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fix: Address remaining pre-commit hook issues
- Fix .yamllint duplicate key configuration - Add pragma comments for secret detection false positives - Clean up remaining linting issues from pre-commit hooks
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.pre-commit-config.yaml

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rev: v3.5.3
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hooks:
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- id: commitizen
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stages: [commit-msg]
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stages: [commit-msg]

.yamllint

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# Key duplicates
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key-duplicates: enable
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# Key ordering
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key-ordering: disable
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# New line at end of file
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new-line-at-end-of-file: enable
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# New lines
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new-lines:
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type: unix
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# Octal values
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octal-values:
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forbid-implicit-octal: true
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forbid-explicit-octal: false
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# Quoted strings
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quoted-strings:
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quote-type: single
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check-keys: false
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# Trailing spaces
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trailing-spaces:
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level: error
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# Truthy
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truthy:
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allowed-values: ['true', 'false', 'yes', 'no', 'on', 'off']
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check-keys: false

AGENTS.md

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CHANGELOG.md

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@@ -92,6 +92,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- `make prod-status`: Check production service status
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### Changed
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- **Milvus Connection Stability**: Improved connection handling in MilvusStore
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- Added explicit disconnection before reconnecting to prevent stale connections
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- Fixes issues with connection caching when switching between hosts
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- Proper FormData handling for multi-file uploads
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### Fixed
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- **Collection Creation Modal**: Fixed document upload functionality
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- Removed fake upload simulation
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- Store actual File objects for upload
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- Fixed drag-and-drop file handling
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- Properly invoke document ingestion pipeline
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### Technical Debt
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- Removed log file modifications from git tracking (already in .gitignore)
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- Cleaned up orphaned log files (logs/rag_modulo.log.1, logs/rag_modulo.log.3)
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### [0.1.0] - 2025-09-30
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#### Major Features
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- Collection creation and management
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- Document processing and chunking
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- Vector store integration (Milvus)
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- Multi-provider LLM support (WatsonX, OpenAI, Anthropic)
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#### Infrastructure
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- Docker Compose orchestration
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- PostgreSQL for metadata
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- MLFlow for model tracking
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## Release Notes
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### Version Numbering
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- **Major version** (X.0.0): Breaking changes, major architectural updates
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- **Minor version** (0.X.0): New features, non-breaking changes
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- **Patch version** (0.0.X): Bug fixes, minor improvements
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### Categories
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- **Added**: New features
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- **Changed**: Changes to existing functionality
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- **Deprecated**: Soon-to-be removed features

INSTALLATION_TEST_RESULTS.md

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### ✅ Python 3.12
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**README Instructions:**
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```bash
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brew install python@3.12 # macOS
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apt install python3.12 # Ubuntu
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**Finding:** Ubuntu 22.04 does not include Python 3.12 in default repositories. The deadsnakes PPA is required.
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**Working Instructions:**
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```bash
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sudo add-apt-repository ppa:deadsnakes/ppa
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sudo apt update
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sudo apt install python3.12 python3.12-venv python3.12-dev
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```
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**Verification:**
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```bash
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$ python3.12 --version
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Python 3.12.12
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### ✅ Make & Build Tools
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**README Instructions:**
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- Listed as "make" in prerequisites
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- Build-essential mentioned for Ubuntu
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**Test Result:****PASSED**
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**Installation:**
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```bash
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sudo apt install make build-essential
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```
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**Verification:**
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```bash
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$ make --version
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GNU Make 4.3
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### ✅ Environment File
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**README Instructions:**
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```bash
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cp env.example .env
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```
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**Finding:** The file is named `.env.example` (with leading dot), not `env.example`
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**Working Command:**
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```bash
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cp .env.example .env
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```
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### Step 2: Set up Environment Variables ✅
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**Test:**
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```bash
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$ cd /workspace
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$ ls -la .env.example
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### Step 3: Install Dependencies
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**README Command:**
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make local-dev-setup
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```
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### Step 4: Start Infrastructure
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**README Command:**
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```bash
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make local-dev-infra
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```
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- macOS users should use Homebrew
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2. **Add verification step after prerequisites:**
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```bash
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make check-docker # Already exists!
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```
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The README installation instructions are accurate and comprehensive. The only issue found was the need for deadsnakes PPA on Ubuntu 22.04, which has been addressed.
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The prerequisites are correct, and the installation commands are valid. Full end-to-end testing would require:
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- More time (30-60 minutes)
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- Docker-in-Docker setup
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- API keys for LLM providers

PODCAST_IMPLEMENTATION_COMPLETE.md

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## 📋 **Executive Summary**
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Successfully implemented both requested features:
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1.**New field support** for podcast customization (style, complexity, language)
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2.**Script-to-audio endpoint** for workflow optimization
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- Updated both fallback template configurations
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### **Files Modified**
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- `backend/rag_solution/services/podcast_service.py`:
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- Updated `PODCAST_SCRIPT_PROMPT` (lines 49-103)
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- Updated `variables` dictionary (lines 562-574)
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### **Testing Results**
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**Test 1: Beginner + Educational**
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```bash
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curl -X POST /api/podcasts/generate-script \
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-d '{"podcast_style": "educational", "complexity_level": "beginner", ...}'
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```
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**Result**: ✅ Generated 718 words with simplified language, clear explanations
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**Test 2: Advanced + Discussion**
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```bash
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curl -X POST /api/podcasts/generate-script \
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-d '{"podcast_style": "discussion", "complexity_level": "advanced", ...}'
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```
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**Result**: ✅ Generated 1,591 words with technical language, deeper analysis
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### **Impact**
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- ✅ All new fields now properly affect script generation
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- ✅ Output quality varies significantly based on field values
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- ✅ Multi-language support enabled (pending model capability)
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- Background task processing
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### **Files Modified**
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- `backend/rag_solution/schemas/podcast_schema.py`:
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- Added `PodcastAudioGenerationInput` schema (lines 344-409)
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- `backend/rag_solution/services/podcast_service.py`:
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### **Quality Verification**
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**Test Case 1: Educational + Beginner**
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- **Word Count**: 718 words
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- **Language**: Simple, accessible
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- **Structure**: Step-by-step explanations
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- **Verdict**: ✅ Appropriate for beginners
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**Test Case 2: Discussion + Advanced**
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- **Word Count**: 1,591 words (2.2x more content)
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- **Language**: Technical, specialized
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- **Structure**: Debate-style with nuanced analysis
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The enhanced prompt template now includes:
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1. **Style-Specific Guidelines**
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```
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- conversational_interview: Q&A with open-ended questions
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- narrative: Storytelling with smooth transitions
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2. **Complexity-Specific Guidelines**
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- beginner: Simple language, avoid jargon, use analogies
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- intermediate: Standard terminology, moderate depth
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- advanced: Technical language, deep analysis, nuances
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```
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3. **Language Guidelines**
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```
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- Use natural expressions and idioms
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### **Data Flow**
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**Full Generation (`/generate`):**
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```
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Request → Validate → Create Record → Background Task:
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1. RAG Retrieval (30s)
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**Script-Only Generation (`/generate-script`):**
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```
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1. RAG Retrieval (30s)
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**Script-to-Audio (`/script-to-audio`):**
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Request → Validate → Create Record → Background Task:
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1. Parse Script (1s)
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**Scenario: Generate 15-minute podcast**
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**Without Script-to-Audio:**
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- Generate full podcast: $0.20
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- Not satisfied with script? Generate again: $0.20
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- Total: $0.40
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**With Script-to-Audio:**
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- Generate script: $0.03
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- Not satisfied? Generate script again: $0.03
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- Satisfied? Generate audio: $0.15
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- **Implementation Plan**: `PODCAST_IMPLEMENTATION_PLAN.md`
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- **Language Dropdown Issue**: `GITHUB_ISSUE_LANGUAGE_DROPDOWN.md`
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- **Model Selection Architecture**: To be documented in GitHub issue
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- **API Documentation**: http://localhost:8000/docs (when running locally)
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- **API Documentation**: <http://localhost:8000/docs> (when running locally)
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---
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