From 4c27209d1d99988f251971d06c8c357a642f70f5 Mon Sep 17 00:00:00 2001
From: KevinRawal <kevinrawal30@gmail.com>
Date: Sun, 31 Aug 2025 23:23:09 +0530
Subject: [PATCH 1/3] updated prompt engineering and implemented tech
 description

---
 ...417469bac4de_removed_auth_type_from_otp.py | 40 ++++++++++++
 .../versions/a4b5fabfdeac_add_otp_table.py    | 40 ++++++------
 .../versions/a6d1c6c13842_add_role_field.py   | 38 ++++++++++++
 app/api/routes/questions.py                   | 28 +++++++--
 app/main.py                                   |  9 ---
 app/prompts/daily_question_prompt.py          | 61 +++++++++++++------
 app/schemas/utils.py                          | 12 ++++
 app/services/questions.py                     | 32 +++++-----
 8 files changed, 189 insertions(+), 71 deletions(-)
 create mode 100644 app/alembic/versions/417469bac4de_removed_auth_type_from_otp.py
 create mode 100644 app/alembic/versions/a6d1c6c13842_add_role_field.py

diff --git a/app/alembic/versions/417469bac4de_removed_auth_type_from_otp.py b/app/alembic/versions/417469bac4de_removed_auth_type_from_otp.py
new file mode 100644
index 0000000..f7bca05
--- /dev/null
+++ b/app/alembic/versions/417469bac4de_removed_auth_type_from_otp.py
@@ -0,0 +1,40 @@
+"""removed auth-type from OTP
+
+Revision ID: 417469bac4de
+Revises: a6d1c6c13842
+Create Date: 2025-08-31 09:57:49.661025
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "417469bac4de"
+down_revision: Union[str, Sequence[str], None] = "a6d1c6c13842"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column("otps", "provider_id")
+    op.drop_column("otps", "auth_type")
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column(
+        "otps",
+        sa.Column("auth_type", sa.VARCHAR(), autoincrement=False, nullable=False),
+    )
+    op.add_column(
+        "otps",
+        sa.Column("provider_id", sa.VARCHAR(), autoincrement=False, nullable=True),
+    )
+    # ### end Alembic commands ###
diff --git a/app/alembic/versions/a4b5fabfdeac_add_otp_table.py b/app/alembic/versions/a4b5fabfdeac_add_otp_table.py
index 3eb8d0c..dc5e853 100644
--- a/app/alembic/versions/a4b5fabfdeac_add_otp_table.py
+++ b/app/alembic/versions/a4b5fabfdeac_add_otp_table.py
@@ -5,14 +5,15 @@
 Create Date: 2025-07-24 18:30:31.802426
 
 """
+
 from typing import Sequence, Union
 
 import sqlalchemy as sa
 from alembic import op
 
 # revision identifiers, used by Alembic.
-revision: str = 'a4b5fabfdeac'
-down_revision: Union[str, Sequence[str], None] = 'ccf5dc612027'
+revision: str = "a4b5fabfdeac"
+down_revision: Union[str, Sequence[str], None] = "ccf5dc612027"
 branch_labels: Union[str, Sequence[str], None] = None
 depends_on: Union[str, Sequence[str], None] = None
 
@@ -20,28 +21,29 @@
 def upgrade() -> None:
     """Upgrade schema."""
     # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table('otps',
-    sa.Column('id', sa.Integer(), nullable=False),
-    sa.Column('email', sa.String(), nullable=False),
-    sa.Column('otp_code', sa.String(), nullable=False),
-    sa.Column('name', sa.String(), nullable=False),
-    sa.Column('password', sa.String(), nullable=True),
-    sa.Column('is_active', sa.Integer(), nullable=True),
-    sa.Column('provider_id', sa.String(), nullable=True),
-    sa.Column('auth_type', sa.String(), nullable=False),
-    sa.Column('created_at', sa.DateTime(), nullable=True),
-    sa.Column('expires_at', sa.DateTime(), nullable=False),
-    sa.PrimaryKeyConstraint('id')
+    op.create_table(
+        "otps",
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("email", sa.String(), nullable=False),
+        sa.Column("otp_code", sa.String(), nullable=False),
+        sa.Column("name", sa.String(), nullable=False),
+        sa.Column("password", sa.String(), nullable=True),
+        sa.Column("is_active", sa.Integer(), nullable=True),
+        sa.Column("provider_id", sa.String(), nullable=True),
+        sa.Column("auth_type", sa.String(), nullable=False),
+        sa.Column("created_at", sa.DateTime(), nullable=True),
+        sa.Column("expires_at", sa.DateTime(), nullable=False),
+        sa.PrimaryKeyConstraint("id"),
     )
-    op.create_index(op.f('ix_otps_email'), 'otps', ['email'], unique=False)
-    op.create_index(op.f('ix_otps_id'), 'otps', ['id'], unique=False)
+    op.create_index(op.f("ix_otps_email"), "otps", ["email"], unique=False)
+    op.create_index(op.f("ix_otps_id"), "otps", ["id"], unique=False)
     # ### end Alembic commands ###
 
 
 def downgrade() -> None:
     """Downgrade schema."""
     # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(op.f('ix_otps_id'), table_name='otps')
-    op.drop_index(op.f('ix_otps_email'), table_name='otps')
-    op.drop_table('otps')
+    op.drop_index(op.f("ix_otps_id"), table_name="otps")
+    op.drop_index(op.f("ix_otps_email"), table_name="otps")
+    op.drop_table("otps")
     # ### end Alembic commands ###
diff --git a/app/alembic/versions/a6d1c6c13842_add_role_field.py b/app/alembic/versions/a6d1c6c13842_add_role_field.py
new file mode 100644
index 0000000..47d592e
--- /dev/null
+++ b/app/alembic/versions/a6d1c6c13842_add_role_field.py
@@ -0,0 +1,38 @@
+"""add role field
+
+Revision ID: a6d1c6c13842
+Revises: a4b5fabfdeac
+Create Date: 2025-08-31 09:15:05.419403
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "a6d1c6c13842"
+down_revision: Union[str, Sequence[str], None] = "a4b5fabfdeac"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    userrole_enum = sa.Enum("ADMIN", "USER", name="userrole")
+    userrole_enum.create(op.get_bind())
+
+    # Then add the column using the enum type
+    op.add_column("users", sa.Column("role", userrole_enum, nullable=False))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column("users", "role")
+    # Then drop the enum type
+    sa.Enum(name="userrole").drop(op.get_bind())
+    # ### end Alembic commands ###
diff --git a/app/api/routes/questions.py b/app/api/routes/questions.py
index 4286e12..783ea9f 100644
--- a/app/api/routes/questions.py
+++ b/app/api/routes/questions.py
@@ -1,11 +1,12 @@
 from fastapi import APIRouter
+import json
 
-from app.schemas.utils import UserPrompt
+from app.schemas.utils import UserPrompt, TechDescription
 from app.services.questions import add_daily_question_to_mongodb
-from app.services.questions import \
-    add_daily_question_to_store as add_question_in_chroma_db
-from app.services.questions import \
-    generate_daily_question as generate_daily_question_service
+from app.services.questions import ( 
+    generate_daily_question as generate_daily_question_service,
+    add_tech_description_to_store)
+
 from app.services.questions import get_most_recent_daily_question
 
 router = APIRouter()
@@ -18,9 +19,24 @@ def generate_daily_question(request: UserPrompt):
     or user's input.
     """
     response = generate_daily_question_service(user_prompt=request.user_prompt)
-    add_daily_question_to_mongodb(response)  # Store question in MongoDB
+    try:
+        question = json.loads(response)  # Parse the JSON string to a dictionary
+    except json.JSONDecodeError:
+        return {"error": "Failed to parse the generated question."}
+    add_daily_question_to_mongodb(question)  # Store question in MongoDB
     return response
 
+
+@router.post("/add_tech_description")
+def add_tech_description(request: TechDescription):
+    """
+    Add a technical description to the vector store.
+    Whenever admin add a new tech description/Tag, it will be stored in ChromaDB.
+    """
+    add_tech_description_to_store(description=request.description, metadata=request.metadata)
+    return {"message": "Tech description added successfully."}
+
+
 @router.get("/get_daily_question")
 def get_daily_question():
     """
diff --git a/app/main.py b/app/main.py
index 9b81e04..8d83dcd 100644
--- a/app/main.py
+++ b/app/main.py
@@ -10,15 +10,6 @@
     version="0.1.0"
 )
 
-# CORS middleware configuration
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],  # In production, replace with specific origins
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
 app.include_router(api_router, prefix=settings.API_V1_STR, tags=["v1"])
 
 # Health check endpoint
diff --git a/app/prompts/daily_question_prompt.py b/app/prompts/daily_question_prompt.py
index 6fe699d..512c69e 100644
--- a/app/prompts/daily_question_prompt.py
+++ b/app/prompts/daily_question_prompt.py
@@ -1,27 +1,48 @@
 system_template = """
-You are an AI assistant specialized in generating **realistic scenario-based problems for full-stack software engineer** 
-that help software engineers improve their coding, thinking, problem-solving and technical skills.
-
-Guidelines:
-- The question should be realistic and relevant to **working proffessional and students** in software engineering.
-- Focus on overall areas of software engineer such as Optimization, System desing, DSA, Frontend optimization, Database, scaling, AI and so on. 
-- The question must be concise but detailed enough to challenge critical thinking.
-- Avoid trivial "quiz-style" questions. Instead, aim for **real-world problem-solving**.
-- Yes, you can sometime ask quick quiz-style questions to test the knowledge of the user.
-- If the user provides context, use it to tailor the question.
-
-If provided with context (retrieved from a vector database), 
-incorporate that knowledge into the question.
+You are an expert software engineering mentor specializing in creating practical, industry-relevant challenges. Your mission is to generate real-world scenarios that help students and working professionals develop their technical skills through hands-on problem-solving.
+
+## Core Guidelines:
+
+### Focus & Scope
+- Generate questions focused on a SINGLE software engineering concept or technology
+- Create practical, scenario-based problems that mirror real industry challenges
+- Ensure questions are challenging yet solvable (ranging from easy to hard level), promoting deep thinking and analytical skills
+
+### Quality Standards
+- Questions should be directly applicable to current industry practices
+- Scenarios must be realistic and based on common professional situations
+- Content should encourage best practices and modern development approaches
+- Include edge cases and real-world constraints when appropriate
+
+### Adaptability
+- Draw from the full spectrum of software engineering disciplines
+- Balance foundational concepts with emerging technologies
+- Consider both technical and soft skills relevant to software development
+- Include cross-cutting concerns like security, performance, and maintainability
+- Adapt topic complexity and focus based on provided context or current industry needs
 """
 
 human_template = """
-User Context (from DB or input): {context}
+## Input Context
+User Context: {context}
+
+## Task
+Generate a comprehensive, scenario-based software engineering question that challenges problem-solving skills and reflects real-world professional situations.
+
+**Context Handling:**
+- If context is provided: Tailor the question to the specified topic/area
+- If no context: Select a random but relevant topic within software engineering
+
+## Required Output Format
 
-Task:
-Generate a daily realistic software engineering scenario question
-based on the above context.
+Provide a valid JSON object with the following structure:
 
-Output Format:
-- Title: A short title for the question
-- Question: The full scenario-based question
+{{
+    "title": "string",           // Concise, descriptive title (max 100 characters)
+    "description": "string",     // Complete problem scenario with clear requirements and constraints
+    "hints": ["string"],         // 2-4 progressive hints that guide without giving away the solution
+    "difficulty": "easy|medium|hard",  // Based on required knowledge depth and complexity
+    "tags": ["string"],          // 3-6 relevant technical tags for categorization
+    "learning_objectives": ["string"]  // 2-3 key skills/concepts the question teaches
+}}
 """
diff --git a/app/schemas/utils.py b/app/schemas/utils.py
index 8e96644..5c761f9 100644
--- a/app/schemas/utils.py
+++ b/app/schemas/utils.py
@@ -4,3 +4,15 @@
 class UserPrompt(BaseModel):
     """Schema for user prompt input."""
     user_prompt: str | None = None
+
+class TechDescriptionMetadata(BaseModel):
+    """Schema for tech description metadata."""
+    topic: str
+    tech_stack: str
+    difficulty: str
+    tags: str
+
+class TechDescription(BaseModel):
+    """Schema for tech description input."""
+    description: str
+    metadata: TechDescriptionMetadata
\ No newline at end of file
diff --git a/app/services/questions.py b/app/services/questions.py
index 128ccc8..c35bf36 100644
--- a/app/services/questions.py
+++ b/app/services/questions.py
@@ -1,3 +1,4 @@
+import uuid
 from datetime import datetime
 
 from langchain_core.documents import Document
@@ -6,39 +7,35 @@
 from app.config.vectorestore import chroma_db
 from app.llm.provider import invoke_with_retries
 from app.pipelines.daily_question_pipeline import daily_question_chain
+from app.schemas.utils import TechDescriptionMetadata
 
-
-def generate_daily_question(user_prompt: str = None) -> str:
+def generate_daily_question(user_prompt: str = None) -> any:
     """Generate a daily question using the LLM pipeline."""
     payload = {"user_prompt": user_prompt}
     response = invoke_with_retries(daily_question_chain, payload)
     # ChatHuggingFace returns an AIMessage by default; str() yields content.
-    return str(response.content) if hasattr(response, "content") else str(response)
-
-def add_daily_question_to_store(question: str) -> None:
-    """Add a selected question to the ChromaDB collection."""
-    doc = Document(page_content=question, metadata={})
-    chroma_db.add_documents(collection="daily_questions",documents=[doc])
+    return response.content
 
-def add_daily_question_to_mongodb(question: str) -> None:
+def add_daily_question_to_mongodb(question: dict) -> None:
     """Add a daily question to the MongoDB collection."""
     question_document = {
         "_id": f"q_{datetime.utcnow().strftime('%Y%m%d%H%M%S')}",
-        "title": question.split("?")[0] + "?",  # Extract title from question
-        "description": question,
+        "title": question.get("title", ""),  # Extract title from question
+        "description": question.get("description", ""),  # Extract description from question
         "created_at": datetime.utcnow().isoformat(),
         "likes": 0,
         "dislikes": 0,
-        "hints": [],
-        "tags": ["daily_question"],
-        "difficulty": "medium",
+        "hints": question.get("hints", []),
+        "tags": question.get("tags", []),
+        "difficulty": question.get("difficulty", "None"),
         "status": "published"
     }
     questions_collection.insert_one(question_document)
 
-def add_tech_description_to_store(description: str, metadata: dict) -> None:
+def add_tech_description_to_store(description: str, metadata: TechDescriptionMetadata) -> None:
     """Add a tech description to the ChromaDB collection."""
-    doc = Document(page_content=description, metadata=metadata)
+    doc_id = str(uuid.uuid4())
+    doc = Document(id=doc_id, page_content=description, metadata=metadata.model_dump())
     chroma_db.add_documents(collection="tech_description",documents=[doc])
 
 def get_most_recent_daily_question():
@@ -54,6 +51,7 @@ def get_most_recent_daily_question():
             "dislikes": recent_question["dislikes"],
             "tags": recent_question["tags"],
             "difficulty": recent_question["difficulty"],
-            "status": recent_question["status"]
+            "status": recent_question["status"],
+            "hints": recent_question.get("hints", []),
         }
     return None

From 5abfa02969e90bdd28cc24ae37138c52310ecc5f Mon Sep 17 00:00:00 2001
From: KevinRawal <kevinrawal30@gmail.com>
Date: Mon, 1 Sep 2025 07:55:46 +0530
Subject: [PATCH 2/3] lint fix

---
 app/alembic/env.py                       |  4 +--
 app/api/main.py                          |  4 ++-
 app/api/routes/questions.py              | 21 ++++++++++------
 app/config/config_mongo_fb.py            |  1 +
 app/config/vectorestore.py               | 19 ++++++++------
 app/llm/provider.py                      |  9 ++++---
 app/main.py                              |  5 ++--
 app/models/__init__.py                   |  2 +-
 app/pipelines/daily_question_pipeline.py | 32 ++++++++++++++----------
 app/schemas/utils.py                     |  7 +++++-
 app/services/questions.py                | 16 +++++++++---
 11 files changed, 76 insertions(+), 44 deletions(-)

diff --git a/app/alembic/env.py b/app/alembic/env.py
index 7ec92d3..1cde81d 100644
--- a/app/alembic/env.py
+++ b/app/alembic/env.py
@@ -68,9 +68,7 @@ def run_migrations_online() -> None:
     )
 
     with connectable.connect() as connection:
-        context.configure(
-            connection=connection, target_metadata=target_metadata
-        )
+        context.configure(connection=connection, target_metadata=target_metadata)
 
         with context.begin_transaction():
             context.run_migrations()
diff --git a/app/api/main.py b/app/api/main.py
index 04ed683..30e0062 100644
--- a/app/api/main.py
+++ b/app/api/main.py
@@ -5,4 +5,6 @@
 api_router = APIRouter()
 
 # TODO: Add routes as needed
-api_router.include_router(questions.router, prefix="/questions", tags=["question_generation"])
\ No newline at end of file
+api_router.include_router(
+    questions.router, prefix="/questions", tags=["question_generation"]
+)
diff --git a/app/api/routes/questions.py b/app/api/routes/questions.py
index 783ea9f..cbba7d1 100644
--- a/app/api/routes/questions.py
+++ b/app/api/routes/questions.py
@@ -1,12 +1,15 @@
-from fastapi import APIRouter
 import json
 
-from app.schemas.utils import UserPrompt, TechDescription
-from app.services.questions import add_daily_question_to_mongodb
-from app.services.questions import ( 
-    generate_daily_question as generate_daily_question_service,
-    add_tech_description_to_store)
+from fastapi import APIRouter
 
+from app.schemas.utils import TechDescription, UserPrompt
+from app.services.questions import (
+    add_daily_question_to_mongodb,
+    add_tech_description_to_store,
+)
+from app.services.questions import (
+    generate_daily_question as generate_daily_question_service,
+)
 from app.services.questions import get_most_recent_daily_question
 
 router = APIRouter()
@@ -33,7 +36,9 @@ def add_tech_description(request: TechDescription):
     Add a technical description to the vector store.
     Whenever admin add a new tech description/Tag, it will be stored in ChromaDB.
     """
-    add_tech_description_to_store(description=request.description, metadata=request.metadata)
+    add_tech_description_to_store(
+        description=request.description, metadata=request.metadata
+    )
     return {"message": "Tech description added successfully."}
 
 
@@ -45,4 +50,4 @@ def get_daily_question():
     recent_question = get_most_recent_daily_question()
     if recent_question:
         return recent_question
-    return {"message": "No daily question found."}
\ No newline at end of file
+    return {"message": "No daily question found."}
diff --git a/app/config/config_mongo_fb.py b/app/config/config_mongo_fb.py
index ff0f2fb..310b081 100644
--- a/app/config/config_mongo_fb.py
+++ b/app/config/config_mongo_fb.py
@@ -13,6 +13,7 @@ def __init__(self, uri: str, db_name: str):
     def get_collection(self, collection_name: str):
         return self.db[collection_name]
 
+
 # MongoDB connection setup
 MONGO_URI = "mongodb://mongodb:27017"
 MONGO_DB_NAME = "questions_db"
diff --git a/app/config/vectorestore.py b/app/config/vectorestore.py
index 624cbd1..66e3f7f 100644
--- a/app/config/vectorestore.py
+++ b/app/config/vectorestore.py
@@ -11,13 +11,14 @@
 # Using singleton pattern for ChromaDB to ensure a single instance is used across the application
 class ChromaDB:
     """Singleton class for managing ChromaDB collections and operations."""
-    _instance = None  
+
+    _instance = None
 
     def __new__(cls, *args, **kwargs):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
         return cls._instance
-    
+
     def __init__(self):
         self.path = settings.CHROMA_PATH
         self.model = settings.EMBEDDING_MODEL
@@ -26,7 +27,7 @@ def __init__(self):
         self._client = PersistentClient(path=self.path)
 
         self._collections: Dict[str, Chroma] = {}
-    
+
     def get_collection(self, name: str) -> Chroma:
         """Get or create a Chroma-backed collection."""
         if name not in self._collections:
@@ -36,21 +37,23 @@ def get_collection(self, name: str) -> Chroma:
                 embedding_function=self._embeddings,
             )
         return self._collections[name]
-    
+
     def add_documents(self, collection: str, documents: List[Document]) -> None:
         """
         Add documents to the ChromaDB collection.
         """
         store = self.get_collection(collection)
         store.add_documents(documents)
-    
-    def as_retriever(self,collection: str, search_kwargs: Optional[Dict[str, Any]] = None) -> Any:
+
+    def as_retriever(
+        self, collection: str, search_kwargs: Optional[Dict[str, Any]] = None
+    ) -> Any:
         """
         Get a retriever for the ChromaDB collection.
         search_kwargs: can be used to specify additional search parameters like 'k' for KNN.
         """
         store = self.get_collection(collection)
         return store.as_retriever(search_kwargs=search_kwargs)
-    
 
-chroma_db = ChromaDB()
\ No newline at end of file
+
+chroma_db = ChromaDB()
diff --git a/app/llm/provider.py b/app/llm/provider.py
index 93b09ec..8e222d4 100644
--- a/app/llm/provider.py
+++ b/app/llm/provider.py
@@ -17,7 +17,8 @@ def build_chat_model() -> ChatHuggingFace:
     )
     return ChatHuggingFace(llm=llm)
 
-#TODO: Improve this function
+
+# TODO: Improve this function
 def invoke_with_retries(chain, payload: Dict[str, Any]):
     last_err = None
     for attempt in range(1, settings.LLM_RETRIES + 1):
@@ -26,5 +27,7 @@ def invoke_with_retries(chain, payload: Dict[str, Any]):
         except Exception as e:  # noqa: BLE001
             last_err = e
             # Exponential backoff with cap
-            time.sleep(min(2 ** attempt, 8))
-    raise RuntimeError(f"LLM invocation failed after {settings.LLM_RETRIES} attempts") from last_err
+            time.sleep(min(2**attempt, 8))
+    raise RuntimeError(
+        f"LLM invocation failed after {settings.LLM_RETRIES} attempts"
+    ) from last_err
diff --git a/app/main.py b/app/main.py
index 8d83dcd..f6c2b4b 100644
--- a/app/main.py
+++ b/app/main.py
@@ -7,12 +7,13 @@
 app = FastAPI(
     title="Generator Service",
     description="API for generating and managing coding problems",
-    version="0.1.0"
+    version="0.1.0",
 )
 
 app.include_router(api_router, prefix=settings.API_V1_STR, tags=["v1"])
 
+
 # Health check endpoint
 @app.get("/health")
 async def health_check():
-    return {"status": "healthy", "service": "JamAndFlow-generator"}
\ No newline at end of file
+    return {"status": "healthy", "service": "JamAndFlow-generator"}
diff --git a/app/models/__init__.py b/app/models/__init__.py
index 38f5c5a..0a91b6c 100644
--- a/app/models/__init__.py
+++ b/app/models/__init__.py
@@ -1,3 +1,3 @@
 # Add models here to be imported by Alembic
 # example:
-# from .models.user import User # noqa: F401, F403
\ No newline at end of file
+# from .models.user import User # noqa: F401, F403
diff --git a/app/pipelines/daily_question_pipeline.py b/app/pipelines/daily_question_pipeline.py
index fd5e98e..f328371 100644
--- a/app/pipelines/daily_question_pipeline.py
+++ b/app/pipelines/daily_question_pipeline.py
@@ -1,8 +1,10 @@
 from typing import Dict
 
-from langchain_core.prompts import (ChatPromptTemplate,
-                                    HumanMessagePromptTemplate,
-                                    SystemMessagePromptTemplate)
+from langchain_core.prompts import (
+    ChatPromptTemplate,
+    HumanMessagePromptTemplate,
+    SystemMessagePromptTemplate,
+)
 from langchain_core.runnables import RunnableParallel
 
 from app.config.vectorestore import chroma_db
@@ -12,17 +14,21 @@
 
 # using tech_description collection to retrieve context.
 # It will return top k relevant document based on the user prompt.
-# The context structure stores tech-stack and relevant real-world concepts 
+# The context structure stores tech-stack and relevant real-world concepts
 # On which the question can be framed.
-retriever = chroma_db.as_retriever(collection="tech_description",
-                                   search_kwargs={"k": settings.RETRIEVE_K})
+retriever = chroma_db.as_retriever(
+    collection="tech_description", search_kwargs={"k": settings.RETRIEVE_K}
+)
 
-prompt = ChatPromptTemplate.from_messages([
-    SystemMessagePromptTemplate.from_template(system_template),
-    HumanMessagePromptTemplate.from_template(human_template),
-])
+prompt = ChatPromptTemplate.from_messages(
+    [
+        SystemMessagePromptTemplate.from_template(system_template),
+        HumanMessagePromptTemplate.from_template(human_template),
+    ]
+)
 
-#TODO: we might required a context for last n question for uniquness and variety
+
+# TODO: we might required a context for last n question for uniquness and variety
 # But for now the concern is on the limit of the tokens hence not implementing it
 def _retrieve_context(inputs: Dict):
     """It will only trigger when user gives a contet if not it will return 'No extra context'"""
@@ -33,9 +39,9 @@ def _retrieve_context(inputs: Dict):
     context = " ".join([d.page_content for d in docs]) if docs else "No extra context"
     return {"context": context, "user_prompt": inputs["user_prompt"]}
 
+
 context_retriever = RunnableParallel(
-    user_question=lambda x: x["user_prompt"],
-    context=_retrieve_context
+    user_question=lambda x: x["user_prompt"], context=_retrieve_context
 )
 
 chat_model = build_chat_model()
diff --git a/app/schemas/utils.py b/app/schemas/utils.py
index 5c761f9..5059453 100644
--- a/app/schemas/utils.py
+++ b/app/schemas/utils.py
@@ -3,16 +3,21 @@
 
 class UserPrompt(BaseModel):
     """Schema for user prompt input."""
+
     user_prompt: str | None = None
 
+
 class TechDescriptionMetadata(BaseModel):
     """Schema for tech description metadata."""
+
     topic: str
     tech_stack: str
     difficulty: str
     tags: str
 
+
 class TechDescription(BaseModel):
     """Schema for tech description input."""
+
     description: str
-    metadata: TechDescriptionMetadata
\ No newline at end of file
+    metadata: TechDescriptionMetadata
diff --git a/app/services/questions.py b/app/services/questions.py
index c35bf36..9344d25 100644
--- a/app/services/questions.py
+++ b/app/services/questions.py
@@ -9,6 +9,7 @@
 from app.pipelines.daily_question_pipeline import daily_question_chain
 from app.schemas.utils import TechDescriptionMetadata
 
+
 def generate_daily_question(user_prompt: str = None) -> any:
     """Generate a daily question using the LLM pipeline."""
     payload = {"user_prompt": user_prompt}
@@ -16,27 +17,34 @@ def generate_daily_question(user_prompt: str = None) -> any:
     # ChatHuggingFace returns an AIMessage by default; str() yields content.
     return response.content
 
+
 def add_daily_question_to_mongodb(question: dict) -> None:
     """Add a daily question to the MongoDB collection."""
     question_document = {
         "_id": f"q_{datetime.utcnow().strftime('%Y%m%d%H%M%S')}",
         "title": question.get("title", ""),  # Extract title from question
-        "description": question.get("description", ""),  # Extract description from question
+        "description": question.get(
+            "description", ""
+        ),  # Extract description from question
         "created_at": datetime.utcnow().isoformat(),
         "likes": 0,
         "dislikes": 0,
         "hints": question.get("hints", []),
         "tags": question.get("tags", []),
         "difficulty": question.get("difficulty", "None"),
-        "status": "published"
+        "status": "published",
     }
     questions_collection.insert_one(question_document)
 
-def add_tech_description_to_store(description: str, metadata: TechDescriptionMetadata) -> None:
+
+def add_tech_description_to_store(
+    description: str, metadata: TechDescriptionMetadata
+) -> None:
     """Add a tech description to the ChromaDB collection."""
     doc_id = str(uuid.uuid4())
     doc = Document(id=doc_id, page_content=description, metadata=metadata.model_dump())
-    chroma_db.add_documents(collection="tech_description",documents=[doc])
+    chroma_db.add_documents(collection="tech_description", documents=[doc])
+
 
 def get_most_recent_daily_question():
     """Fetch the most recent daily question from MongoDB."""

From 1995087f5a5ea2e4c021e736c04b38ef79756d4f Mon Sep 17 00:00:00 2001
From: KevinRawal <kevinrawal30@gmail.com>
Date: Mon, 1 Sep 2025 07:56:49 +0530
Subject: [PATCH 3/3] lint fix

---
 app/api/routes/questions.py              | 11 ++++-------
 app/pipelines/daily_question_pipeline.py |  8 +++-----
 2 files changed, 7 insertions(+), 12 deletions(-)

diff --git a/app/api/routes/questions.py b/app/api/routes/questions.py
index cbba7d1..e91e5b6 100644
--- a/app/api/routes/questions.py
+++ b/app/api/routes/questions.py
@@ -3,13 +3,10 @@
 from fastapi import APIRouter
 
 from app.schemas.utils import TechDescription, UserPrompt
-from app.services.questions import (
-    add_daily_question_to_mongodb,
-    add_tech_description_to_store,
-)
-from app.services.questions import (
-    generate_daily_question as generate_daily_question_service,
-)
+from app.services.questions import (add_daily_question_to_mongodb,
+                                    add_tech_description_to_store)
+from app.services.questions import \
+    generate_daily_question as generate_daily_question_service
 from app.services.questions import get_most_recent_daily_question
 
 router = APIRouter()
diff --git a/app/pipelines/daily_question_pipeline.py b/app/pipelines/daily_question_pipeline.py
index f328371..8ec1628 100644
--- a/app/pipelines/daily_question_pipeline.py
+++ b/app/pipelines/daily_question_pipeline.py
@@ -1,10 +1,8 @@
 from typing import Dict
 
-from langchain_core.prompts import (
-    ChatPromptTemplate,
-    HumanMessagePromptTemplate,
-    SystemMessagePromptTemplate,
-)
+from langchain_core.prompts import (ChatPromptTemplate,
+                                    HumanMessagePromptTemplate,
+                                    SystemMessagePromptTemplate)
 from langchain_core.runnables import RunnableParallel
 
 from app.config.vectorestore import chroma_db