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Yes, I can help you with the required Pinecone dimensions, pod type, and metrics. Based on the information provided in the
extract (
https://github.com/jerryjliu/gpt_index/tree/main/examples/vector_indices/PineconeIndexDemo.ipynb), you can create a Pinecone index with the following parameters:
- Dimension: 1536 (for text-embedding-ada-002)
- Metric: "euclidean"
- Pod type: "p1"
Here's the code snippet to create a Pinecone index with these parameters:
pinecone.create_index("quickstart", dimension=1536, metric="euclidean", pod_type="p1")
Keep in mind that these parameters are specific to the example provided in the extract. You may need to adjust them according to your use case and the model you are using.
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Note: you can ask me a follow up question by @ mentioning me again
:speech_balloon:
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