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@nsatya02 nsatya02 commented Mar 14, 2025

This is my submission for the Daily Dose of Data Science Technical Writer Assignment—Task 1: RAG and Text-to-SQL.

New Features

  • Built a web interface using streamlit to allow user to upload the pdf file.
  • Created an ReAct Agent using llama index to smoothen the workflow to automatically identify the user query and choose the appropriate tool to answer the queries accurately.
  • Also provided how create index via API and Manually. Having issues while creating index using API. So, gave information about both and gave code examples which(API or manually) one to use when.

Documentation

Published comprehensive project documentation covering setup guides, usage instructions, and customization options.

Blog post : Typefully blog post on X

Llama Index & Cloud ---> Orchestration.
Llama cloud vector DB --> Vector DB(default)
Streamlit--> UI

Summary by CodeRabbit

  • New Features
    • Introduced an interactive web interface that lets users seamlessly query city data and document content with AI-enhanced natural language processing.
  • Documentation
    • Released a comprehensive guide with demo instructions and step-by-step setup and configuration details.
  • Chores
    • Refined project dependencies to support the enhanced query and display functionalities.

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coderabbitai bot commented Mar 14, 2025

Walkthrough

The pull request introduces key documentation and application files for the Hybrid RAG & SQL Query Engine. A new README details the project overview, functionality, setup instructions, and workflow. Additionally, two Streamlit applications (in app.py and app1.py) have been developed to integrate SQL querying with retrieval-augmented generation (RAG), each offering model initialization, SQL engine setup, agent creation, and error handling. A requirements file listing necessary dependencies is also added.

Changes

File(s) Change Summary
rag-text-to-sql/README.md Introduced a README detailing the project overview, demo instructions, index creation methods via API/manual (using app.py/app1.py), installation steps, features, and a workflow diagram.
rag-text-to-sql/app.py, rag-text-to-sql/app1.py Added two Streamlit applications integrating SQL and RAG functionalities. Both apps include functions for model initialization, SQL engine setup (in-memory SQLite with a pre-populated city_stats table), agent creation, query processing, and respective error handling. app1.py differs by connecting to an existing index.
rag-text-to-sql/requirements.txt Created a dependency file listing required libraries such as Streamlit, various llama-index packages, Ollama integration, and SQLAlchemy.

Sequence Diagram(s)

sequenceDiagram
    participant U as User
    participant A as Application (app.py)
    participant M as Models
    participant D as SQL Engine
    participant R as RAG Index
    U->>A: Launch application
    A->>M: initialize_models()
    A->>D: setup_sql_engine() → Create city_stats table
    U->>A: Upload PDF file
    A->>R: create_rag_index_from_file(file)
    U->>A: Submit query
    A->>R: create_agent() processes query
    R->>D: Execute SQL query
    R->>R: Process RAG response
    A->>U: Return combined answer
Loading
sequenceDiagram
    participant U as User
    participant A as Application (app1.py)
    participant M as Models
    participant D as SQL Engine
    participant R as Existing Index
    U->>A: Launch application
    A->>M: initialize_models()
    A->>D: setup_sql_engine() → Create city_stats table
    A->>R: connect_to_existing_index()
    U->>A: Submit query
    A->>R: create_agent() processes query
    R->>D: Execute SQL query
    R->>R: Process RAG response
    A->>U: Return combined answer
Loading

Poem

I'm a little bunny of code so fine,
Hop-scotching through data, every line divine.
SQL and RAG join in a merry dance,
Streamlit lights up every query's chance.
My whiskers twitch with joy—let's celebrate this design! 🐇✨

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Actionable comments posted: 1

🧹 Nitpick comments (11)
rag-text-to-sql/requirements.txt (1)

1-6: Consider pinning or specifying exact package versions.
Unpinned dependencies can introduce breaking changes if newer versions introduce compatibility or security issues.

Proposed diff to pin versions (example versions shown; please adjust as needed):

-streamlit
-llama-index
-llama-index-embeddings-huggingface
-llama-index-indices-managed-llama-cloud
-llama_index.llms.ollama
-sqlalchemy
+streamlit==1.26.0
+llama-index==0.7.0
+llama-index-embeddings-huggingface==0.3.0
+llama-index-indices-managed-llama-cloud==0.1.1
+llama_index.llms.ollama==0.2.0
+sqlalchemy==2.1.1
rag-text-to-sql/README.md (5)

12-12: Use more concise wording.
As per the static analysis suggestion, replace “able to” with “can.”

-  If you are able to create an index using API then use "app.py". 
+  If you can create an index using the API, then use "app.py".
🧰 Tools
🪛 LanguageTool

[style] ~12-~12: As a shorter alternative for ‘able to’, consider using “can”.
Context: ... & API)📖🔄 - USE app.py : If you are able to create an index using API then use "app...

(BE_ABLE_TO)


17-17: Correct pronoun usage.
Capitalize “I’m” to maintain a professional tone in documentation.

-  It worked for me fine for some period of time but later for some unknown reasons i'm unable to create an index using API. 
+  It worked fine for some time, but later, for some unknown reason, I’m unable to create an index using the API.
🧰 Tools
🪛 LanguageTool

[uncategorized] ~17-~17: Did you mean “I”?
Context: ...time but later for some unknown reasons i'm unable to create an index using API. ...

(I_LOWERCASE_PREMIUM)


21-21: Improve clarity and grammar.
Add the missing article “an” and revise punctuation.

-  If you are unable to create index using API. By following the below steps you can create it manually :
+  If you are unable to create an index using the API, then follow the steps below to create it manually:
🧰 Tools
🪛 LanguageTool

[uncategorized] ~21-~21: You might be missing the article “an” here.
Context: ...p1.py :** If you are unable to create index using API. By following the below steps...

(AI_EN_LECTOR_MISSING_DETERMINER_AN)


[uncategorized] ~21-~21: A comma might be missing here.
Context: ...index using API. By following the below steps you can create it manually : 1. Open ...

(AI_EN_LECTOR_MISSING_PUNCTUATION_COMMA)


24-24: Use consistent instructions or formatting.
Enclose the UI labels in quotes for clarity.

-  3. Click create index.
+  3. Click "Create Index."
🧰 Tools
🪛 LanguageTool

[grammar] ~24-~24: There seems to be a noun/verb agreement error. Did you mean “creates” or “created”?
Context: ...macloud. 2. Go to indexes. 3. Click create index. 4. upload your documents. 5....

(SINGULAR_NOUN_VERB_AGREEMENT)


78-78: Consider using a hyphen for compound adjectives.
“Open Source” stack can be written as “Open-Source Stack.”

-  - **Open Source Stack**
+  - **Open-Source Stack**
🧰 Tools
🪛 LanguageTool

[uncategorized] ~78-~78: If this is a compound adjective that modifies the following noun, use a hyphen.
Context: ...rface 📤 PDF upload capability - Open Source Stack 🦙 Ollama LLM integration ...

(EN_COMPOUND_ADJECTIVE_INTERNAL)

rag-text-to-sql/app1.py (2)

25-53: In-memory database limits data persistence.
Using sqlite:///:memory: creates a temporary DB that’s lost after each session. If persistent data storage is desired, store it on disk or a dedicated DB server.


84-84: Remove unnecessary f-string prefix.
No placeholders exist in the string, so the f is superfluous.

-        description=f"Useful for answering semantic questions about documents."
+        description="Useful for answering semantic questions about documents."
🧰 Tools
🪛 Ruff (0.8.2)

84-84: f-string without any placeholders

Remove extraneous f prefix

(F541)

rag-text-to-sql/app.py (3)

31-53: In-memory database limits data persistence.
Similar to app1.py, using sqlite:///:memory: is ephemeral. If persistent data storage is important, consider a file-based SQLite connection or a dedicated DB.


157-174: Remove or clarify commented-out code.
Leaving large commented sections can confuse maintainers. Delete or document why it’s left as reference.


185-185: Remove leftover debugging comment.
It’s typically best practice to take out commented debugging references before merging.

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 6140fc3 and f20449f.

⛔ Files ignored due to path filters (1)
  • .DS_Store is excluded by !**/.DS_Store
📒 Files selected for processing (4)
  • rag-text-to-sql/README.md (1 hunks)
  • rag-text-to-sql/app.py (1 hunks)
  • rag-text-to-sql/app1.py (1 hunks)
  • rag-text-to-sql/requirements.txt (1 hunks)
🧰 Additional context used
🪛 LanguageTool
rag-text-to-sql/README.md

[style] ~12-~12: As a shorter alternative for ‘able to’, consider using “can”.
Context: ... & API)📖🔄 - USE app.py : If you are able to create an index using API then use "app...

(BE_ABLE_TO)


[uncategorized] ~17-~17: Did you mean “I”?
Context: ...time but later for some unknown reasons i'm unable to create an index using API. ...

(I_LOWERCASE_PREMIUM)


[uncategorized] ~21-~21: You might be missing the article “an” here.
Context: ...p1.py :** If you are unable to create index using API. By following the below steps...

(AI_EN_LECTOR_MISSING_DETERMINER_AN)


[uncategorized] ~21-~21: A comma might be missing here.
Context: ...index using API. By following the below steps you can create it manually : 1. Open ...

(AI_EN_LECTOR_MISSING_PUNCTUATION_COMMA)


[grammar] ~24-~24: There seems to be a noun/verb agreement error. Did you mean “creates” or “created”?
Context: ...macloud. 2. Go to indexes. 3. Click create index. 4. upload your documents. 5....

(SINGULAR_NOUN_VERB_AGREEMENT)


[uncategorized] ~78-~78: If this is a compound adjective that modifies the following noun, use a hyphen.
Context: ...rface 📤 PDF upload capability - Open Source Stack 🦙 Ollama LLM integration ...

(EN_COMPOUND_ADJECTIVE_INTERNAL)

🪛 Ruff (0.8.2)
rag-text-to-sql/app1.py

84-84: f-string without any placeholders

Remove extraneous f prefix

(F541)

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