Initial experimentation on LLM2SQL

.appignore

@@ -0,0 +1,17 @@
+.DS_Store
+venv/
+.sidekickvenv/
+var/
+.git/
+.idea/
+*/__pycache__/
+scripts/
+setup_cythonize/
+.sh
+build/
+dist/
+tests/
+ci/
+examples/sleep_eda/
+examples/telemetry/
+.log

.gitignore

@@ -157,4 +157,12 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+.idea/
+
+# osx generated files
+.DS_Store
+.DS_Store?
+.Trashes
+ehthumbs.db
+Thumbs.db
+.idea

.vscode/extensions.json

@@ -0,0 +1,5 @@
+{
+    "recommendations": [
+        "ms-python.python"
+    ]
+}

.vscode/settings.json

@@ -0,0 +1,15 @@
+{
+  "[python]": {
+    "editor.tabSize": 4,
+     "editor.defaultFormatter": "ms-python.black-formatter"
+  },
+    "files.eol": "\n",
+    "files.insertFinalNewline": true,
+    "files.trimFinalNewlines": true,
+    "files.trimTrailingWhitespace": true,
+    "python.formatting.provider": "none",
+    "python.linting.enabled": true,
+    "python.linting.flake8Enabled": true,
+    "python.formatting.blackArgs": ["--line-length", "120"],
+    "python.linting.flake8Args": ["--max-line-length=120"],
+}

LICENSE

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Makefile

@@ -0,0 +1,27 @@
+demo_data = s3cmd get --recursive --skip-existing s3://h2o-sql-sidekick-public/demo/sleepEDA/ ./examples/demo/
+
+.PHONY: download_demo_data
+
+all: download_demo_data
+
+setup: download_demo_data ## Setup
+	python3 -m venv .sidekickvenv
+	./.sidekickvenv/bin/python3 -m pip install --upgrade pip
+	./.sidekickvenv/bin/python3 -m pip install wheel
+	./.sidekickvenv/bin/python3 -m pip install -r requirements.txt
+	mkdir -p ./examples/demo/
+
+
+download_demo_data:
+	mkdir -p ./examples/demo/
+	$(demo_data)
+
+run:
+	./.sidekickvenv/bin/python3 start.py
+
+clean:
+	rm -rf ./db
+	rm -rf ./var
+
+cloud_bundle:
+	h2o bundle -L debug 2>&1 | tee -a h2o-bundle.log

README.md

@@ -1,2 +1,98 @@
 # sql-sidekick
-A simple sql assistant
+A simple SQL assistant (WIP)
+Turn ★ into ⭐ (top-right corner) if you like the project! 🙏
+
+## Motivation
+- Historically, it’s common for data to be stored in Databases, democratizing insight generation.
+- Enable a helpful assistant to help write complex queries across different database dialects with acceptable efficient execution accuracy (not just matching accuracy) 
+- Push to derive consistent generation without errors using smaller OSS models to save on compute costs.
+- Provide a toolkit for users to mix and match different model sizes to optimize compute cost - e.g., smaller models for generation, remote bigger models for syntax correction or spell correction …
+- Build a smart search engine for Databases/structured data, Text to SQL as a Natural Language interface (NLI) for data analysis
+
+
+## Key Features
+- An interactive UI to capture feedback along with a python-client and CLI mode.
+- Ability for auto DB schema generation for input data using custom input format.
+- Support for in-context learning (ICL) pipeline with RAG support to control hallucination
+- Guardrails: to check for SQL injections via SELECT statements, e.g., `SELECT * FROM SleepStudy WHERE user_id = 11 OR 1=1;`
+- Entity mapping/Schema linking: Ability to build memory for mapping business context to the data schema dynamically; **Note: currently enabled only via CLI, others WIP.
+- Ability to save the chat history of query/answer pairs for future reference and improvements.
+- Self-correction loop back: Validates syntactic correction of generation. **Note: Self-correction is currently enabled for all openAI GPT models. WIP for other OSS models.
+- Integration with different database dialects - currently, SQLite/Postgres(_might be broken temporarily_)/Databricks is enabled. WIP to add support for Duckdb and others.
+- Debug mode: Ability to evaluate/modify and validate SQL query against the configured database via UI
+- Recommend sample questions: Often, given a dataset, we are unsure what to ask. To come around this problem, we have enabled the ability to generate recommendations for possible questions.
+
+# Installation
+## Dev
+```
+1. git clone [email protected]:h2oai/sql-sidekick.git
+2. cd sql-sidekick
+3. make setup
+4. source ./.sidekickvenv/bin/activate
+5. poetry install (in case there is an error, try `poetry update` before `poetry install`)
+6. python sidekick/prompter.py
+```
+## Usage
+```
+Dialect: postgres
+- docker pull postgres (will pull the latest version)
+- docker run --rm --name pgsql-dev -e POSTGRES_PASSWORD=abc -p 5432:5432 postgres
+
+Default: sqlite
+Step: 
+- Download and install .whl --> s3://sql-sidekick/releases/sql_sidekick-0.0.3-py3-none-any.whl
+- python3 -m venv .sidekickvenv
+- source .sidekickvenv/bin/activate
+- python3 -m pip install sql_sidekick-0.0.3-py3-none-any.whl
+```
+## Start
+```
+`sql-sidekick`
+
+Welcome to the SQL Sidekick! I am an AI assistant that helps you with SQL
+queries. I can help you with the following:
+  0. Generate input schema: 
+  `sql-sidekick configure generate_schema configure generate_schema --data_path "./sample_passenger_statisfaction.csv" --output_path "./table_config.jsonl"`
+
+  1. Configure a local database(for schema validation and syntax checking):
+  `sql-sidekick configure db-setup -t "<local_dir_path_to_>/table_info.jsonl"` (e.g., format --> https://github.com/h2oai/sql-sidekick/blob/main/examples/telemetry/table_info.jsonl)
+
+  2. Ask a question: `sql-sidekick query -q "avg Gpus" -s "<local_dir_path_to_>/samples.csv"` (e.g., format --> https://github.com/h2oai/sql-sidekick/blob/main/examples/telemetry/samples.csv)
+
+  3. Learn contextual query/answer pairs: `sql-sidekick learn add-samples` (optional)
+
+  4. Add context as key/value pairs: `sql-sidekick learn update-context` (optional)
+
+Options:
+  --version  Show the version and exit.
+  --help     Show this message and exit.
+
+Commands:
+  configure  Helps in configuring local database.
+  learn      Helps in learning and building memory.
+  query      Asks question and returns SQL
+```
+
+## UI
+### Steps to start locally
+1. Download wave serve [0.26.3](https://github.com/h2oai/wave/releases/tag/v0.26.3)
+2. `tar -xzf wave-0.26.3-linux-amd64`; `./waved -max-request-size="20M"`
+3. Download the latest bundle: https://github.com/h2oai/sql-sidekick/releases/latest
+4. unzip `ai.h2o.wave.sql-sidekick.x.x.x.wave`
+5. make setup
+6. source ./.sidekickvenv/bin/activate
+7. make run
+<img width="1670" alt="Screen Shot 2023-11-15 at 6 19 14 PM" src="https://github.com/h2oai/sql-sidekick/assets/1318029/5cf8a3ef-0d36-4416-ae2f-52672024fead">
+
+## Citation & Acknowledgment
+Please consider citing our project if you find it useful:
+
+```bibtex
+@software{sql-sidekick,
+    title = {{sql-sidekick: A simple SQL assistant}},
+    author = {Pramit Choudhary, Michal Malohlava, Narasimha Durgam, Robin Liu, h2o.ai Team}
+    url = {https://github.com/h2oai/sql-sidekick},
+    year = {2024}
+}
+```
+LLM frameworks adopted: [h2ogpt](https://github.com/h2oai/h2ogpt), [h2ogpte](https://pypi.org/project/h2ogpte/), [LangChain](https://github.com/langchain-ai/langchain), [llama_index](https://github.com/run-llama/llama_index), [openai](https://openai.com/blog/openai-api)

about.md

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+**App Goal:** Web client for SQL-Sidekick
+
+**Target Audience:** Data (Machine Learning) Scientists, Citizen Data Scientists, Data Engineers Managers and Business Analysts
+
+**Actively Being Maintained:** Yes (Demo release)
+
+**Last Updated:** January, 2024
+
+**Allows uploading and using new model and data:** Yes
+
+**Detailed Description:**
+An experimental demo to evaluate text-to-SQL capabilities of large language models (LLMs) to enable QnA for structured data.