.0.1)"]
 
+[[package]]
+name = "pygments"
+version = "2.19.2"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
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+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
 [[package]]
 name = "pytest"
 version = "8.3.5"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
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 [package.extras]
 dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
+[[package]]
+name = "pytest-cov"
+version = "7.0.0"
+description = "Pytest plugin for measuring coverage."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
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+]
+
+[package.dependencies]
+coverage = {version = ">=7.10.6", extras = ["toml"]}
+pluggy = ">=1.2"
+pytest = ">=7"
+
+[package.extras]
+testing = ["process-tests", "pytest-xdist", "virtualenv"]
+
 [[package]]
 name = "python-dotenv"
 version = "1.1.0"
@@ -492,6 +1385,426 @@ files = [
 [package.extras]
 cli = ["click (>=5.0)"]
 
+[[package]]
+name = "python-multipart"
+version = "0.0.22"
+description = "A streaming multipart parser for Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
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+]
+
+[[package]]
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+version = "6.0.3"
+description = "YAML parser and emitter for Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["main", "dev"]
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+
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+description = "Tool to Detect Surrounding Shell"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
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 version = "1.3.1"
@@ -504,6 +1817,25 @@ files = [
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 version = "4.67.1"
@@ -526,6 +1858,24 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
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+    {file = "websockets-16.0.tar.gz", hash = "sha256:5f6261a5e56e8d5c42a4497b364ea24d94d9563e8fbd44e78ac40879c60179b5"},
+]
+
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.12"
-content-hash = "ab4835ca90a84fadcee7c0a945ae753d7285a60550e372d04cfd869458d49678"
+content-hash = "8687342f9d43012e51d168133e67a4c3cd0d2a7ecff78b1aa3e5bf9ae5930932"
diff --git a/pyproject.toml b/pyproject.toml
index 728a20d..e86ca6f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,14 +4,32 @@ version = "0.1.0"
 description = ""
 authors = ["jhonvalderrama <jhonvalderrama@aceup.com>"]
 readme = "README.md"
+package-mode = false
 
 [tool.poetry.dependencies]
 python = "^3.12"
 openai = "^1.76.2"
 pydantic-settings = "^2.9.1"
 pytest = "^8.3.5"
+fastapi = {extras = ["standard"], version = "^0.128.0"}
+redis = {extras = ["hiredis"], version = "^7.1.0"}
 
 
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
+
+[dependency-groups]
+dev = [
+    "pytest-cov (>=7.0.0,<8.0.0)",
+    "ruff (>=0.14.14,<0.15.0)",
+    "pre-commit (>=4.5.1,<5.0.0)"
+]
+
+[tool.ruff]
+line-length = 88
+select = ["E", "F", "I"] # Error, Flake8, Isort rules
+
+[tool.ruff.format]
+quote-style = "double"
+indent-style = "space"
diff --git a/tests/__pycache__/__init__.cpython-312.pyc b/tests/__pycache__/__init__.cpython-312.pyc
deleted file mode 100644
index d1f71a0..0000000
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diff --git a/tests/adapters/__pycache__/__init__.cpython-312.pyc b/tests/adapters/__pycache__/__init__.cpython-312.pyc
deleted file mode 100644
index 8f0038b..0000000
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diff --git a/tests/adapters/__pycache__/mock_data.cpython-312.pyc b/tests/adapters/__pycache__/mock_data.cpython-312.pyc
deleted file mode 100644
index b9ed2e4..0000000
Binary files a/tests/adapters/__pycache__/mock_data.cpython-312.pyc and /dev/null differ
diff --git a/tests/adapters/__pycache__/test_openai.cpython-312-pytest-8.3.5.pyc b/tests/adapters/__pycache__/test_openai.cpython-312-pytest-8.3.5.pyc
deleted file mode 100644
index 7d09ff1..0000000
Binary files a/tests/adapters/__pycache__/test_openai.cpython-312-pytest-8.3.5.pyc and /dev/null differ
diff --git a/tests/adapters/mock_data.py b/tests/adapters/mock_data.py
index 1d1a950..b4d1445 100644
--- a/tests/adapters/mock_data.py
+++ b/tests/adapters/mock_data.py
@@ -5,7 +5,7 @@
 RAW_USER_PROMPT = """Given the transcript below, generate:
                     1. A brief, insightful summary highlighting key points discussed.
                     2. A clear, structured list of recommended next actions.
-                    
+
                     Transcript:
                     {transcript}"""
 
diff --git a/tests/adapters/test_openai.py b/tests/adapters/test_openai.py
index 556d6f4..d9cfda0 100644
--- a/tests/adapters/test_openai.py
+++ b/tests/adapters/test_openai.py
@@ -1,7 +1,8 @@
-from app import configurations
 import pydantic
-from tests.adapters import mock_data
+
+from app import configurations
 from app.adapters import openai
+from tests.adapters import mock_data
 
 
 class Response(pydantic.BaseModel):
@@ -17,9 +18,10 @@ def test_openai_adapter() -> None:
     raw_user_prompt = mock_data.RAW_USER_PROMPT
     transcript = mock_data.TRANSCRIPT
 
-    user_prompt = raw_user_prompt.format(
-        transcript=transcript)
-    openai_adapter = openai.OpenAIAdapter(env_variables.OPENAI_API_KEY, env_variables.OPENAI_MODEL)
+    user_prompt = raw_user_prompt.format(transcript=transcript)
+    openai_adapter = openai.OpenAIAdapter(
+        env_variables.OPENAI_API_KEY, env_variables.OPENAI_MODEL
+    )
 
     # action
     response = openai_adapter.run_completion(system_prompt, user_prompt, Response)