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@aj47 aj47 commented Apr 7, 2025

This PR refactors the LiteLLM integration to support dynamic selection of inference providers and API keys, replacing the previous hardcoded configuration approach. The LiteLLMClient class now accepts provider and api_key parameters during initialization or per call, enabling flexible runtime behavior. Configuration persistence is updated to store and retrieve selected providers and their key sources via the database layer. The chat completion method dynamically routes requests based on the configured provider, utilizing the correct key.

The test suite is expanded to ensure robustness, including:

  • Unit tests for LiteLLMClient initialization with various provider/api_key inputs, handling invalid cases gracefully.
  • Verification that chat completions are routed to the correct provider and mock litellm calls accordingly.
  • Database tests to confirm saving and loading of provider/api key configurations, covering error scenarios.
  • Integration tests validating API endpoints for creating and updating configurations, and correct end-to-end wiring during agent creation.
  • Fixtures to mock environment variables, secret files, and litellm responses, fully isolating side effects.

Overall, these enhancements enable multi-provider support out of the box and prepare the system for future extensibility in LLM backend management.

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aj47 commented Apr 9, 2025

https://github.com/coderabbitai full review

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aj47 commented Apr 9, 2025

@coderabbitai can you compare this to #149

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coderabbitai bot commented Apr 9, 2025

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🧩 Analysis chain

I'll compare PR #148 with PR #149 for you, but first I need to gather information about PR #149. Let me check that for you.


🏁 Script executed:

#!/bin/bash
# Get information about PR #149
gh pr view 149 --json title,body,state,additions,deletions,changedFiles,files

# Check if PR #149 has specific objectives documented
gh pr view 149 --json comments | jq '.comments[] | select(.body | contains("objectives")) | .body'

# Get a list of files changed in both PRs for comparison
echo "Files changed in PR #148:"
gh pr view 148 --json files | jq '.files[].path'
echo "Files changed in PR #149:"
gh pr view 149 --json files | jq '.files[].path'

Length of output: 2355


Let me analyze both PRs to provide a comparison of their approaches and changes.


🏁 Script executed:

#!/bin/bash
# Let's get a more detailed look at the code changes in both PRs 

# For PR #148, examine test file changes
echo "PR #148 - test_litellm_client.py changes:"
gh pr view 148 --json files | jq '.files[] | select(.path=="tests/test_litellm_client.py") | {additions, deletions}'

# For PR #149, examine core implementation changes
echo "PR #149 - app.py changes:"
gh pr view 149 --json files | jq '.files[] | select(.path=="app.py") | {additions, deletions}'

# Compare the actual implementation approaches
echo "PR #148 file diff - checking LiteLLMClient implementation:"
gh pr diff 148 | grep -A 20 "LiteLLMClient"

echo "PR #149 file diff - checking LiteLLMClient implementation:"
gh pr diff 149 | grep -A 20 "LiteLLMClient"

# Get PR #148 description for more context
echo "PR #148 description:"
gh pr view 148 --json body | jq '.body'

Length of output: 12507


Let me look more deeply at the implementation changes in both PRs to understand how they differ.


🏁 Script executed:

#!/bin/bash
# Get the specific implementation of the LiteLLMClient in both PRs

# Check the actual test file contents to understand implementation differences
echo "Looking at test_litellm_client.py in PR #148:"
gh pr view 148 --json files | jq '.files[] | select(.path=="tests/test_litellm_client.py") | .patch' | grep -A 50 "def test_"

echo "Looking at LiteLLM implementation in actual app code (PR #149):"
gh pr view 149 --json files | jq '.files[] | select(.path=="app.py") | .patch' | grep -A 20 "LiteLLMClient"

# Check if we can find the actual LiteLLMClient implementation
echo "Checking for core LiteLLMClient implementation in files:"
gh pr diff 148 | grep -n -A 3 -B 3 "class LiteLLMClient"
gh pr diff 149 | grep -n -A 3 -B 3 "class LiteLLMClient"

# Let's also check database changes in PR #148
echo "Database changes in PR #148:"
gh pr view 148 --json files | jq '.files[] | select(.path=="tests/test_database.py") | .patch' | head -n 50

Length of output: 896


Let me look for the implementation of LiteLLMClient class and compare how both PRs approach dynamic provider configuration.


🏁 Script executed:

#!/bin/bash
# Search for litellm_client.py in the repository and check both PRs
echo "Searching for litellm_client.py:"
fd litellm_client.py

# Let's see if we can find the core implementation in either PR
echo "PR #148 changes to litellm_client.py (if any):"
gh pr diff 148 | grep -A 50 -B 5 "litellm_client.py" | head -n 100

echo "PR #149 changes to litellm_client.py (if any):"
gh pr diff 149 | grep -A 50 -B 5 "litellm_client.py" | head -n 100

# Let's check app.py changes in PR #148
echo "PR #148 changes to app.py:"
gh pr view 148 --json files | jq '.files[] | select(.path=="app.py") | .patch' | head -n 50

# Check database changes in PR #148
echo "Database file changes in PR #148:"
gh pr diff 148 | grep -A 20 "database.py"

Length of output: 5968


@aj47 Based on my analysis of both PR #148 and PR #149, here's a comparison of their approaches:

PR #148 vs PR #149 Comparison

Core Focus

Implementation Approach

Test Coverage

Recommendation

PR #148 appears to be more comprehensive and robust with better test coverage and proper database integration for configuration persistence. It seems to follow better software engineering practices with a test-driven approach and consideration for different API key sources and error scenarios.

Would you like me to look more deeply at any particular aspect of these PRs?

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