# migrations

dir: embeddings_queue
filename: 00001-embeddings.sqlite.sql
hash: d3755dfd232be8e8301f4d7fcfb3a486
sql:
CREATE TABLE embeddings_queue (
    seq_id INTEGER PRIMARY KEY,
    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
    operation INTEGER NOT NULL,
    topic TEXT NOT NULL,
    id TEXT NOT NULL,
    vector BLOB,
    encoding TEXT,
    metadata TEXT
);


dir: sysdb
filename: 00001-collections.sqlite.sql
hash: 38352d725ad1c16074fac420b22b4633
sql:
CREATE TABLE collections (
    id TEXT PRIMARY KEY,
    name TEXT NOT NULL,
    topic TEXT NOT NULL,
    UNIQUE (name)
);

CREATE TABLE collection_metadata (
    collection_id TEXT REFERENCES collections(id) ON DELETE CASCADE,
    key TEXT NOT NULL,
    str_value TEXT,
    int_value INTEGER,
    float_value REAL,
    PRIMARY KEY (collection_id, key)
);


dir: sysdb
filename: 00002-segments.sqlite.sql
hash: 2913cb6a503055a95f625448037e8912
sql:
CREATE TABLE segments (
    id TEXT PRIMARY KEY,
    type TEXT NOT NULL,
    scope TEXT NOT NULL,
    topic TEXT,
    collection TEXT REFERENCES collection(id)
);

CREATE TABLE segment_metadata (
    segment_id TEXT  REFERENCES segments(id) ON DELETE CASCADE,
    key TEXT NOT NULL,
    str_value TEXT,
    int_value INTEGER,
    float_value REAL,
    PRIMARY KEY (segment_id, key)
);


dir: sysdb
filename: 00004-tenants-databases.sqlite.sql
hash: 048867ce8fcdefe4023c7110e4433591
sql:
CREATE TABLE IF NOT EXISTS tenants (
    id TEXT PRIMARY KEY,
    UNIQUE (id)
);

CREATE TABLE IF NOT EXISTS databases (
    id TEXT PRIMARY KEY, -- unique globally
    name TEXT NOT NULL, -- unique per tenant
    tenant_id TEXT NOT NULL REFERENCES tenants(id) ON DELETE CASCADE,
    UNIQUE (tenant_id, name) -- Ensure that a tenant has only one database with a given name
);

CREATE TABLE IF NOT EXISTS collections_tmp (
    id TEXT PRIMARY KEY, -- unique globally
    name TEXT NOT NULL, -- unique per database
    topic TEXT NOT NULL,
    dimension INTEGER,
    database_id TEXT NOT NULL REFERENCES databases(id) ON DELETE CASCADE,
    UNIQUE (name, database_id)
);

-- Create default tenant and database
INSERT OR REPLACE INTO tenants (id) VALUES ('default_tenant'); -- The default tenant id is 'default_tenant' others are UUIDs
INSERT OR REPLACE INTO databases (id, name, tenant_id) VALUES ('00000000-0000-0000-0000-000000000000', 'default_database', 'default_tenant');

INSERT OR REPLACE INTO collections_tmp (id, name, topic, dimension, database_id)
    SELECT id, name, topic, dimension, '00000000-0000-0000-0000-000000000000' FROM collections;
DROP TABLE collections;
ALTER TABLE collections_tmp RENAME TO collections;


dir: sysdb
filename: 00005-remove-topic.sqlite.sql
hash: b1367c826b8fba5f96f27befdc1d42d2
sql:
-- Remove the topic column from the Collections and Segments tables

ALTER TABLE collections DROP COLUMN topic;
ALTER TABLE segments DROP COLUMN topic;


dir: metadb
filename: 00001-embedding-metadata.sqlite.sql
hash: 2b4cf52c4bb2676e21d6860a4409f856
sql:
CREATE TABLE embeddings (
    id INTEGER PRIMARY KEY,
    segment_id TEXT NOT NULL,
    embedding_id TEXT NOT NULL,
    seq_id BLOB NOT NULL,
    created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
    UNIQUE (segment_id, embedding_id)
);

CREATE TABLE embedding_metadata (
    id INTEGER REFERENCES embeddings(id),
    key TEXT NOT NULL,
    string_value TEXT,
    int_value INTEGER,
    float_value REAL,
    PRIMARY KEY (id, key)
);

CREATE TABLE max_seq_id (
    segment_id TEXT PRIMARY KEY,
    seq_id BLOB NOT NULL
);

CREATE VIRTUAL TABLE embedding_fulltext USING fts5(id, string_value);


dir: metadb
filename: 00002-embedding-metadata.sqlite.sql
hash: 12a570f7121b3a8ce750a2a7c36da20f
sql:
-- SQLite does not support adding check with alter table, as a result, adding a check
-- involve creating a new table and copying the data over. It is over kill with adding
-- a boolean type column. The application write to the table needs to ensure the data
-- integrity.
ALTER TABLE embedding_metadata ADD COLUMN bool_value INTEGER


dir: metadb
filename: 00003-full-text-tokenize.sqlite.sql
hash: f97ad6334aeaa8f419f01110b648b97a
sql:
CREATE VIRTUAL TABLE embedding_fulltext_search USING fts5(string_value, tokenize='trigram');
INSERT INTO embedding_fulltext_search (rowid, string_value) SELECT rowid, string_value FROM embedding_metadata;
DROP TABLE embedding_fulltext;


# embeddings_queue

created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: e0773784-4b3b-4664-8669-dbfaaed56ae5
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 0, "chroma:document": "i Sungwon Kim  \nAI Research Scientist   \nIntel Corporation, Advanced Design   \nHillsboro , OR 97124  \n(503) 415-1675  \nsorg20@gmail.com  \nhttp://github.com/sorg20  \nwww.linkedin.com/in/sungwon -kim-5b10276  \nAsk anything about my CV in  intercative mode  https://huggingface.co/spaces/sorg20/llm_rag_cv   \n \nExperience  \n   July. 2020 \u2013 present  : AI Research Scientist , Intel path finding group . Lead many AI/ML project s  \n-Graph Neural Net work model in EDA design  \n  Developed circuit design tools based on GNN. Present in 2021 Design Automation Conference  \n-Rotary Embedding Transformer based IP contents optimization   \n-Machine Learning based design technology co -optimization model   \n-Deep learning based computer vision/ design -validatio n software development  \n   Jan. 2012 \u2013 July. 2020 : Modeling Engineer ,  Intel Advanced Design                \n              -Intel transistor compact model development  \n-Intel Dev Model/Calibration CAD software development (currently used in production line)"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 10a480be-a0a0-4c2e-9286-9f056933bcfb
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 0, "chroma:document": "-Intel Dev Model/Calibration CAD software development (currently used in production line)  \n              -Machine learning based device optimization tool development  \n -Machine learning based n oise analysis and signal processing  (owner of noise model)    \n   Jan. 2005 \u2013 Dec. 2011 : Research Scientist , Intel Design Technology Solution  \n               -Large sc ale CAD /Scientific  software development  \n              -Computational  imaging /EM modeling and software  development   \n -Computational geo metry /Numerical optimization  tool development  \nResearch Interests  \n \uf09e Graph Neural Network based Circuit design (2021 DAC conference)  \n \uf09e Computer vision and machine learning . \n \uf09e Machine learning based multi -scale  optimization . \nEducation  \n   Ph.D   - Pennsylvania State  University , P A \n   M.S    - Korea Advanced Institute of Science and Technology , Korea  \n   B.S     - Yonsei University , Korea  \nResearch Publications  in Intel"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 03b8f751-ae50-41ce-8d60-33d3caf45e61
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 0, "chroma:document": "M.S    - Korea Advanced Institute of Science and Technology , Korea  \n   B.S     - Yonsei University , Korea  \nResearch Publications  in Intel  \n1. Dual Feature Vector Hetero Graph Neural Network (DFV -GNN) based Post -Layout Parasitic \nEstimation, 2021 Design Automation Conference."}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: d8cce9b8-7d0d-4cef-a35a-6ab0a8604c7d
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 1, "chroma:document": "ii 2. CMOS -based cryogenic control of silicon quantum circuits, Nature  volume  593(2021) , pp 205\u2013210 \n3. A Scalable Cryo -CMOS Controller for the Wideband Frequency -Multiplexed Control of Spin -Qubits \nand Transmons , 2020 IEEE Journal of Solid State Circuits , V ol 55(2020), 11, pp 2930 -2946  \n4. A Scalable Cryo -CMOS 2 -to-20GHz Digitally Intensive Controller for 4 \u00d732 Frequency Multiplexed \nSpin Qubits/Transmons in 22nm FinFET Technology for Quantum Computers, 2020 IEEE International \nSolid -State Circuits Conference . Selected as the ISSCC 2020 Jan Van Vessem  Award for \nOutstanding  European Paper  \n5. Roy, Ananda; kim, Sungwon; Mudanai Siva; \u201cAn Improved Flicker Noise Model for Circuit \nSimulation\u201d, IEEE Transactions on Electron Devices, Vol 64  (2017) , No 4, pp. 1689 -1694  \nOther Publications  \n1 Malkova, Sungwon Kim, and V . Gopalan \u201c Symmetrical analysis of the defect level splitting in two -"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 6a685cc9-d298-4142-8a8f-dfd16489a461
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 1, "chroma:document": "Other Publications  \n1 Malkova, Sungwon Kim, and V . Gopalan \u201c Symmetrical analysis of the defect level splitting in two -\ndimensional photonic crystals ,\u201d Journal of Physics: Condensed Matter as a Topical review , 15, 4535 \n(2003)   \n2 Kun-Wook Chung, Sungwon Kim, and  Shizhuo Yin \u201c Design of a highly nonlinear dispersion -shifted \nfiber with a small effective area by use of the beam propagation method with the Gaussian approximation \nmethod \u201d, Optics Letter. 28, 2031 (2003)  \n3 D. Scrymgeour, N. Malkova, Sungwon Kim, and V . Gopalan \u201cElectro -Optic control of Superprism in  \n  Photonic Crystal\u201d, Appl. Phys. Lett, 82, 3176 (2003)  \n4 N. Malkova, Sungwon Kim, and V . Gopalan \u201cStrain tunable light transmission through a 90 \uf0b0 bend \nwaveguide in a two -dimensional photonic crystal,\u201d Appl. Phys. Lett, 83, 1509 (2003)  \n5 N. Malkova, Sungwon Kim, and V . Gopalan \u201cJahn -Teller Effect in Two -Dimensional Photonic  \n  Crystals,\u201d Physical Review B, 68, 045105 (2003)"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 8056700d-6673-4dee-bf22-fb186bbb9efd
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 1, "chroma:document": "5 N. Malkova, Sungwon Kim, and V . Gopalan \u201cJahn -Teller Effect in Two -Dimensional Photonic  \n  Crystals,\u201d Physical Review B, 68, 045105 (2003)  \n6 N. Malkova, Sungwon Kim, and V . Gopalan \u201cSymmetrical Analysis of Complex Two Dimensional  \n  Hexagonal Photonic Crystals,\u201d Physical Review B, 67, 125203 (2003)  \n7 Sungwon Kim and Venkatraman Gopalan \u201cStrain -Tunable Photonic Bandgap Crystals,\u201d Appl. Phys.  \n  Lett. 78, 3015 (2001)  \nSkill Set  \n   NLP/RAG/LangChain/LlamaIndex/ C++/C/Python/Pytorch/Tensorflow /Java /Unix /OpenCV /Go/MIPS  \n   Develop ing mathematical AI/ML  software for solving complex multi scale real world problem s \n \n \nintroduction for Sungwon Kim:"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: cc1b3bfb-0dd5-43e1-9c78-2664e2005f2f
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 2, "chroma:document": "iii Meet Sungwon Kim, a dynamic individual thriving in the vibrant city of Portland, Oregon, where he shares his life with his \nbeloved wife. Proud father to Eric, currently pursuing his passion for Computer Science at Columbia University, Sungwon \nhimself is deeply entrenched in the realm of cutting -edge technology.  \nAs an AI Research Scientist at Intel, Sungwon is at the forefront of innovation, spearheading the development of \ngroundbreaking AI and ML solutions tailored for chip design. Renowned as a leading figure in Intel's AI landscape, his \nexpertise spans across various facets of artificial intelligence, with a track record of involvement in numerous pioneering \nresearch endeavors.  \nBeyond his professional achievements, Sungwon finds solace in the serenity of nature, particularly on the ski slopes where hi s \nprowess as an expert skier shines through. A voracious reader, he indulges in the world of literature, constantly expanding h is \nhorizons."}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 6a3ec18f-378c-41e8-9e63-c3bf7d614bd5
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 2, "chroma:document": "prowess as an expert skier shines through. A voracious reader, he indulges in the world of literature, constantly expanding h is \nhorizons.  \nDriven by a sense of wanderlust, Sungwon's travels often lead him to idyllic beach destinations, where he unwinds and \nrejuvenates. Fluent in both Korean and English, with a proficiency in reading Chinese characters, he effortlessly navigates \nlinguistic landscapes.  \nSungwon's impact extends beyond the confines of his technical prowess; his exceptional interpersonal skills and dedication to  \nmentorship have empowered countless young engineers within Intel. In addition to his engineering acumen, Sungwon \npossesses a unique proficiency in large language model tuning and neural language translation.  \nHarnessing these skills, he has pioneered transformative projects, such as the development of a transformer architecture -based \ncircuit modeling tool. Recently, Sungwon delved into the realm of RAG -based modeling to create a personalized Large"}


created_at: 2024-05-05 03:21:11
topic: persistent://default/default/d15dced2-a7be-489c-9a89-43498e71e4e3
id: 1c9f1461-9b88-4048-a66a-58e83e4cdc76
encoding: FLOAT32
metadata:
{"source": "./data/Sungwon_Kim_ML_DL_Intro_together.pdf", "page": 2, "chroma:document": "circuit modeling tool. Recently, Sungwon delved into the realm of RAG -based modeling to create a personalized Large \nLanguage Model app, showcasing his boundless curiosity and innovative spirit.  \n \nBased on sungwon \u2019s tech nical leadership and integrity  it would be a great opportunity hire Sungwon  as \nleading engineer  especially for AI/ML software develop ment."}


# embedding_metadata

key: chroma:document
string_value:
i Sungwon Kim  
AI Research Scientist   
Intel Corporation, Advanced Design   
Hillsboro , OR 97124  
(503) 415-1675  
sorg20@gmail.com  
http://github.com/sorg20  
www.linkedin.com/in/sungwon -kim-5b10276  
Ask anything about my CV in  intercative mode  https://huggingface.co/spaces/sorg20/llm_rag_cv   
 
Experience  
   July. 2020 – present  : AI Research Scientist , Intel path finding group . Lead many AI/ML project s  
-Graph Neural Net work model in EDA design  
  Developed circuit design tools based on GNN. Present in 2021 Design Automation Conference  
-Rotary Embedding Transformer based IP contents optimization   
-Machine Learning based design technology co -optimization model   
-Deep learning based computer vision/ design -validatio n software development  
   Jan. 2012 – July. 2020 : Modeling Engineer ,  Intel Advanced Design                
              -Intel transistor compact model development  
-Intel Dev Model/Calibration CAD software development (currently used in production line)


key: chroma:document
string_value:
-Intel Dev Model/Calibration CAD software development (currently used in production line)  
              -Machine learning based device optimization tool development  
 -Machine learning based n oise analysis and signal processing  (owner of noise model)    
   Jan. 2005 – Dec. 2011 : Research Scientist , Intel Design Technology Solution  
               -Large sc ale CAD /Scientific  software development  
              -Computational  imaging /EM modeling and software  development   
 -Computational geo metry /Numerical optimization  tool development  
Research Interests  
  Graph Neural Network based Circuit design (2021 DAC conference)  
  Computer vision and machine learning . 
  Machine learning based multi -scale  optimization . 
Education  
   Ph.D   - Pennsylvania State  University , P A 
   M.S    - Korea Advanced Institute of Science and Technology , Korea  
   B.S     - Yonsei University , Korea  
Research Publications  in Intel


key: chroma:document
string_value:
M.S    - Korea Advanced Institute of Science and Technology , Korea  
   B.S     - Yonsei University , Korea  
Research Publications  in Intel  
1. Dual Feature Vector Hetero Graph Neural Network (DFV -GNN) based Post -Layout Parasitic 
Estimation, 2021 Design Automation Conference.


key: chroma:document
string_value:
ii 2. CMOS -based cryogenic control of silicon quantum circuits, Nature  volume  593(2021) , pp 205–210 
3. A Scalable Cryo -CMOS Controller for the Wideband Frequency -Multiplexed Control of Spin -Qubits 
and Transmons , 2020 IEEE Journal of Solid State Circuits , V ol 55(2020), 11, pp 2930 -2946  
4. A Scalable Cryo -CMOS 2 -to-20GHz Digitally Intensive Controller for 4 ×32 Frequency Multiplexed 
Spin Qubits/Transmons in 22nm FinFET Technology for Quantum Computers, 2020 IEEE International 
Solid -State Circuits Conference . Selected as the ISSCC 2020 Jan Van Vessem  Award for 
Outstanding  European Paper  
5. Roy, Ananda; kim, Sungwon; Mudanai Siva; “An Improved Flicker Noise Model for Circuit 
Simulation”, IEEE Transactions on Electron Devices, Vol 64  (2017) , No 4, pp. 1689 -1694  
Other Publications  
1 Malkova, Sungwon Kim, and V . Gopalan “ Symmetrical analysis of the defect level splitting in two -


key: chroma:document
string_value:
Other Publications  
1 Malkova, Sungwon Kim, and V . Gopalan “ Symmetrical analysis of the defect level splitting in two -
dimensional photonic crystals ,” Journal of Physics: Condensed Matter as a Topical review , 15, 4535 
(2003)   
2 Kun-Wook Chung, Sungwon Kim, and  Shizhuo Yin “ Design of a highly nonlinear dispersion -shifted 
fiber with a small effective area by use of the beam propagation method with the Gaussian approximation 
method ”, Optics Letter. 28, 2031 (2003)  
3 D. Scrymgeour, N. Malkova, Sungwon Kim, and V . Gopalan “Electro -Optic control of Superprism in  
  Photonic Crystal”, Appl. Phys. Lett, 82, 3176 (2003)  
4 N. Malkova, Sungwon Kim, and V . Gopalan “Strain tunable light transmission through a 90  bend 
waveguide in a two -dimensional photonic crystal,” Appl. Phys. Lett, 83, 1509 (2003)  
5 N. Malkova, Sungwon Kim, and V . Gopalan “Jahn -Teller Effect in Two -Dimensional Photonic  
  Crystals,” Physical Review B, 68, 045105 (2003)


key: chroma:document
string_value:
5 N. Malkova, Sungwon Kim, and V . Gopalan “Jahn -Teller Effect in Two -Dimensional Photonic  
  Crystals,” Physical Review B, 68, 045105 (2003)  
6 N. Malkova, Sungwon Kim, and V . Gopalan “Symmetrical Analysis of Complex Two Dimensional  
  Hexagonal Photonic Crystals,” Physical Review B, 67, 125203 (2003)  
7 Sungwon Kim and Venkatraman Gopalan “Strain -Tunable Photonic Bandgap Crystals,” Appl. Phys.  
  Lett. 78, 3015 (2001)  
Skill Set  
   NLP/RAG/LangChain/LlamaIndex/ C++/C/Python/Pytorch/Tensorflow /Java /Unix /OpenCV /Go/MIPS  
   Develop ing mathematical AI/ML  software for solving complex multi scale real world problem s 
 
 
introduction for Sungwon Kim:


key: chroma:document
string_value:
iii Meet Sungwon Kim, a dynamic individual thriving in the vibrant city of Portland, Oregon, where he shares his life with his 
beloved wife. Proud father to Eric, currently pursuing his passion for Computer Science at Columbia University, Sungwon 
himself is deeply entrenched in the realm of cutting -edge technology.  
As an AI Research Scientist at Intel, Sungwon is at the forefront of innovation, spearheading the development of 
groundbreaking AI and ML solutions tailored for chip design. Renowned as a leading figure in Intel's AI landscape, his 
expertise spans across various facets of artificial intelligence, with a track record of involvement in numerous pioneering 
research endeavors.  
Beyond his professional achievements, Sungwon finds solace in the serenity of nature, particularly on the ski slopes where hi s 
prowess as an expert skier shines through. A voracious reader, he indulges in the world of literature, constantly expanding h is 
horizons.


key: chroma:document
string_value:
prowess as an expert skier shines through. A voracious reader, he indulges in the world of literature, constantly expanding h is 
horizons.  
Driven by a sense of wanderlust, Sungwon's travels often lead him to idyllic beach destinations, where he unwinds and 
rejuvenates. Fluent in both Korean and English, with a proficiency in reading Chinese characters, he effortlessly navigates 
linguistic landscapes.  
Sungwon's impact extends beyond the confines of his technical prowess; his exceptional interpersonal skills and dedication to  
mentorship have empowered countless young engineers within Intel. In addition to his engineering acumen, Sungwon 
possesses a unique proficiency in large language model tuning and neural language translation.  
Harnessing these skills, he has pioneered transformative projects, such as the development of a transformer architecture -based 
circuit modeling tool. Recently, Sungwon delved into the realm of RAG -based modeling to create a personalized Large


key: chroma:document
string_value:
circuit modeling tool. Recently, Sungwon delved into the realm of RAG -based modeling to create a personalized Large 
Language Model app, showcasing his boundless curiosity and innovative spirit.  
 
Based on sungwon ’s tech nical leadership and integrity  it would be a great opportunity hire Sungwon  as 
leading engineer  especially for AI/ML software develop ment.


