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fix(aws): fixed cpu 1
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commit
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@ -4,7 +4,7 @@
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{
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"name": "quivr",
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"image": "253053805092.dkr.ecr.eu-west-3.amazonaws.com/quivr:bada136312ad3497664c3562a36b263d43c89c53",
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"cpu": "512",
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"cpu": "1024",
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"memory": "2048",
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"portMappings": [
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{
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@ -93,7 +93,7 @@
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"requiresCompatibilities": [
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"FARGATE"
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],
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"cpu": "512",
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"cpu": "1024",
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"memory": "2048",
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"runtimePlatform": {
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"cpuArchitecture": "X86_64",
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@ -4,7 +4,7 @@
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{
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"name": "quivr",
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"image": "253053805092.dkr.ecr.eu-west-3.amazonaws.com/quivr:c0ff0301002fe6d043270b26dabcfda797437afc",
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"cpu": "512",
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"cpu": "1024",
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"memory": "2048",
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"portMappings": [
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{
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@ -94,7 +94,7 @@
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"requiresCompatibilities": [
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"FARGATE"
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],
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"cpu": "512",
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"cpu": "1024",
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"memory": "2048",
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"runtimePlatform": {
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"cpuArchitecture": "X86_64",
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@ -85,7 +85,7 @@
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"requiresCompatibilities": [
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"FARGATE"
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],
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"cpu": "512",
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"cpu": "1024",
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"memory": "2048",
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"runtimePlatform": {
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"cpuArchitecture": "X86_64",
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@ -12,7 +12,6 @@ def create_embedding_for_document(
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neurons = Neurons()
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doc = DocumentSerializable.from_json(doc_with_metadata)
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created_vector = neurons.create_vector(doc, user_openai_api_key)
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# add_usage(stats_db, "embedding", "audio", metadata={"file_name": file_meta_name,"file_type": ".txt", "chunk_size": chunk_size, "chunk_overlap": chunk_overlap})
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database = get_supabase_db()
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database.set_file_sha_from_metadata(file_sha1)
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