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LarFii
2024-11-11 10:45:22 +08:00
parent 958cb9627e
commit d0c1844264
10 changed files with 35 additions and 33 deletions
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README.md
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@@ -196,7 +196,7 @@ rag = LightRAG(
### Using Neo4J for Storage
* For production level scenarios you will most likely want to leverage an enterprise solution
* for KG storage. Running Neo4J in Docker is recommended for seamless local testing.
* for KG storage. Running Neo4J in Docker is recommended for seamless local testing.
* See: https://hub.docker.com/_/neo4j
@@ -209,7 +209,7 @@ When you launch the project be sure to override the default KG: NetworkS
by specifying kg="Neo4JStorage".
# Note: Default settings use NetworkX
#Initialize LightRAG with Neo4J implementation.
#Initialize LightRAG with Neo4J implementation.
WORKING_DIR = "./local_neo4jWorkDir"
rag = LightRAG(
@@ -503,8 +503,8 @@ pip install fastapi uvicorn pydantic
export RAG_DIR="your_index_directory" # Optional: Defaults to "index_default"
export OPENAI_BASE_URL="Your OpenAI API base URL" # Optional: Defaults to "https://api.openai.com/v1"
export OPENAI_API_KEY="Your OpenAI API key" # Required
export LLM_MODEL="Your LLM model" # Optional: Defaults to "gpt-4o-mini"
export EMBEDDING_MODEL="Your embedding model" # Optional: Defaults to "text-embedding-3-large"
export LLM_MODEL="Your LLM model" # Optional: Defaults to "gpt-4o-mini"
export EMBEDDING_MODEL="Your embedding model" # Optional: Defaults to "text-embedding-3-large"
```
3. Run the API server:
@@ -923,4 +923,3 @@ primaryClass={cs.IR}
}
```
**Thank you for your interest in our work!**