upgrade graphrag-sdk and move to litellm #40
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WalkthroughThe pull request introduces changes to the project's model configuration and dependency management. In the Changes
Sequence DiagramsequenceDiagram
participant User
participant LLMAgent as Knowledge Graph Agent
participant LiteModel as LiteModel
User->>LLMAgent: Create Knowledge Graph
LLMAgent->>LiteModel: Initialize with model name
LiteModel-->>LLMAgent: Model Ready
LLMAgent-->>User: Knowledge Graph Prepared
Poem
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Actionable comments posted: 2
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⛔ Files ignored due to path filters (1)
poetry.lockis excluded by!**/*.lock
📒 Files selected for processing (2)
api/llm.py(1 hunks)pyproject.toml(1 hunks)
🧰 Additional context used
🪛 Ruff (0.8.2)
api/llm.py
202-202: Undefined name LiteModel
(F821)
🔇 Additional comments (1)
api/llm.py (1)
208-208: Configuration logic appears sound
The updated model_config references the newly created model object. This is consistent with the dependency change to LiteModel, and no immediate issues are apparent.
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Copilot reviewed 3 out of 3 changed files in this pull request and generated no comments.
Comments suppressed due to low confidence (3)
api/llm.py:4
- [nitpick] The variable name 'model' is generic. It should be renamed to 'lite_model' to be more descriptive.
from graphrag_sdk.models.litellm import LiteModel
api/llm.py:202
- [nitpick] The variable name 'model' is generic. It should be renamed to 'lite_model' to be more descriptive.
model = LiteModel(model_name="gemini/gemini-2.0-flash-exp")
api/llm.py:208
- Ensure that the new behavior introduced by switching to LiteLLM is covered by tests.
model_config=KnowledgeGraphModelConfig.with_model(model)
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🧹 Nitpick comments (1)
api/graph.py (1)
31-31: Consider a more extensible filtering approach.While this change is valid, if the codebase expands the set of unwanted graph suffixes over time, consider centralizing these suffixes in a set or list, making the logic easier to maintain. For instance:
-graphs = [g for g in graphs if not (g.endswith('_git') or g.endswith('_schema'))] +excluded_suffixes = ["_git", "_schema"] +graphs = [g for g in graphs if not any(g.endswith(suffix) for suffix in excluded_suffixes)]
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.env.template (1)
6-6: Add documentation for GEMINI_API_KEYConsider adding a comment above the GEMINI_API_KEY line to explain:
- How to obtain the API key
- Any specific requirements or limitations
- Link to relevant documentation
+# Gemini API key from Google AI Studio (https://makersuite.google.com/app/apikey) GEMINI_API_KEY=<gemini_api_key>
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.env.template(1 hunks)
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.env.template (1)
5-6: Verify if OPENAI_API_KEY is still required
Since the PR objectives mention moving to litellm and the changes introduce GEMINI_API_KEY, please verify if OPENAI_API_KEY is still needed. If not, it should be removed to avoid confusion.
✅ Verification successful
Both OpenAI and Gemini API keys are required
Based on the codebase analysis:
- The project uses LiteLLM as an abstraction layer to support multiple LLM providers
- The dependencies in
poetry.lockandrequirements.txtshow both OpenAI and LiteLLM are required dependencies - The code in
api/llm.pyshows the system is configured to use Gemini by default (model_name = os.getenv('MODEL_NAME', 'gemini/gemini-2.0-flash-exp')) but can be switched to use other providers through LiteLLM - Both API keys should be kept in the template to support this flexibility
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for OpenAI API key usage in the codebase
echo "Checking for OpenAI API key usage..."
rg -l "OPENAI_API_KEY"
# Search for OpenAI related imports or configurations
echo "Checking for OpenAI related code..."
rg -l "openai\."
Length of output: 205
Script:
#!/bin/bash
# Let's try a more comprehensive search for OpenAI and LiteLLM related code
echo "Checking for OpenAI references..."
rg -i "openai"
echo -e "\nChecking for LiteLLM references..."
rg -i "litellm"
echo -e "\nChecking for environment variable usage..."
rg -i "process\.env\.(OPENAI|GEMINI)"
echo -e "\nChecking Python environment variable usage..."
rg -i "os\.environ\.(get)?.*(OPENAI|GEMINI)"
echo -e "\nLooking for configuration files..."
fd -e json -e yaml -e yml -e config
Length of output: 2580
Script:
#!/bin/bash
# Let's check the LLM implementation to understand how the API keys are used
echo "Checking LLM implementation..."
cat api/llm.py
echo -e "\nChecking for environment variable loading..."
rg -i "load_dotenv|getenv|environ" -A 3 -B 3
Length of output: 12356
Summary by CodeRabbit
graphrag-sdkto version 0.4.1.