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Dependency Maintenance Routine for Langchain integration #100

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1 change: 1 addition & 0 deletions README.md
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DataJourney demonstrates how organizations can effectively manage and utilize data by harnessing the power of open-source technologies. It's designed to help navigate the complex landscape of data tools, offering a structured approach to building **scalable**, and **reproducible** data workflows.

Built on open-source principles, the framework guides users through essential steps—from **identifying** goals and **selecting tools** to **testing** and **customising** workflows. With its flexible, modular design, DataJourney can be tailored to individual needs, making it an invaluable toolkit for data professionals.

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### 🧱 Design Philosophy (LEGO)
Built with additive, subtractive capabilities glued with open source.
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- PO (Base): Static home(s) to keep it together `(GitHub)`
- P1 (Tooling): Tooling, strings `(Powered by open source)`
- P2 (Maintenance + Monitoring): Env, automations `(Pixi + GHA)`

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- P3 (Abstraction): Layer(s), CLI/task manager for users to interact with `(Pixi)`


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✅ `GitHub actions` configured\
✅ `Vale.sh` configured at PR level\
✅ `Pre-commit hooks` configured for code linting/formatting\
✅ Environment management via [pixi](https://prefix.dev/)\

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✅ Reading data from online sources using [intake](https://github.com/intake/intake)\
✅ Sample pipeline built using [Dagster](https://github.com/dagster-io/dagster)\

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✅ Building Dashboard using [holoviews](https://holoviews.org/gallery/index.html) + [panel](https://panel.holoviz.org/reference/index.html)\

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✅ Exploratory data analysis (EDA) using [mito](https://www.trymito.io/)\

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✅ Web UI build on [Flask](https://flask.palletsprojects.com/en/3.0.x/) \
✅ Web UI re-done and expanded with [FastHTML](https://docs.fastht.ml/)\
✅ Leverage AI models to analyse data [GitHub AI models Beta](https://docs.github.com/en/github-models/prototyping-with-ai-models)
✨ LangChain integration

### ☕️ Quickly getting started with DataJourney

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- Generate & add `GITHUB_TOKEN`, instructions [here](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens#creating-a-personal-access-token-classic)
- Added requirement to run the LLM workflows
- Switch directory `cd DataJourney`
- Download pixi : [prefix.dev](https://prefix.dev/)

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- Activate env: `pixi shell`

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- Install DJ framework locally `pixi run DJ_package`
- List all the tasks: `pixi task list`
- Execute a task from the list: `pixi run <TASK>`
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### 🏃🏽‍♀️ Active `tasks` under DJ

- GIT_TOKEN_CHECK
- DJ_package

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- DJ_pre_commit

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- DJ_dagster

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- DJ_fasthtml_app

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- DJ_flask_app

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- DJ_mito_app

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{"message": "[Vale.Spelling] Did you really mean 'DJ_mito_app'?", "location": {"path": "README.md", "range": {"start": {"line": 80, "column": 3}}}, "severity": "ERROR"}
- DJ_panel_app

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- DJ_llm_analysis

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### 🔌 About pre-commit-hooks and activating
Just like the name suggests, pre-commit-hooks are designed to format the code based on PEP standards before committing. [More details](https://pre-commit.com/)

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{"message": "[Google.Passive] In general, use active voice instead of passive voice ('are designed').", "location": {"path": "README.md", "range": {"start": {"line": 86, "column": 47}}}, "severity": "INFO"}

```shell
pixi run DJ_pre_commit
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pixi run DJ_llm_analysis
```

### 🪼 Execute pre-configured Dagster pipeline

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```shell
pixi run DJ_dagster
```
![Dagit UI output](assets/pipeline/dagster_ui.png)

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### 🐙 Panel app
```shell
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```

*NOTE:*
The dashboard generated is exported into HTML format and saved as [stock_price_twilio_dashboard](analytics_framework%2Fdashboard%2Fstock_price_twilio_dashboard.html)

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![Panel app output](assets/dashboard/panel_app_stock.png)

### 🐵 Mito

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{"message": "[Vale.Spelling] Did you really mean 'Mito'?", "location": {"path": "README.md", "range": {"start": {"line": 115, "column": 7}}}, "severity": "ERROR"}

To explore further visit [trymito.io](https://docs.trymito.io/)
```shell
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[//]: # (![mito output]&#40;assets/pipeline/mito_graph.png "Graph generated via mitosheet"&#41; ![mito output operation]&#40;assets/pipeline/mito_operations.png "Operations performed via mitosheet"&#41;)

<div style="display: flex; justify-content: space-between;">
<img src="assets/pipeline/mito_graph.png" alt="mito_output" width="400"/>

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<img src="assets/pipeline/mito_operations.png" alt="mito_output" width="400"/>

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{"message": "[Vale.Spelling] Did you really mean 'mito_output'?", "location": {"path": "README.md", "range": {"start": {"line": 126, "column": 57}}}, "severity": "ERROR"}
</div>

### 🦋 Display all data sources present via web UI
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