I intended to execute the instruction python main.py -opt Option/Method/RAPTOR.yaml -dataset_name HotpotQA, but an error occurred. The traceback information is as follows:
Traceback (most recent call last):
File "/home/ldy/GraphRAG/main.py", line 77, in <module>
asyncio.run(digimon.insert(corpus))
File "/opt/conda/envs/digimon/lib/python3.10/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/opt/conda/envs/digimon/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
return future.result()
File "/home/ldy/GraphRAG/Core/GraphRAG.py", line 243, in insert
await self.entities_vdb.build_index(await self.graph.nodes_data(),node_metadata, False)
File "/home/ldy/GraphRAG/Core/Index/BaseIndex.py", line 26, in build_index
await self._update_index(elements, meta_data)
File "/home/ldy/GraphRAG/Core/Index/FaissIndex.py", line 83, in _update_index
vector_store = FaissVectorStore(faiss_index=faiss.IndexHNSWFlat(self.embedding_model.dimensions, 32))
File "/opt/conda/envs/digimon/lib/python3.10/site-packages/pydantic/main.py", line 984, in __getattr__
raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')
AttributeError: 'OllamaEmbedding' object has no attribute 'dimensions'
To address this issue, I attempted to add code to the _try_set_model_and_batch_size function as follows:
def _try_set_model_and_batch_size(params: dict, config):
"""Set the model_name and embed_batch_size only when they are specified."""
if config.embedding.model:
params["model_name"] = config.embedding.model
if config.embedding.embed_batch_size:
params["embed_batch_size"] = config.embedding.embed_batch_size
if config.embedding.dimensions:
params["dimensions"] = config.embedding.dimensions
print(f"setting dimensions for model is {params['dimensions']}") # **the added code**
def _raise_for_key(self, key: Any):
raise ValueError(f"The embedding type is currently not supported: `{type(key)}`, {key}")Although the output "setting dimensions for model is 1024" was successfully printed, the code still did not execute correctly and the aforementioned error persisted.
I intended to execute the instruction
python main.py -opt Option/Method/RAPTOR.yaml -dataset_name HotpotQA, but an error occurred. The traceback information is as follows:To address this issue, I attempted to add code to the
_try_set_model_and_batch_sizefunction as follows:Although the output "setting dimensions for model is 1024" was successfully printed, the code still did not execute correctly and the aforementioned error persisted.