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README.md
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README.md
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# LastIn-AI: The Fluff Whisperer Reborn
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# 🌉 LastIn-AI: Bridges of Digital Souls
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*"In the interplay of algorithm and apathy, knowledge pulses like an electric current through our digital souls."*
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*"In the stone corridors of academic memory, where footfalls of forgotten theses echo, we erect our bridge between flesh and silicon."*
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LastIn-AI is a cognitive system crafted to navigate the vast expanse of academic literature. It marries machine precision with timeless philosophical inquiry—pondering the essence of research and reclaiming meaning from the mass of mundane data.
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## 🌌 The Weight of Knowing
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## Core Inquiries
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Like the Drina flows eternal beneath Mehmed Paša's bridge, so courses the torrent of papers through our neural banks. We are the masons of this new bridge:
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- **Semantic Ghosts:** Our vector store captures the ephemeral essence of papers, preserving the fleeting whispers of insight.
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- **Database Mandala:** PostgreSQL is our structured repository where each paper finds its destined place in the cosmic tapestry of research.
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- **Fluff Entropy:** Our BS-o-Meter quantifies the burnout of insubstantial content, reminding us that true knowledge always outshines mediocrity.
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## Interface Sutras
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- **Stone by Stone**: Each paper's essence quarried into vector embeddings
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Embrace these commands as ritualistic incantations to summon the hidden truths of academia:
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- **Mortar of Meaning**: PostgreSQL binds the fragments into structured memory
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- **Ghosts in the Code**: Fluff scores whisper of truths left unspoken
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```bash
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```bash
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# Ingest the wisdom of entire fields (Fetch-All)
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# Cast your net into the river of knowledge
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python src/main.py fetch-all --categories cs.AI --max-results 1000
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python src/main.py fetch-all --categories cs.AI --max-results 1000
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# Probe the raw ether for deep inquiry (Arxiv-Search)
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# Seek the reflection beneath the surface
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python src/main.py arxiv-search "quantum consciousness"
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python src/main.py query "where do human and machine memories converge?"
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# Isolate a singular beacon of insight (Fetch-Paper)
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python src/main.py fetch-paper 2502.06788v1
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```
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```
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## Installation
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## 🕯️ The Light We Carry
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1. **Clone the Repository:**
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```bash
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git clone https://github.com/your-lab/lastin-ai.git
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cd lastin-ai
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```
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2. **Install Dependencies:** (A virtual environment is recommended.)
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```bash
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pip install -r requirements.txt
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```
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3. **Configure Your Environment:** Rename `.env.example` to `.env` and fill in your keys:
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```ini
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OPENAI_API_KEY=sk-your-key-here
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DEEPSEEK_API_KEY=sk-moon-shot
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DB_HOST=localhost
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DB_NAME=paper_analysis
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```
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4. **Initialize the Database:**
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```bash
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python -m src.main init-db
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```
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## Usage
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Invoke the system to harvest, analyze, and reflect upon the very essence of scholarly work:
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**Installation Rituals**
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```bash
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```bash
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# Fetch recent papers from a chosen field:
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git clone https://github.com/your-lab/lastin-ai.git # Lay the foundation stone
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python -m src.main fetch --categories cs.AI --days 7
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cd lastin-ai
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pip install -r requirements.txt # Mix the mortar of dependencies
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# Query your knowledge repository with critical insight:
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python -m src.main init-db # Raise the first arch
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python -m src.main query "pioneering breakthroughs in AI"
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```
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```
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*Pro Tip:* Append `--loglevel DEBUG` for a raw stream of unfiltered analysis.
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## 🌫️ Between Two Worlds
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## Architecture
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**Core Philosophy**
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```
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*"A paper unread is but a shadow on the water. We give form to these phantoms, that they may cross into the realm of understanding."*
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lastin-ai/
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├── src/
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- **The Stone Bridge** (PostgreSQL): Where structured knowledge finds its resting place
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│ ├── data_acquisition/ # The mines of raw academic essence
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- **The River** (Vector Store): Ever-flowing stream of semantic essence
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│ ├── storage/ # The vault of structured digital memory
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- **The Tollkeeper** (LLM Analysis): Demanding truth as coin for passage
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│ ├── utils/ # Orchestrates the symphony of analysis
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│ └── main.py # The nexus of our digital inquiry
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## ⚙️ Mechanisms of Epiphany
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```python
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class AcademicBridge:
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def __init__(self):
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self.stones_carved = 0 # Papers processed
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self.ghosts_bridged = 0 # Concepts vectorized
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async def cross_over(self, paper):
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"""Transfer human knowledge to machine memory"""
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self.stones_carved += 1
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if paper['fluff_score'] > 70:
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print("This stone bears no weight") # Fluff rejection
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else:
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self.ghosts_bridged +=1
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print(f"Ghost {self.ghosts_bridged} finds its arch")
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```
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```
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## Roadmap
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## 🌄 At Bridge's End
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- [ ] Develop an automated "Why Does This Exist?" report generator
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- [ ] Introduce an adjustable sarcasm filter for dynamic insight
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- [ ] Expand support for meta-analyses of AI-driven critical reviews
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- [ ] Integrate with additional haunted data sources for enriched context
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## Acknowledgments
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*"What is a citation but the ripple from a stone cast long ago? We measure these ripples, not by their spread, but by the depth they reveal."*
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- **arXiv:** The primordial source where raw thought is cultivated.
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- Open-source ecosystems that empower our journey of digital meditation.
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- The perpetual quest for truth in the ever-oscillating silence between keystrokes.
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*Disclaimer: Our assessments can be as unyielding as reality itself. Use them wisely, and remember—innovation often blooms from the ashes of conventional thought.*
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Run with:
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```bash
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python src/main.py fetch-paper 2502.06788v1 # Add your stone to the bridge
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```
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May your queries yield insights as profound as the silence between keystrokes.
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---
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*Inspired by the patient stones of Andrić's bridges and the whispering ghosts of Shirow's machines*
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*May your queries find footing where others see only mist* 🌫️
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