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@kevinacker kevinacker commented Oct 31, 2025

Overview: This PR introduces mock agent files to simulate data retrieval, which will be used for testing the orchestrator's concurrent execution capabilities.

Changes

  • Created a new directory app/services/agents/ to house the new agent modules.
  • Implemented price_agent.py, volume_agent.py, and trend_agent.py with an async run(token_id: str) function.
  • Each agent returns simple mock data after a brief simulated delay.
  • These agents will be crucial for developing and verifying the orchestrator's ability to handle multiple concurrent tasks.

Summary by CodeRabbit

  • New Features
    • Added backend data retrieval services for token market data including pricing, trend analysis, and trading volume metrics.

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coderabbitai bot commented Oct 31, 2025

Important

Review skipped

Review was skipped as selected files did not have any reviewable changes.

💤 Files selected but had no reviewable changes (1)
  • backend/app/services/agents/init.py
⛔ Files ignored due to path filters (2)
  • backend/app/services/agents/__pycache__/__init__.cpython-313.pyc is excluded by !**/*.pyc
  • backend/app/services/agents/__pycache__/volume_agent.cpython-313.pyc is excluded by !**/*.pyc

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Walkthrough

Three new asynchronous agent modules are introduced: price_agent.py, trend_agent.py, and volume_agent.py. Each module provides a run(token_id: str) function that simulates fetching market data for a given token by awaiting a brief delay and returning mock data dictionaries.

Changes

Cohort / File(s) Summary
New agent modules
backend/app/services/agents/price_agent.py, backend/app/services/agents/trend_agent.py, backend/app/services/agents/volume_agent.py
Added three new async agent modules, each containing a run(token_id: str) function that simulates data fetching with a 0.1s delay and returns mock market data (price/trend/volume info with token_id).

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~5 minutes

  • All three modules follow an identical, straightforward pattern: simple async functions with minimal logic
  • Homogeneous changes reduce review complexity despite multiple files
  • No complex control flow, external dependencies, or intricate business logic

Possibly related PRs

Suggested reviewers

  • felixjordandev

Poem

🐰 Three new agents hop into the fold,
Price and trend and volume bold,
Each awaits their moment true,
Mock data flowing, fresh and new!
The warren grows, where markets are told! 📊

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)
Check name Status Explanation
Description Check ✅ Passed Check skipped - CodeRabbit’s high-level summary is enabled.
Title Check ✅ Passed The pull request title "Feat: Add mock agents for orchestrator concurrent execution testing" directly and accurately summarizes the main changes in the changeset. The PR adds three new mock agent modules (price_agent.py, trend_agent.py, and volume_agent.py) designed specifically for testing the orchestrator's concurrent execution capabilities, which aligns perfectly with the title's content. The title is concise, uses clear language that conveys meaningful information, and provides sufficient context for a developer scanning the commit history to understand the primary purpose of the change.
Docstring Coverage ✅ Passed Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

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Actionable comments posted: 1

🧹 Nitpick comments (3)
backend/app/services/agents/price_agent.py (1)

1-8: LGTM! Clean mock implementation.

The mock agent correctly simulates async data fetching with a brief delay and returns appropriate mock data. The implementation is straightforward and serves the testing objectives well.

Consider adding a return type hint for better type safety:

-async def run(token_id: str):
+async def run(token_id: str) -> dict[str, str | float]:
     """
     Mocks fetching price data for a given token.
     """
backend/app/services/agents/trend_agent.py (1)

1-8: LGTM! Consistent with the agent pattern.

The trend agent follows the same clean pattern as the price agent and correctly returns mock trend data.

Consider adding a return type hint:

-async def run(token_id: str):
+async def run(token_id: str) -> dict[str, str | float]:
     """
     Mocks fetching trend data for a given token.
     """
backend/app/services/agents/volume_agent.py (1)

1-8: LGTM! Completes the agent trio.

The volume agent correctly implements the mock pattern consistent with the other agents.

Consider adding a return type hint:

-async def run(token_id: str):
+async def run(token_id: str) -> dict[str, str | float]:
     """
     Mocks fetching volume data for a given token.
     """
📜 Review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between ce9b3bd and 888bbf4.

📒 Files selected for processing (3)
  • backend/app/services/agents/price_agent.py (1 hunks)
  • backend/app/services/agents/trend_agent.py (1 hunks)
  • backend/app/services/agents/volume_agent.py (1 hunks)
🧰 Additional context used
🧬 Code graph analysis (3)
backend/app/services/agents/volume_agent.py (2)
backend/app/services/agents/price_agent.py (1)
  • run (3-8)
backend/app/services/agents/trend_agent.py (1)
  • run (3-8)
backend/app/services/agents/price_agent.py (2)
backend/app/services/agents/trend_agent.py (1)
  • run (3-8)
backend/app/services/agents/volume_agent.py (1)
  • run (3-8)
backend/app/services/agents/trend_agent.py (2)
backend/app/services/agents/price_agent.py (1)
  • run (3-8)
backend/app/services/agents/volume_agent.py (1)
  • run (3-8)

Comment on lines +1 to +8
import asyncio

async def run(token_id: str):
"""
Mocks fetching volume data for a given token.
"""
await asyncio.sleep(0.1) # Simulate a small delay
return {"volume": 987654.32, "token_id": token_id}
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⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Verify the agents directory is a proper Python package.

Since a new directory backend/app/services/agents/ was created, ensure it includes an __init__.py file so Python recognizes it as a package and the orchestrator can properly import these agents.


🏁 Script executed:

#!/bin/bash
# Check if __init__.py exists in the agents directory
fd -t f __init__.py backend/app/services/agents/

Length of output: 0


🏁 Script executed:

#!/bin/bash
# Check if the agents directory exists and list its contents
fd -t f . backend/app/services/agents/ 2>/dev/null || echo "Directory check with fd failed, trying ls..."
ls -la backend/app/services/agents/ 2>/dev/null || echo "agents directory does not exist or is empty"

Length of output: 429


Add __init__.py to backend/app/services/agents/

The agents directory is missing an __init__.py file. Without it, Python won't recognize this as a package and the orchestrator won't be able to import the agents. Create an empty __init__.py file in backend/app/services/agents/.

🤖 Prompt for AI Agents
In backend/app/services/agents/ (lines 1-8 reference file volume_agent.py), the
directory lacks an __init__.py so Python won't treat it as a package; create an
empty file named __init__.py in backend/app/services/agents/ (touch
backend/app/services/agents/__init__.py), add and commit it to the repo so the
orchestrator can import the agent modules.

@felixjordandev felixjordandev merged commit 5cf25f9 into main Oct 31, 2025
1 check passed
@felixjordandev felixjordandev deleted the feat/mock-agents-for-orchestrator-testing branch October 31, 2025 01:12
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3 participants