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Browse files- .env +3 -0
- .gitignore +1 -0
- USEME.MD +375 -0
.env
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# Store your API key securely
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SWARMS_API_KEY=sk-f763a9c6f898aa3ec74bf49047736a0201c293eefc36d5a04be8af647b93b711
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.gitignore
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__pycache__/
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USEME.MD
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Here are sample inputs for the key POST endpoints in the FastAPI backend:
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### 1. POST `/api/v1/funds/sip-calculate`
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**Request Body:**
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```json
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{
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"monthly_amount": 10000,
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"annual_return": 12.0,
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"years": 10
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}
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```
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### 2. POST `/api/v1/funds/required-sip`
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**Request Body:**
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```json
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{
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"target_amount": 5000000,
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"years": 15,
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"expected_return": 12.0
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}
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```
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### 3. POST `/api/v1/funds/analyze`
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**Request Body:**
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```json
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{
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"fund_names": ["HDFC Top 100 Fund", "SBI Bluechip Fund"],
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"investment_amount": 100000,
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"start_date": "2023-01-01T00:00:00",
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"end_date": "2024-01-01T00:00:00"
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}
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```
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### 4. POST `/api/v1/portfolio/metrics`
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**Request Body:**
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```json
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{
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"holdings": {
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"HDFC Top 100 Fund": {
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"scheme_code": "120503",
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"category": "Large Cap Equity",
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"fund_house": "HDFC Mutual Fund",
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"invested_amount": 50000,
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"current_value": 58000,
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"units": 500,
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"current_nav": 116.0,
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"investment_type": "SIP (Monthly)",
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"nav_data": []
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},
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"SBI Small Cap Fund": {
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"scheme_code": "122639",
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"category": "Small Cap Equity",
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"fund_house": "SBI Mutual Fund",
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"invested_amount": 30000,
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"current_value": 35000,
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"units": 300,
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"current_nav": 116.67,
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"investment_type": "SIP (Monthly)",
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"nav_data": []
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}
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}
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}
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```
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### 5. POST `/api/v1/goals/dashboard`
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**Request Body:**
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```json
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{
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"goals": [
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{
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"name": "Child's Education",
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"amount": 2000000,
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"inflation_adjusted_amount": 4781564.0,
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"years": 15,
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"priority": "High",
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"required_sip": 10000,
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"expected_inflation": 6.0,
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"id": 0
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},
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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],
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"monthly_savings": 80000
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}
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```
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### 6. POST `/api/v1/goals/inflation-adjusted`
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**Request Body:**
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```json
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{
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"target_amount": 1000000,
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"years": 10,
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"expected_inflation": 6.0
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}
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```
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### 7. POST `/api/v1/ai/analyze`
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**Request Body:**
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```json
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{
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"client_profile": {
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"age": 35,
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"monthly_income": 50000,
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"risk_tolerance": "Moderate",
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"investment_experience": "Intermediate",
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"tax_bracket": "20%",
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"monthly_savings": 15000
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},
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"portfolio_data": {
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"holdings": ["HDFC Top 100 Fund", "SBI Small Cap Fund"],
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"categories": ["Large Cap Equity", "Small Cap Equity"],
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"total_value": 93000,
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"total_invested": 80000,
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"total_gains": 13000,
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"category_allocation": {
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"Large Cap Equity": 62.37,
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"Small Cap Equity": 37.63
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}
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},
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"goals_data": {
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"goals": ["Child's Education", "Retirement"],
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"goal_details": [
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{
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"name": "Child's Education",
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"amount": 2000000,
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"inflation_adjusted_amount": 4781564.0,
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"years": 15,
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"priority": "High",
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"required_sip": 10000,
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"expected_inflation": 6.0,
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"id": 0
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},
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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],
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"total_required_sip": 25000,
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"timeline_range": "15-25 years",
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"priority_goals": [
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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]
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},
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"analysis_focus": ["Fund Selection", "Risk Assessment", "Goal Alignment"],
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"market_conditions": "Neutral",
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"investment_horizon": "Medium Term (3-7 years)"
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}
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```
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### 8. POST `/api/v1/ai/fund-selection`
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**Request Body:**
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```json
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{
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"client_profile": {
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"age": 35,
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"monthly_income": 50000,
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"risk_tolerance": "Moderate",
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"investment_experience": "Intermediate",
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"tax_bracket": "20%",
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"monthly_savings": 15000
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},
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"goals_data": {
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"goals": ["Child's Education", "Retirement"],
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"goal_details": [
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{
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"name": "Child's Education",
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"amount": 2000000,
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"inflation_adjusted_amount": 4781564.0,
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"years": 15,
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"priority": "High",
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"required_sip": 10000,
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"expected_inflation": 6.0,
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"id": 0
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},
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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],
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"total_required_sip": 25000,
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"timeline_range": "15-25 years",
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"priority_goals": [
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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]
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},
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"market_conditions": "Neutral",
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"investment_horizon": "Medium Term (3-7 years)"
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}
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```
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### 9. POST `/api/v1/ai/risk-assessment`
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**Request Body:**
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```json
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{
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"client_profile": {
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"age": 35,
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"monthly_income": 50000,
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"risk_tolerance": "Moderate",
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"investment_experience": "Intermediate",
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"tax_bracket": "20%",
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"monthly_savings": 15000
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},
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"portfolio_data": {
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"holdings": ["HDFC Top 100 Fund", "SBI Small Cap Fund"],
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"categories": ["Large Cap Equity", "Small Cap Equity"],
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"total_value": 93000,
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"total_invested": 80000,
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"total_gains": 13000,
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"category_allocation": {
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"Large Cap Equity": 62.37,
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"Small Cap Equity": 37.63
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}
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},
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"market_conditions": "Neutral"
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}
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```
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### 10. POST `/api/v1/ai/goal-planning`
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**Request Body:**
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```json
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{
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"client_profile": {
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"age": 35,
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"monthly_income": 50000,
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"risk_tolerance": "Moderate",
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"investment_experience": "Intermediate",
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"tax_bracket": "20%",
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"monthly_savings": 15000
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},
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"goals_data": {
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"goals": ["Child's Education", "Retirement"],
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"goal_details": [
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{
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"name": "Child's Education",
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"amount": 2000000,
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"inflation_adjusted_amount": 4781564.0,
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"years": 15,
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"priority": "High",
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"required_sip": 10000,
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"expected_inflation": 6.0,
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"id": 0
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},
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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],
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"total_required_sip": 25000,
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"timeline_range": "15-25 years",
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"priority_goals": [
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{
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"name": "Retirement",
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"amount": 5000000,
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"inflation_adjusted_amount": 11953910.0,
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"years": 25,
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"priority": "Critical",
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"required_sip": 15000,
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"expected_inflation": 6.0,
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"id": 1
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}
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]
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},
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309 |
+
"investment_horizon": "Medium Term (3-7 years)"
|
310 |
+
}
|
311 |
+
```
|
312 |
+
|
313 |
+
### 11. POST `/api/v1/portfolio/rebalance`
|
314 |
+
**Request Body:**
|
315 |
+
```json
|
316 |
+
{
|
317 |
+
"holdings": {
|
318 |
+
"HDFC Top 100 Fund": {
|
319 |
+
"scheme_code": "120503",
|
320 |
+
"category": "Large Cap Equity",
|
321 |
+
"fund_house": "HDFC Mutual Fund",
|
322 |
+
"invested_amount": 50000,
|
323 |
+
"current_value": 58000,
|
324 |
+
"units": 500,
|
325 |
+
"current_nav": 116.0,
|
326 |
+
"investment_type": "SIP (Monthly)",
|
327 |
+
"nav_data": []
|
328 |
+
},
|
329 |
+
"SBI Small Cap Fund": {
|
330 |
+
"scheme_code": "122639",
|
331 |
+
"category": "Small Cap Equity",
|
332 |
+
"fund_house": "SBI Mutual Fund",
|
333 |
+
"invested_amount": 30000,
|
334 |
+
"current_value": 35000,
|
335 |
+
"units": 300,
|
336 |
+
"current_nav": 116.67,
|
337 |
+
"investment_type": "SIP (Monthly)",
|
338 |
+
"nav_data": []
|
339 |
+
}
|
340 |
+
}
|
341 |
+
}
|
342 |
+
```
|
343 |
+
|
344 |
+
### 12. POST `/api/v1/portfolio/performance`
|
345 |
+
**Request Body:**
|
346 |
+
```json
|
347 |
+
{
|
348 |
+
"holdings": {
|
349 |
+
"HDFC Top 100 Fund": {
|
350 |
+
"scheme_code": "120503",
|
351 |
+
"category": "Large Cap Equity",
|
352 |
+
"fund_house": "HDFC Mutual Fund",
|
353 |
+
"invested_amount": 50000,
|
354 |
+
"current_value": 58000,
|
355 |
+
"units": 500,
|
356 |
+
"current_nav": 116.0,
|
357 |
+
"investment_type": "SIP (Monthly)",
|
358 |
+
"nav_data": []
|
359 |
+
},
|
360 |
+
"SBI Small Cap Fund": {
|
361 |
+
"scheme_code": "122639",
|
362 |
+
"category": "Small Cap Equity",
|
363 |
+
"fund_house": "SBI Mutual Fund",
|
364 |
+
"invested_amount": 30000,
|
365 |
+
"current_value": 35000,
|
366 |
+
"units": 300,
|
367 |
+
"current_nav": 116.67,
|
368 |
+
"investment_type": "SIP (Monthly)",
|
369 |
+
"nav_data": []
|
370 |
+
}
|
371 |
+
}
|
372 |
+
}
|
373 |
+
```
|
374 |
+
|
375 |
+
These sample inputs cover all the major POST endpoints in the FastAPI backend. Each request includes realistic data that matches the expected Pydantic models for each endpoint. You can use these samples to test the API endpoints directly or integrate them with your Streamlit frontend.
|