Merge pull request 'rewrite/frontend' (#2) from rewrite/frontend into main
Build and Push Docker Images / build-api (push) Has been cancelled
Build and Push Docker Images / build-frontend (push) Has been cancelled

Reviewed-on: http://10.0.1.10/0xWheatyz/SPARC/pulls/2
This commit was merged in pull request #2.
This commit is contained in:
2026-03-14 22:02:12 +00:00
41 changed files with 3216 additions and 1010 deletions
+11 -6
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@@ -6,11 +6,16 @@ API_KEY=your_serpapi_key_here
# OpenRouter API key for LLM analysis
OPENROUTER_API_KEY=your_openrouter_key_here
# Database configuration (for docker-compose setup)
# Database configuration
# All messages are stored in the database for persistence and caching
DATABASE_URL=postgresql://postgres:postgres@localhost:5432/sparc
# Toggle between database mode and API mode
# When USE_DATABASE=true: stores all messages in database instead of sending to OpenRouter
# When USE_DATABASE=false: sends messages to OpenRouter API as normal
# Default: false
USE_DATABASE=false
# Cache configuration
# When USE_CACHE=true: check database for cached responses before making API calls
# When USE_CACHE=false: always make fresh API calls (still stores results in database)
# Default: true
USE_CACHE=true
# JWT Secret for authentication
# IMPORTANT: Change this to a secure random string in production
JWT_SECRET=your-secure-jwt-secret-change-in-production
+76 -15
View File
@@ -1,4 +1,4 @@
name: Build and Push Docker Image
name: Build and Push Docker Images
on:
push:
@@ -9,7 +9,7 @@ on:
workflow_dispatch:
jobs:
build-and-push:
build-api:
runs-on: ubuntu-latest
steps:
- name: Install dependencies
@@ -31,32 +31,24 @@ jobs:
REPO_OWNER="${{ gitea.repository_owner }}"
REPO_NAME="${{ gitea.repository }}"
# Extract repository name without owner
REPO_NAME_ONLY=$(echo "$REPO_NAME" | cut -d'/' -f2)
# Convert to lowercase for Docker registry compatibility
REPO_OWNER_LOWER=$(echo "$REPO_OWNER" | tr '[:upper:]' '[:lower:]')
REPO_NAME_LOWER=$(echo "$REPO_NAME_ONLY" | tr '[:upper:]' '[:lower:]')
# Base image path
IMAGE_BASE="${REGISTRY}/${REPO_OWNER_LOWER}/${REPO_NAME_LOWER}"
# Determine tag based on ref
case "${{ gitea.ref }}" in
refs/tags/*)
# Tag push - use the tag name
TAG_NAME="${{ gitea.ref_name }}"
echo "IMAGE_TAG=${IMAGE_BASE}:${TAG_NAME}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=true" >> $GITHUB_OUTPUT
;;
refs/heads/main)
# Main branch - use commit SHA (shortened to 7 chars) and latest
SHORT_SHA=$(echo "${{ gitea.sha }}" | cut -c1-7)
echo "IMAGE_TAG=${IMAGE_BASE}:${SHORT_SHA}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=true" >> $GITHUB_OUTPUT
;;
*)
# Other branches - use branch name
BRANCH_TAG=$(echo "${{ gitea.ref_name }}" | sed 's/\//-/g')
echo "IMAGE_TAG=${IMAGE_BASE}:${BRANCH_TAG}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=false" >> $GITHUB_OUTPUT
@@ -70,13 +62,13 @@ jobs:
run: |
echo "${{ secrets.PERSONAL_TOKEN }}" | docker login gitea.leeworks.dev -u "${{ gitea.actor }}" --password-stdin
- name: Build and push with Docker
- name: Build and push API image
shell: sh
run: |
echo "Building image..."
echo "Building API image..."
docker build -t ${{ steps.tags.outputs.IMAGE_TAG }} .
echo "Pushing image..."
echo "Pushing API image..."
docker push ${{ steps.tags.outputs.IMAGE_TAG }}
if [ "${{ steps.tags.outputs.PUSH_LATEST }}" = "true" ]; then
@@ -85,5 +77,74 @@ jobs:
docker push ${{ steps.tags.outputs.IMAGE_LATEST }}
fi
echo "Build and push completed successfully!"
echo "Image available at ${{ steps.tags.outputs.IMAGE_TAG }}"
echo "API image available at ${{ steps.tags.outputs.IMAGE_TAG }}"
build-frontend:
runs-on: ubuntu-latest
steps:
- name: Install dependencies
shell: sh
run: |
apk add --no-cache git docker-cli
- name: Checkout code
shell: sh
run: |
git clone https://gitea.leeworks.dev/${{ gitea.repository }}.git .
git checkout ${{ gitea.sha }}
- name: Determine image tags
id: tags
shell: sh
run: |
REGISTRY="gitea.leeworks.dev"
REPO_OWNER="${{ gitea.repository_owner }}"
REPO_NAME="${{ gitea.repository }}"
REPO_NAME_ONLY=$(echo "$REPO_NAME" | cut -d'/' -f2)
REPO_OWNER_LOWER=$(echo "$REPO_OWNER" | tr '[:upper:]' '[:lower:]')
REPO_NAME_LOWER=$(echo "$REPO_NAME_ONLY" | tr '[:upper:]' '[:lower:]')
IMAGE_BASE="${REGISTRY}/${REPO_OWNER_LOWER}/${REPO_NAME_LOWER}"
case "${{ gitea.ref }}" in
refs/tags/*)
TAG_NAME="${{ gitea.ref_name }}"
echo "IMAGE_TAG=${IMAGE_BASE}:frontend-${TAG_NAME}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=true" >> $GITHUB_OUTPUT
;;
refs/heads/main)
SHORT_SHA=$(echo "${{ gitea.sha }}" | cut -c1-7)
echo "IMAGE_TAG=${IMAGE_BASE}:frontend-${SHORT_SHA}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=true" >> $GITHUB_OUTPUT
;;
*)
BRANCH_TAG=$(echo "${{ gitea.ref_name }}" | sed 's/\//-/g')
echo "IMAGE_TAG=${IMAGE_BASE}:frontend-${BRANCH_TAG}" >> $GITHUB_OUTPUT
echo "PUSH_LATEST=false" >> $GITHUB_OUTPUT
;;
esac
echo "IMAGE_LATEST=${IMAGE_BASE}:frontend-latest" >> $GITHUB_OUTPUT
- name: Login to registry
shell: sh
run: |
echo "${{ secrets.PERSONAL_TOKEN }}" | docker login gitea.leeworks.dev -u "${{ gitea.actor }}" --password-stdin
- name: Build and push frontend image
shell: sh
run: |
echo "Building frontend image..."
docker build -t ${{ steps.tags.outputs.IMAGE_TAG }} ./frontend
echo "Pushing frontend image..."
docker push ${{ steps.tags.outputs.IMAGE_TAG }}
if [ "${{ steps.tags.outputs.PUSH_LATEST }}" = "true" ]; then
echo "Tagging and pushing frontend-latest..."
docker tag ${{ steps.tags.outputs.IMAGE_TAG }} ${{ steps.tags.outputs.IMAGE_LATEST }}
docker push ${{ steps.tags.outputs.IMAGE_LATEST }}
fi
echo "Frontend image available at ${{ steps.tags.outputs.IMAGE_TAG }}"
+14 -11
View File
@@ -17,7 +17,7 @@ SPARC automatically collects, parses, and analyzes patents from companies to pro
- **Portfolio Analysis**: Evaluates multiple patents holistically for comprehensive insights
- **Batch Processing**: Analyze multiple companies concurrently with progress tracking
- **REST API**: FastAPI web service with async job support
- **Dashboard**: Interactive Streamlit visualization dashboard
- **Dashboard**: React TypeScript web dashboard with authentication
- **Robust Testing**: 40 tests covering all major functionality
## Architecture
@@ -27,7 +27,9 @@ SPARC/
├── serp_api.py # Patent retrieval and PDF parsing
├── llm.py # Claude AI integration via OpenRouter
├── analyzer.py # High-level orchestration
├── api.py # FastAPI web service
├── api.py # FastAPI web service with auth endpoints
├── auth.py # JWT authentication module
├── database.py # PostgreSQL storage with caching
├── types.py # Data models
└── config.py # Environment configuration
```
@@ -48,7 +50,7 @@ docker-compose up -d
# Access the services
# - API: http://localhost:8000
# - Dashboard: http://localhost:8501
# - Dashboard: http://localhost:8080
# - API Docs: http://localhost:8000/docs
```
@@ -186,21 +188,22 @@ curl -X POST http://localhost:8000/analyze/batch/async \
-d '{"companies": ["nvidia", "amd", "intel", "qualcomm"]}'
```
### Visualization Dashboard
### Web Dashboard
Launch the interactive Streamlit dashboard:
The React dashboard is included in Docker Compose:
```bash
streamlit run dashboard.py
docker-compose up -d
```
Dashboard features:
- **Authentication**: User registration, login, and JWT-based sessions
- **Company Analysis**: Analyze individual companies with real-time results
- **Batch Analysis**: Process multiple companies with progress tracking and charts
- **Analytics**: View historical analysis data and trends (requires database mode)
- **System Status**: Monitor database and analyzer health
- **Batch Analysis**: Process multiple companies with progress tracking
- **Analytics**: View historical analysis data and trends
- **Admin Panel**: User management for administrators
The dashboard runs at `http://localhost:8501` by default.
The dashboard runs at `http://localhost:8080` when using Docker Compose.
## Running Tests
@@ -280,4 +283,4 @@ For open source projects, say how it is licensed.
Core functionality complete. Ready for production use with API keys configured.
All major features implemented: REST API, Streamlit dashboard, Docker containerization, database storage, and multi-company batch processing.
All major features implemented: REST API, React dashboard with authentication, Docker containerization, database storage with caching, and multi-company batch processing.
+256 -7
View File
@@ -5,12 +5,23 @@ Provides REST API endpoints for analyzing company patent portfolios.
from contextlib import asynccontextmanager
from datetime import datetime
from typing import Annotated
from typing import Annotated, List
from fastapi import BackgroundTasks, FastAPI, HTTPException, Query
from pydantic import BaseModel, Field
from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, EmailStr, Field
from SPARC import config
from SPARC.analyzer import CompanyAnalyzer
from SPARC.auth import (
TokenResponse,
UserResponse,
create_tokens,
decode_token,
get_current_admin,
get_current_user,
get_db_client,
)
from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
@@ -67,6 +78,42 @@ class HealthResponse(BaseModel):
timestamp: datetime
# Auth request/response models
class RegisterRequest(BaseModel):
"""User registration request."""
email: EmailStr
password: str = Field(..., min_length=8, description="Password (min 8 characters)")
class LoginRequest(BaseModel):
"""User login request."""
email: EmailStr
password: str
class RefreshRequest(BaseModel):
"""Token refresh request."""
refresh_token: str
class UpdateRoleRequest(BaseModel):
"""Update user role request."""
role: str = Field(..., pattern="^(admin|user)$")
class AnalyticsResponse(BaseModel):
"""Analytics response model."""
total_messages: int
by_company: List[dict]
by_type: List[dict]
period_days: int
# In-memory job storage (for demo; production would use Redis/DB)
_jobs: dict[str, JobStatus] = {}
_job_counter = 0
@@ -116,6 +163,196 @@ app = FastAPI(
lifespan=lifespan,
)
# Add CORS middleware for React frontend
app.add_middleware(
CORSMiddleware,
allow_origins=["http://localhost:3000", "http://localhost:5173"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# ============== Auth Endpoints ==============
@app.post("/auth/register", response_model=UserResponse, tags=["Auth"])
async def register(request: RegisterRequest):
"""Register a new user.
The first registered user automatically becomes an admin.
"""
db = get_db_client()
# First user becomes admin
user_count = db.get_user_count()
role = "admin" if user_count == 0 else "user"
user = db.create_user(
email=request.email,
password=request.password,
role=role,
)
if not user:
raise HTTPException(
status_code=400,
detail="Email already registered",
)
return UserResponse(
id=user["id"],
email=user["email"],
role=user["role"],
created_at=user["created_at"],
)
@app.post("/auth/login", response_model=TokenResponse, tags=["Auth"])
async def login(request: LoginRequest):
"""Authenticate user and return JWT tokens."""
db = get_db_client()
user = db.authenticate_user(request.email, request.password)
if not user:
raise HTTPException(
status_code=401,
detail="Invalid email or password",
)
return create_tokens(user["id"], user["email"], user["role"])
@app.post("/auth/refresh", response_model=TokenResponse, tags=["Auth"])
async def refresh_token(request: RefreshRequest):
"""Refresh access token using refresh token."""
payload = decode_token(request.refresh_token)
if not payload or payload.type != "refresh":
raise HTTPException(
status_code=401,
detail="Invalid refresh token",
)
db = get_db_client()
user = db.get_user_by_id(payload.user_id)
if not user:
raise HTTPException(
status_code=401,
detail="User not found",
)
return create_tokens(user["id"], user["email"], user["role"])
@app.get("/auth/me", response_model=UserResponse, tags=["Auth"])
async def get_me(current_user: UserResponse = Depends(get_current_user)):
"""Get current authenticated user."""
return current_user
# ============== Admin Endpoints ==============
@app.get("/admin/users", response_model=List[UserResponse], tags=["Admin"])
async def list_users(
limit: int = Query(default=100, ge=1, le=1000),
offset: int = Query(default=0, ge=0),
_: UserResponse = Depends(get_current_admin),
):
"""List all users (admin only)."""
db = get_db_client()
users = db.get_all_users(limit=limit, offset=offset)
return [
UserResponse(
id=u["id"],
email=u["email"],
role=u["role"],
created_at=u["created_at"],
)
for u in users
]
@app.patch("/admin/users/{user_id}/role", response_model=UserResponse, tags=["Admin"])
async def update_user_role(
user_id: int,
request: UpdateRoleRequest,
current_admin: UserResponse = Depends(get_current_admin),
):
"""Update a user's role (admin only)."""
if user_id == current_admin.id:
raise HTTPException(
status_code=400,
detail="Cannot change your own role",
)
db = get_db_client()
user = db.update_user_role(user_id, request.role)
if not user:
raise HTTPException(
status_code=404,
detail="User not found",
)
return UserResponse(
id=user["id"],
email=user["email"],
role=user["role"],
created_at=user["created_at"],
)
@app.delete("/admin/users/{user_id}", tags=["Admin"])
async def delete_user(
user_id: int,
current_admin: UserResponse = Depends(get_current_admin),
):
"""Delete a user (admin only)."""
if user_id == current_admin.id:
raise HTTPException(
status_code=400,
detail="Cannot delete yourself",
)
db = get_db_client()
deleted = db.delete_user(user_id)
if not deleted:
raise HTTPException(
status_code=404,
detail="User not found",
)
return {"message": "User deleted"}
# ============== Analytics Endpoint ==============
@app.get("/analytics", response_model=AnalyticsResponse, tags=["Analytics"])
async def get_analytics(
days: int = Query(default=30, ge=1, le=365),
_: UserResponse = Depends(get_current_user),
):
"""Get analytics data (authenticated users only)."""
db = get_db_client()
analytics = db.get_analytics(days=days)
return AnalyticsResponse(
total_messages=analytics["total_messages"],
by_company=analytics["by_company"],
by_type=analytics["by_type"],
period_days=analytics["period_days"],
)
# ============== System Endpoints ==============
@app.get("/health", response_model=HealthResponse, tags=["System"])
async def health_check():
@@ -132,7 +369,10 @@ async def health_check():
response_model=CompanyAnalysisResponse,
tags=["Analysis"],
)
async def analyze_company(company_name: str):
async def analyze_company(
company_name: str,
_: UserResponse = Depends(get_current_user),
):
"""Analyze a single company's patent portfolio.
This endpoint retrieves recent patents for the specified company,
@@ -156,7 +396,10 @@ async def analyze_company(company_name: str):
response_model=BatchAnalysisResponse,
tags=["Analysis"],
)
async def analyze_companies_batch(request: BatchAnalysisRequest):
async def analyze_companies_batch(
request: BatchAnalysisRequest,
_: UserResponse = Depends(get_current_user),
):
"""Analyze multiple companies' patent portfolios.
Processes companies concurrently for improved performance.
@@ -209,7 +452,9 @@ def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
@app.post("/analyze/batch/async", response_model=JobStatus, tags=["Analysis"])
async def analyze_companies_async(
request: BatchAnalysisRequest, background_tasks: BackgroundTasks
request: BatchAnalysisRequest,
background_tasks: BackgroundTasks,
_: UserResponse = Depends(get_current_user),
):
"""Start an asynchronous batch analysis job.
@@ -243,7 +488,10 @@ async def analyze_companies_async(
@app.get("/jobs/{job_id}", response_model=JobStatus, tags=["Jobs"])
async def get_job_status(job_id: str):
async def get_job_status(
job_id: str,
_: UserResponse = Depends(get_current_user),
):
"""Get the status of a background analysis job.
Args:
@@ -265,6 +513,7 @@ async def list_jobs(
Query(description="Filter by status: pending, running, completed, failed"),
] = None,
limit: Annotated[int, Query(ge=1, le=100)] = 10,
_: UserResponse = Depends(get_current_user),
):
"""List all analysis jobs.
+210
View File
@@ -0,0 +1,210 @@
"""JWT authentication utilities for SPARC API."""
import os
from datetime import datetime, timedelta, timezone
from typing import Optional
import jwt
from fastapi import Depends, HTTPException, status
from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
from pydantic import BaseModel
from SPARC import config
from SPARC.database import DatabaseClient
# JWT Configuration
JWT_SECRET = os.getenv("JWT_SECRET", "sparc-secret-key-change-in-production")
JWT_ALGORITHM = "HS256"
ACCESS_TOKEN_EXPIRE_MINUTES = 30
REFRESH_TOKEN_EXPIRE_DAYS = 7
security = HTTPBearer()
class TokenPayload(BaseModel):
"""JWT token payload."""
sub: str # user_id as string (JWT RFC 7519 requires sub to be a string)
email: str
role: str
exp: datetime
type: str # "access" or "refresh"
@property
def user_id(self) -> int:
"""Get user_id as integer."""
return int(self.sub)
class TokenResponse(BaseModel):
"""Token response model."""
access_token: str
refresh_token: str
token_type: str = "bearer"
class UserResponse(BaseModel):
"""User response model."""
id: int
email: str
role: str
created_at: datetime
def create_access_token(user_id: int, email: str, role: str) -> str:
"""Create a JWT access token.
Args:
user_id: User ID
email: User email
role: User role
Returns:
Encoded JWT token
"""
expire = datetime.now(timezone.utc) + timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
payload = {
"sub": str(user_id),
"email": email,
"role": role,
"exp": expire,
"type": "access",
}
return jwt.encode(payload, JWT_SECRET, algorithm=JWT_ALGORITHM)
def create_refresh_token(user_id: int, email: str, role: str) -> str:
"""Create a JWT refresh token.
Args:
user_id: User ID
email: User email
role: User role
Returns:
Encoded JWT token
"""
expire = datetime.now(timezone.utc) + timedelta(days=REFRESH_TOKEN_EXPIRE_DAYS)
payload = {
"sub": str(user_id),
"email": email,
"role": role,
"exp": expire,
"type": "refresh",
}
return jwt.encode(payload, JWT_SECRET, algorithm=JWT_ALGORITHM)
def create_tokens(user_id: int, email: str, role: str) -> TokenResponse:
"""Create both access and refresh tokens.
Args:
user_id: User ID
email: User email
role: User role
Returns:
TokenResponse with both tokens
"""
return TokenResponse(
access_token=create_access_token(user_id, email, role),
refresh_token=create_refresh_token(user_id, email, role),
)
def decode_token(token: str) -> Optional[TokenPayload]:
"""Decode and validate a JWT token.
Args:
token: JWT token string
Returns:
TokenPayload if valid, None otherwise
"""
try:
payload = jwt.decode(token, JWT_SECRET, algorithms=[JWT_ALGORITHM])
return TokenPayload(**payload)
except jwt.ExpiredSignatureError:
return None
except jwt.InvalidTokenError:
return None
def get_db_client() -> DatabaseClient:
"""Get database client for auth operations."""
client = DatabaseClient(config.database_url)
client.connect()
return client
async def get_current_user(
credentials: HTTPAuthorizationCredentials = Depends(security),
) -> UserResponse:
"""Get the current authenticated user from JWT token.
Args:
credentials: Bearer token from request
Returns:
UserResponse with user details
Raises:
HTTPException: If token is invalid or expired
"""
token = credentials.credentials
payload = decode_token(token)
if not payload:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid or expired token",
headers={"WWW-Authenticate": "Bearer"},
)
if payload.type != "access":
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid token type",
headers={"WWW-Authenticate": "Bearer"},
)
db = get_db_client()
user = db.get_user_by_id(payload.user_id)
if not user:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="User not found",
headers={"WWW-Authenticate": "Bearer"},
)
return UserResponse(
id=user["id"],
email=user["email"],
role=user["role"],
created_at=user["created_at"],
)
async def get_current_admin(
current_user: UserResponse = Depends(get_current_user),
) -> UserResponse:
"""Require admin role for the current user.
Args:
current_user: Current authenticated user
Returns:
UserResponse if admin
Raises:
HTTPException: If user is not admin
"""
if current_user.role != "admin":
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Admin access required",
)
return current_user
+9 -4
View File
@@ -13,10 +13,15 @@ api_key = os.getenv("API_KEY")
# OpenRouter API key for LLM analysis
openrouter_api_key = os.getenv("OPENROUTER_API_KEY")
# Database configuration
# Database configuration - all messages are stored in the database
# The database serves as both a persistent store and a cache layer
database_url = os.getenv("DATABASE_URL", "postgresql://postgres:postgres@localhost:5432/sparc")
# Toggle between database mode and API mode
# When True: stores all messages in database instead of sending to OpenRouter
# When False: sends messages to OpenRouter API as normal
# Cache configuration
# When enabled (default), the system checks the database for cached responses
# before making API calls, saving tokens and reducing latency
use_cache = os.getenv("USE_CACHE", "true").lower() in ("true", "1", "yes")
# Legacy compatibility - USE_DATABASE is deprecated, database is always used
# This variable is kept for backwards compatibility but has no effect
use_database = os.getenv("USE_DATABASE", "false").lower() in ("true", "1", "yes")
+324 -4
View File
@@ -1,10 +1,12 @@
"""Database client for storing and retrieving LLM messages."""
"""Database client for storing and retrieving LLM messages and user authentication."""
import psycopg2
from psycopg2.extras import RealDictCursor
from typing import Dict, List, Optional
from datetime import datetime
import json
import hashlib
import bcrypt
class DatabaseClient:
@@ -43,10 +45,12 @@ class DatabaseClient:
analysis_type VARCHAR(50),
model VARCHAR(100),
prompt TEXT NOT NULL,
prompt_hash VARCHAR(64),
response TEXT,
metadata JSONB,
token_usage JSONB,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
is_cached BOOLEAN DEFAULT FALSE
)
""")
@@ -62,8 +66,109 @@ class DatabaseClient:
ON llm_messages(company_name)
""")
# Add prompt_hash and is_cached columns if they don't exist (for existing tables)
# This must run BEFORE creating the index on prompt_hash
cursor.execute("""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_name = 'llm_messages' AND column_name = 'prompt_hash'
) THEN
ALTER TABLE llm_messages ADD COLUMN prompt_hash VARCHAR(64);
END IF;
IF NOT EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_name = 'llm_messages' AND column_name = 'is_cached'
) THEN
ALTER TABLE llm_messages ADD COLUMN is_cached BOOLEAN DEFAULT FALSE;
END IF;
END $$;
""")
# Create index on prompt_hash for cache lookups
cursor.execute("""
CREATE INDEX IF NOT EXISTS idx_messages_prompt_hash
ON llm_messages(prompt_hash)
""")
# Create users table for authentication
cursor.execute("""
CREATE TABLE IF NOT EXISTS users (
id SERIAL PRIMARY KEY,
email VARCHAR(255) UNIQUE NOT NULL,
password_hash VARCHAR(255) NOT NULL,
role VARCHAR(20) DEFAULT 'user' CHECK (role IN ('admin', 'user')),
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
""")
# Create index on email for fast lookups
cursor.execute("""
CREATE INDEX IF NOT EXISTS idx_users_email
ON users(email)
""")
self.conn.commit()
@staticmethod
def hash_prompt(prompt: str) -> str:
"""Generate a hash of the prompt for cache lookups.
Args:
prompt: The prompt text to hash
Returns:
SHA-256 hash of the prompt
"""
return hashlib.sha256(prompt.encode()).hexdigest()
def get_cached_response(
self,
prompt: str,
company_name: Optional[str] = None,
analysis_type: Optional[str] = None,
) -> Optional[Dict]:
"""Look up a cached response for a given prompt.
Args:
prompt: The prompt to look up
company_name: Optional company name filter
analysis_type: Optional analysis type filter
Returns:
Cached message dict if found, None otherwise
"""
self.connect()
prompt_hash = self.hash_prompt(prompt)
query = """
SELECT * FROM llm_messages
WHERE prompt_hash = %s
AND response IS NOT NULL
AND response NOT LIKE '[DATABASE MODE]%%'
AND response NOT LIKE '[TEST MODE]%%'
AND response NOT LIKE '[NO API]%%'
"""
params = [prompt_hash]
if company_name:
query += " AND company_name = %s"
params.append(company_name)
if analysis_type:
query += " AND analysis_type = %s"
params.append(analysis_type)
query += " ORDER BY timestamp DESC LIMIT 1"
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(query, params)
result = cursor.fetchone()
return dict(result) if result else None
def store_message(
self,
prompt: str,
@@ -73,6 +178,7 @@ class DatabaseClient:
model: Optional[str] = None,
metadata: Optional[Dict] = None,
token_usage: Optional[Dict] = None,
is_cached: bool = False,
) -> int:
"""Store an LLM message exchange in the database.
@@ -84,28 +190,33 @@ class DatabaseClient:
model: Model identifier used
metadata: Additional metadata as dict
token_usage: Token usage information
is_cached: Whether this response was served from cache
Returns:
The ID of the inserted record
"""
self.connect()
prompt_hash = self.hash_prompt(prompt)
with self.conn.cursor() as cursor:
cursor.execute(
"""
INSERT INTO llm_messages
(prompt, response, company_name, analysis_type, model, metadata, token_usage)
VALUES (%s, %s, %s, %s, %s, %s, %s)
(prompt, prompt_hash, response, company_name, analysis_type, model, metadata, token_usage, is_cached)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
RETURNING id
""",
(
prompt,
prompt_hash,
response,
company_name,
analysis_type,
model,
json.dumps(metadata) if metadata else None,
json.dumps(token_usage) if token_usage else None,
is_cached,
),
)
@@ -208,3 +319,212 @@ class DatabaseClient:
"by_type": [dict(row) for row in by_type],
"period_days": days,
}
# User Authentication Methods
@staticmethod
def hash_password(password: str) -> str:
"""Hash a password using bcrypt.
Args:
password: Plain text password
Returns:
Hashed password string
"""
return bcrypt.hashpw(password.encode(), bcrypt.gensalt()).decode()
@staticmethod
def verify_password(password: str, password_hash: str) -> bool:
"""Verify a password against its hash.
Args:
password: Plain text password
password_hash: Stored hash
Returns:
True if password matches
"""
return bcrypt.checkpw(password.encode(), password_hash.encode())
def create_user(
self,
email: str,
password: str,
role: str = "user",
) -> Optional[Dict]:
"""Create a new user.
Args:
email: User email
password: Plain text password
role: User role ('admin' or 'user')
Returns:
Created user dict or None if email exists
"""
self.connect()
password_hash = self.hash_password(password)
try:
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
INSERT INTO users (email, password_hash, role)
VALUES (%s, %s, %s)
RETURNING id, email, role, created_at
""",
(email, password_hash, role),
)
user = cursor.fetchone()
self.conn.commit()
return dict(user) if user else None
except psycopg2.errors.UniqueViolation:
self.conn.rollback()
return None
def authenticate_user(self, email: str, password: str) -> Optional[Dict]:
"""Authenticate a user by email and password.
Args:
email: User email
password: Plain text password
Returns:
User dict if authenticated, None otherwise
"""
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT * FROM users WHERE email = %s",
(email,),
)
user = cursor.fetchone()
if user and self.verify_password(password, user["password_hash"]):
return {
"id": user["id"],
"email": user["email"],
"role": user["role"],
"created_at": user["created_at"],
}
return None
def get_user_by_id(self, user_id: int) -> Optional[Dict]:
"""Get a user by ID.
Args:
user_id: User ID
Returns:
User dict or None
"""
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT id, email, role, created_at FROM users WHERE id = %s",
(user_id,),
)
user = cursor.fetchone()
return dict(user) if user else None
def get_user_by_email(self, email: str) -> Optional[Dict]:
"""Get a user by email.
Args:
email: User email
Returns:
User dict or None
"""
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT id, email, role, created_at FROM users WHERE email = %s",
(email,),
)
user = cursor.fetchone()
return dict(user) if user else None
def get_all_users(self, limit: int = 100, offset: int = 0) -> List[Dict]:
"""Get all users (admin only).
Args:
limit: Maximum number of users
offset: Offset for pagination
Returns:
List of user dicts
"""
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
SELECT id, email, role, created_at
FROM users
ORDER BY created_at DESC
LIMIT %s OFFSET %s
""",
(limit, offset),
)
return [dict(row) for row in cursor.fetchall()]
def update_user_role(self, user_id: int, role: str) -> Optional[Dict]:
"""Update a user's role (admin only).
Args:
user_id: User ID
role: New role ('admin' or 'user')
Returns:
Updated user dict or None
"""
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
UPDATE users
SET role = %s, updated_at = CURRENT_TIMESTAMP
WHERE id = %s
RETURNING id, email, role, created_at
""",
(role, user_id),
)
user = cursor.fetchone()
self.conn.commit()
return dict(user) if user else None
def delete_user(self, user_id: int) -> bool:
"""Delete a user (admin only).
Args:
user_id: User ID
Returns:
True if deleted
"""
self.connect()
with self.conn.cursor() as cursor:
cursor.execute("DELETE FROM users WHERE id = %s", (user_id,))
deleted = cursor.rowcount > 0
self.conn.commit()
return deleted
def get_user_count(self) -> int:
"""Get total user count.
Returns:
Number of users
"""
self.connect()
with self.conn.cursor() as cursor:
cursor.execute("SELECT COUNT(*) FROM users")
return cursor.fetchone()[0]
+107 -69
View File
@@ -9,31 +9,29 @@ from typing import Dict
class LLMAnalyzer:
"""Handles LLM-based analysis of patent content."""
def __init__(self, api_key: str | None = None, test_mode: bool = False, use_database: bool | None = None):
def __init__(self, api_key: str | None = None, test_mode: bool = False, use_cache: bool | None = None):
"""Initialize the LLM analyzer.
Args:
api_key: OpenRouter API key. If None, will attempt to load from config.
test_mode: If True, print prompts instead of making API calls
use_database: If True, store messages in database instead of calling API.
If None, will use config.use_database
use_cache: If True, check database cache before making API calls.
If None, uses config.use_cache (default: True)
"""
self.test_mode = test_mode
self.use_database = use_database if use_database is not None else config.use_database
self.db_client = None
self.use_cache = use_cache if use_cache is not None else config.use_cache
self.model = "anthropic/claude-3.5-sonnet"
# Initialize database client if in database mode
if self.use_database:
self.db_client = DatabaseClient(config.database_url)
self.db_client.initialize_schema()
# Always initialize database client for storage and caching
self.db_client = DatabaseClient(config.database_url)
self.db_client.initialize_schema()
# Initialize OpenRouter client if not in database mode
if (api_key or config.openrouter_api_key) and not test_mode and not self.use_database:
# Initialize OpenRouter client if API key is available
if (api_key or config.openrouter_api_key) and not test_mode:
self.client = OpenAI(
api_key=api_key or config.openrouter_api_key,
base_url="https://openrouter.ai/api/v1"
)
self.model = "anthropic/claude-3.5-sonnet"
else:
self.client = None
@@ -68,22 +66,31 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
print("=" * 80)
return "[TEST MODE - No API call made]"
# Database mode: store the prompt and return a placeholder response
if self.use_database:
response_text = "[DATABASE MODE] Message stored for testing/analytics. Enable API mode to get actual analysis."
self.db_client.store_message(
# Check cache first
if self.use_cache:
cached = self.db_client.get_cached_response(
prompt=prompt,
response=response_text,
company_name=company_name,
analysis_type="single_patent",
model=self.model if hasattr(self, 'model') else None,
metadata={"patent_content_length": len(patent_content)}
analysis_type="single_patent"
)
if cached:
# Log the cache hit
self.db_client.store_message(
prompt=prompt,
response=cached["response"],
company_name=company_name,
analysis_type="single_patent",
model=self.model,
metadata={
"patent_content_length": len(patent_content),
"cache_hit": True,
"original_message_id": cached["id"]
},
is_cached=True
)
return cached["response"]
return response_text
# API mode: send to OpenRouter
# Call API if no cache hit and client is available
if self.client:
response = self.client.chat.completions.create(
model=self.model,
@@ -92,23 +99,34 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
)
response_text = response.choices[0].message.content
# Store in database if db_client is available (for logging even in API mode)
if self.db_client:
self.db_client.store_message(
prompt=prompt,
response=response_text,
company_name=company_name,
analysis_type="single_patent",
model=self.model,
metadata={"patent_content_length": len(patent_content)},
token_usage={
"prompt_tokens": response.usage.prompt_tokens,
"completion_tokens": response.usage.completion_tokens,
"total_tokens": response.usage.total_tokens
} if hasattr(response, 'usage') else None
)
# Store in database for future cache lookups
self.db_client.store_message(
prompt=prompt,
response=response_text,
company_name=company_name,
analysis_type="single_patent",
model=self.model,
metadata={"patent_content_length": len(patent_content)},
token_usage={
"prompt_tokens": response.usage.prompt_tokens,
"completion_tokens": response.usage.completion_tokens,
"total_tokens": response.usage.total_tokens
} if hasattr(response, 'usage') else None
)
return response_text
# No API client available - store prompt for later processing
placeholder = "[NO API] Prompt stored in database. Configure OPENROUTER_API_KEY to enable analysis."
self.db_client.store_message(
prompt=prompt,
response=placeholder,
company_name=company_name,
analysis_type="single_patent",
model=self.model,
metadata={"patent_content_length": len(patent_content), "pending": True}
)
return placeholder
def analyze_patent_portfolio(
self, patents_data: list[Dict[str, str]], company_name: str
@@ -150,46 +168,54 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
print(prompt)
return "[TEST MODE]"
# Database mode: store the prompt and return a placeholder response
if self.use_database:
response_text = "[DATABASE MODE] Message stored for testing/analytics. Enable API mode to get actual analysis."
metadata = {
"patent_count": len(patents_data),
"patent_ids": [p['patent_id'] for p in patents_data]
}
self.db_client.store_message(
# Check cache first
if self.use_cache:
cached = self.db_client.get_cached_response(
prompt=prompt,
response=response_text,
company_name=company_name,
analysis_type="portfolio",
model=self.model if hasattr(self, 'model') else None,
metadata={
"patent_count": len(patents_data),
"patent_ids": [p['patent_id'] for p in patents_data]
}
analysis_type="portfolio"
)
if cached:
# Log the cache hit
self.db_client.store_message(
prompt=prompt,
response=cached["response"],
company_name=company_name,
analysis_type="portfolio",
model=self.model,
metadata={
**metadata,
"cache_hit": True,
"original_message_id": cached["id"]
},
is_cached=True
)
return cached["response"]
return response_text
# Call API if no cache hit and client is available
if self.client:
try:
response = self.client.chat.completions.create(
model=self.model,
max_tokens=2048,
messages=[{"role": "user", "content": prompt}],
)
# API mode: send to OpenRouter
try:
response = self.client.chat.completions.create(
model=self.model,
max_tokens=2048,
messages=[{"role": "user", "content": prompt}],
)
response_text = response.choices[0].message.content
response_text = response.choices[0].message.content
# Store in database if db_client is available (for logging even in API mode)
if self.db_client:
# Store in database for future cache lookups
self.db_client.store_message(
prompt=prompt,
response=response_text,
company_name=company_name,
analysis_type="portfolio",
model=self.model,
metadata={
"patent_count": len(patents_data),
"patent_ids": [p['patent_id'] for p in patents_data]
},
metadata=metadata,
token_usage={
"prompt_tokens": response.usage.prompt_tokens,
"completion_tokens": response.usage.completion_tokens,
@@ -197,7 +223,19 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
} if hasattr(response, 'usage') else None
)
return response_text
except AttributeError:
return prompt
return response_text
except AttributeError:
return prompt
# No API client available - store prompt for later processing
placeholder = "[NO API] Prompt stored in database. Configure OPENROUTER_API_KEY to enable analysis."
self.db_client.store_message(
prompt=prompt,
response=placeholder,
company_name=company_name,
analysis_type="portfolio",
model=self.model,
metadata={**metadata, "pending": True}
)
return placeholder
-778
View File
@@ -1,778 +0,0 @@
"""SPARC Visualization Dashboard.
A Streamlit-based dashboard for visualizing patent analysis results.
Run with: streamlit run dashboard.py
"""
import streamlit as st
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
from datetime import datetime, timedelta
from SPARC.analyzer import CompanyAnalyzer
from SPARC.database import DatabaseClient
from SPARC import config
st.set_page_config(
page_title="SPARC Dashboard",
page_icon="",
layout="wide",
initial_sidebar_state="collapsed",
)
# Modern CSS styling
st.markdown("""
<style>
/* Hide default Streamlit elements */
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
header {visibility: hidden;}
/* Root variables for theming */
:root {
--primary: #6366f1;
--primary-dark: #4f46e5;
--secondary: #0ea5e9;
--success: #10b981;
--warning: #f59e0b;
--error: #ef4444;
--bg-dark: #0f172a;
--bg-card: #1e293b;
--bg-card-hover: #334155;
--text-primary: #f8fafc;
--text-secondary: #94a3b8;
--border: #334155;
}
/* Main app background */
.stApp {
background: linear-gradient(135deg, #0f172a 0%, #1e1b4b 100%);
}
/* Top navigation bar */
.nav-container {
background: rgba(30, 41, 59, 0.8);
backdrop-filter: blur(12px);
border-bottom: 1px solid rgba(99, 102, 241, 0.2);
padding: 1rem 2rem;
margin: -1rem -1rem 2rem -1rem;
display: flex;
align-items: center;
justify-content: space-between;
}
.nav-brand {
display: flex;
align-items: center;
gap: 0.75rem;
}
.nav-brand h1 {
font-size: 1.5rem;
font-weight: 700;
background: linear-gradient(135deg, #6366f1, #0ea5e9);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
margin: 0;
}
.nav-brand span {
font-size: 0.75rem;
color: var(--text-secondary);
text-transform: uppercase;
letter-spacing: 0.1em;
}
/* Card styling */
.modern-card {
background: rgba(30, 41, 59, 0.6);
backdrop-filter: blur(8px);
border: 1px solid rgba(99, 102, 241, 0.15);
border-radius: 16px;
padding: 1.5rem;
margin-bottom: 1rem;
transition: all 0.3s ease;
}
.modern-card:hover {
border-color: rgba(99, 102, 241, 0.4);
box-shadow: 0 8px 32px rgba(99, 102, 241, 0.15);
}
/* Metric cards */
.metric-card {
background: linear-gradient(135deg, rgba(99, 102, 241, 0.1), rgba(14, 165, 233, 0.1));
border: 1px solid rgba(99, 102, 241, 0.2);
border-radius: 12px;
padding: 1.25rem;
text-align: center;
}
.metric-value {
font-size: 2rem;
font-weight: 700;
background: linear-gradient(135deg, #6366f1, #0ea5e9);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.metric-label {
font-size: 0.875rem;
color: var(--text-secondary);
text-transform: uppercase;
letter-spacing: 0.05em;
margin-top: 0.25rem;
}
/* Section headers */
.section-header {
font-size: 1.25rem;
font-weight: 600;
color: var(--text-primary);
margin-bottom: 1rem;
padding-bottom: 0.5rem;
border-bottom: 2px solid rgba(99, 102, 241, 0.3);
}
/* Input fields */
.stTextInput > div > div > input,
.stTextArea > div > div > textarea {
background: rgba(30, 41, 59, 0.8) !important;
border: 1px solid rgba(99, 102, 241, 0.3) !important;
border-radius: 10px !important;
color: var(--text-primary) !important;
padding: 0.75rem 1rem !important;
}
.stTextInput > div > div > input:focus,
.stTextArea > div > div > textarea:focus {
border-color: var(--primary) !important;
box-shadow: 0 0 0 2px rgba(99, 102, 241, 0.2) !important;
}
/* Buttons */
.stButton > button {
background: linear-gradient(135deg, #6366f1, #4f46e5) !important;
color: white !important;
border: none !important;
border-radius: 10px !important;
padding: 0.75rem 1.5rem !important;
font-weight: 600 !important;
transition: all 0.3s ease !important;
box-shadow: 0 4px 14px rgba(99, 102, 241, 0.3) !important;
}
.stButton > button:hover {
transform: translateY(-2px) !important;
box-shadow: 0 6px 20px rgba(99, 102, 241, 0.4) !important;
}
/* Tabs styling */
.stTabs [data-baseweb="tab-list"] {
background: rgba(30, 41, 59, 0.6);
border-radius: 12px;
padding: 0.5rem;
gap: 0.5rem;
border: 1px solid rgba(99, 102, 241, 0.15);
}
.stTabs [data-baseweb="tab"] {
background: transparent;
border-radius: 8px;
color: var(--text-secondary);
padding: 0.75rem 1.5rem;
font-weight: 500;
}
.stTabs [aria-selected="true"] {
background: linear-gradient(135deg, #6366f1, #4f46e5) !important;
color: white !important;
}
.stTabs [data-baseweb="tab-border"] {
display: none;
}
.stTabs [data-baseweb="tab-highlight"] {
display: none;
}
/* Expander styling */
.streamlit-expanderHeader {
background: rgba(30, 41, 59, 0.6) !important;
border: 1px solid rgba(99, 102, 241, 0.15) !important;
border-radius: 10px !important;
color: var(--text-primary) !important;
}
.streamlit-expanderContent {
background: rgba(30, 41, 59, 0.4) !important;
border: 1px solid rgba(99, 102, 241, 0.1) !important;
border-top: none !important;
border-radius: 0 0 10px 10px !important;
}
/* Slider */
.stSlider > div > div > div {
background: var(--primary) !important;
}
/* Select box */
.stSelectbox > div > div {
background: rgba(30, 41, 59, 0.8) !important;
border: 1px solid rgba(99, 102, 241, 0.3) !important;
border-radius: 10px !important;
}
/* Progress bar */
.stProgress > div > div > div {
background: linear-gradient(90deg, #6366f1, #0ea5e9) !important;
}
/* Alerts */
.stAlert {
border-radius: 10px !important;
border: none !important;
}
/* Metrics */
[data-testid="stMetricValue"] {
background: linear-gradient(135deg, #6366f1, #0ea5e9);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
font-weight: 700;
}
[data-testid="stMetricLabel"] {
color: var(--text-secondary) !important;
}
/* Plotly charts */
.js-plotly-plot {
border-radius: 12px;
overflow: hidden;
}
/* Status badges */
.status-badge {
display: inline-block;
padding: 0.25rem 0.75rem;
border-radius: 9999px;
font-size: 0.75rem;
font-weight: 600;
text-transform: uppercase;
}
.status-success {
background: rgba(16, 185, 129, 0.2);
color: #10b981;
border: 1px solid rgba(16, 185, 129, 0.3);
}
.status-warning {
background: rgba(245, 158, 11, 0.2);
color: #f59e0b;
border: 1px solid rgba(245, 158, 11, 0.3);
}
.status-error {
background: rgba(239, 68, 68, 0.2);
color: #ef4444;
border: 1px solid rgba(239, 68, 68, 0.3);
}
/* Dividers */
hr {
border: none;
border-top: 1px solid rgba(99, 102, 241, 0.2);
margin: 1.5rem 0;
}
/* Info boxes */
.info-box {
background: linear-gradient(135deg, rgba(99, 102, 241, 0.1), rgba(14, 165, 233, 0.05));
border: 1px solid rgba(99, 102, 241, 0.2);
border-radius: 12px;
padding: 1rem 1.25rem;
margin: 1rem 0;
}
/* Feature list */
.feature-item {
display: flex;
align-items: flex-start;
gap: 0.75rem;
padding: 0.75rem 0;
border-bottom: 1px solid rgba(99, 102, 241, 0.1);
}
.feature-icon {
color: var(--primary);
font-size: 1.25rem;
}
</style>
""", unsafe_allow_html=True)
@st.cache_resource
def get_analyzer():
"""Get or create the CompanyAnalyzer instance."""
return CompanyAnalyzer()
@st.cache_resource
def get_db_client():
"""Get database client if available."""
if config.use_database:
try:
client = DatabaseClient()
client.connect()
return client
except Exception:
return None
return None
def render_header():
"""Render the modern dashboard header."""
st.markdown("""
<div class="nav-container">
<div class="nav-brand">
<h1>⚡ SPARC</h1>
<span>Semiconductor Patent Analytics</span>
</div>
</div>
""", unsafe_allow_html=True)
def render_navigation():
"""Render horizontal tab navigation at the top."""
tabs = st.tabs(["🔍 Company Analysis", "📦 Batch Analysis", "📊 Analytics", "️ About"])
return tabs
def render_company_analysis():
"""Render single company analysis page."""
st.markdown('<p class="section-header">Single Company Analysis</p>', unsafe_allow_html=True)
st.markdown("Analyze a company's patent portfolio using AI-powered insights.")
st.markdown("")
# Search card
with st.container():
col1, col2 = st.columns([3, 1])
with col1:
company_name = st.text_input(
"Company Name",
placeholder="Enter company name (e.g., nvidia, intel, amd)",
help="Enter the company name to analyze their patent portfolio",
label_visibility="collapsed",
)
with col2:
analyze_btn = st.button("🔍 Analyze", type="primary", use_container_width=True)
if analyze_btn and company_name:
with st.spinner(f"Analyzing {company_name}..."):
analyzer = get_analyzer()
result = analyzer._analyze_company_safe(company_name)
if result.success:
st.success(f"✓ Analysis complete for {company_name.upper()}")
st.markdown("")
# Metrics row with custom styling
col1, col2, col3 = st.columns(3)
with col1:
st.metric("Patents Found", result.patent_count)
with col2:
st.metric("Analysis Status", "Complete")
with col3:
st.metric("Timestamp", result.timestamp.strftime("%H:%M:%S"))
st.markdown("")
# Analysis content in a styled container
st.markdown('<p class="section-header">AI Analysis Results</p>', unsafe_allow_html=True)
with st.container():
st.markdown(result.analysis)
else:
st.error(f"Analysis failed: {result.error}")
elif not company_name and analyze_btn:
st.warning("Please enter a company name to analyze.")
def render_batch_analysis():
"""Render batch analysis page."""
st.markdown('<p class="section-header">Batch Company Analysis</p>', unsafe_allow_html=True)
st.markdown("Analyze multiple companies simultaneously for comparative insights.")
st.markdown("")
# Input section
col1, col2 = st.columns([2, 1])
with col1:
companies_input = st.text_area(
"Company Names",
placeholder="Enter company names (one per line or comma-separated):\nnvidia\namd\nintel\nqualcomm",
height=150,
label_visibility="collapsed",
)
with col2:
st.markdown("**Configuration**")
max_workers = st.slider("Concurrent Workers", 1, 5, 3, help="Number of parallel analysis threads")
st.markdown("")
analyze_btn = st.button(
"🚀 Run Batch Analysis", type="primary", use_container_width=True
)
if analyze_btn and companies_input:
# Parse company names
companies = [
c.strip()
for c in companies_input.replace(",", "\n").split("\n")
if c.strip()
]
if not companies:
st.warning("Please enter at least one company name")
return
st.info(f"🔄 Starting analysis of {len(companies)} companies...")
# Progress tracking
progress_bar = st.progress(0)
status_text = st.empty()
analyzer = get_analyzer()
def update_progress(company: str, completed: int, total: int):
progress = completed / total
progress_bar.progress(progress)
status_text.text(f"Analyzing {company}... ({completed}/{total})")
result = analyzer.analyze_companies(
companies=companies,
max_workers=max_workers,
progress_callback=update_progress,
)
progress_bar.progress(1.0)
status_text.text("✓ Analysis complete!")
st.markdown("")
# Summary metrics
st.markdown('<p class="section-header">Results Summary</p>', unsafe_allow_html=True)
col1, col2, col3, col4 = st.columns(4)
with col1:
st.metric("Total Companies", result.total_companies)
with col2:
st.metric("Successful", result.successful)
with col3:
st.metric("Failed", result.failed)
with col4:
success_rate = (
(result.successful / result.total_companies * 100)
if result.total_companies > 0
else 0
)
st.metric("Success Rate", f"{success_rate:.1f}%")
# Results chart
if result.results:
df = pd.DataFrame(
[
{
"Company": r.company_name.upper(),
"Patents": r.patent_count,
"Status": "Success" if r.success else "Failed",
}
for r in result.results
]
)
fig = px.bar(
df,
x="Company",
y="Patents",
color="Status",
color_discrete_map={"Success": "#10b981", "Failed": "#ef4444"},
title="",
)
fig.update_layout(
plot_bgcolor="rgba(0,0,0,0)",
paper_bgcolor="rgba(0,0,0,0)",
font_color="#94a3b8",
legend=dict(
orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1
),
xaxis=dict(showgrid=False),
yaxis=dict(showgrid=True, gridcolor="rgba(99, 102, 241, 0.1)"),
)
st.plotly_chart(fig, use_container_width=True)
st.markdown("")
# Individual results
st.markdown('<p class="section-header">Detailed Results</p>', unsafe_allow_html=True)
for r in result.results:
status_icon = "" if r.success else ""
status_class = "status-success" if r.success else "status-error"
with st.expander(
f"{status_icon} {r.company_name.upper()}{r.patent_count} patents"
):
if r.success:
st.markdown(r.analysis)
else:
st.error(r.error)
def render_analytics():
"""Render analytics page with database insights."""
st.markdown('<p class="section-header">Analytics Dashboard</p>', unsafe_allow_html=True)
st.markdown("Track historical analysis data and view insights.")
db_client = get_db_client()
if not db_client:
st.markdown("")
st.markdown("""
<div class="info-box">
<strong>⚠️ Database Not Connected</strong><br>
<span style="color: #94a3b8;">Set <code>USE_DATABASE=true</code> in your .env file to enable analytics tracking.</span>
</div>
""", unsafe_allow_html=True)
st.info("Analytics features require storing analysis results in PostgreSQL for historical tracking.")
return
st.markdown("")
# Time range selector
col1, col2, col3 = st.columns([1, 2, 1])
with col1:
days = st.selectbox("Time Range", [7, 14, 30, 90], index=0, format_func=lambda x: f"Last {x} days")
try:
analytics = db_client.get_analytics(days=days)
if not analytics:
st.info("No analytics data available yet. Run some analyses first!")
return
st.markdown("")
# Summary metrics
col1, col2, col3 = st.columns(3)
with col1:
total = analytics.get("total_messages", 0)
st.metric("Total Analyses", total)
with col2:
companies = len(analytics.get("by_company", {}))
st.metric("Companies Analyzed", companies)
with col3:
types = len(analytics.get("by_type", {}))
st.metric("Analysis Types", types)
st.markdown("")
# Charts
col1, col2 = st.columns(2)
with col1:
by_company = analytics.get("by_company", {})
if by_company:
df = pd.DataFrame(
[{"Company": k.upper(), "Count": v} for k, v in by_company.items()]
)
fig = px.pie(
df, values="Count", names="Company", title="Distribution by Company",
hole=0.4,
color_discrete_sequence=px.colors.sequential.Purp_r,
)
fig.update_layout(
plot_bgcolor="rgba(0,0,0,0)",
paper_bgcolor="rgba(0,0,0,0)",
font_color="#94a3b8",
)
st.plotly_chart(fig, use_container_width=True)
with col2:
by_type = analytics.get("by_type", {})
if by_type:
df = pd.DataFrame(
[{"Type": k, "Count": v} for k, v in by_type.items()]
)
fig = px.bar(df, x="Type", y="Count", title="Analysis Types",
color_discrete_sequence=["#6366f1"])
fig.update_layout(
plot_bgcolor="rgba(0,0,0,0)",
paper_bgcolor="rgba(0,0,0,0)",
font_color="#94a3b8",
xaxis=dict(showgrid=False),
yaxis=dict(showgrid=True, gridcolor="rgba(99, 102, 241, 0.1)"),
)
st.plotly_chart(fig, use_container_width=True)
st.markdown("")
# Recent messages
st.markdown('<p class="section-header">Recent Analyses</p>', unsafe_allow_html=True)
messages = db_client.get_messages(limit=10)
if messages:
for msg in messages:
with st.expander(
f"📄 {msg.get('company_name', 'Unknown').upper()}{msg.get('analysis_type', 'N/A')} ({msg.get('timestamp', 'N/A')})"
):
st.markdown(f"**Model:** `{msg.get('model', 'N/A')}`")
if msg.get("response"):
st.markdown(msg["response"][:500] + "...")
except Exception as e:
st.error(f"Error fetching analytics: {e}")
def render_about():
"""Render about page."""
st.markdown('<p class="section-header">About SPARC</p>', unsafe_allow_html=True)
col1, col2 = st.columns([2, 1])
with col1:
st.markdown("""
**SPARC** (Semiconductor Patent & Analytics Report Core) is an AI-powered patent analysis
platform that evaluates company performance by analyzing their patent portfolios
with cutting-edge language models.
""")
st.markdown("")
st.markdown("**Key Features**")
features = [
("🔍", "Patent Retrieval", "Automated collection via SerpAPI's Google Patents"),
("📄", "Intelligent Parsing", "Extracts key sections from patent documents"),
("🤖", "AI Analysis", "Deep analysis powered by Claude 3.5 Sonnet"),
("", "Batch Processing", "Analyze multiple companies concurrently"),
("🌐", "REST API", "FastAPI web service for seamless integration"),
("📊", "Analytics", "Track and visualize historical analysis data"),
]
for icon, title, desc in features:
st.markdown(f"""
<div class="feature-item">
<span class="feature-icon">{icon}</span>
<div>
<strong>{title}</strong><br>
<span style="color: #94a3b8; font-size: 0.875rem;">{desc}</span>
</div>
</div>
""", unsafe_allow_html=True)
with col2:
st.markdown("**Technology Stack**")
st.markdown("""
<div class="info-box">
<div style="display: grid; gap: 0.5rem;">
<div><span style="color: #6366f1;">Backend</span><br><span style="color: #94a3b8;">Python, FastAPI</span></div>
<div><span style="color: #6366f1;">AI Model</span><br><span style="color: #94a3b8;">Claude 3.5 Sonnet</span></div>
<div><span style="color: #6366f1;">Database</span><br><span style="color: #94a3b8;">PostgreSQL</span></div>
<div><span style="color: #6366f1;">Dashboard</span><br><span style="color: #94a3b8;">Streamlit, Plotly</span></div>
<div><span style="color: #6366f1;">Data Source</span><br><span style="color: #94a3b8;">SerpAPI Patents</span></div>
</div>
</div>
""", unsafe_allow_html=True)
st.markdown("")
st.markdown("**API Endpoints**")
st.code("http://localhost:8000/docs", language=None)
st.code("http://localhost:8000/health", language=None)
st.markdown("")
st.markdown("")
# System status
st.markdown('<p class="section-header">System Status</p>', unsafe_allow_html=True)
col1, col2, col3 = st.columns(3)
with col1:
db_client = get_db_client()
if db_client:
st.markdown("""
<div class="metric-card">
<div style="color: #10b981; font-size: 1.5rem;">●</div>
<div class="metric-label">Database</div>
<div style="color: #10b981; font-weight: 600;">Connected</div>
</div>
""", unsafe_allow_html=True)
else:
st.markdown("""
<div class="metric-card">
<div style="color: #f59e0b; font-size: 1.5rem;">●</div>
<div class="metric-label">Database</div>
<div style="color: #f59e0b; font-weight: 600;">Not Configured</div>
</div>
""", unsafe_allow_html=True)
with col2:
analyzer = get_analyzer()
if analyzer:
st.markdown("""
<div class="metric-card">
<div style="color: #10b981; font-size: 1.5rem;">●</div>
<div class="metric-label">Analyzer</div>
<div style="color: #10b981; font-weight: 600;">Ready</div>
</div>
""", unsafe_allow_html=True)
else:
st.markdown("""
<div class="metric-card">
<div style="color: #ef4444; font-size: 1.5rem;">●</div>
<div class="metric-label">Analyzer</div>
<div style="color: #ef4444; font-weight: 600;">Not Initialized</div>
</div>
""", unsafe_allow_html=True)
with col3:
st.markdown("""
<div class="metric-card">
<div style="color: #10b981; font-size: 1.5rem;">●</div>
<div class="metric-label">Dashboard</div>
<div style="color: #10b981; font-weight: 600;">Online</div>
</div>
""", unsafe_allow_html=True)
def main():
"""Main dashboard entry point."""
render_header()
tabs = render_navigation()
with tabs[0]:
render_company_analysis()
with tabs[1]:
render_batch_analysis()
with tabs[2]:
render_analytics()
with tabs[3]:
render_about()
if __name__ == "__main__":
main()
+4 -12
View File
@@ -23,7 +23,6 @@ services:
command: python scripts/init_database.py
environment:
DATABASE_URL: postgresql://postgres:postgres@postgres:5432/sparc
USE_DATABASE: "true"
depends_on:
postgres:
condition: service_healthy
@@ -37,7 +36,8 @@ services:
API_KEY: ${API_KEY}
OPENROUTER_API_KEY: ${OPENROUTER_API_KEY}
DATABASE_URL: postgresql://postgres:postgres@postgres:5432/sparc
USE_DATABASE: "true"
USE_CACHE: "true"
JWT_SECRET: ${JWT_SECRET:-sparc-secret-key-change-in-production}
ports:
- "8000:8000"
depends_on:
@@ -50,20 +50,12 @@ services:
restart: unless-stopped
dashboard:
build: .
build: ./frontend
container_name: sparc-dashboard
command: streamlit run dashboard.py --server.port 8501 --server.address 0.0.0.0
environment:
API_KEY: ${API_KEY}
OPENROUTER_API_KEY: ${OPENROUTER_API_KEY}
DATABASE_URL: postgresql://postgres:postgres@postgres:5432/sparc
USE_DATABASE: "true"
ports:
- "8501:8501"
- "8080:80"
depends_on:
- api
volumes:
- ./patents:/app/patents
restart: unless-stopped
volumes:
+58 -45
View File
@@ -1,16 +1,19 @@
# Database Mode for Testing and Analytics
# Database Storage and Caching
This document explains how to use SPARC's database mode for storing LLM messages for testing and analytics purposes.
This document explains how SPARC uses PostgreSQL for storing LLM messages, enabling response caching and analytics.
## Overview
SPARC supports two modes of operation:
SPARC stores all LLM interactions in PostgreSQL, providing:
1. **API Mode** (default): Messages are sent to OpenRouter's API and you receive real LLM responses
2. **Database Mode**: Messages are stored in a PostgreSQL database without making API calls, useful for:
- Testing the application without consuming API credits
- Collecting analytics on message patterns and usage
- Development and debugging
- **Response Caching**: Avoid redundant API calls for previously analyzed patents
- **Analytics**: Track usage patterns, token consumption, and analysis history
- **Persistence**: Maintain analysis history across sessions
SPARC supports two cache modes:
1. **Cache Mode** (default, `USE_CACHE=true`): Check database for cached responses before making API calls
2. **Fresh Mode** (`USE_CACHE=false`): Always make fresh API calls (still stores results in database)
## Setup
@@ -45,43 +48,43 @@ cp .env.example .env
Edit `.env` and set:
```env
# For database mode (testing/analytics)
USE_DATABASE=true
# Database connection (required)
DATABASE_URL=postgresql://postgres:postgres@localhost:5432/sparc
# For API mode (production)
USE_DATABASE=false
# Cache mode: use cached responses when available
USE_CACHE=true
# API key for fresh LLM calls
OPENROUTER_API_KEY=your_openrouter_key_here
```
## Usage
### Running in Database Mode
### Running with Cache Mode (Default)
Set `USE_DATABASE=true` in your `.env` file, then run the application normally:
Set `USE_CACHE=true` in your `.env` file, then run the application normally:
```bash
python main.py
```
Instead of sending messages to OpenRouter, the application will:
- Store all prompts in the database
- Return a placeholder response
- Log metadata (company name, analysis type, timestamps)
The application will:
- Check the database for cached responses matching the request
- If found, return the cached response (no API call)
- If not found, make an API call and store the response for future use
### Running in API Mode
### Running with Fresh Mode
Set `USE_DATABASE=false` in your `.env` file, then run the application normally:
Set `USE_CACHE=false` in your `.env` file to always get fresh responses:
```bash
python main.py
```
The application will send messages to OpenRouter and return real LLM responses.
### Hybrid Mode (Optional)
You can also enable database logging while still using the API by initializing the database client in your code. The `LLMAnalyzer` will automatically log all API calls to the database if a database client is available.
The application will:
- Always send messages to OpenRouter for real LLM responses
- Store all responses in the database
- Useful when you need the latest analysis or want to refresh cached data
## Viewing Analytics
@@ -195,16 +198,16 @@ docker-compose down -v
## Toggling Between Modes
You can easily switch between modes by changing the `USE_DATABASE` environment variable:
You can easily switch between modes by changing the `USE_CACHE` environment variable:
### Quick Toggle (temporary, for testing)
### Quick Toggle (temporary)
```bash
# Run in database mode
USE_DATABASE=true python main.py
# Run with caching enabled
USE_CACHE=true python main.py
# Run in API mode
USE_DATABASE=false python main.py
# Run with fresh API calls
USE_CACHE=false python main.py
```
### Persistent Toggle
@@ -212,38 +215,48 @@ USE_DATABASE=false python main.py
Edit your `.env` file:
```env
# For testing/analytics
USE_DATABASE=true
# Use cached responses when available (recommended for most use)
USE_CACHE=true
# For production use
USE_DATABASE=false
# Always make fresh API calls
USE_CACHE=false
```
## Use Cases
### Testing Without API Costs
### Cost Optimization with Caching
During development, enable database mode to test the full application flow without consuming API credits:
Cache mode reduces API costs by reusing previous analysis results:
```bash
USE_DATABASE=true python main.py
USE_CACHE=true python main.py
```
If the same company/patent combination was analyzed before, the cached response is returned instantly.
### Fresh Analysis
When you need the latest LLM analysis (e.g., after model updates):
```bash
USE_CACHE=false python main.py
```
### Collecting Usage Analytics
Enable database mode in a test environment to collect analytics on:
The database stores all interactions, enabling analytics on:
- Which companies are analyzed most frequently
- Types of analyses performed
- Prompt patterns and lengths
- Usage over time
- Token usage and costs over time
- Response caching hit rates
### Development and Debugging
Database mode is useful for:
- Testing patent parsing logic without API calls
Database storage is useful for:
- Reviewing actual prompts sent to the LLM
- Analyzing response patterns
- Debugging the full pipeline end-to-end
- Collecting sample prompts for optimization
- Understanding token usage patterns (when in API mode with logging)
- Understanding token usage patterns
## Troubleshooting
+24 -22
View File
@@ -64,7 +64,7 @@ docker-compose ps
# You should see:
# - sparc-postgres (healthy)
# - sparc-api (running on port 8000)
# - sparc-dashboard (running on port 8501)
# - sparc-dashboard (running on port 8080)
```
The database is automatically initialized by the `init-db` service.
@@ -116,11 +116,13 @@ docker-compose up -d postgres
# Wait for database to be healthy, then initialize
python scripts/init_database.py
# Terminal 1: Start FastAPI backend
# Start FastAPI backend
uvicorn SPARC.api:app --host 0.0.0.0 --port 8000 --reload
# Terminal 2: Start Streamlit dashboard
streamlit run dashboard.py --server.port 8501 --server.address 0.0.0.0
# For the React frontend (separate terminal)
cd frontend
npm install
npm run dev
```
---
@@ -141,7 +143,7 @@ Access the services:
|---------|-----|
| REST API | http://localhost:8000 |
| API Documentation (Swagger) | http://localhost:8000/docs |
| Dashboard (Web UI) | http://localhost:8501 |
| Dashboard (Web UI) | http://localhost:8080 |
---
@@ -149,16 +151,17 @@ Access the services:
### Via Dashboard (Web UI)
1. Open http://localhost:8501
2. Select **"Company Analysis"** from the sidebar
3. Enter a company name (e.g., "Intel")
4. Click **"Analyze"**
1. Open http://localhost:8080
2. Register a new account or login (default admin: `admin` / `admin`)
3. Navigate to **"Analysis"** from the sidebar
4. Enter a company name (e.g., "Intel")
5. Click **"Analyze"**
This will:
- Query SerpAPI for recent patents
- Download and parse patent PDFs
- Send patent content to Claude for analysis
- Store prompt/response in PostgreSQL
- Store prompt/response in PostgreSQL (with caching)
- Display results in the dashboard
### Via REST API
@@ -233,12 +236,12 @@ docker exec -it sparc-postgres psql -U postgres -d sparc -c \
| Component | Purpose |
|-----------|---------|
| **Dashboard** | Streamlit web UI for interactive analysis |
| **FastAPI** | REST API for programmatic access |
| **Dashboard** | React TypeScript web UI with authentication |
| **FastAPI** | REST API with JWT authentication |
| **Analyzer** | Orchestrates patent retrieval and LLM analysis |
| **SerpAPI** | Retrieves patent data from Google Patents |
| **OpenRouter** | Routes requests to Claude for AI analysis |
| **PostgreSQL** | Stores prompts, responses, and analytics |
| **PostgreSQL** | Stores prompts, responses, users, and cached results |
---
@@ -248,10 +251,9 @@ docker exec -it sparc-postgres psql -U postgres -d sparc -c \
|----------|----------|---------|-------------|
| `API_KEY` | Yes | - | SerpAPI key for patent search |
| `OPENROUTER_API_KEY` | Yes | - | OpenRouter API key for Claude access |
| `DATABASE_URL` | Yes* | - | PostgreSQL connection string |
| `USE_DATABASE` | No | `false` | Set to `true` to enable database storage |
*Required when `USE_DATABASE=true`
| `DATABASE_URL` | Yes | - | PostgreSQL connection string |
| `USE_CACHE` | No | `true` | Check database for cached responses before API calls |
| `JWT_SECRET` | Yes | - | Secret key for JWT authentication (change in production!) |
### Database URL Format
@@ -273,9 +275,9 @@ The `docker-compose.yml` includes all services needed for production:
| Service | Container | Port | Description |
|---------|-----------|------|-------------|
| `postgres` | sparc-postgres | 5432 | PostgreSQL database |
| `init-db` | sparc-init-db | - | One-time database initialization |
| `api` | sparc-api | 8000 | FastAPI REST API |
| `dashboard` | sparc-dashboard | 8501 | Streamlit web UI |
| `init-db` | sparc-init-db | - | One-time database initialization (seeds admin user) |
| `api` | sparc-api | 8000 | FastAPI REST API with JWT auth |
| `dashboard` | sparc-dashboard | 8080 | React TypeScript web UI |
### Common Docker Compose Commands
@@ -382,11 +384,11 @@ cp .env.example .env
docker-compose up -d postgres
python scripts/init_database.py
uvicorn SPARC.api:app --reload &
streamlit run dashboard.py
cd frontend && npm install && npm run dev &
# Check status
curl http://localhost:8000/health
open http://localhost:8501
open http://localhost:8080
# View data
python scripts/view_analytics.py
+22
View File
@@ -0,0 +1,22 @@
# Dependencies
node_modules/
# Build output
dist/
# Local env files
.env.local
.env.*.local
# Editor directories
.vscode/
.idea/
# OS files
.DS_Store
Thumbs.db
# Debug logs
npm-debug.log*
yarn-debug.log*
yarn-error.log*
+29
View File
@@ -0,0 +1,29 @@
# Build stage
FROM node:20-alpine AS build
WORKDIR /app
# Copy package files
COPY package.json package-lock.json* ./
# Install dependencies
RUN npm install
# Copy source files
COPY . .
# Build the application
RUN npm run build
# Production stage
FROM nginx:alpine
# Copy built files
COPY --from=build /app/dist /usr/share/nginx/html
# Copy nginx config
COPY nginx.conf /etc/nginx/conf.d/default.conf
EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]
+13
View File
@@ -0,0 +1,13 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>SPARC Dashboard</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>
+34
View File
@@ -0,0 +1,34 @@
server {
listen 80;
server_name localhost;
root /usr/share/nginx/html;
index index.html;
# Gzip compression
gzip on;
gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript;
# Handle React Router (SPA)
location / {
try_files $uri $uri/ /index.html;
}
# Proxy API requests to backend
location /api/ {
proxy_pass http://api:8000/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection 'upgrade';
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_cache_bypass $http_upgrade;
}
# Cache static assets
location ~* \.(js|css|png|jpg|jpeg|gif|ico|svg|woff|woff2)$ {
expires 1y;
add_header Cache-Control "public, immutable";
}
}
+37
View File
@@ -0,0 +1,37 @@
{
"name": "sparc-dashboard",
"private": true,
"version": "1.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "tsc -b && vite build",
"lint": "eslint .",
"preview": "vite preview"
},
"dependencies": {
"@tanstack/react-query": "^5.51.0",
"axios": "^1.7.2",
"lucide-react": "^0.400.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
"recharts": "^2.12.7"
},
"devDependencies": {
"@eslint/js": "^9.6.0",
"@types/react": "^18.3.3",
"@types/react-dom": "^18.3.0",
"@vitejs/plugin-react": "^4.3.1",
"autoprefixer": "^10.4.19",
"eslint": "^9.6.0",
"eslint-plugin-react-hooks": "^5.1.0",
"eslint-plugin-react-refresh": "^0.4.7",
"globals": "^15.8.0",
"postcss": "^8.4.39",
"tailwindcss": "^3.4.4",
"typescript": "~5.5.3",
"typescript-eslint": "^8.0.0",
"vite": "^5.3.3"
}
}
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export default {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}
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import { BrowserRouter, Routes, Route, Navigate } from 'react-router-dom';
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
import { AuthProvider } from './context/AuthContext';
import { Layout } from './components/Layout';
import { ProtectedRoute } from './components/ProtectedRoute';
import { Login } from './pages/Login';
import { Register } from './pages/Register';
import { Analysis } from './pages/Analysis';
import { Batch } from './pages/Batch';
import { AnalyticsPage } from './pages/Analytics';
import { About } from './pages/About';
import { AdminUsers } from './pages/AdminUsers';
const queryClient = new QueryClient({
defaultOptions: {
queries: {
staleTime: 1000 * 60 * 5, // 5 minutes
retry: 1,
},
},
});
function App() {
return (
<QueryClientProvider client={queryClient}>
<AuthProvider>
<BrowserRouter>
<Routes>
{/* Public routes */}
<Route path="/login" element={<Login />} />
<Route path="/register" element={<Register />} />
{/* Protected routes */}
<Route
element={
<ProtectedRoute>
<Layout />
</ProtectedRoute>
}
>
<Route path="/analysis" element={<Analysis />} />
<Route path="/batch" element={<Batch />} />
<Route path="/analytics" element={<AnalyticsPage />} />
<Route path="/about" element={<About />} />
{/* Admin routes */}
<Route
path="/admin/users"
element={
<ProtectedRoute requireAdmin>
<AdminUsers />
</ProtectedRoute>
}
/>
</Route>
{/* Default redirect */}
<Route path="/" element={<Navigate to="/analysis" replace />} />
<Route path="*" element={<Navigate to="/analysis" replace />} />
</Routes>
</BrowserRouter>
</AuthProvider>
</QueryClientProvider>
);
}
export default App;
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import axios, { AxiosError, InternalAxiosRequestConfig } from 'axios';
import type { TokenResponse, User, CompanyAnalysis, BatchAnalysisResult, JobStatus, Analytics } from '../types';
const API_BASE_URL = import.meta.env.VITE_API_URL || '/api';
const api = axios.create({
baseURL: API_BASE_URL,
headers: {
'Content-Type': 'application/json',
},
});
// Token management
let accessToken: string | null = localStorage.getItem('access_token');
let refreshToken: string | null = localStorage.getItem('refresh_token');
export const setTokens = (tokens: TokenResponse) => {
accessToken = tokens.access_token;
refreshToken = tokens.refresh_token;
localStorage.setItem('access_token', tokens.access_token);
localStorage.setItem('refresh_token', tokens.refresh_token);
};
export const clearTokens = () => {
accessToken = null;
refreshToken = null;
localStorage.removeItem('access_token');
localStorage.removeItem('refresh_token');
};
export const getAccessToken = () => accessToken;
// Request interceptor to add auth header
api.interceptors.request.use((config: InternalAxiosRequestConfig) => {
if (accessToken) {
config.headers.Authorization = `Bearer ${accessToken}`;
}
return config;
});
// Response interceptor to handle token refresh
api.interceptors.response.use(
(response) => response,
async (error: AxiosError) => {
const originalRequest = error.config as InternalAxiosRequestConfig & { _retry?: boolean };
if (error.response?.status === 401 && !originalRequest._retry && refreshToken) {
originalRequest._retry = true;
try {
const response = await axios.post<TokenResponse>(`${API_BASE_URL}/auth/refresh`, {
refresh_token: refreshToken,
});
setTokens(response.data);
originalRequest.headers.Authorization = `Bearer ${response.data.access_token}`;
return api(originalRequest);
} catch {
clearTokens();
window.location.href = '/login';
}
}
return Promise.reject(error);
}
);
// Auth API
export const authApi = {
register: async (email: string, password: string): Promise<User> => {
const response = await api.post<User>('/auth/register', { email, password });
return response.data;
},
login: async (email: string, password: string): Promise<TokenResponse> => {
const response = await api.post<TokenResponse>('/auth/login', { email, password });
setTokens(response.data);
return response.data;
},
getMe: async (): Promise<User> => {
const response = await api.get<User>('/auth/me');
return response.data;
},
logout: () => {
clearTokens();
},
};
// Analysis API
export const analysisApi = {
analyzeCompany: async (companyName: string): Promise<CompanyAnalysis> => {
const response = await api.get<CompanyAnalysis>(`/analyze/${encodeURIComponent(companyName)}`);
return response.data;
},
analyzeBatch: async (companies: string[], maxWorkers = 3): Promise<BatchAnalysisResult> => {
const response = await api.post<BatchAnalysisResult>('/analyze/batch', {
companies,
max_workers: maxWorkers,
});
return response.data;
},
analyzeBatchAsync: async (companies: string[], maxWorkers = 3): Promise<JobStatus> => {
const response = await api.post<JobStatus>('/analyze/batch/async', {
companies,
max_workers: maxWorkers,
});
return response.data;
},
getJobStatus: async (jobId: string): Promise<JobStatus> => {
const response = await api.get<JobStatus>(`/jobs/${jobId}`);
return response.data;
},
listJobs: async (status?: string, limit = 10): Promise<JobStatus[]> => {
const params = new URLSearchParams();
if (status) params.append('status', status);
params.append('limit', limit.toString());
const response = await api.get<JobStatus[]>(`/jobs?${params}`);
return response.data;
},
};
// Analytics API
export const analyticsApi = {
getAnalytics: async (days = 30): Promise<Analytics> => {
const response = await api.get<Analytics>(`/analytics?days=${days}`);
return response.data;
},
};
// Admin API
export const adminApi = {
listUsers: async (limit = 100, offset = 0): Promise<User[]> => {
const response = await api.get<User[]>(`/admin/users?limit=${limit}&offset=${offset}`);
return response.data;
},
updateUserRole: async (userId: number, role: 'admin' | 'user'): Promise<User> => {
const response = await api.patch<User>(`/admin/users/${userId}/role`, { role });
return response.data;
},
deleteUser: async (userId: number): Promise<void> => {
await api.delete(`/admin/users/${userId}`);
},
};
export default api;
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import { Outlet, NavLink, useNavigate } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
import { Search, Layers, BarChart3, Info, Users, LogOut } from 'lucide-react';
export function Layout() {
const { user, isAdmin, logout } = useAuth();
const navigate = useNavigate();
const handleLogout = () => {
logout();
navigate('/login');
};
const navItems = [
{ to: '/analysis', icon: Search, label: 'Analysis' },
{ to: '/batch', icon: Layers, label: 'Batch' },
{ to: '/analytics', icon: BarChart3, label: 'Analytics' },
{ to: '/about', icon: Info, label: 'About' },
];
if (isAdmin) {
navItems.push({ to: '/admin/users', icon: Users, label: 'Users' });
}
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950">
{/* Header */}
<header className="bg-bg-card/80 backdrop-blur-lg border-b border-primary/20">
<div className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div className="flex items-center justify-between h-16">
{/* Brand */}
<div className="flex items-center gap-3">
<span className="text-2xl"></span>
<div>
<h1 className="text-xl font-bold bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent">
SPARC
</h1>
<span className="text-xs text-text-secondary uppercase tracking-wider">
Semiconductor Patent Analytics
</span>
</div>
</div>
{/* Navigation */}
<nav className="hidden md:flex items-center gap-1 bg-bg-card/60 rounded-xl p-1 border border-primary/15">
{navItems.map(({ to, icon: Icon, label }) => (
<NavLink
key={to}
to={to}
className={({ isActive }) =>
`flex items-center gap-2 px-4 py-2 rounded-lg text-sm font-medium transition-all ${
isActive
? 'bg-gradient-to-r from-primary to-primary-dark text-white'
: 'text-text-secondary hover:text-text-primary hover:bg-bg-card-hover'
}`
}
>
<Icon size={16} />
{label}
</NavLink>
))}
</nav>
{/* User menu */}
<div className="flex items-center gap-4">
<div className="text-right hidden sm:block">
<div className="text-sm font-medium text-text-primary">{user?.email}</div>
<div className="text-xs text-text-secondary capitalize">{user?.role}</div>
</div>
<button
onClick={handleLogout}
className="flex items-center gap-2 px-3 py-2 rounded-lg text-text-secondary hover:text-error hover:bg-error/10 transition-all"
>
<LogOut size={18} />
<span className="hidden sm:inline">Logout</span>
</button>
</div>
</div>
</div>
</header>
{/* Mobile Navigation */}
<nav className="md:hidden fixed bottom-0 left-0 right-0 bg-bg-card/95 backdrop-blur-lg border-t border-primary/20 z-50">
<div className="flex justify-around py-2">
{navItems.map(({ to, icon: Icon, label }) => (
<NavLink
key={to}
to={to}
className={({ isActive }) =>
`flex flex-col items-center gap-1 px-3 py-2 rounded-lg text-xs font-medium transition-all ${
isActive ? 'text-primary' : 'text-text-secondary'
}`
}
>
<Icon size={20} />
{label}
</NavLink>
))}
</div>
</nav>
{/* Main content */}
<main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8 pb-24 md:pb-8">
<Outlet />
</main>
</div>
);
}
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import { Navigate, useLocation } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
interface ProtectedRouteProps {
children: React.ReactNode;
requireAdmin?: boolean;
}
export function ProtectedRoute({ children, requireAdmin = false }: ProtectedRouteProps) {
const { isAuthenticated, isAdmin, isLoading } = useAuth();
const location = useLocation();
if (isLoading) {
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center">
<div className="animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-primary"></div>
</div>
);
}
if (!isAuthenticated) {
return <Navigate to="/login" state={{ from: location }} replace />;
}
if (requireAdmin && !isAdmin) {
return <Navigate to="/analysis" replace />;
}
return <>{children}</>;
}
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import { createContext, useContext, useState, useEffect, ReactNode } from 'react';
import { authApi, getAccessToken } from '../api/client';
import type { User } from '../types';
interface AuthContextType {
user: User | null;
isLoading: boolean;
isAuthenticated: boolean;
isAdmin: boolean;
login: (email: string, password: string) => Promise<void>;
register: (email: string, password: string) => Promise<void>;
logout: () => void;
refreshUser: () => Promise<void>;
}
const AuthContext = createContext<AuthContextType | undefined>(undefined);
export function AuthProvider({ children }: { children: ReactNode }) {
const [user, setUser] = useState<User | null>(null);
const [isLoading, setIsLoading] = useState(true);
const refreshUser = async () => {
try {
const userData = await authApi.getMe();
setUser(userData);
} catch {
setUser(null);
}
};
useEffect(() => {
const initAuth = async () => {
if (getAccessToken()) {
await refreshUser();
}
setIsLoading(false);
};
initAuth();
}, []);
const login = async (email: string, password: string) => {
await authApi.login(email, password);
await refreshUser();
};
const register = async (email: string, password: string) => {
await authApi.register(email, password);
await authApi.login(email, password);
await refreshUser();
};
const logout = () => {
authApi.logout();
setUser(null);
};
return (
<AuthContext.Provider
value={{
user,
isLoading,
isAuthenticated: !!user,
isAdmin: user?.role === 'admin',
login,
register,
logout,
refreshUser,
}}
>
{children}
</AuthContext.Provider>
);
}
export function useAuth() {
const context = useContext(AuthContext);
if (context === undefined) {
throw new Error('useAuth must be used within an AuthProvider');
}
return context;
}
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@tailwind base;
@tailwind components;
@tailwind utilities;
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
/* Custom scrollbar */
::-webkit-scrollbar {
width: 8px;
height: 8px;
}
::-webkit-scrollbar-track {
background: #1e293b;
}
::-webkit-scrollbar-thumb {
background: #6366f1;
border-radius: 4px;
}
::-webkit-scrollbar-thumb:hover {
background: #4f46e5;
}
/* Selection */
::selection {
background: rgba(99, 102, 241, 0.3);
color: #f8fafc;
}
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import { StrictMode } from 'react';
import { createRoot } from 'react-dom/client';
import App from './App';
import './index.css';
createRoot(document.getElementById('root')!).render(
<StrictMode>
<App />
</StrictMode>
);
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import { useQuery } from '@tanstack/react-query';
import axios from 'axios';
import { Search, FileText, Bot, Zap, Globe, BarChart3, CheckCircle, AlertTriangle, XCircle } from 'lucide-react';
const API_BASE_URL = import.meta.env.VITE_API_URL || '/api';
export function About() {
const { data: health } = useQuery({
queryKey: ['health'],
queryFn: async () => {
const response = await axios.get(`${API_BASE_URL}/health`);
return response.data;
},
refetchInterval: 30000,
});
const features = [
{
icon: Search,
title: 'Patent Retrieval',
description: 'Automated collection via SerpAPI\'s Google Patents',
},
{
icon: FileText,
title: 'Intelligent Parsing',
description: 'Extracts key sections from patent documents',
},
{
icon: Bot,
title: 'AI Analysis',
description: 'Deep analysis powered by Claude 3.5 Sonnet',
},
{
icon: Zap,
title: 'Batch Processing',
description: 'Analyze multiple companies concurrently',
},
{
icon: Globe,
title: 'REST API',
description: 'FastAPI web service for seamless integration',
},
{
icon: BarChart3,
title: 'Analytics',
description: 'Track and visualize historical analysis data',
},
];
const techStack = [
{ label: 'Backend', value: 'Python, FastAPI' },
{ label: 'AI Model', value: 'Claude 3.5 Sonnet' },
{ label: 'Database', value: 'PostgreSQL' },
{ label: 'Frontend', value: 'React, TailwindCSS' },
{ label: 'Data Source', value: 'SerpAPI Patents' },
];
return (
<div className="space-y-8">
{/* Header */}
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
About SPARC
</h2>
</div>
<div className="grid grid-cols-1 lg:grid-cols-3 gap-8">
{/* Main Content */}
<div className="lg:col-span-2 space-y-6">
{/* Description */}
<p className="text-text-secondary leading-relaxed">
<strong className="text-text-primary">SPARC</strong> (Semiconductor Patent & Analytics Report Core)
is an AI-powered patent analysis platform that evaluates company performance by analyzing their
patent portfolios with cutting-edge language models.
</p>
{/* Features */}
<div>
<h3 className="text-lg font-semibold text-text-primary mb-4">Key Features</h3>
<div className="space-y-3">
{features.map(({ icon: Icon, title, description }) => (
<div
key={title}
className="flex items-start gap-4 py-3 border-b border-primary/10 last:border-0"
>
<div className="flex-shrink-0">
<Icon className="text-primary" size={20} />
</div>
<div>
<div className="font-medium text-text-primary">{title}</div>
<div className="text-sm text-text-secondary">{description}</div>
</div>
</div>
))}
</div>
</div>
</div>
{/* Sidebar */}
<div className="space-y-6">
{/* Tech Stack */}
<div className="bg-gradient-to-br from-primary/10 to-secondary/5 border border-primary/20 rounded-xl p-5">
<h3 className="font-semibold text-text-primary mb-4">Technology Stack</h3>
<div className="space-y-3">
{techStack.map(({ label, value }) => (
<div key={label}>
<div className="text-primary text-sm">{label}</div>
<div className="text-text-secondary text-sm">{value}</div>
</div>
))}
</div>
</div>
{/* API Endpoints */}
<div className="bg-bg-card/60 border border-primary/15 rounded-xl p-5">
<h3 className="font-semibold text-text-primary mb-4">API Endpoints</h3>
<div className="space-y-2">
<code className="block bg-bg-dark px-3 py-2 rounded text-sm text-text-secondary">
http://localhost:8000/docs
</code>
<code className="block bg-bg-dark px-3 py-2 rounded text-sm text-text-secondary">
http://localhost:8000/health
</code>
</div>
</div>
</div>
</div>
{/* System Status */}
<div>
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
System Status
</h3>
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
<StatusCard
label="API"
status={health ? 'online' : 'offline'}
/>
<StatusCard
label="Database"
status="configured"
/>
<StatusCard
label="Dashboard"
status="online"
/>
</div>
</div>
</div>
);
}
function StatusCard({ label, status }: { label: string; status: 'online' | 'offline' | 'configured' }) {
const statusConfig = {
online: { icon: CheckCircle, color: 'text-success', bg: 'bg-success' },
offline: { icon: XCircle, color: 'text-error', bg: 'bg-error' },
configured: { icon: AlertTriangle, color: 'text-warning', bg: 'bg-warning' },
};
const { icon: Icon, color, bg } = statusConfig[status];
return (
<div className="bg-gradient-to-br from-primary/10 to-secondary/10 border border-primary/20 rounded-xl p-5 text-center">
<div className={`inline-flex items-center justify-center w-8 h-8 rounded-full ${bg}/20 mb-2`}>
<Icon className={color} size={20} />
</div>
<div className="text-sm text-text-secondary uppercase tracking-wide">{label}</div>
<div className={`font-semibold ${color} capitalize`}>{status}</div>
</div>
);
}
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import { useState } from 'react';
import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
import { adminApi } from '../api/client';
import { useAuth } from '../context/AuthContext';
import { Users, Shield, User, Trash2, AlertCircle } from 'lucide-react';
import type { User as UserType } from '../types';
export function AdminUsers() {
const { user: currentUser } = useAuth();
const queryClient = useQueryClient();
const [deleteConfirm, setDeleteConfirm] = useState<number | null>(null);
const { data: users, isLoading, isError } = useQuery({
queryKey: ['admin-users'],
queryFn: () => adminApi.listUsers(),
});
const updateRoleMutation = useMutation({
mutationFn: ({ userId, role }: { userId: number; role: 'admin' | 'user' }) =>
adminApi.updateUserRole(userId, role),
onSuccess: () => {
queryClient.invalidateQueries({ queryKey: ['admin-users'] });
},
});
const deleteMutation = useMutation({
mutationFn: (userId: number) => adminApi.deleteUser(userId),
onSuccess: () => {
queryClient.invalidateQueries({ queryKey: ['admin-users'] });
setDeleteConfirm(null);
},
});
const handleRoleChange = (user: UserType) => {
const newRole = user.role === 'admin' ? 'user' : 'admin';
updateRoleMutation.mutate({ userId: user.id, role: newRole });
};
const handleDelete = (userId: number) => {
deleteMutation.mutate(userId);
};
if (isLoading) {
return (
<div className="flex items-center justify-center min-h-[400px]">
<div className="animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-primary"></div>
</div>
);
}
if (isError) {
return (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Failed to load users.</span>
</div>
);
}
return (
<div className="space-y-6">
{/* Header */}
<div className="flex items-center justify-between">
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
User Management
</h2>
<p className="text-text-secondary">Manage user accounts and permissions.</p>
</div>
<div className="flex items-center gap-2 bg-primary/10 border border-primary/20 rounded-xl px-4 py-2">
<Users size={18} className="text-primary" />
<span className="text-text-primary font-semibold">{users?.length || 0} Users</span>
</div>
</div>
{/* Users Table */}
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl overflow-hidden">
<div className="overflow-x-auto">
<table className="w-full">
<thead>
<tr className="border-b border-primary/10">
<th className="text-left px-6 py-4 text-sm font-semibold text-text-secondary uppercase tracking-wider">
User
</th>
<th className="text-left px-6 py-4 text-sm font-semibold text-text-secondary uppercase tracking-wider">
Role
</th>
<th className="text-left px-6 py-4 text-sm font-semibold text-text-secondary uppercase tracking-wider">
Created
</th>
<th className="text-right px-6 py-4 text-sm font-semibold text-text-secondary uppercase tracking-wider">
Actions
</th>
</tr>
</thead>
<tbody className="divide-y divide-primary/10">
{users?.map((user) => (
<tr key={user.id} className="hover:bg-bg-card-hover/50 transition-colors">
<td className="px-6 py-4">
<div className="flex items-center gap-3">
<div className="w-10 h-10 rounded-full bg-gradient-to-br from-primary/20 to-secondary/20 flex items-center justify-center">
{user.role === 'admin' ? (
<Shield className="text-primary" size={18} />
) : (
<User className="text-secondary" size={18} />
)}
</div>
<div>
<div className="font-medium text-text-primary">{user.email}</div>
{user.id === currentUser?.id && (
<span className="text-xs text-primary">(You)</span>
)}
</div>
</div>
</td>
<td className="px-6 py-4">
<span
className={`inline-flex items-center gap-1 px-3 py-1 rounded-full text-xs font-semibold uppercase ${
user.role === 'admin'
? 'bg-primary/20 text-primary border border-primary/30'
: 'bg-secondary/20 text-secondary border border-secondary/30'
}`}
>
{user.role === 'admin' ? <Shield size={12} /> : <User size={12} />}
{user.role}
</span>
</td>
<td className="px-6 py-4 text-text-secondary">
{new Date(user.created_at).toLocaleDateString()}
</td>
<td className="px-6 py-4">
<div className="flex items-center justify-end gap-2">
{user.id !== currentUser?.id && (
<>
<button
onClick={() => handleRoleChange(user)}
disabled={updateRoleMutation.isPending}
className={`px-3 py-1.5 rounded-lg text-sm font-medium transition-all ${
user.role === 'admin'
? 'bg-secondary/10 text-secondary hover:bg-secondary/20 border border-secondary/30'
: 'bg-primary/10 text-primary hover:bg-primary/20 border border-primary/30'
} disabled:opacity-50`}
>
{user.role === 'admin' ? 'Demote' : 'Promote'}
</button>
{deleteConfirm === user.id ? (
<div className="flex items-center gap-1">
<button
onClick={() => handleDelete(user.id)}
disabled={deleteMutation.isPending}
className="px-3 py-1.5 rounded-lg text-sm font-medium bg-error text-white hover:bg-error/80 transition-all disabled:opacity-50"
>
Confirm
</button>
<button
onClick={() => setDeleteConfirm(null)}
className="px-3 py-1.5 rounded-lg text-sm font-medium bg-bg-card-hover text-text-secondary hover:text-text-primary transition-all"
>
Cancel
</button>
</div>
) : (
<button
onClick={() => setDeleteConfirm(user.id)}
className="p-1.5 rounded-lg text-error/70 hover:text-error hover:bg-error/10 transition-all"
>
<Trash2 size={18} />
</button>
)}
</>
)}
</div>
</td>
</tr>
))}
</tbody>
</table>
</div>
</div>
</div>
);
}
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import { useState } from 'react';
import { useMutation } from '@tanstack/react-query';
import { analysisApi } from '../api/client';
import { Search, CheckCircle, AlertCircle, Clock, FileText } from 'lucide-react';
import type { CompanyAnalysis } from '../types';
export function Analysis() {
const [companyName, setCompanyName] = useState('');
const [result, setResult] = useState<CompanyAnalysis | null>(null);
const mutation = useMutation({
mutationFn: (name: string) => analysisApi.analyzeCompany(name),
onSuccess: (data) => setResult(data),
});
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
if (companyName.trim()) {
mutation.mutate(companyName.trim());
}
};
return (
<div className="space-y-6">
{/* Header */}
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Single Company Analysis
</h2>
<p className="text-text-secondary">
Analyze a company's patent portfolio using AI-powered insights.
</p>
</div>
{/* Search Form */}
<form onSubmit={handleSubmit} className="flex gap-4">
<div className="flex-1 relative">
<Search className="absolute left-4 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
type="text"
value={companyName}
onChange={(e) => setCompanyName(e.target.value)}
placeholder="Enter company name (e.g., nvidia, intel, amd)"
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl pl-12 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
/>
</div>
<button
type="submit"
disabled={mutation.isPending || !companyName.trim()}
className="bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-6 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center gap-2"
>
{mutation.isPending ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<Search size={18} />
Analyze
</>
)}
</button>
</form>
{/* Error */}
{mutation.isError && (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Analysis failed. Please try again.</span>
</div>
)}
{/* Results */}
{result && (
<div className="space-y-6">
{/* Success/Failure Status */}
{result.success ? (
<div className="flex items-center gap-2 bg-success/10 border border-success/20 text-success rounded-xl px-4 py-3">
<CheckCircle size={18} />
<span>Analysis complete for {result.company_name.toUpperCase()}</span>
</div>
) : (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Analysis failed: {result.error}</span>
</div>
)}
{/* Metrics */}
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
<MetricCard
icon={FileText}
label="Patents Found"
value={result.patent_count.toString()}
/>
<MetricCard
icon={CheckCircle}
label="Analysis Status"
value={result.success ? 'Complete' : 'Failed'}
/>
<MetricCard
icon={Clock}
label="Timestamp"
value={new Date(result.timestamp).toLocaleTimeString()}
/>
</div>
{/* Analysis Content */}
{result.success && result.analysis && (
<div className="bg-bg-card/60 backdrop-blur-lg border border-primary/15 rounded-2xl p-6">
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
AI Analysis Results
</h3>
<div className="prose prose-invert max-w-none">
<div className="text-text-primary whitespace-pre-wrap leading-relaxed">
{result.analysis}
</div>
</div>
</div>
)}
</div>
)}
</div>
);
}
function MetricCard({ icon: Icon, label, value }: { icon: typeof FileText; label: string; value: string }) {
return (
<div className="bg-gradient-to-br from-primary/10 to-secondary/10 border border-primary/20 rounded-xl p-5 text-center">
<Icon className="mx-auto mb-2 text-primary" size={24} />
<div className="text-2xl font-bold bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent">
{value}
</div>
<div className="text-sm text-text-secondary uppercase tracking-wide mt-1">{label}</div>
</div>
);
}
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import { useState } from 'react';
import { useQuery } from '@tanstack/react-query';
import { analyticsApi } from '../api/client';
import { AlertCircle, Database } from 'lucide-react';
import { PieChart, Pie, Cell, BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer, Legend } from 'recharts';
const COLORS = ['#6366f1', '#0ea5e9', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6', '#ec4899', '#14b8a6'];
export function AnalyticsPage() {
const [days, setDays] = useState(30);
const { data, isLoading, isError } = useQuery({
queryKey: ['analytics', days],
queryFn: () => analyticsApi.getAnalytics(days),
});
if (isLoading) {
return (
<div className="flex items-center justify-center min-h-[400px]">
<div className="animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-primary"></div>
</div>
);
}
if (isError) {
return (
<div className="space-y-6">
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Analytics Dashboard
</h2>
</div>
<div className="bg-gradient-to-br from-primary/10 to-secondary/5 border border-primary/20 rounded-xl p-6">
<div className="flex items-center gap-3 text-warning mb-2">
<Database size={24} />
<span className="font-semibold">Database Not Connected</span>
</div>
<p className="text-text-secondary">
Set <code className="bg-bg-card px-2 py-1 rounded">USE_DATABASE=true</code> in your .env file to enable analytics tracking.
</p>
</div>
<div className="flex items-center gap-2 bg-secondary/10 border border-secondary/20 text-secondary rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Analytics features require storing analysis results in PostgreSQL for historical tracking.</span>
</div>
</div>
);
}
if (!data || (data.total_messages === 0 && data.by_company.length === 0)) {
return (
<div className="space-y-6">
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Analytics Dashboard
</h2>
<p className="text-text-secondary">Track historical analysis data and view insights.</p>
</div>
<div className="flex items-center gap-2 bg-secondary/10 border border-secondary/20 text-secondary rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>No analytics data available yet. Run some analyses first!</span>
</div>
</div>
);
}
const companyData = data.by_company.map((c) => ({
name: (c.company_name || 'Unknown').toUpperCase(),
value: c.count,
}));
const typeData = data.by_type.map((t) => ({
name: t.analysis_type || 'Unknown',
count: t.count,
}));
return (
<div className="space-y-6">
{/* Header */}
<div className="flex flex-wrap items-center justify-between gap-4">
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Analytics Dashboard
</h2>
<p className="text-text-secondary">Track historical analysis data and view insights.</p>
</div>
{/* Time Range Selector */}
<select
value={days}
onChange={(e) => setDays(Number(e.target.value))}
className="bg-bg-card/80 border border-primary/30 rounded-xl px-4 py-2 text-text-primary focus:outline-none focus:border-primary"
>
<option value={7}>Last 7 days</option>
<option value={14}>Last 14 days</option>
<option value={30}>Last 30 days</option>
<option value={90}>Last 90 days</option>
</select>
</div>
{/* Summary Metrics */}
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
<MetricCard label="Total Analyses" value={data.total_messages} />
<MetricCard label="Companies Analyzed" value={data.by_company.length} />
<MetricCard label="Analysis Types" value={data.by_type.length} />
</div>
{/* Charts */}
<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
{/* Pie Chart - Distribution by Company */}
{companyData.length > 0 && (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<h3 className="text-lg font-semibold text-text-primary mb-4">Distribution by Company</h3>
<ResponsiveContainer width="100%" height={300}>
<PieChart>
<Pie
data={companyData}
cx="50%"
cy="50%"
innerRadius={60}
outerRadius={100}
paddingAngle={2}
dataKey="value"
label={({ name, percent }) => `${name} ${(percent * 100).toFixed(0)}%`}
labelLine={false}
>
{companyData.map((_, index) => (
<Cell key={`cell-${index}`} fill={COLORS[index % COLORS.length]} />
))}
</Pie>
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
/>
<Legend />
</PieChart>
</ResponsiveContainer>
</div>
)}
{/* Bar Chart - Analysis Types */}
{typeData.length > 0 && (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<h3 className="text-lg font-semibold text-text-primary mb-4">Analysis Types</h3>
<ResponsiveContainer width="100%" height={300}>
<BarChart data={typeData}>
<XAxis dataKey="name" stroke="#94a3b8" fontSize={12} />
<YAxis stroke="#94a3b8" fontSize={12} />
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
labelStyle={{ color: '#f8fafc' }}
/>
<Bar dataKey="count" fill="#6366f1" radius={[4, 4, 0, 0]} />
</BarChart>
</ResponsiveContainer>
</div>
)}
</div>
</div>
);
}
function MetricCard({ label, value }: { label: string; value: number }) {
return (
<div className="bg-gradient-to-br from-primary/10 to-secondary/10 border border-primary/20 rounded-xl p-5 text-center">
<div className="text-3xl font-bold bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent">
{value}
</div>
<div className="text-sm text-text-secondary uppercase tracking-wide mt-1">{label}</div>
</div>
);
}
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import { useState } from 'react';
import { useMutation } from '@tanstack/react-query';
import { analysisApi } from '../api/client';
import { Rocket, CheckCircle, AlertCircle, ChevronDown, ChevronUp } from 'lucide-react';
import { BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer, Cell } from 'recharts';
import type { BatchAnalysisResult } from '../types';
export function Batch() {
const [companiesInput, setCompaniesInput] = useState('');
const [maxWorkers, setMaxWorkers] = useState(3);
const [result, setResult] = useState<BatchAnalysisResult | null>(null);
const [expandedItems, setExpandedItems] = useState<Set<string>>(new Set());
const mutation = useMutation({
mutationFn: ({ companies, workers }: { companies: string[]; workers: number }) =>
analysisApi.analyzeBatch(companies, workers),
onSuccess: (data) => setResult(data),
});
const handleSubmit = (e: React.FormEvent) => {
e.preventDefault();
const companies = companiesInput
.split(/[,\n]/)
.map((c) => c.trim())
.filter((c) => c.length > 0);
if (companies.length > 0) {
mutation.mutate({ companies, workers: maxWorkers });
}
};
const toggleExpand = (company: string) => {
const newExpanded = new Set(expandedItems);
if (newExpanded.has(company)) {
newExpanded.delete(company);
} else {
newExpanded.add(company);
}
setExpandedItems(newExpanded);
};
const chartData = result?.results.map((r) => ({
name: r.company_name.toUpperCase(),
patents: r.patent_count,
success: r.success,
}));
return (
<div className="space-y-6">
{/* Header */}
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Batch Company Analysis
</h2>
<p className="text-text-secondary">
Analyze multiple companies simultaneously for comparative insights.
</p>
</div>
{/* Input Form */}
<form onSubmit={handleSubmit} className="grid grid-cols-1 md:grid-cols-3 gap-4">
<div className="md:col-span-2">
<textarea
value={companiesInput}
onChange={(e) => setCompaniesInput(e.target.value)}
placeholder="Enter company names (one per line or comma-separated):&#10;nvidia&#10;amd&#10;intel&#10;qualcomm"
rows={6}
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl px-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all resize-none"
/>
</div>
<div className="space-y-4">
<div>
<label className="block text-sm font-medium text-text-secondary mb-2">
Concurrent Workers
</label>
<input
type="range"
min={1}
max={5}
value={maxWorkers}
onChange={(e) => setMaxWorkers(Number(e.target.value))}
className="w-full accent-primary"
/>
<div className="text-center text-text-primary font-semibold">{maxWorkers}</div>
</div>
<button
type="submit"
disabled={mutation.isPending || !companiesInput.trim()}
className="w-full bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-6 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center justify-center gap-2"
>
{mutation.isPending ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<Rocket size={18} />
Run Batch Analysis
</>
)}
</button>
</div>
</form>
{/* Progress */}
{mutation.isPending && (
<div className="bg-bg-card/60 border border-primary/15 rounded-xl p-4">
<div className="flex items-center gap-2 text-secondary">
<div className="animate-spin rounded-full h-4 w-4 border-t-2 border-b-2 border-secondary"></div>
<span>Analyzing companies...</span>
</div>
</div>
)}
{/* Error */}
{mutation.isError && (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Batch analysis failed. Please try again.</span>
</div>
)}
{/* Results */}
{result && (
<div className="space-y-6">
{/* Summary Metrics */}
<div>
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
Results Summary
</h3>
<div className="grid grid-cols-2 md:grid-cols-4 gap-4">
<SummaryCard label="Total Companies" value={result.total_companies} />
<SummaryCard label="Successful" value={result.successful} color="success" />
<SummaryCard label="Failed" value={result.failed} color="error" />
<SummaryCard
label="Success Rate"
value={`${Math.round((result.successful / result.total_companies) * 100)}%`}
/>
</div>
</div>
{/* Chart */}
{chartData && chartData.length > 0 && (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<ResponsiveContainer width="100%" height={300}>
<BarChart data={chartData}>
<XAxis dataKey="name" stroke="#94a3b8" fontSize={12} />
<YAxis stroke="#94a3b8" fontSize={12} />
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
labelStyle={{ color: '#f8fafc' }}
/>
<Bar dataKey="patents" radius={[4, 4, 0, 0]}>
{chartData.map((entry, index) => (
<Cell
key={`cell-${index}`}
fill={entry.success ? '#10b981' : '#ef4444'}
/>
))}
</Bar>
</BarChart>
</ResponsiveContainer>
</div>
)}
{/* Detailed Results */}
<div>
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
Detailed Results
</h3>
<div className="space-y-3">
{result.results.map((r) => (
<div
key={r.company_name}
className="bg-bg-card/60 border border-primary/15 rounded-xl overflow-hidden"
>
<button
onClick={() => toggleExpand(r.company_name)}
className="w-full flex items-center justify-between p-4 hover:bg-bg-card-hover transition-colors"
>
<div className="flex items-center gap-3">
{r.success ? (
<CheckCircle className="text-success" size={20} />
) : (
<AlertCircle className="text-error" size={20} />
)}
<span className="font-semibold text-text-primary">
{r.company_name.toUpperCase()}
</span>
<span className="text-text-secondary">
{r.patent_count} patents
</span>
</div>
{expandedItems.has(r.company_name) ? (
<ChevronUp className="text-text-secondary" size={20} />
) : (
<ChevronDown className="text-text-secondary" size={20} />
)}
</button>
{expandedItems.has(r.company_name) && (
<div className="border-t border-primary/10 p-4 bg-bg-dark/40">
{r.success ? (
<div className="text-text-primary whitespace-pre-wrap leading-relaxed">
{r.analysis}
</div>
) : (
<div className="text-error">{r.error}</div>
)}
</div>
)}
</div>
))}
</div>
</div>
</div>
)}
</div>
);
}
function SummaryCard({
label,
value,
color,
}: {
label: string;
value: number | string;
color?: 'success' | 'error';
}) {
const colorClass = color === 'success' ? 'text-success' : color === 'error' ? 'text-error' : '';
return (
<div className="bg-gradient-to-br from-primary/10 to-secondary/10 border border-primary/20 rounded-xl p-4 text-center">
<div
className={`text-2xl font-bold ${
colorClass || 'bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent'
}`}
>
{value}
</div>
<div className="text-sm text-text-secondary uppercase tracking-wide mt-1">{label}</div>
</div>
);
}
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import { useState } from 'react';
import { Link, useNavigate, useLocation } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
import { LogIn, Mail, Lock, AlertCircle } from 'lucide-react';
export function Login() {
const [email, setEmail] = useState('');
const [password, setPassword] = useState('');
const [error, setError] = useState('');
const [isLoading, setIsLoading] = useState(false);
const { login } = useAuth();
const navigate = useNavigate();
const location = useLocation();
const from = (location.state as { from?: { pathname: string } })?.from?.pathname || '/analysis';
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
setError('');
setIsLoading(true);
try {
await login(email, password);
navigate(from, { replace: true });
} catch (err) {
setError(err instanceof Error ? err.message : 'Invalid email or password');
} finally {
setIsLoading(false);
}
};
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center px-4">
<div className="w-full max-w-md">
{/* Brand */}
<div className="text-center mb-8">
<div className="flex items-center justify-center gap-3 mb-4">
<span className="text-4xl"></span>
<h1 className="text-3xl font-bold bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent">
SPARC
</h1>
</div>
<p className="text-text-secondary">Semiconductor Patent Analytics Dashboard</p>
</div>
{/* Login Card */}
<div className="bg-bg-card/60 backdrop-blur-lg border border-primary/15 rounded-2xl p-8">
<h2 className="text-xl font-semibold text-text-primary mb-6">Sign in to your account</h2>
{error && (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-lg px-4 py-3 mb-6">
<AlertCircle size={18} />
<span className="text-sm">{error}</span>
</div>
)}
<form onSubmit={handleSubmit} className="space-y-5">
<div>
<label htmlFor="email" className="block text-sm font-medium text-text-secondary mb-2">
Email
</label>
<div className="relative">
<Mail className="absolute left-3 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
id="email"
type="email"
value={email}
onChange={(e) => setEmail(e.target.value)}
required
className="w-full bg-bg-dark/80 border border-primary/30 rounded-xl pl-10 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
placeholder="you@example.com"
/>
</div>
</div>
<div>
<label htmlFor="password" className="block text-sm font-medium text-text-secondary mb-2">
Password
</label>
<div className="relative">
<Lock className="absolute left-3 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
id="password"
type="password"
value={password}
onChange={(e) => setPassword(e.target.value)}
required
className="w-full bg-bg-dark/80 border border-primary/30 rounded-xl pl-10 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
placeholder="Enter your password"
/>
</div>
</div>
<button
type="submit"
disabled={isLoading}
className="w-full bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-4 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center justify-center gap-2"
>
{isLoading ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<LogIn size={18} />
Sign In
</>
)}
</button>
</form>
<div className="mt-6 text-center">
<span className="text-text-secondary text-sm">Don't have an account? </span>
<Link to="/register" className="text-primary hover:text-primary-dark font-medium text-sm">
Sign up
</Link>
</div>
</div>
</div>
</div>
);
}
+153
View File
@@ -0,0 +1,153 @@
import { useState } from 'react';
import { Link, useNavigate } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
import { UserPlus, Mail, Lock, AlertCircle } from 'lucide-react';
export function Register() {
const [email, setEmail] = useState('');
const [password, setPassword] = useState('');
const [confirmPassword, setConfirmPassword] = useState('');
const [error, setError] = useState('');
const [isLoading, setIsLoading] = useState(false);
const { register } = useAuth();
const navigate = useNavigate();
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
setError('');
if (password !== confirmPassword) {
setError('Passwords do not match');
return;
}
if (password.length < 8) {
setError('Password must be at least 8 characters');
return;
}
setIsLoading(true);
try {
await register(email, password);
navigate('/analysis', { replace: true });
} catch (err) {
setError(err instanceof Error ? err.message : 'Registration failed');
} finally {
setIsLoading(false);
}
};
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center px-4">
<div className="w-full max-w-md">
{/* Brand */}
<div className="text-center mb-8">
<div className="flex items-center justify-center gap-3 mb-4">
<span className="text-4xl"></span>
<h1 className="text-3xl font-bold bg-gradient-to-r from-primary to-secondary bg-clip-text text-transparent">
SPARC
</h1>
</div>
<p className="text-text-secondary">Semiconductor Patent Analytics Dashboard</p>
</div>
{/* Register Card */}
<div className="bg-bg-card/60 backdrop-blur-lg border border-primary/15 rounded-2xl p-8">
<h2 className="text-xl font-semibold text-text-primary mb-6">Create your account</h2>
{error && (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-lg px-4 py-3 mb-6">
<AlertCircle size={18} />
<span className="text-sm">{error}</span>
</div>
)}
<form onSubmit={handleSubmit} className="space-y-5">
<div>
<label htmlFor="email" className="block text-sm font-medium text-text-secondary mb-2">
Email
</label>
<div className="relative">
<Mail className="absolute left-3 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
id="email"
type="email"
value={email}
onChange={(e) => setEmail(e.target.value)}
required
className="w-full bg-bg-dark/80 border border-primary/30 rounded-xl pl-10 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
placeholder="you@example.com"
/>
</div>
</div>
<div>
<label htmlFor="password" className="block text-sm font-medium text-text-secondary mb-2">
Password
</label>
<div className="relative">
<Lock className="absolute left-3 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
id="password"
type="password"
value={password}
onChange={(e) => setPassword(e.target.value)}
required
minLength={8}
className="w-full bg-bg-dark/80 border border-primary/30 rounded-xl pl-10 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
placeholder="At least 8 characters"
/>
</div>
</div>
<div>
<label htmlFor="confirmPassword" className="block text-sm font-medium text-text-secondary mb-2">
Confirm Password
</label>
<div className="relative">
<Lock className="absolute left-3 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
id="confirmPassword"
type="password"
value={confirmPassword}
onChange={(e) => setConfirmPassword(e.target.value)}
required
className="w-full bg-bg-dark/80 border border-primary/30 rounded-xl pl-10 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
placeholder="Confirm your password"
/>
</div>
</div>
<button
type="submit"
disabled={isLoading}
className="w-full bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-4 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center justify-center gap-2"
>
{isLoading ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<UserPlus size={18} />
Create Account
</>
)}
</button>
</form>
<div className="mt-6 text-center">
<span className="text-text-secondary text-sm">Already have an account? </span>
<Link to="/login" className="text-primary hover:text-primary-dark font-medium text-sm">
Sign in
</Link>
</div>
</div>
<p className="mt-6 text-center text-xs text-text-secondary">
The first registered user will automatically become an admin.
</p>
</div>
</div>
);
}
+46
View File
@@ -0,0 +1,46 @@
export interface User {
id: number;
email: string;
role: 'admin' | 'user';
created_at: string;
}
export interface TokenResponse {
access_token: string;
refresh_token: string;
token_type: string;
}
export interface CompanyAnalysis {
company_name: string;
analysis: string;
patent_count: number;
success: boolean;
error: string | null;
timestamp: string;
}
export interface BatchAnalysisResult {
results: CompanyAnalysis[];
total_companies: number;
successful: number;
failed: number;
timestamp: string;
}
export interface JobStatus {
job_id: string;
status: 'pending' | 'running' | 'completed' | 'failed';
progress: number;
total_companies: number;
completed_companies: number;
result: BatchAnalysisResult | null;
error: string | null;
}
export interface Analytics {
total_messages: number;
by_company: Array<{ company_name: string; count: number }>;
by_type: Array<{ analysis_type: string; count: number }>;
period_days: number;
}
+9
View File
@@ -0,0 +1,9 @@
/// <reference types="vite/client" />
interface ImportMetaEnv {
readonly VITE_API_URL: string;
}
interface ImportMeta {
readonly env: ImportMetaEnv;
}
+32
View File
@@ -0,0 +1,32 @@
/** @type {import('tailwindcss').Config} */
export default {
content: [
"./index.html",
"./src/**/*.{js,ts,jsx,tsx}",
],
theme: {
extend: {
colors: {
primary: {
DEFAULT: '#6366f1',
dark: '#4f46e5',
},
secondary: '#0ea5e9',
success: '#10b981',
warning: '#f59e0b',
error: '#ef4444',
bg: {
dark: '#0f172a',
card: '#1e293b',
'card-hover': '#334155',
},
text: {
primary: '#f8fafc',
secondary: '#94a3b8',
},
border: '#334155',
},
},
},
plugins: [],
}
+24
View File
@@ -0,0 +1,24 @@
{
"compilerOptions": {
"target": "ES2020",
"useDefineForClassFields": true,
"lib": ["ES2020", "DOM", "DOM.Iterable"],
"module": "ESNext",
"skipLibCheck": true,
"moduleResolution": "bundler",
"allowImportingTsExtensions": true,
"isolatedModules": true,
"moduleDetection": "force",
"noEmit": true,
"jsx": "react-jsx",
"strict": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"noFallthroughCasesInSwitch": true,
"baseUrl": ".",
"paths": {
"@/*": ["src/*"]
}
},
"include": ["src"]
}
+16
View File
@@ -0,0 +1,16 @@
import { defineConfig } from 'vite'
import react from '@vitejs/plugin-react'
export default defineConfig({
plugins: [react()],
server: {
port: 3000,
proxy: {
'/api': {
target: 'http://localhost:8000',
changeOrigin: true,
rewrite: (path) => path.replace(/^\/api/, ''),
},
},
},
})
+3 -2
View File
@@ -8,8 +8,9 @@ openai
psycopg2-binary
fastapi
uvicorn[standard]
pydantic[email]
httpx
streamlit
plotly
numpy
pandas
bcrypt
PyJWT
+33
View File
@@ -8,6 +8,8 @@ Usage:
python scripts/init_database.py
"""
import secrets
import string
import sys
import os
@@ -17,6 +19,14 @@ sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from SPARC import config
from SPARC.database import DatabaseClient
DEFAULT_ADMIN_EMAIL = "admin@sparc.dev"
def generate_password(length: int = 16) -> str:
"""Generate a secure random password."""
alphabet = string.ascii_letters + string.digits
return "".join(secrets.choice(alphabet) for _ in range(length))
def main():
"""Initialize the database schema."""
@@ -29,9 +39,32 @@ def main():
print("Database schema initialized successfully!")
print("\nTables created:")
print(" - llm_messages: Stores all LLM prompts and responses")
print(" - users: Stores user accounts")
print("\nIndexes created:")
print(" - idx_messages_timestamp: For time-based queries")
print(" - idx_messages_company: For company-specific queries")
print(" - idx_users_email: For user lookups")
# Create default admin user if not exists
existing_admin = db_client.get_user_by_email(DEFAULT_ADMIN_EMAIL)
if existing_admin:
print(f"\nDefault admin user already exists: {DEFAULT_ADMIN_EMAIL}")
else:
password = generate_password()
admin_user = db_client.create_user(
email=DEFAULT_ADMIN_EMAIL,
password=password,
role="admin",
)
if admin_user:
print("\n" + "=" * 50)
print("DEFAULT ADMIN CREDENTIALS")
print("=" * 50)
print(f"Email: {DEFAULT_ADMIN_EMAIL}")
print(f"Password: {password}")
print("=" * 50)
print("Please save these credentials securely!")
print("=" * 50)
except Exception as e:
print(f"Error initializing database: {e}")
+79 -25
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env python3
"""Test script to verify database mode functionality.
"""Test script to verify database caching functionality.
This script tests the LLMAnalyzer in database mode without requiring
This script tests the LLMAnalyzer with database caching without requiring
actual API keys or patent downloads.
"""
@@ -9,28 +9,29 @@ from SPARC.llm import LLMAnalyzer
from SPARC.database import DatabaseClient
from SPARC import config
def test_database_mode():
"""Test that database mode stores messages correctly."""
print("Testing Database Mode")
def test_database_storage():
"""Test that messages are always stored in database."""
print("Testing Database Storage & Caching")
print("=" * 70)
# Initialize analyzer in database mode
print("\n1. Initializing LLMAnalyzer in database mode...")
analyzer = LLMAnalyzer(use_database=True)
# Initialize analyzer (database is always used)
print("\n1. Initializing LLMAnalyzer...")
analyzer = LLMAnalyzer(use_cache=True)
print(f" - use_database: {analyzer.use_database}")
print(f" - use_cache: {analyzer.use_cache}")
print(f" - db_client: {analyzer.db_client is not None}")
print(f" - client (API): {analyzer.client is not None}")
# Test single patent analysis
print("\n2. Testing single patent analysis (database mode)...")
# Test single patent analysis (without API key, stores placeholder)
print("\n2. Testing single patent analysis (no API key)...")
result = analyzer.analyze_patent_content(
patent_content="Test patent content about semiconductor innovation",
company_name="TestCorp"
)
print(f" Result: {result}")
print(f" Result: {result[:80]}...")
# Test portfolio analysis
print("\n3. Testing portfolio analysis (database mode)...")
print("\n3. Testing portfolio analysis (no API key)...")
test_patents = [
{"patent_id": "US001", "content": "First test patent"},
{"patent_id": "US002", "content": "Second test patent"},
@@ -39,7 +40,7 @@ def test_database_mode():
patents_data=test_patents,
company_name="TestCorp"
)
print(f" Result: {result}")
print(f" Result: {result[:80]}...")
# Verify messages were stored
print("\n4. Verifying messages were stored...")
@@ -48,7 +49,8 @@ def test_database_mode():
print(f" Found {len(messages)} stored messages")
for msg in messages:
print(f" - ID: {msg['id']}, Type: {msg['analysis_type']}, Timestamp: {msg['timestamp']}")
cached_status = "CACHED" if msg.get('is_cached') else "NEW"
print(f" - ID: {msg['id']}, Type: {msg['analysis_type']}, Status: {cached_status}")
# Get analytics
print("\n5. Getting analytics...")
@@ -58,18 +60,68 @@ def test_database_mode():
print(f" By type: {analytics['by_type']}")
print("\n" + "=" * 70)
print("Database mode test completed successfully!")
print("Database storage test completed successfully!")
def test_api_mode():
"""Test that API mode initializes correctly."""
print("\nTesting API Mode")
def test_caching():
"""Test that caching works correctly."""
print("\nTesting Cache Functionality")
print("=" * 70)
print("\n1. Initializing LLMAnalyzer in API mode...")
analyzer = LLMAnalyzer(use_database=False, test_mode=True)
db_client = DatabaseClient(config.database_url)
db_client.initialize_schema()
# Store a fake cached response
print("\n1. Storing a test response in database...")
test_prompt = "Test prompt for caching"
test_response = "This is a cached response from previous API call"
db_client.store_message(
prompt=test_prompt,
response=test_response,
company_name="CacheTest",
analysis_type="test",
model="test-model"
)
# Try to retrieve from cache
print("\n2. Testing cache retrieval...")
cached = db_client.get_cached_response(
prompt=test_prompt,
company_name="CacheTest",
analysis_type="test"
)
if cached:
print(f" Cache hit! Response: {cached['response']}")
else:
print(" Cache miss (unexpected)")
# Test cache miss
print("\n3. Testing cache miss...")
cached = db_client.get_cached_response(
prompt="Different prompt",
company_name="CacheTest",
analysis_type="test"
)
if cached:
print(" Unexpected cache hit")
else:
print(" Cache miss as expected")
print("\n" + "=" * 70)
print("Cache test completed successfully!")
def test_test_mode():
"""Test that test mode works correctly."""
print("\nTesting Test Mode")
print("=" * 70)
print("\n1. Initializing LLMAnalyzer in test mode...")
analyzer = LLMAnalyzer(test_mode=True)
print(f" - use_database: {analyzer.use_database}")
print(f" - test_mode: {analyzer.test_mode}")
print(f" - db_client: {analyzer.db_client is not None}")
print("\n2. Testing single patent analysis (test mode)...")
result = analyzer.analyze_patent_content(
@@ -79,9 +131,11 @@ def test_api_mode():
print(f" Result: {result}")
print("\n" + "=" * 70)
print("API mode test completed successfully!")
print("Test mode test completed successfully!")
if __name__ == "__main__":
test_database_mode()
test_database_storage()
print("\n")
test_api_mode()
test_caching()
print("\n")
test_test_mode()
+66 -10
View File
@@ -1,13 +1,22 @@
"""Tests for LLM analysis functionality."""
import pytest
from unittest.mock import Mock, MagicMock
from unittest.mock import Mock, MagicMock, patch
from SPARC.llm import LLMAnalyzer
class TestLLMAnalyzer:
"""Test LLM analyzer initialization and API interaction."""
@pytest.fixture(autouse=True)
def mock_database(self, mocker):
"""Mock the database client for all tests."""
mock_db_client = Mock()
mock_db_client.get_cached_response.return_value = None # No cache hit by default
mock_db_client.store_message.return_value = 1
mocker.patch("SPARC.llm.DatabaseClient", return_value=mock_db_client)
return mock_db_client
def test_analyzer_initialization_with_api_key(self, mocker):
"""Test that analyzer initializes with provided API key."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
@@ -25,7 +34,7 @@ class TestLLMAnalyzer:
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_config = mocker.patch("SPARC.llm.config")
mock_config.openrouter_api_key = "config-key-456"
mock_config.use_database = False
mock_config.use_cache = True
mock_config.database_url = "postgresql://localhost/test"
analyzer = LLMAnalyzer()
@@ -35,7 +44,7 @@ class TestLLMAnalyzer:
base_url="https://openrouter.ai/api/v1"
)
def test_analyze_patent_content(self, mocker):
def test_analyze_patent_content(self, mocker, mock_database):
"""Test single patent content analysis."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_client = Mock()
@@ -44,9 +53,10 @@ class TestLLMAnalyzer:
# Mock the API response
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="Innovative GPU architecture."))]
mock_response.usage = Mock(prompt_tokens=100, completion_tokens=50, total_tokens=150)
mock_client.chat.completions.create.return_value = mock_response
analyzer = LLMAnalyzer(api_key="test-key")
analyzer = LLMAnalyzer(api_key="test-key", use_cache=False)
result = analyzer.analyze_patent_content(
patent_content="ABSTRACT: GPU with new cache design...",
company_name="NVIDIA",
@@ -61,7 +71,32 @@ class TestLLMAnalyzer:
assert "NVIDIA" in prompt_text
assert "GPU with new cache design" in prompt_text
def test_analyze_patent_portfolio(self, mocker):
# Verify message was stored in database
mock_database.store_message.assert_called_once()
def test_analyze_patent_content_cache_hit(self, mocker, mock_database):
"""Test that cached responses are returned without API call."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_client = Mock()
mock_openai.return_value = mock_client
# Set up cache hit
mock_database.get_cached_response.return_value = {
"id": 1,
"response": "Cached analysis result"
}
analyzer = LLMAnalyzer(api_key="test-key", use_cache=True)
result = analyzer.analyze_patent_content(
patent_content="ABSTRACT: GPU with new cache design...",
company_name="NVIDIA",
)
assert result == "Cached analysis result"
# API should NOT be called on cache hit
mock_client.chat.completions.create.assert_not_called()
def test_analyze_patent_portfolio(self, mocker, mock_database):
"""Test portfolio analysis with multiple patents."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_client = Mock()
@@ -72,9 +107,10 @@ class TestLLMAnalyzer:
mock_response.choices = [
Mock(message=Mock(content="Strong portfolio in AI and graphics."))
]
mock_response.usage = Mock(prompt_tokens=200, completion_tokens=100, total_tokens=300)
mock_client.chat.completions.create.return_value = mock_response
analyzer = LLMAnalyzer(api_key="test-key")
analyzer = LLMAnalyzer(api_key="test-key", use_cache=False)
patents_data = [
{"patent_id": "US123", "content": "AI acceleration patent"},
{"patent_id": "US456", "content": "Graphics rendering patent"},
@@ -95,7 +131,7 @@ class TestLLMAnalyzer:
assert "AI acceleration patent" in prompt_text
assert "Graphics rendering patent" in prompt_text
def test_analyze_patent_portfolio_with_correct_token_limit(self, mocker):
def test_analyze_patent_portfolio_with_correct_token_limit(self, mocker, mock_database):
"""Test that portfolio analysis uses higher token limit."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_client = Mock()
@@ -103,9 +139,10 @@ class TestLLMAnalyzer:
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="Analysis result."))]
mock_response.usage = Mock(prompt_tokens=100, completion_tokens=50, total_tokens=150)
mock_client.chat.completions.create.return_value = mock_response
analyzer = LLMAnalyzer(api_key="test-key")
analyzer = LLMAnalyzer(api_key="test-key", use_cache=False)
patents_data = [{"patent_id": "US123", "content": "Test content"}]
analyzer.analyze_patent_portfolio(patents_data, "TestCo")
@@ -114,7 +151,7 @@ class TestLLMAnalyzer:
# Portfolio analysis should use 2048 tokens
assert call_args[1]["max_tokens"] == 2048
def test_analyze_single_patent_with_correct_token_limit(self, mocker):
def test_analyze_single_patent_with_correct_token_limit(self, mocker, mock_database):
"""Test that single patent analysis uses lower token limit."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
mock_client = Mock()
@@ -122,11 +159,30 @@ class TestLLMAnalyzer:
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content="Analysis result."))]
mock_response.usage = Mock(prompt_tokens=100, completion_tokens=50, total_tokens=150)
mock_client.chat.completions.create.return_value = mock_response
analyzer = LLMAnalyzer(api_key="test-key")
analyzer = LLMAnalyzer(api_key="test-key", use_cache=False)
analyzer.analyze_patent_content("Test content", "TestCo")
call_args = mock_client.chat.completions.create.call_args
# Single patent should use 1024 tokens
assert call_args[1]["max_tokens"] == 1024
def test_database_always_initialized(self, mocker, mock_database):
"""Test that database client is always initialized."""
mock_openai = mocker.patch("SPARC.llm.OpenAI")
analyzer = LLMAnalyzer(api_key="test-key")
assert analyzer.db_client is not None
def test_no_api_key_stores_placeholder(self, mocker, mock_database):
"""Test that without API key, a placeholder is stored."""
mocker.patch("SPARC.llm.config")
analyzer = LLMAnalyzer(use_cache=False)
result = analyzer.analyze_patent_content("Test content", "TestCo")
assert "[NO API]" in result
mock_database.store_message.assert_called_once()