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@m-gie m-gie commented May 20, 2025

Summary by CodeRabbit

  • New Features

    • Introduced a new workflow for generating AI-powered interviews, offering users a guided, multi-step conversation to set up and confirm interview generation.
  • Improvements

    • Enhanced reliability and clarity of interview generation by explicitly handling message flows during the process.
  • Chores

    • Updated a core dependency to improve performance and compatibility.

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coderabbitai bot commented May 20, 2025

Walkthrough

A new workflow constant named generator was introduced in the constants module, defining a multi-step conversational flow for generating interviews. The Agent component was updated to utilize this new workflow and to explicitly specify client and server message arrays in calls to vapi.start. The @vapi-ai/web dependency was upgraded to version ^2.3.0.

Changes

File(s) Change Summary
constants/index.ts Added exported constant generator, a multi-node workflow for generating interviews.
components/Agent.tsx Updated imports to include generator; modified vapi.start calls to use new workflow and explicit message arrays.
package.json Upgraded "@vapi-ai/web" dependency from ^2.2.4 to ^2.3.0.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant AgentComponent
    participant vapi
    participant GeneratorWorkflow
    participant API

    User->>AgentComponent: Initiate "generate" action
    AgentComponent->>vapi: start(undefined, {clientMessages, serverMessages, variableValues}, generator)
    vapi->>GeneratorWorkflow: Begin workflow
    GeneratorWorkflow->>User: Greet and extract interview variables
    GeneratorWorkflow->>API: POST /api/vapi/generate with variables
    API-->>GeneratorWorkflow: Respond with interview data
    GeneratorWorkflow->>User: Inform about generation and confirm
    GeneratorWorkflow->>User: Thank you and end conversation
Loading

Poem

In the warren of code, a new path unfurled,
A generator workflow hops into the world.
With messages clear and dependencies anew,
Interviews are crafted, just for you!
Version bumps and flows refined—
A rabbit’s delight, in code well-aligned.
🐇✨

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npm error https://github.com/npm/cli/issues
npm error A complete log of this run can be found in: /.npm/_logs/2025-05-20T14_04_49_666Z-debug-0.log

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Actionable comments posted: 2

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
Cache: Disabled due to data retention organization setting
Knowledge Base: Disabled due to data retention organization setting

📥 Commits

Reviewing files that changed from the base of the PR and between 96d01db and a342806.

⛔ Files ignored due to path filters (1)
  • package-lock.json is excluded by !**/package-lock.json
📒 Files selected for processing (3)
  • components/Agent.tsx (3 hunks)
  • constants/index.ts (2 hunks)
  • package.json (1 hunks)
🧰 Additional context used
🧬 Code Graph Analysis (1)
components/Agent.tsx (2)
lib/vapi.sdk.ts (1)
  • vapi (3-3)
constants/index.ts (1)
  • generator (100-292)
🔇 Additional comments (5)
package.json (1)

16-16: Package dependency upgrade looks good.

The @vapi-ai/web package has been updated from version ^2.2.4 to ^2.3.0. This update is aligned with the implementation of the new workflow system and explicit message arrays in Agent.tsx.

components/Agent.tsx (3)

9-9: Import statement updated correctly to include the new workflow.

The import statement now correctly includes both the new generator workflow constant alongside the existing interviewer constant.


121-133: Implementation of the new workflow system for interview generation.

The code now uses the declarative workflow approach instead of relying on an external workflow ID. This improves code maintainability by keeping the workflow definition within the codebase.

The explicit clientMessages and serverMessages arrays follow best practices for the updated Vapi SDK.


146-147: Consistent message handling for both workflow types.

The non-generate case now also uses explicit message arrays, maintaining consistency across different workflow types and aligning with the SDK's best practices.

constants/index.ts (1)

100-292: Well-structured workflow for interview generation.

The new generator workflow is well-designed with:

  • Clear conversation nodes for user interaction
  • Proper variable extraction for interview setup
  • An API request to generate the interview content
  • Appropriate transitions between nodes using AI-driven conditions
  • Clean completion with user notification and hangup

The workflow design follows a logical conversation flow and properly handles all required user inputs.

Comment on lines +195 to +199
userid: {
type: "string",
description: "",
value: "{{ userid }}",
},
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💡 Verification agent

🧩 Analysis chain

Verify user ID handling in the API request.

The workflow passes userid to the API, but make sure the backend API at /api/vapi/generate correctly handles and validates this user identifier to prevent potential security issues.


🏁 Script executed:

#!/bin/bash
# Check how the API validates user IDs
fd "api/vapi/generate" --type f | xargs rg -A 10 -B 5 "userid"

Length of output: 3671


Add proper validation and authentication for userid in the generate route

The handler in app/api/vapi/generate/route.ts currently does:

const { type, role, level, techstack, amount, userid } = await request.json();
// …  
const interview = {
  // …
  userId: userid,
  // …
};
await db.collection("interviews").add(interview);

There’s no check that userid is well-formed or that it matches an authenticated user. To prevent spoofing or injection:

  • Enforce authentication (e.g. via session or JWT) and derive userId from the auth context rather than client payload.
  • If you must accept it in the body, validate its format (UUID, Firebase UID, etc.) and verify the user exists.
  • Sanitize or whitelist allowed characters/lengths to guard against injection attacks.

Files to update:

  • app/api/vapi/generate/route.ts – around the JSON destructuring and before writing to Firestore.

Please implement these checks before persisting any interview data.

🤖 Prompt for AI Agents
In app/api/vapi/generate/route.ts around the lines where the request JSON is
destructured, the userid from the client payload is used directly without
validation or authentication. To fix this, enforce authentication by extracting
the userId from the authenticated session or JWT token instead of the request
body. If accepting userid from the body is unavoidable, validate its format
strictly (e.g., UUID or Firebase UID), check that the user exists in the
database, and sanitize the input to prevent injection. Implement these checks
before creating and saving the interview data to ensure userid integrity and
security.

},
},
method: "POST",
url: `${process.env.NEXT_PUBLIC_BASE_URL}/api/vapi/generate`,
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💡 Verification agent

🧩 Analysis chain

Ensure environment variable is properly defined.

The API URL uses ${process.env.NEXT_PUBLIC_BASE_URL} - make sure this environment variable is properly defined in all environments where this code will run.


🏁 Script executed:

#!/bin/bash
# Check for environment variable definition or usage
rg "NEXT_PUBLIC_BASE_URL" --type ts --type js

Length of output: 132


Define and Configure NEXT_PUBLIC_BASE_URL in All Environments

We’ve only located the usage at constants/index.ts:167 and no committed definitions for NEXT_PUBLIC_BASE_URL. To prevent runtime errors:

  • Add NEXT_PUBLIC_BASE_URL to your environment files (e.g.,
    .env.development
    .env.production
    .env.example
    NEXT_PUBLIC_BASE_URL=https://your-domain.com
  • Ensure it’s set in your hosting/CI environment (Vercel, Netlify, Docker, etc.).
  • Optionally, guard against undefined values in code:
    // constants/index.ts (line 167)
    const baseUrl = process.env.NEXT_PUBLIC_BASE_URL ?? "";
    export const API_URL = `${baseUrl}/api/vapi/generate`;

Please update your .env files and deployment settings accordingly.

🤖 Prompt for AI Agents
In constants/index.ts at line 167, the environment variable NEXT_PUBLIC_BASE_URL
is used but not defined in any environment files. To fix this, add
NEXT_PUBLIC_BASE_URL with the appropriate URL value to all your environment
files such as .env.development, .env.production, and .env.example. Also, ensure
this variable is set in your deployment environment settings like Vercel or
Netlify. Optionally, update the code to safely handle undefined values by
assigning a default empty string before constructing the API URL.

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6 participants