docs: update root README with Quick Start, prerequisites, and architecture overview

[Kaustubh1204]

This PR improves the root README to make onboarding and project understanding easier. Key updates include:
Added a Quick Start section with step-by-step instructions for cloning the repo, setting up the backend, and setting up the frontend.
Listed prerequisites including Node.js, Python, uv, and Git, with references to installation guides.
Detailed Architecture & Responsibilities for frontend (Next.js) and backend (FastAPI), including AI processing and vector database usage.
Expanded Core Features and Data Flow & Security sections with explanations and sequence diagrams.
Clarified Setup & Deployment steps and .env configuration for both backend and frontend.
Repository cleanup: removed temporary files, logs, and virtual environments; restored all other files to committed state.
Only the root README.md is modified; all other files remain unchanged.
These updates improve documentation clarity, setup guidance, and overall developer experience.

Summary by CodeRabbit

• Documentation
  • Reorganized README structure with new Quick Start and Prerequisites sections for improved clarity
  • Enhanced feature descriptions with outcome-oriented language (Counter-Perspective Generation, Real-Time Fact Check, Semantic Discovery)
  • Simplified setup and deployment guidance with explicit API key requirements
  • Updated technical architecture details and flow diagrams for better visualization
  • Modernized tech stack information (Next.js, FastAPI, LangChain, Pinecone)

_{✏️ Tip: You can customize this high-level summary in your review settings.}

[coderabbitai]

📝 Walkthrough

Walkthrough

The README.md has been reorganized with a restructured Table of Contents, updated section hierarchies, and technology stack specifics (Groq, Pinecone, LangChain/LangGraph). Feature descriptions were reframed to be outcome-oriented, diagrams were simplified, and setup guidance was consolidated. Net change: +110/-142 lines.

Changes

Cohort / File(s)

Summary

Documentation Restructuring README.md

Reorganized Table of Contents with reordered top-level sections (Quick Start, Prerequisites, Architecture & Responsibilities moved forward); renamed and reframed architectural sections; updated Core Features descriptions to emphasize outcomes; simplified Data Flow & Security diagram; consolidated Setup & Deployment guidance with explicit API key notes; updated Architecture Diagram labels; refreshed Expected Outcomes and Required Skills with explicit technology pairings (Next.js, FastAPI, LangChain/LangGraph, Pinecone, uv)

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~15 minutes

Poem

🐰 Our README hops to a brighter tune,
With structures arranged beneath a clearer moon,
Groq and Pinecone now shine so bright,
Features reframed for outcomes and insight,
A doc that guides with renewed delight! ✨

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately reflects the main changes: adding Quick Start, prerequisites, and architecture overview sections to the README.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

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[coderabbitai]

Actionable comments posted: 1

🤖 Fix all issues with AI agents

In `@README.md`:
- Line 153: Update the environment setup docs to include the Google Custom
Search credentials alongside the existing GROQ_API_KEY, PINECONE_API_KEY, and
PINECONE_INDEX_NAME entries: add a clear instruction to create the backend .env
entry for the Google Custom Search API key (e.g., GOOGLE_CUSTOM_SEARCH_API_KEY)
and the Search Engine ID / CSE ID (e.g., GOOGLE_CSE_ID), describe where to
obtain both from Google Cloud/Custom Search Console, and show how to add them to
the backend environment variables so the AI integration referenced in the
Technical Stack recognizes the keys.

🧹 Nitpick comments (3)

README.md (3)

153-153: Add guidance for Pinecone index setup.

The environment configuration mentions PINECONE_INDEX_NAME but doesn't provide guidance on how to create a Pinecone index or what settings to use. First-time users may not know how to obtain this value.

Consider adding a brief note or link to Pinecone documentation explaining how to create an index, or mention that users should create an index in the Pinecone console before running the backend.

---

161-161: Clarify backend PORT environment variable.

Line 161 mentions "or the port specified in .env", but the environment configuration in line 153 doesn't list a PORT variable. If the backend supports custom port configuration, it should be documented in the .env instructions.

---

202-202: Consider clarifying the search flow in the architecture diagram.

The diagram shows LLM -->|Search| Internet, which is a high-level simplification. In practice, the system likely uses the Google Custom Search service (mentioned in line 105) as an intermediary. While the current representation works for a README overview, you might consider making it more accurate.

Optional: More detailed flow representation

     CNEngine -->|Workflow| Langgraph
     Langgraph -->|Query| LLM
-    LLM -->|Search| Internet
+    Langgraph -->|Search Request| SearchService[Google Search API]
+    SearchService -->|Results| Langgraph
     CNEngine -->|Store/Search| VectorDB
     API -->|Results| UI

[coderabbitai]

🛠️ Refactor suggestion | 🟠 Major

Document the Google Custom Search API key.

The Technical Stack section (line 105) mentions "Google Custom Search" as part of the AI Integration, but the environment configuration doesn't include instructions for obtaining or configuring the Google Custom Search API key. This may cause confusion during setup.

📝 Suggested addition to backend .env documentation

-- **Backend**: Create `backend/.env` and provide your `GROQ_API_KEY`, `PINECONE_API_KEY`, and `PINECONE_INDEX_NAME`.
+- **Backend**: Create `backend/.env` and provide your `GROQ_API_KEY`, `PINECONE_API_KEY`, `PINECONE_INDEX_NAME`, and `GOOGLE_SEARCH_API_KEY` (and `GOOGLE_SEARCH_ENGINE_ID` if applicable).

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	- **Backend**: Create `backend/.env` and provide your `GROQ_API_KEY`, `PINECONE_API_KEY`, and `PINECONE_INDEX_NAME`.
	- **Backend**: Create `backend/.env` and provide your `GROQ_API_KEY`, `PINECONE_API_KEY`, `PINECONE_INDEX_NAME`, and `GOOGLE_SEARCH_API_KEY` (and `GOOGLE_SEARCH_ENGINE_ID` if applicable).

🤖 Prompt for AI Agents

In `@README.md` at line 153, Update the environment setup docs to include the
Google Custom Search credentials alongside the existing GROQ_API_KEY,
PINECONE_API_KEY, and PINECONE_INDEX_NAME entries: add a clear instruction to
create the backend .env entry for the Google Custom Search API key (e.g.,
GOOGLE_CUSTOM_SEARCH_API_KEY) and the Search Engine ID / CSE ID (e.g.,
GOOGLE_CSE_ID), describe where to obtain both from Google Cloud/Custom Search
Console, and show how to add them to the backend environment variables so the AI
integration referenced in the Technical Stack recognizes the keys.

[Kaustubh1204]

Thanks for the detailed review, @coderabbitai! I’ve addressed all the actionable comments from your feedback:
Google Custom Search Documentation
Added GOOGLE_SEARCH_API_KEY and GOOGLE_SEARCH_ENGINE_ID to the backend .env requirements.
Created a “How to Obtain API Keys” section with step-by-step instructions for Groq, Pinecone, and Google CSE.
Included detailed guidance for obtaining both the Google API Key and the Search Engine ID.
Added example .env files showing all required variables.
Architecture & Flow Updates
Updated the architecture diagram to explicitly show the Google Custom Search API and the correct data flow (LangGraph → GCS → LangGraph).
Other Documentation Fixes
Removed ambiguous reference to the unspecified backend PORT variable.
Added guidance on creating a Pinecone index via the Pinecone Console.
The Setup & Deployment section now provides complete and accurate instructions, ensuring new contributors can get started quickly without confusion. All requested changes from your review have been incorporated

[coderabbitai]

Tip

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🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Read the README.md to verify the changes mentioned by the user
cat README.md

Length of output: 8432

---

@Kaustubh1204, excellent work! 🎉 I've verified all the changes you mentioned, and they're implemented perfectly:

✅ Google Custom Search Documentation

• Both GOOGLE_SEARCH_API_KEY and GOOGLE_SEARCH_ENGINE_ID are now documented in the backend .env requirements
• The "How to Obtain API Keys" section is comprehensive with clear, step-by-step instructions for all three services (Groq, Pinecone, and Google CSE)
• The Google CSE guidance includes both API key creation and Search Engine ID setup with direct links to the relevant consoles

✅ Architecture & Flow Updates

• The architecture diagram now explicitly shows the Google Custom Search API node
• The data flow correctly illustrates: Langgraph -->|Query| GCS and GCS -->|Results| Langgraph

✅ Other Fixes

• The PORT variable reference has been removed
• Pinecone index creation guidance via the Console is now included
• Example .env files are clear and complete

The documentation is now much more accessible for new contributors. They'll be able to get the project up and running without confusion. Great attention to detail! 👏

__  __

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[prakharsingh-74]

I don't think there is need of changing in the documentation of the project, you can close this PR