text:
Network Agent demo doesn't respond

Setup arch on MacOS 15.1 with Docker. Following steps for Network Agent demo and after entering tell me what you can help me with in the UI, nothing happens.
Logs from archgw logs --follow below:
archgw-1  | [2024-10-30 15:44:57.207][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: ||| create_http_context called with context_id: 3 |||
archgw-1  | [2024-10-30 15:44:57.207][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: llm provider hint: None
archgw-1  | [2024-10-30 15:44:57.208][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: no llm provider found for hint, using default llm provider
archgw-1  | [2024-10-30 15:44:57.208][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: selected llm: OpenAI
archgw-1  | [2024-10-30 15:44:57.208][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: S[3] req_headers=[(":authority", "host.docker.internal:10000"), (":path", "/v1/chat/completions"), (":method", "POST"), (":scheme", "https"), ("accept-encoding", "gzip, deflate"), ("accept", "application/json"), ("content-type", "application/json"), ("user-agent", "OpenAI/Python 1.51.0"), ("x-stainless-lang", "python"), ("x-stainless-package-version", "1.51.0"), ("x-stainless-os", "Linux"), ("x-stainless-arch", "arm64"), ("x-stainless-runtime", "CPython"), ("x-stainless-runtime-version", "3.10.15"), ("x-stainless-async", "false"), ("x-stainless-retry-count", "0"), ("x-forwarded-proto", "https"), ("x-request-id", "e85ca1c1-53ee-4bdd-b074-7fa7b01988d8"), ("x-arch-upstream", "arch_llm_listener"), ("authorization", "Bearer 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")]
archgw-1  | [2024-10-30 15:44:57.209][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: Missing input guard. Making inline call to retrieve
archgw-1  | [2024-10-30 15:44:57.209][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: dispatching http call with args=CallArgs { upstream: "arch_internal", path: "/embeddings", headers: [("x-arch-upstream", "model_server"), (":method", "POST"), (":path", "/embeddings"), (":authority", "model_server"), ("content-type", "application/json"), ("x-envoy-max-retries", "3"), ("x-envoy-upstream-rq-timeout-ms", "60000"), ("x-request-id", "e85ca1c1-53ee-4bdd-b074-7fa7b01988d8")], trailers: [], timeout: 5s } context=StreamCallContext { response_handler_type: GetEmbeddings, user_message: Some("tell me what you can help me with?"), prompt_target_name: None, request_body: ChatCompletionsRequest { model: "gpt-3.5-turbo", messages: [Message { role: "user", content: Some("tell me what you can help me with?"), model: None, tool_calls: None }], tools: None, stream: true, stream_options: Some(StreamOptions { include_usage: true }), metadata: None }, tool_calls: None, similarity_scores: None, upstream_cluster: None, upstream_cluster_path: None }
archgw-1  | [2024-10-30 15:44:57.210][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: ||| create_http_context called with context_id: 3 |||
archgw-1  | [2024-10-30 15:44:57.210][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: llm provider hint: None
archgw-1  | [2024-10-30 15:44:57.210][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: no llm provider found for hint, using default llm provider
archgw-1  | [2024-10-30 15:44:57.210][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: selected llm: OpenAI
archgw-1  | [2024-10-30 15:44:57.210][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: S[3] req_headers=[(":authority", "arch_llm_listener"), (":path", "/v1/chat/completions"), (":method", "POST"), (":scheme", "https"), ("accept-encoding", "gzip, deflate"), ("accept", "application/json"), ("content-type", "application/json"), ("user-agent", "OpenAI/Python 1.51.0"), ("x-stainless-lang", "python"), ("x-stainless-package-version", "1.51.0"), ("x-stainless-os", "Linux"), ("x-stainless-arch", "arm64"), ("x-stainless-runtime", "CPython"), ("x-stainless-runtime-version", "3.10.15"), ("x-stainless-async", "false"), ("x-stainless-retry-count", "0"), ("x-forwarded-proto", "https"), ("x-request-id", "e85ca1c1-53ee-4bdd-b074-7fa7b01988d8"), ("x-arch-upstream", "arch_llm_listener"), ("x-arch-llm-provider", "OpenAI"), ("authorization", "Bearer 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")]
2024-10-30 08:44:57,219 - INFO - Embedding req: input='tell me what you can help me with?' model='katanemo/bge-large-en-v1.5'
2024-10-30 08:44:57,287 - INFO - Embedding Call Complete Time: 0.06710670800021035
archgw-1  | [2024-10-30 15:44:57.290][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: embedding model: katanemo/bge-large-en-v1.5, vector length: 1024
archgw-1  | [2024-10-30 15:44:57.290][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: similarity scores based on description embeddings match: [("reboot_devices", 0.457049393984019), ("device_summary", 0.4756624797098869)]
archgw-1  | [2024-10-30 15:44:57.290][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: dispatching http call with args=CallArgs { upstream: "arch_internal", path: "/zeroshot", headers: [("x-arch-upstream", "model_server"), (":method", "POST"), (":path", "/zeroshot"), (":authority", "model_server"), ("content-type", "application/json"), ("x-envoy-max-retries", "3"), ("x-envoy-upstream-rq-timeout-ms", "60000"), ("x-request-id", "e85ca1c1-53ee-4bdd-b074-7fa7b01988d8")], trailers: [], timeout: 5s } context=StreamCallContext { response_handler_type: ZeroShotIntent, user_message: Some("tell me what you can help me with?"), prompt_target_name: None, request_body: ChatCompletionsRequest { model: "gpt-3.5-turbo", messages: [Message { role: "user", content: Some("tell me what you can help me with?"), model: None, tool_calls: None }], tools: None, stream: true, stream_options: Some(StreamOptions { include_usage: true }), metadata: None }, tool_calls: None, similarity_scores: Some([("reboot_devices", 0.457049393984019), ("device_summary", 0.4756624797098869)]), upstream_cluster: None, upstream_cluster_path: None }
2024-10-30 08:44:57,293 - INFO - zero-shot request: input='tell me what you can help me with?' labels=['reboot_devices', 'device_summary'] model='katanemo/bart-large-mnli'
2024-10-30 08:44:57,787 - INFO - zero-shot taking 0.49322237500018673 seconds
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: zeroshot intent response: ZeroShotClassificationResponse { predicted_class: "device_summary", predicted_class_score: 0.3438539206981659, scores: {"device_summary": 0.3438539206981659, "reboot_devices": 0.16097179055213928}, model: "katanemo/bart-large-mnli" }
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: similarity score: 0.383, intent score: 0.344, description embedding score: 0.476, prompt: tell me what you can help me with?
archgw-1  | [2024-10-30 15:44:57.787][23][info][wasm] [source/extensions/common/wasm/context.cc:1195] wasm log http_config prompt_gateway: no assistant message found, probably first interaction
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: intent score is low or arch assistant is handling the conversation
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: checking for default prompt target
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: default prompt target found
archgw-1  | [2024-10-30 15:44:57.787][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: no prompt target found with similarity score above threshold, using default prompt target
archgw-1  | [2024-10-30 15:44:57.788][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: dispatching http call with args=CallArgs { upstream: "arch_internal", path: "/agent/network_summary", headers: [(":method", "POST"), ("x-arch-upstream", "app_server"), (":path", "/agent/network_summary"), (":authority", "app_server"), ("content-type", "application/json"), ("x-envoy-max-retries", "3"), ("x-envoy-upstream-rq-timeout-ms", "120000"), ("x-request-id", "e85ca1c1-53ee-4bdd-b074-7fa7b01988d8")], trailers: [], timeout: 5s } context=StreamCallContext { response_handler_type: DefaultTarget, user_message: Some("tell me what you can help me with?"), prompt_target_name: Some("network_qa"), request_body: ChatCompletionsRequest { model: "gpt-3.5-turbo", messages: [Message { role: "user", content: Some("tell me what you can help me with?"), model: None, tool_calls: None }], tools: None, stream: true, stream_options: Some(StreamOptions { include_usage: true }), metadata: None }, tool_calls: None, similarity_scores: Some([("reboot_devices", 0.457049393984019), ("device_summary", 0.4756624797098869)]), upstream_cluster: None, upstream_cluster_path: None }
archgw-1  | [2024-10-30 15:44:57.789][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: llm gateway mode, skipping over all prompt targets
archgw-1  | [2024-10-30 15:44:57.789][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: arch => "gpt-3.5-turbo", body: {"model":"gpt-3.5-turbo","messages":[{"role":"user","content":"tell me what you can help me with?"}],"stream":true}
archgw-1  | [2024-10-30 15:44:57.795][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: response received for default target: network_qa
archgw-1  | [2024-10-30 15:44:57.795][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: sending response back to developer: {"choices":[{"message":{"role":"assistant","content":"I am a helpful networking agent, and I can help you get status for network devices or reboot them"},"finish_reason":"completed","index":0}],"model":"network_agent","usage":{"completion_tokens":0}}
archgw-1  | [2024-10-30 15:44:57.795][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: recv [S=3] bytes=250 end_stream=true
archgw-1  | [2024-10-30 15:44:57.795][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: streaming response
archgw-1  | [2024-10-30 15:44:57.795][23][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config prompt_gateway: server error occurred: parsing error in streaming data
archgw-1  | [2024-10-30 15:44:58.134][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=531 end_stream=false
archgw-1  | [2024-10-30 15:44:58.168][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=531 end_stream=false
archgw-1  | [2024-10-30 15:44:58.216][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=1288 end_stream=false
archgw-1  | [2024-10-30 15:44:58.233][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=2044 end_stream=false
archgw-1  | [2024-10-30 15:44:58.257][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=2803 end_stream=false
archgw-1  | [2024-10-30 15:44:58.303][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=3562 end_stream=false
archgw-1  | [2024-10-30 15:44:58.312][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=4078 end_stream=false
archgw-1  | [2024-10-30 15:44:58.344][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=4844 end_stream=false
archgw-1  | [2024-10-30 15:44:58.348][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=5603 end_stream=false
archgw-1  | [2024-10-30 15:44:58.387][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=6116 end_stream=false
archgw-1  | [2024-10-30 15:44:58.408][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=6630 end_stream=false
archgw-1  | [2024-10-30 15:44:58.435][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=7390 end_stream=false
archgw-1  | [2024-10-30 15:44:58.464][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=7902 end_stream=false
archgw-1  | [2024-10-30 15:44:58.504][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=8659 end_stream=false
archgw-1  | [2024-10-30 15:44:58.544][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=9421 end_stream=false
archgw-1  | [2024-10-30 15:44:58.641][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=10176 end_stream=false
archgw-1  | [2024-10-30 15:44:58.670][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=10932 end_stream=false
archgw-1  | [2024-10-30 15:44:58.690][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=13704 end_stream=false
archgw-1  | [2024-10-30 15:44:58.705][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=14459 end_stream=false
archgw-1  | [2024-10-30 15:44:58.705][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: recv [S=3] bytes=15467 end_stream=true
archgw-1  | [2024-10-30 15:44:58.705][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: non streaming response
archgw-1  | [2024-10-30 15:44:58.705][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: invalid response: data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"I"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" can"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" help"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" you"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" with"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" a"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" wide"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" range"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" of"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" tasks"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" and"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" questions"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" including"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" providing"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" information"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" offering"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" advice"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" giving"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" recommendations"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" answering"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" queries"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" assisting"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" with"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" problem"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"-solving"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" engaging"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" in"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" conversation"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" and"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" much"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" more"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" Just"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" let"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" me"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" know"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" what"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" you"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" need"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" help"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" with"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" and"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" I"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" will"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" do"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" my"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" best"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" to"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" assist"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":" you"},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}]}
archgw-1  |
archgw-1  | data: {"id":"chatcmpl-AO5APbZPEb6BikORBvRYfVLIYwrMC","object":"chat.completion.chunk","created":1730303097,"model":"gpt-3.5-turbo-0125","system_fingerprint":null,"choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
archgw-1  |
archgw-1  | data: [DONE]
archgw-1  |
archgw-1  |
archgw-1  | [2024-10-30 15:44:58.705][30][debug][wasm] [source/extensions/common/wasm/context.cc:1192] wasm log http_config llm_gateway: server error occurred: expected value at line 1 column 1

Thanks for putting this issue up. Looking. Last night some of our pypi distributions broke because of a tensorflow update that we didn't catch in testing. We are patch fixing that now and making sure that doesn't happen again. Can you please share the version of the archgw that you are using. archgw --version. This would help us debug this a bit better.

It was installed from pypi using pip and doesn't have the version command. Check pip, it is 0.0.3. Manually built the CLI from source and it is now:
(.venv) ➜  tools git:(main) ✗ archgw --version
archgw cli version: 0.0.5
(.venv) ➜  tools git:(main) ✗ archgw
Arch (The Intelligent Prompt Gateway) CLI

     _                _
    / \    _ __  ___ | |__
   / _ \  | '__|/ __|| '_ \
  / ___ \ | |  | (__ | | | |
 /_/   \_\|_|   \___||_| |_|

Usage: archgw [OPTIONS] COMMAND [ARGS]...

Options:
  --version  Show the archgw cli version and exit.
  --help     Show this message and exit.

Commands:
  build                    Build Arch from source.
  down                     Stops Arch.
  generate-prompt-targets  Generats prompt_targets from python methods.
  logs                     Stream logs from access logs services.
  up                       Starts Arch.
(.venv) ➜  tools git:(main) ✗

Will retest using the new cli install. Also as a note, the logs are wiring the API keys out. Might be worth looking at obfuscating those things even in debug logs.

Absolutely fair on the keys bit. Created a new issue https://github.com/katanemo/arch/issues/234 to fix that. Separately, if you build from source right now, the only thing we know that will cause a failure is that Arch-Function model deployment failed last night. Team reverted the change, but we are seeing intermittent failures. Debugging and will post here, when that is fixed

Several fixes went in today - Looks like the network_agent should be functional now. Justed

authors: dougalb salmanap

repo: katanemo/arch


text:
resizes Cannot adjust selection area size      wavesurfer.regions.js

wavesurfer.js regions plugin 2.2.1 (2019-03-18)
add to
if (this.drag || this.resize) {
e.stopPropagation();
}
Cannot adjust selection area size

Someone taught me how to revise it like this.
Old areas allow coverage of new areas
if (e.target.tagName === "HANDLE") {
e.stopPropagation();
}

this change was added in https://github.com/katspaugh/wavesurfer.js/commit/25a0fb40375379e8330bac41c2a80806e0e9b9c8 by @moritzvieli. Can you check this ticket @moritzvieli?

@chwang9 sorry, I did not fully understand the issue. Can you tell me exactly, how I need to reproduce it? Thanks a lot!

no feedback, closing.

source: gharchive/issue

authors: chwang9 moritzvieli thijstriemstra

license_type: permissive

license_source: github-api


text:
Added Python Program & Fixed a Minor Typo

Added Python Program & Fixed a Minor Typo
I added two simple two python program from my practices in the respected python folder and fixed a minor typo in the main README.md file
Type of change
Please delete options that are not relevant.

[ ] fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation(Corrected a typo)
[ ] My changes generates no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have been merged and published in downstream modules

The readme file has been updated. Kindly make another PR

source: gharchive/pull-request

authors: SulthanNK kaustubhgupta

license: MIT


text:
🛑 Instance 81946 is down

In 2835848, Instance 81946 (https://dev81946.service-now.com/) was down:

HTTP code: 503
Response time: 402 ms

Resolved: Instance 81946 is back up in 59869e2 after 10 minutes.


text:
Uncaught (in promise) TypeError: Cannot read properties of undefined (reading 'addEventListener')

以下のエラーが発生している

発生バージョン
1.1.0
コンテキスト
https://ap-northeast-1.console.aws.amazon.com/console/home?region=ap-northeast-1#
スタック トレース
dist/content.js:10 (無名関数)

v1.1.0 で content-scripts の動く対象が追加されたことが影響している
これまでは AWS Apps のスタートページのみを対象としていたが、AWS マネジメントコンソールも対象に加えたことで
const portalApps = document.getElementsByTagName("portal-application");

この要素が取得できないケースが発生するようになった
修正方針
以下のような判定を入れることになりそう

対象の DOM が見つからない場合
動作対象ページのホワイトリスト化

repo: kawakubox/awsapps-extension


text:
Implement a ReportButton in each Contact field

Description
Currently, we're hiding the ReportButton component in #128 because it has no functionality yet.
This issue is similar to #83, but it's for the ContactPage instead of FaqPage.
Current Tasks

[ ] Research the Google Form URL
[ ] Implement a dynamic URL for the ReportButton
[ ] Re-enable the ReportButton in the ContactPage

Mas @zainfathoni, which Google Form I can use? Let me handle this.

Please correspond in Slack with Mas @baraeb92 and Mas Awe (Ardiwilda) for this matter. Thanks! 🙏

authors: kalwabed zainfathoni


text:
Follow all bluesky accounts found in one click

When you have finished retrieving the bluesky account, press f12 and switch to the console tab; copy the following content and execute it to follow all accounts.
const shadowRoot = document.querySelector("html > plasmo-csui").shadowRoot;
const buttons = shadowRoot.querySelectorAll('.card-actions button');
let index = 0;
const interval = setInterval(() => {
const button = buttons[index];
if (button && button.textContent.trim() === 'Follow on Bluesky') {
button.click();
}
index++;
if (index >= buttons.length) {
clearInterval(interval);
}
}, 100);

Thank you for the workaround. We have added the "Follow All" feature in v1.0.0. If you have access to v1.0.0, please try it out using this button.

Thank you for the workaround. We have added the "Follow All" feature in v1.0.0. If you have access to v1.0.0, please try it out using this button.

This update is not available on Firefox.

Great to see that Follow all feature!
Latest addon released on the firefox addon page is v0.7.2 instead of 1.x and there are not built extensions (xpi & co) in github releases. Could be useful to add addon releases as github releases as well!

authors: John-Enigma drkying jo-chemla kawamataryo

repo: kawamataryo/sky-follower-bridge


text:
🛑 GITHUB is down

In 88bfba8, GITHUB (https://www.githubstatus.com) was down:

HTTP code: 0
Response time: 0 ms

Resolved: GITHUB is back up in 7c40081.

repo: kayketeixeira/upptime


text:
system has hash

-nh : hashが残らなくする
通常はハッシュ値が残る

オプションの話は #1 でしていて内容が被っているから、このイシューはNot-plannedで閉じておく。その代わり、#1 のイシューに同等の内容のコメントをしておくよ。


text:
SFC i18n block breaks debug

I'm currently using VSCode for vue frontend development, and when i add single  block, to any component, IDE debug totally brokes for entire project. I cant find what causes wrong behavior, but  i am pretty sure, that it happens when i add this  block.

This is not issue of vue-i18n-loader.
maybe, I think that it' is issue of vscode. if you use vetur, I think it's is issue of vetur.
Thanks!

authors: kazupon oorooroot

license: mit

license_source: bigquery


text:
Updated #L58 in test.html

The example was showing I'm a small tooltip but In Code Example it was Hover me!
Ref. :

Nice catch!
But actually, this typo is in branch gh-pages (website) on index.html. Would you mind changing there too so I can accept this PR?

okay, as I was making changes through the GitHub website only (patch branches ), so closing this PR and created #160 for that.

authors: Siddhant-K-code kazzkiq


text:
Kafka security parameters configuration

Hi @kbastani
Not sure if this is right place to ask. Great example. Any example or documentation that you can point me to configure security parameters for Kafka. I use Kafka from Confluent Cloud. Thanks in advance.

Hi @ffazil.
I'm not sure if this helps: https://docs.confluent.io/platform/current/connect/security.html#separate-principals

authors: ffazil kbastani

repo: kbastani/pinot-debezium-basic-example


text:
Black tall screenshot for a certain URL

repo to reproduce https://github.com/d668/puppeteer-sharp-test
black tall screen:

I'm getting a new image with your code

i guess it depends on environment.
I will close it, anyway I decided to limit it with viewport height to avoid too long screenshots and it works fine

repo: kblok/puppeteer-sharp


text:
Protocol error(Target.attachToTarget): Target closed. (The remote party closed the WebSocket connection without completing the close handshake.)

Protocol error(Target.attachToTarget): Target closed. (The remote party closed the WebSocket connection without completing the close handshake.)
at PuppeteerSharp.Connection.SendAsync(String method, Object args, Boolean waitForCallback)
at PuppeteerSharp.Connection.SendAsync[T](String method, Object args)
at PuppeteerSharp.Connection.CreateSessionAsync(TargetInfo targetInfo)
at PuppeteerSharp.Target.CreatePageAsync()
at PuppeteerSharp.Browser.CreatePageInContextAsync(String contextId)

using (var browser = await Puppeteer.LaunchAsync(launchOptions))
            {
                try
                {
                    using (var page = await browser.NewPageAsync())

Bug appears in using (var page = await browser.NewPageAsync()) line

Are you using BrowserFetcher to download a browser or using an existing one?
This looks like a wrong Chrome version.

Wrong Chrome version

authors: Saibamen kblok


text:
test/e2e/apibinding/maximalpermissionpolicy: fix e2e test

fixed by @s-urbaniak, thx!
xref: https://github.com/p0lyn0mial/kcp/pull/9

closing in favour of https://github.com/kcp-dev/kcp/pull/2427

repo: kcp-dev/kcp


text:
actualizar el modulo de carrito para cambiar el id_orden_compra por cve_orden_compra

Actualmente recibe un int autoincremental, pero desde el front se genera la cve_orden_compra, un id único que puede ser empleado mejor como llave primaria

delete from orden_compra;
DROP TABLE IF EXISTS carrito;
DROP TABLE IF EXISTS carrito_anuncio;
DROP TABLE IF EXISTS orden_compra;
/*!40101 SET @saved_cs_client     = @@character_set_client /;
/!40101 SET character_set_client = utf8 */;
CREATE TABLE orden_compra (
cve_orden_compra varchar(20) NOT NULL COMMENT 'Atributo que representa la clave alfanumerica que identifica de manera univoca a la orden de compra',
id_usuario int(11) NOT NULL COMMENT 'Atributo que representa el identificador del usuario asociado a la compra',
id_direccion_envio int(11) NOT NULL COMMENT 'Atributo que representa la direccion a donde se enviar la mascota',
id_paqueteria int(11) NOT NULL COMMENT 'Atributo que representa el identificador de la paqueteria asociada a la compra',
id_metodo_pago int(11) NOT NULL COMMENT 'Atributo que representa el identificador del mtodo de pago asociada a la compra',
id_moneda int(11) NOT NULL COMMENT 'Atributo que representa el tipo de moneda involucrada en la compra, por ejemplo, pesos, dolares, etc.',
importe_total decimal(10,2) NOT NULL COMMENT 'Atributo que representa el importe total, es decir, costo de la mascota + costo de paqueteria',
fecha_hora_comprar date NOT NULL COMMENT 'Atributo que representa la fecha y hora en que se realiza la comprar',
estado_envio tinyint(1) NOT NULL COMMENT 'Atributo que representa el estado del envio, los valores validos son 1-En preparacion, 2-En camino, 3-Entregado',
recibo varchar(256) NOT NULL COMMENT 'Atributo que representa el nombre del archivo con el recibo de comprar en pdf',
PRIMARY KEY (cve_orden_compra),
KEY fk_orden_compra_usuario (id_usuario),
KEY fk_orden_compra_direccion_envio (id_direccion_envio),
KEY fk_orden_compra_paqueteria (id_paqueteria),
KEY fk_orden_compra_metodo_pago (id_metodo_pago),
KEY fk_orden_compra_moneda (id_moneda),
CONSTRAINT fk_orden_compra_direccion_envio FOREIGN KEY (id_direccion_envio) REFERENCES direccion (id),
CONSTRAINT fk_orden_compra_metodo_pago FOREIGN KEY (id_metodo_pago) REFERENCES metodo_pago (id),
CONSTRAINT fk_orden_compra_moneda FOREIGN KEY (id_moneda) REFERENCES moneda (id),
CONSTRAINT fk_orden_compra_paqueteria FOREIGN KEY (id_paqueteria) REFERENCES paqueteria (id),
CONSTRAINT fk_orden_compra_usuario FOREIGN KEY (id_usuario) REFERENCES usuario (id)
) ENGINE=InnoDB AUTO_INCREMENT=3 DEFAULT CHARSET=utf8mb4;
CREATE TABLE carrito (
id int(11) NOT NULL AUTO_INCREMENT COMMENT 'Atributo que representa el identificador de un carrito de compras',
id_usuario int(11) NOT NULL COMMENT 'Atributo que representa el identificador del usuario dueño del carrito de compras',
id_anuncio int(11) NOT NULL COMMENT 'Atributo que representa el identificador del anuncio asociado al carrito',
cve_orden_compra varchar(20) NULL COMMENT 'Atributo que representa la clave alfanumerica que identifica de manera univoca a la orden de compra',
PRIMARY KEY (id),
KEY fk_carrito_usuario (id_usuario),
KEY fk_carrito_anuncio (id_anuncio),
KEY fk_carrito_orden_compra (cve_orden_compra),
CONSTRAINT fk_carrito_usuario FOREIGN KEY (id_usuario) REFERENCES usuario (id),
CONSTRAINT fk_carrito_anuncio FOREIGN KEY (id_anuncio) REFERENCES anuncio (id),
CONSTRAINT fk_carrito_orden_compra FOREIGN KEY (cve_orden_compra) REFERENCES orden_compra (cve_orden_compra)
);

gracias Lix!!!

authors: fherevans lixleal

repo: kebblar/petstore-back


text:
Update interactive-kpi-reporting.md

renaming

Jira issue(s): PROOF-XXX

Changes:

@MonikaFeigler jeste tu zmenu prosim udelej i v navigaci. Dik!

authors: MonikaFeigler hhanova

repo: keboola/connection-docs


text:
Disable ECR cleanup

kvůli https://keboola.slack.com/archives/C02CGK5CL/p1560884989026800
Chtělo by to asi zoptimalizovat (nebo možná jen natáhnout timeout). Nicméně ten kód se zatím ani nepoužívá, běží to jen na "dry run" a vypisuje do logu co je ke smazání.

nebo by se daly ty image promazat a treba by to prestalo timeoutovat? :trollface:

Ono to stejně nic nedělá a bylo by docela fajn kdyby ten kód prošel někdo druhej jestli to fakt funguje správně, abychom to pak spustili naostro. Mohl bych ručně projít ECR a trochu to tam promazat, ale asi by to dost trvalo a finančně to zatím nic moc negeneruje. ;o)

authors: JakubMatejka odinuv

repo: keboola/developer-portal


text:
Docs for all branches

Supersedes #2

Mergneme až bude #1 v masteru.

Huh, to nevim, jak jsem to zavřel teda! :D

repo: keboola/php-component


text:
o11y: add Prometheus metric for scaledObject condition array

Proposal
The scaledObject object has a condition attribute that shows an array of conditions the object has passed through. An example:
status:
  conditions:
  - message: ScaledObject is defined correctly and is ready for scaling
    reason: ScaledObjectReady
    status: "True"
    type: Ready
  - message: Scaling is performed because triggers are active
    reason: ScalerActive
    status: "True"
    type: Active
  - message: No fallbacks are active on this scaled object
    reason: NoFallbackFound
    status: "False"
    type: Fallback

I would like to add a Prometheus metric for this which in the core is very similar to the HPA condition metric kube_horizontalpodautoscaler_status_condition (here).
What do you guys think? I am happy to pick this one up when it receives positive feedback from the community.
Use-Case
Show health of scaledObjects and alerting
Anything else?
No response

That's OK for me, @zroubalik @JorTurFer?

Agree

I like this idea as well.

Let's do it @erikkn! Thanks for picking it up.

authors: JorTurFer erikkn tomkerkhove zroubalik

repo: kedacore/keda


text:
ScaledObject CRD missing after keda reinstall

Report
Reinstalled keda doesn't has ScaledObject CRD.
+ rm -rf test
+ helm create test
Creating test
+ cd test
+ tee templates/hpa.yaml
{{- if .Values.autoscaling.enabled }}
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: {{ include "test.fullname" . }}
  namespace: {{ .Release.Namespace}}
spec:
  scaleTargetRef:
    name: {{ include "test.fullname" . }}
  pollingInterval:  {{ .Values.autoscaling.pollingInterval }}
  minReplicaCount:  {{ .Values.autoscaling.minReplicas }}
  maxReplicaCount:  {{ .Values.autoscaling.maxReplicas }}
  triggers:
  - type: cpu
    metadata:
      type: Utilization # Deprecated in favor of trigger.metricType; allowed types are 'Utilization' or 'AverageValue'
      value: "60"
      containerName: "" # Optional. You can use this to target a specific container in a pod
{{- end }}
+ minikube start
😄  minikube v1.28.0 on Linuxmint 21
✨  Automatically selected the docker driver. Other choices: virtualbox, ssh, none
📌  Using Docker driver with root privileges
👍  Starting control plane node minikube in cluster minikube
🚜  Pulling base image ...
🔥  Creating docker container (CPUs=2, Memory=7900MB) ...
🐳  Preparing Kubernetes v1.25.3 on Docker 20.10.20 ...
    ▪ Generating certificates and keys ...
    ▪ Booting up control plane ...
    ▪ Configuring RBAC rules ...
🔎  Verifying Kubernetes components...
    ▪ Using image gcr.io/k8s-minikube/storage-provisioner:v5
🌟  Enabled addons: storage-provisioner, default-storageclass
🏄  Done! kubectl is now configured to use "minikube" cluster and "default" namespace by default
+ kubectl create namespace keda
namespace/keda created
+ helm install keda -n keda kedacore/keda --version 2.9.3
NAME: keda
LAST DEPLOYED: Mon Mar 20 17:54:21 2023
NAMESPACE: keda
STATUS: deployed
REVISION: 1
TEST SUITE: None
+ sleep 60
+ helm install test . --set autoscaling.enabled=true
NAME: test
LAST DEPLOYED: Mon Mar 20 17:55:22 2023
NAMESPACE: default
STATUS: deployed
REVISION: 1
NOTES:
1. Get the application URL by running these commands:
  export POD_NAME=$(kubectl get pods --namespace default -l "app.kubernetes.io/name=test,app.kubernetes.io/instance=test" -o jsonpath="{.items[0].metadata.name}")
  export CONTAINER_PORT=$(kubectl get pod --namespace default $POD_NAME -o jsonpath="{.spec.containers[0].ports[0].containerPort}")
  echo "Visit http://127.0.0.1:8080 to use your application"
  kubectl --namespace default port-forward $POD_NAME 8080:$CONTAINER_PORT
+ sleep 60
+ kubectl get scaledobject
NAME   SCALETARGETKIND      SCALETARGETNAME   MIN   MAX   TRIGGERS   AUTHENTICATION   READY   ACTIVE   FALLBACK   AGE
test   apps/v1.Deployment   test              1     100   cpu                         True    True     Unknown    60s
+ kubectl get hpa
NAME            REFERENCE         TARGETS         MINPODS   MAXPODS   REPLICAS   AGE
keda-hpa-test   Deployment/test   <unknown>/60%   1         100       1          60s
+ helm delete keda -n keda
release "keda" uninstalled
+ sleep 60
+ kubectl get crd
NAME                    CREATED AT
scaledobjects.keda.sh   2023-03-20T16:54:21Z
+ sleep 60
+ helm install keda -n keda kedacore/keda --version 2.9.3
NAME: keda
LAST DEPLOYED: Mon Mar 20 17:58:24 2023
NAMESPACE: keda
STATUS: deployed
REVISION: 1
TEST SUITE: None
+ sleep 10
+ kubectl get crd
NAME                                    CREATED AT
clustertriggerauthentications.keda.sh   2023-03-20T16:58:25Z
scaledjobs.keda.sh                      2023-03-20T16:58:25Z
scaledobjects.keda.sh                   2023-03-20T16:54:21Z            <==== now its here
triggerauthentications.keda.sh          2023-03-20T16:58:25Z
+ sleep 60
+ kubectl get crd
NAME                                    CREATED AT
clustertriggerauthentications.keda.sh   2023-03-20T16:58:25Z
scaledjobs.keda.sh                      2023-03-20T16:58:25Z            <==== and now its missing
triggerauthentications.keda.sh          2023-03-20T16:58:25Z

Expected Behavior
Expect to keep the existing ScaledObject.
Actual Behavior
ScaledObject CRD is missing (disapears) after (re)deployment.
Steps to Reproduce the Problem
Here is a test script to reproduce the problem:
#!/bin/bash
set -x
rm -rf test;helm create test; cd test
tee templates/hpa.yaml << EOF
{{- if .Values.autoscaling.enabled }}
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: {{ include "test.fullname" . }}
  namespace: {{ .Release.Namespace}}
spec:
  scaleTargetRef:
    name: {{ include "test.fullname" . }}
  pollingInterval:  {{ .Values.autoscaling.pollingInterval }}
  minReplicaCount:  {{ .Values.autoscaling.minReplicas }}
  maxReplicaCount:  {{ .Values.autoscaling.maxReplicas }}
  triggers:
  - type: cpu
    metadata:
      type: Utilization # Deprecated in favor of trigger.metricType; allowed types are 'Utilization' or 'AverageValue'
      value: "60"
      containerName: "" # Optional. You can use this to target a specific container in a pod
{{- end }}
EOF
minikube start
kubectl create namespace keda
helm install keda -n keda kedacore/keda --version 2.9.3
sleep 60
helm install test . --set autoscaling.enabled=true
sleep 60
kubectl get scaledobject
kubectl get hpa

helm delete keda -n keda
sleep 60
kubectl get crd
sleep 60

helm install keda -n keda kedacore/keda --version 2.9.3
sleep 10
kubectl get crd
sleep 60
kubectl get crd

kubectl logs -n keda $(kubectl get pods -n keda -l "app.kubernetes.io/component=operator,app.kubernetes.io/instance=keda" -o jsonpath="{.items[0].metadata.name}")

Logs from KEDA operator
I0320 16:58:29.995313       1 request.go:682] Waited for 1.041706036s due to client-side throttling, not priority and fairness, request: GET:https://10.96.0.1:443/apis/autoscaling/v1?timeout=32s
2023-03-20T16:58:30Z    INFO    controller-runtime.metrics      Metrics server is starting to listen    {"addr": ":8080"}
2023-03-20T16:58:30Z    INFO    setup   Starting manager
2023-03-20T16:58:30Z    INFO    setup   KEDA Version: 2.9.2
2023-03-20T16:58:30Z    INFO    setup   Git Commit: 9bc3f66578a08cdfe084468ea3ef998fa6bf3bb0
2023-03-20T16:58:30Z    INFO    setup   Go Version: go1.18.8
2023-03-20T16:58:30Z    INFO    setup   Go OS/Arch: linux/amd64
2023-03-20T16:58:30Z    INFO    setup   Running on Kubernetes 1.25      {"version": "v1.25.3"}
2023-03-20T16:58:30Z    INFO    Starting server {"kind": "health probe", "addr": "[::]:8081"}
I0320 16:58:30.348653       1 leaderelection.go:248] attempting to acquire leader lease keda/operator.keda.sh...
2023-03-20T16:58:30Z    INFO    Starting server {"path": "/metrics", "kind": "metrics", "addr": "[::]:8080"}
I0320 16:58:46.362875       1 leaderelection.go:258] successfully acquired lease keda/operator.keda.sh
2023-03-20T16:58:46Z    INFO    grpc_server     Starting Metrics Service gRPC Server    {"address": ":9666"}
2023-03-20T16:58:46Z    INFO    Starting EventSource    {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "source": "kind source: *v1alpha1.ScaledObject"}
2023-03-20T16:58:46Z    INFO    Starting EventSource    {"controller": "scaledjob", "controllerGroup": "keda.sh", "controllerKind": "ScaledJob", "source": "kind source: *v1alpha1.ScaledJob"}
2023-03-20T16:58:46Z    INFO    Starting EventSource    {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "source": "kind source: *v2.HorizontalPodAutoscaler"}
2023-03-20T16:58:46Z    INFO    Starting Controller     {"controller": "scaledjob", "controllerGroup": "keda.sh", "controllerKind": "ScaledJob"}
2023-03-20T16:58:46Z    INFO    Starting EventSource    {"controller": "triggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "TriggerAuthentication", "source": "kind source: *v1alpha1.TriggerAuthentication"}
2023-03-20T16:58:46Z    INFO    Starting Controller     {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject"}
2023-03-20T16:58:46Z    INFO    Starting Controller     {"controller": "triggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "TriggerAuthentication"}
2023-03-20T16:58:46Z    INFO    Starting EventSource    {"controller": "clustertriggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "ClusterTriggerAuthentication", "source": "kind source: *v1alpha1.ClusterTriggerAuthentication"}
2023-03-20T16:58:46Z    INFO    Starting Controller     {"controller": "clustertriggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "ClusterTriggerAuthentication"}
2023-03-20T16:58:46Z    INFO    Starting workers        {"controller": "triggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "TriggerAuthentication", "worker count": 1}
2023-03-20T16:58:46Z    INFO    Starting workers        {"controller": "clustertriggerauthentication", "controllerGroup": "keda.sh", "controllerKind": "ClusterTriggerAuthentication", "worker count": 1}
2023-03-20T16:58:46Z    INFO    Starting workers        {"controller": "scaledjob", "controllerGroup": "keda.sh", "controllerKind": "ScaledJob", "worker count": 1}
2023-03-20T16:58:46Z    INFO    Starting workers        {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "worker count": 5}
2023-03-20T16:58:46Z    INFO    Reconciling ScaledObject        {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "ScaledObject": {"name":"test","namespace":"default"}, "namespace": "default", "name": "test", "reconcileID": "5e90b7c5-e34
0-4528-8fb0-070fbe3e196a"}
2023-03-20T16:58:46Z    INFO    Successfully finalized ScaledObject     {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "ScaledObject": {"name":"test","namespace":"default"}, "namespace": "default", "name": "test", "reconcileID": "5e90
b7c5-e340-4528-8fb0-070fbe3e196a"}
2023-03-20T16:58:46Z    INFO    Reconciling ScaledObject        {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "ScaledObject": {"name":"test","namespace":"default"}, "namespace": "default", "name": "test", "reconcileID": "12f79e95-7ce
a-4c1a-8b0a-6efe0c48a1df"}
2023-03-20T16:58:46Z    ERROR   Failed to update ScaledObject after removing a finalizer        {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "ScaledObject": {"name":"test","namespace":"default"}, "namespace": "default", "name": "tes
t", "reconcileID": "12f79e95-7cea-4c1a-8b0a-6efe0c48a1df", "finalizer": "finalizer.keda.sh", "error": "Operation cannot be fulfilled on scaledobjects.keda.sh \"test\": StorageError: invalid object, Code: 4, Key: /registry/keda.sh/scaledobjects/default/test, ResourceVersion: 0, Addi
tionalErrorMsg: Precondition failed: UID in precondition: a65118f8-97d1-4a47-8e9e-a72d122a0d90, UID in object meta: "}
github.com/kedacore/keda/v2/controllers/keda.(*ScaledObjectReconciler).finalizeScaledObject
        /workspace/controllers/keda/scaledobject_finalizer.go:78
github.com/kedacore/keda/v2/controllers/keda.(*ScaledObjectReconciler).Reconcile
        /workspace/controllers/keda/scaledobject_controller.go:158
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).Reconcile
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:121
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).reconcileHandler
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:320
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).processNextWorkItem
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:273
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).Start.func2.2
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:234
2023-03-20T16:58:46Z    ERROR   Reconciler error        {"controller": "scaledobject", "controllerGroup": "keda.sh", "controllerKind": "ScaledObject", "ScaledObject": {"name":"test","namespace":"default"}, "namespace": "default", "name": "test", "reconcileID": "12f79e95-7cea-4c1a-8
b0a-6efe0c48a1df", "error": "Operation cannot be fulfilled on scaledobjects.keda.sh \"test\": StorageError: invalid object, Code: 4, Key: /registry/keda.sh/scaledobjects/default/test, ResourceVersion: 0, AdditionalErrorMsg: Precondition failed: UID in precondition: a65118f8-97d1-4a
47-8e9e-a72d122a0d90, UID in object meta: "}
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).reconcileHandler
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:326
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).processNextWorkItem
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:273
sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).Start.func2.2
        /workspace/vendor/sigs.k8s.io/controller-runtime/pkg/internal/controller/controller.go:234
E0320 16:58:49.546844       1 reflector.go:140] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: Failed to watch *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
W0320 16:58:50.451285       1 reflector.go:424] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
E0320 16:58:50.451382       1 reflector.go:140] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: Failed to watch *v1alpha1.ScaledObject: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
W0320 16:58:52.799581       1 reflector.go:424] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
E0320 16:58:52.799609       1 reflector.go:140] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: Failed to watch *v1alpha1.ScaledObject: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
W0320 16:58:57.032471       1 reflector.go:424] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
E0320 16:58:57.032538       1 reflector.go:140] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: Failed to watch *v1alpha1.ScaledObject: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
W0320 16:59:07.527743       1 reflector.go:424] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
E0320 16:59:07.527811       1 reflector.go:140] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: Failed to watch *v1alpha1.ScaledObject: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)
W0320 16:59:23.872201       1 reflector.go:424] sigs.k8s.io/controller-runtime/pkg/cache/internal/informers_map.go:262: failed to list *v1alpha1.ScaledObject: the server could not find the requested resource (get scaledobjects.keda.sh)

KEDA Version
2.9.3
Kubernetes Version
1.25
Platform
Amazon Web Services
Scaler Details
Doesn't matter, tried with CPU, Redis, Prometheus
Anything else?
v2.10.0 is also affected.

Hello,
That issue is because before removing KEDA, all the ScaledObjects and ScaledJobs have to be removed, otherwise they can become stuck due to the finalizer.
The uninstallation process is documented in docs with a script to remove them at once https://keda.sh/docs/2.10/deploy/#uninstall
I close this, issue, feel free to reopen it if you need anything else 😄

yes, that's because KEDA adds a finalizer to the resources, so when you delete the CRD, KEDA has to "approve" it, until KEDA does it, the deletion is locked. When you uninstall the helm chart without removing the ScaledObjects/ScaledJobs, this happens:

helm removes KEDA deployment
helm removes CRDs
not blocked CRDs are removed but CRDs with any resource locked by a finalizer is "queued" to delete (KEDA pos was already removed, so the finalizer can't be removed)
helm install adds all again
KEDA operator starts, process the pending request of ScaledObject deletions and removes the finalizers
kubernetes removes the pending to delete CRD

After this, you can see that KEDA has been resintalled, but a CRD is missing

Now it's much clearer for me, thanks a lot @JorTurFer!
I'm just trying to find the right way how to recover from such a situation if it happens again in the future.
The solution so far is to helm upgrade keda to deploy missing CRDs and helm upgrade application(s) to recreate ScaledObjects and HPAs.

Yeah, once you have deployed all the CRDs using helm, you will need to redeploy all the apps for redeploying the ScaledObjects. That's the only way I can imagine at this point

authors: JorTurFer kubroid


text:
enable golangci-lint: scopelint, structcheck (#1158)

Signed-off-by: akartasov agneum@gmail.com
Enable golangci-lint for scopelint and structcheck
Checklist

[x] Commits are signed with Developer Certificate of Origin (DCO)
[ ] Tests have been added
[ ] A PR is opened to update the documentation on https://github.com/kedacore/keda-docs
[ ] Changelog has been updated

Fixes #1158

@agneum thanks!

authors: agneum zroubalik


text:
replace deprecated golang/gomock with uber/gomock

Provide a description of what has been changed
Checklist

[ ] When introducing a new scaler, I agree with the scaling governance policy
[x] I have verified that my change is according to the deprecations & breaking changes policy
[x] Tests have been added
[x] Changelog has been updated and is aligned with our changelog requirements
[ ] A PR is opened to update our Helm chart (repo) (if applicable, ie. when deployment manifests are modified)
[ ] A PR is opened to update the documentation on (repo) (if applicable)
[x] Commits are signed with Developer Certificate of Origin (DCO - learn more)

Fixes #5440

Relates to #

/run-e2e internal

Could you solve the changelog conflict?

Could you solve the changelog conflict?

done!

/run-e2e

/run-e2e

/run-e2e

Only us can trigger the e2e tests because they use real infra 😄

/run-e2e

/run-e2e kafka

authors: JorTurFer rahulii zroubalik


text:
Combine Telemetry hook to send heap event once

Description

Fix #730
Development notes

The test isn't quite working yet, as some test is passing when run individually but fail when I run in a batch. The change is quite big already so I want to get some review:

KedroTelemetryCLIHooks and KedroTelemetryProjectHooks are combined to avoid cross hook communication and make it possible to send event ONCE only by storing some intermediate states (handle entrypoint for both kedro command or just session.run()
Added Integration test as I think it's important to make sure the event is only sent once, mocking wouldn't work so I need a real project here. For the effort I just create a minimal kedro project. I don't think we should spend too much effort as we moved kedro-telemetry back to kedro then we can share the same starter project. It's a temporary structure as I don't think adding it to the current test_plugin.py fits as the test is more high level.
I created a fake telemetry ID in case something isn't working we would still capture the fake telemetry from ourselves.

[tool.kedro_telemetry]
project_id = "KEDRO_TELEMETRY_TEST"

As discussed, the almost duplicate CLI command event is removed. https://github.com/kedro-org/kedro-plugins/issues/730#issuecomment-2223050576
There are more detailed conversation internally  for this approach.

Checklist

[ ] Opened this PR as a 'Draft Pull Request' if it is work-in-progress
[ ] Updated the documentation to reflect the code changes
[ ] Added a description of this change in the relevant RELEASE.md file
[ ] Added tests to cover my changes

Generally, the approach makes sense but I think it would be good to wait to switch to after_command_run till @lrcouto's analysis on the Kedro side is complete (re #709) - i.e. if the hook is executed even if there's an exception during the command execution. Otherwise we miss out on data about commands run with failures.

Generally, the approach makes sense but I think it would be good to wait to switch to after_command_run till @lrcouto's analysis on the Kedro side is complete (re #709) - i.e. if the hook is executed even if there's an exception during the command execution. Otherwise we miss out on data about commands run with failures.

My opinion is that it would be better to proceed with current approach, but first completely remove the after_command_run() hook for clarity. The logic will be clear: if a step includes catalog creation, enhanced data will be sent in the after_catalog_creation() hook; otherwise, a simple set of telemetry data will be sent at the last step.
I think it's acceptable to lose information about failed runs for now because we are not currently analysing it properly. I believe it makes sense to implement a special flow for failed runs later, such as collecting error types and analysing them for some insights.

@ankatiyar
The after_command_run change is slightly tricky.
There may be conflicts between the two requirements:

Send event even if command fails
Make sure event is not sent at the beginning and only sent it after the metadata is enriched

I can't approve my own PR, but it looks good to me now :)

As agreed, we have merged KedroTelemetryCLIHooks and KedroTelemetryProjectHooks into KedroTelemetryHook. I refactored the code to improve clarity and reduce repetition by consolidating relevant parts into the new class. Additionally, I updated the tests to reflect this merge.
The current logic is as follows:

We collect information about the CLI command and basic project details in the before_command_run hook.
If the after_catalog_created hook is triggered, we add information about nodes and pipelines and then send the event.
If step 2 does not occur, we send the event in the after_command_run hook.

I attempted to fix the integration tests but was unsuccessful. After discussing with @noklam, I have moved the integration tests to a separate issue and PR (#771).
Please re-review the PR.

authors: DimedS ankatiyar noklam

repo: kedro-org/kedro-plugins


text:
Update README.md

Corrected data param in example

👍

👍

authors: elof jvanderwee

repo: keen/keen-cli


text:
Documenting Joyboy Listing Requirements

Title: Comprehensive Documentation for Joyboy Listings
Objective: To systematically identify all potential platforms and directories where Joyboy needs to be listed and document the requirements and processes for each listing.
Background:
Joyboy is a decentralized social platform built using the Nostr protocol and enhanced by Starknet's account abstraction. Proper listing on relevant directories and platforms is crucial for visibility and integration within the wider ecosystem. This task involves researching and documenting all the necessary steps to ensure Joyboy is listed appropriately across various platforms.
Task Details:

Identify Listing Locations:

Review and list all potential websites, directories, and platforms where Joyboy elements (such as clients and relays) need to be referenced.
Examples include:

Listing as a Nostr client on the Nostr website clients page.
Adding the Joyboy relay at nostr.joyboy.community to directories like nostr.watch which lists Nostr relays.

Research Listing Requirements:

For each identified location, research and document specific requirements for getting listed. This may include forms to fill out, information to provide, or contacts to reach out to.
Document any costs, prerequisites, and timelines associated with each listing.

Documentation:

Create a detailed markdown file titled joyboy-listing.md.
Store this file under resources/branding/listing/ in the repository.
The document should be structured to include:

Platform/Directory Name: Description and relevance to Joyboy.
Listing Requirements: Detailed steps and requirements for listing.
Contact Information: If applicable, include contact information or submission links.
Additional Notes: Any other relevant information or strategic considerations.

Expected Outcome:

A comprehensive guide that will serve as a reference for getting Joyboy listed across all relevant platforms, enhancing its visibility and integration within the ecosystem.

Acceptance Criteria:

The markdown document must be clear, well-organized, and easy to navigate.
All information should be accurately researched and referenced.
The guide should cover all necessary platforms and provide detailed steps for the listing process.

Please ensure the documentation is thorough and consider potential updates as platforms evolve. This will be a critical resource for our marketing and partnership teams to extend Joyjoy's reach and utility.

Can I contribute on this @AbdelStark

@AbdelStark kindly assign

Can I contribute on this @AbdelStark

Are you in the telegram group ?

Yes @AbdelStark

kateberryd

ohhh you are Temi Hardhek on telegram ?

@t0rp3d0 here

No,  @zintarh

No, @zintarh

Gotcha. ok sorry then I already assigned to @tEmhItHoRpHe and @mubarak23 since we discussed about it on telegram.
Bare with us and be ready to take something else on Joyboy!

Alright. Thank you @AbdelStark

can i contribute to this too @AbdelStark

repo: keep-starknet-strange/joyboy


text:
bug: correctly set compiled_class_hash in DeclareTransaction

#744 has a bug in transaction/mod.rs where inside impl TryInto<DeclareTransaction> for &Transaction we set the compiled_class_hash equal to class_hash. This is because compiled_class_hash is not yet implemented in CallEntryPoint in blockifier @LucasLvy. Once this is done, we can fix this issue.

Hey, is the the CallEntryPoint in blockifier implemented? I can't find it but neither can I find an issue related to its implementation

Are we able to fix it now ?

I think yes, so may I take this one ?

Sorry for the late reply guys. This hasn't been implemented it in the blockifier yet. @LucasLvy, can someone do that as a part of this issue itself?

There will be big change in the implem of this soon. I'm working on it. It should most likely solve the issue

Hey,
Is this still open and if so can i take it? This is my first contribution so might need some help.

Hey @mbtariq82, thanks for taking the initiative. Unfortunately, this issue is closed now, we should have closed it earlier. However, there are a lot of other issues you can pick up! Do let me know if you need help in finding an issue.

authors: apoorvsadana edisontim mbtariq82 sparqet tdelabro

repo: keep-starknet-strange/madara


text:
catmath

Testing pull request.

Coverage increased (+5.7%) to 42.529% when pulling 2501b1d7e6c087116d60b0bb39406bad6754802a on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Coverage increased (+5.7%) to 42.529% when pulling 2501b1d7e6c087116d60b0bb39406bad6754802a on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Coverage increased (+10.3%) to 47.126% when pulling 18039d0f41ded5dd37a0c21d4adfd5a1d8c29aa8 on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Coverage increased (+10.3%) to 47.126% when pulling 705401b2d1064d2a8d57695d02f9f4015c6d0d84 on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Why do the builds fail?

Coverage increased (+63.2%) to 100.0% when pulling 14305a1a8545f8673d07e6eef8cd9026fb548197 on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Coverage increased (+63.2%) to 100.0% when pulling 83c816036b9aea66d857bdd1dea328c64630b24a on greventlov0:tutorial_wip into cad3d2ba400a71b24a6aee9b7ecf44938b97fa0a on keeppythonweird:master.

Thanks for this tutorial!

repo: keeppythonweird/catinabox


text:
Blue screen error without stopping

Hi team,
If I stop the project via visual studio without stopping the captured device, I get a blue screen error on the computer. I think it's a general problem with Directshow.
Do you have any suggestions for this?
The error I get is "SYSTEM THREAD EXCEPTION NOT HANDLED"

Thank you reached out!
In my opinion, the error means that the exception raised in the kernel mode driver thread was not caught.
Possible reasons are:

A camera driver malfunction.
Invalid response from the camera hardware.
Hardware problem in the system (CPU/memory/chipset, etc.)

It is impossible to generate this error with the user mode process software we usually design. Therefore, I don't think the code you wrote is the cause.

repo: kekyo/FlashCap


text:
I try to use confd in docker, but it says: ERROR 501: All the given peers are not reachable

I try to use confd in docker, but it says: ERROR 501: All the given peers are not reachable
the related environment:
docker: server version 1.5
confd: version 0.8.0, container's address 172.17.0.3
etcd: version 2.0.5, container's address 172.17.0.1
run command in 172.17.0.3:
curl http://172.17.0.1:2379/version
returns:
{"releaseVersion":"2.0.5","internalVersion":"2"}

Confd is incompatible with etcd 2.0 at this time. Closing as a dupe of #195, which is being tracked in #250. Thanks!

This is still a problem with the latest version.
etcdctl --version
etcdctl version 2.0.9

confd --version
confd 0.9.0

I started etcd like this
etcd -addr=$IP:4001 -bind-addr=0.0.0.0:4001

2015-04-21_00:52:02.09525 2015/04/21 00:52:02 etcd: no data-dir provided, using default data-dir ./default.etcd
2015-04-21_00:52:02.09527 2015/04/21 00:52:02 etcd: listening for peers on http://localhost:2380
2015-04-21_00:52:02.09527 2015/04/21 00:52:02 etcd: listening for peers on http://localhost:7001
2015-04-21_00:52:02.09528 2015/04/21 00:52:02 etcd: listening for client requests on http://0.0.0.0:4001
2015-04-21_00:52:02.09528 2015/04/21 00:52:02 etcdserver: datadir is valid for the 2.0.1 format
2015-04-21_00:52:02.09529 2015/04/21 00:52:02 etcdserver: name = default
2015-04-21_00:52:02.09529 2015/04/21 00:52:02 etcdserver: data dir = default.etcd
2015-04-21_00:52:02.09530 2015/04/21 00:52:02 etcdserver: member dir = default.etcd/member
2015-04-21_00:52:02.09530 2015/04/21 00:52:02 etcdserver: heartbeat = 100ms
2015-04-21_00:52:02.09531 2015/04/21 00:52:02 etcdserver: election = 1000ms
2015-04-21_00:52:02.09531 2015/04/21 00:52:02 etcdserver: snapshot count = 100002015-04-21_00:52:02.09532 2015/04/21 00:52:02 etcdserver: advertise client URLs = http://172.17.0.169:4001
2015-04-21_00:52:02.09532 2015/04/21 00:52:02 etcdserver: initial advertise peer URLs = http://localhost:2380,http://localhost:7001

I started confd like this
confd -watch=true -interval 30 -backend=etcd -node "http://$ETCD_HOST:4001" -log-level="debug"

2015-04-21_00:52:02.48287 2015-04-20T19:52:02-05:00 boot2docker confd[24]: INFO Backend set to etcd
2015-04-21_00:52:02.48288 2015-04-20T19:52:02-05:00 boot2docker confd[24]: INFO Starting confd
2015-04-21_00:52:02.48288 2015-04-20T19:52:02-05:00 boot2docker confd[24]: INFO Backend nodes set to http://localhost:4001
2015-04-21_00:52:02.48289 2015-04-20T19:52:02-05:00 boot2docker confd[24]: DEBUG Loading template resources from confdir /etc/confd
2015-04-21_00:52:02.48291 2015-04-20T19:52:02-05:00 boot2docker confd[24]: DEBUG Loading template resource from /etc/confd/conf.d/kubernetes.toml
 501: All the given peers are not reachable (Tried to connect to each peer twice and failed) [0]
2015-04-21_00:52:04.48578 2015-04-20T19:52:04-05:00 boot2docker confd[24]: ERROR 501: All the given peers are not reachable (Tried to connect to each peer twice and failed) [0]

This happens only when etcd and confd are started about the same time.
If I then restart confd then everything works.

@mingfang interesting. If you can reproduce it using the integration tests which test confd against v2.0.9, that would be appreciated.

The problem appears to only occur when both etcd and confd are started at the same time.
Unfortunately it looks like the existing integration tests starts etcd before running the tests.

in that case, it's probably due to etcd having some time to boot up before it starts accepting connections. Either that, or the go-etcd client does not have a connection timeout set up by default. Can you confirm that setting a DialTimeout on the etcd backend fixes this issue?

I would love to try.
How do I set the dial timeout?

Same problem here.
etcd & confd started at the same time, confd gives the error.
restart confd and the problem is gone.
version info:
confd --version
confd 0.11.0
etcd --version
etcd Version: 2.3.3
Git SHA: c41345d
Go Version: go1.6.2
Go OS/Arch: linux/amd64

authors: HD-DBC bacongobbler king6cong mingfang

repo: kelseyhightower/confd


text:
No instructions on setting up jumpbox?

Is it implied that we need to look it up? It says to ssh root@jumpbox but I of course get 'no address associated with hostname'

That's correct -- it's implied that you'll know the hostname or IP of your server that you'll be executing commands from. If you want a 1:1 match, you can map the jumpbox hostname to the server you'll be using:
Host jumpbox
  HostName <your-hostname-here>
  StrictHostKeyChecking yes
  PreferredAuthentications publickey
  IdentityFile ~/path/to/ssh-key

After doing so, executing ssh root@jumpbox will allow you to connect.
If you haven't setup a server for this, then it will be your local workstation. This is where the following applies:

While a dedicated machine is being used to ensure consistency, these commands can also be run from just about any machine including your personal workstation running macOS or Linux

I hope this helps!

authors: MattDevOps dcoy

repo: kelseyhightower/kubernetes-the-hard-way


text:
Create composer.json - added Composer support

Great work!

I am still in process of reviewing your suggestion, @ivanignacio , I will inform you when I finish.

repo: kelseyhightower/nocode


text:
Upload Request Question and Submission

Does the image need to already be on Cloudinary or is that part of your process?
Also, here's a wallpaper submission! I made it myself and have full rights:

thanks, will get that uploaded later. also i moved away from cloudinary!

authors: foldsters kennethnym

repo: kennethnym/doors-wallpaper


text:
Run tests against Python 3.7

This might have helped surface https://github.com/kennethreitz/pipenv/issues/956 sooner.

Oddly, this passes on 3.7.

Thanks for checking in on this @jacebrowning. I don't think we're going to enable this until 3.7 is at least out of alpha which isn't for a few months. We're also 8 months out from release so there's no rush here.

authors: jacebrowning nateprewitt

repo: kennethreitz/pipenv


text:
Honor HTTP strict transport security headers

HTTP strict transport security header helps protect web applications against communications interception and MITM attacks. I would recommend that requests look for and honor the header by default.

See shazow/urllib3#608, and the comment I just made on #3063: the same limitations that apply there apply here.

Perfect, thank you! :bow:

authors: Lukasa asieira

repo: kennethreitz/requests


text:
Image handler overwrites image resize

With an image handler in place, resizing does not work anymore.
The resulting error message is:
[Warning] quill – "Overwriting modules/imageResize with" – function t(e) { (2.chunk.js, line 42025)
var n = this,
r = arguments.length > 1 && void 0 !== arguments[1] ? arguments[1] : {};
o(this, t), this.initializeModules = function () {
n.removeModules(), n.modules = n.moduleClasses.map(function (t) {...

Hello, did you find a fix to this?

Hello, did you find a fix to this?

In my case, the issue arose because I registered the module in an incorrect location.
Incorrect
import Quill from 'quill';
import ImageResize from 'quill-image-resize';

import React, { useState, useRef } from 'react';
import ReactQuill from 'react-quill';

const Test = () => {
  Quill.register('modules/imageResize', ImageResize);
  const [value, setValue] = useState('');
  const quillRef = useRef(null);

  const modules = {
    toolbar: [
      // Your toolbar options
    ],
    imageResize: true,
  };

  return (
    <ReactQuill
      ref={quillRef}
      theme="snow"
      value={value}
      onChange={setValue}
      modules={modules}
    />
  );
};

export default Test;

Correct
import Quill from 'quill';
import ImageResize from 'quill-image-resize';

Quill.register('modules/imageResize', ImageResize);

import React, { useState, useRef } from 'react';
import ReactQuill from 'react-quill';

const Test = () => {
  const [value, setValue] = useState('');
  const quillRef = useRef(null);

  const modules = {
    toolbar: [
      // Your toolbar options
    ],
    imageResize: true,
  };

  return (
    <ReactQuill
      ref={quillRef}
      theme="snow"
      value={value}
      onChange={setValue}
      modules={modules}
    />
  );
};

export default Test;

repo: kensnyder/quill-image-resize-module


text:
Unable to import match sorter from versions 5.0.0+

match-sorter version: 5.0.0+
node version: 12.16.3

Relevant code or config
import matchSorter from 'match-sorter';

What you did:
Tried to import match-sorter and use it.
What happened:
When trying to use match-sorter I get the TypeScript error:

node_modules/match-sorter/dist/index")' has no call signatures.ts(2349)

Reproduction repository:
Going to https://github.com/kentcdodds/match-sorter/blob/master/other/EXAMPLES.md and clicking on the "Basic Example" and then changing the library version to 5.0.0+ will show the broken imports. 4.2.1 seems to be the last one that built correctly.
https://codesandbox.io/s/xenodochial-water-ffdow

Problem description:
No index.js appears to be created in the build.
Suggested solution:
Make the build work again.

Closing because I copied an old example I guess and it should be:
import {matchSorter} from 'match-sorter';

whoops!

repo: kentcdodds/match-sorter


text:
docs: fix typo in textMatch example(#101)

What: Fix typo in textMatch example
Checklist:

[X] Documentation
[X] Tests
[X] Ready to be merged
[X] Added myself to contributors table

:tada: This PR is included in version 3.1.4 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

authors: bsotodo kentcdodds

repo: kentcdodds/react-testing-library


text:
Branching Properly

Hi,
It's probably not the correct place to pose this question, but I'd like to modify the InceptionV4 model you provided (default) in a way to meet the requirements of a project I am working on. Since you've written the InceptionV4 code you can tell me perhaps how to branch off.
What I want to achieve is the following:
In order to get a feature map of 71x71x384, branch off before the last pooling layer within the stem and append one 'Inception-A' block.
Thereafter, successively branch off after the "Inception-A' blocks for a 35x35x384 feature map, after the 'Inception-B'  blocks for a 17x17x384 feature map and after the 'Inception-C' blocks for a 9x9x1536 map.
Also extend the network with two more parts: first a 'Reduction-B' followed by two 'Inception-C- blocks to output a 5x5x1024 map. Second, one 'Reduction-B' and one 'Inception-C' to produce 3x3x1024 map.
This text itself is not really understandable as I am looking at the InceptionV4 graph and can't seem to understand how to branch off exactly as it is written. I've "branched off" within the stem before the last pooling layer (as it is said in the text):
branch_0 = conv2d_bn(net, 192, 3, 3, strides=(2, 2), padding='valid')
branch_a =  block_inception_a(net)
branch_1 = MaxPooling2D((3, 3), strides=(2, 2), padding='valid')(net)

net = concatenate([branch_0, branch_1 , branch_a], axis=channel_axis)

but got an error:
ValueError: A Concatenatelayer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 35, 35, 192), (None, 35, 35, 192), (None, 71, 71, 384)]
which clearly means I did not branch off properly. What does "branch off for a AxBxC feature map" mean in this context? To add another conv2d_bn function with the A,B,C parameters?
Am I misunderstanding the text or is there something wrong with the branching strategy of the text? Could you give me some insights if possible? (Gonna close the issue afterwards as this is not a bug or anything to worth an issue).
Thanks in advance.

Closing this out after a long hiatus from Github.
You have probably moved on from this work but in the spirit of making sure I give some sort of answer, it has been a very long time since I have looked at these models/code and unfortunately I don't know what might have been causing the issues you were seeing.
Happy to chat if you happen to still be working on this (feel free to reopen or create a new issue).

authors: eyildiz-ugoe kentsommer


text:
Remove style attribute on slick-dots

Hi,
Do you now if i can drop the "style" attribute on slick-dots element ? For display: flex, he creat bug on iOS :(
Thank you,

Please create a JS Fiddle according to the contribution guidelines :)

Hey, I'm closing because there's no test-case, per the contribution guidlines, but if you make one we could possibly reopen. Thanks!

authors: LeG3nDz leggomuhgreggo simeydotme

repo: kenwheeler/slick


text:
fix(operator): update workload if spec changes

Signed-off-by: Thomas Schuetz thomas.schuetz@dynatrace.com

pls signoff commits with git rebase HEAD~5 --signoff, otherwise LGTM

authors: odubajDT thschue

repo: keptn-sandbox/lifecycle-controller


text:
Refactoring :: Lifecycle Operator

Goal
Clean up some parts of the lifecycle operator wrt observability signals.
Details
The lifecycle operator exposes logs, traces, and metrics.
For traces, the operator exposes the deployment traces and internal traces that were useful for debugging internal behavior.
These traces are noisy and not super helpful for end users.
For logs, sometimes error level logs are printed when the App autodiscovery is taking place. We should not emit these log lines at the error level.
Acceptance Criteria

[ ] Remove internal traces
[ ] Clean up error logs only when it is indeed an error that impact the user

DoD
The lifecycle operator has observability signals that help the end users.

Closing this issue as the related PRs have been merged

authors: bacherfl thisthat

repo: keptn/lifecycle-toolkit


text:
Remove Integration Test Reports from the pipeline

When all collectors are in place we should not need to retrieve integration test logs.
This ticket depends on:

#2697
#2698
#2699
#2700

Please keep in mind that the above mentioned tickets need to be finished before handling this ticket.
DoD

[ ] remove logs extraction from the pipeline here

@RealAnna I am interested in this.

This ticket has a few open dependencies, that first need to be done for this ticket to be ready.

This ticket has a few open dependencies, that first need to be done for this ticket to be ready.

I am aware of that, I just wanted to indicate my interest

authors: RealAnna Vickysomtee mowies


text:
feat: tasktype to function execution context

In this PR:
-added  "PreDeploymentTasks and PostDeploymentTasks" inside TaskContext struct
-fixes issue #616
signed-off by: Ayush Prakash  itsnotmymailid140@gmail.com

Hey @prkshayush , could you please rebase your branch with main? you can do it via git pull --rebase upstream main if you defined the main KLT repo upstream git repo under the upstream name. This can be done via git remote add upstream https://github.com/keptn/lifecycle-controller.git

authors: prkshayush thisthat


text:
keras_core tensor assignment error with TensorFlow and JAX backend

While trying to implement a model with keras_core, I faced a problem with  tensor assignment in TensorFlow and JAX:
This is the code I have tried:
tensor = keras_core.random.normal((2, 12))
tensor[0, 1] = 2

Updating tensor values is tricky in TensorFlow as the most popular (and inefficient) way is to convert it to a tf.Variable and then convert it back to tensor.
For JAX, we need to set up values using set and at methods.
Does keras_core has any cross-framework way of doing it?
The assignment code above works with the PyTorch backend.
Thank you!

TensorFlow does not support dynamic tensor assignment in this manner, while PyTorch does. I do not think TensorFlow Backend would be able to support it in this way, although I think one of the maintainers should be a better person to comment.

Thank you for the letting know @innat  @suvadityamuk.
For my problem, this seems the only way out:
def forward_with_coords(coords_input, image_size):
        """Positionally encode points that are not normalized to [0,1]."""
        if keras.backend.backend() == "tensorflow":
            import tensorflow as tf
            coords = tf.Variable(coords_input)
            coords[:, :, 0].assign(coords[:, :, 0] / image_size[1])
            coords[:, :, 1].assign(coords[:, :, 1] / image_size[0])
            return coords
        elif keras.backend.backend() == 'torch':
            coords = coords_input.clone()
            coords[:, :, 0] = coords[:, :, 0] / image_size[1]
            coords[:, :, 1] = coords[:, :, 1] / image_size[0]
            return coords
        else:
            coords = coords_input.copy()
            coords.at[:, :, 0].set(coords[:, :, 0] / image_size[1])
            coords.at[:, :, 1].set(coords[:, :, 1] / image_size[0])
            return coords

If you have any better way, please let me know.

coords = coords_input.copy()
coords.at[:, :, 0].set(coords[:, :, 0] / image_size[1])
coords.at[:, :, 1].set(coords[:, :, 1] / image_size[0])
return coords

I believe this is incorrect for JAX.  The .at[...].set(...) method returns a new tensor, so you would need to do
            coords = coords_input.at[:, :, 0].set(coords[:, :, 0] / image_size[1])
            coords = coords.at[:, :, 1].set(coords[:, :, 1] / image_size[0])
            return coords

JAX has the same issue as tensorflow, in that the tensors are immutable, so we can't just directly assign a slice via indexing.

To do tensor assignment, you can use the following solutions:

Use the backend-native solution. Some backends support tensor assignment, so you could use what they offer -- but keep in mind that your code will then be specific to that backend.
Use Keras Core assignment ops. There are 2 assignment ops:

scatter_update for updates indexed by coordinates
slice_update for block-shaped updates

These ops will work with all backends.
For instance you can do:
inputs = ops.zeros((5, 5))
start_indices = [3, 3]
updates = ops.ones((2, 2))
inputs = keras_core.ops.slice_update(inputs, start_indices, updates)

Which is equivalent to inputs[3:, 3:] = updates

authors: anas-rz cantonios fchollet suvadityamuk

repo: keras-team/keras-core


text:
KerasTuner "Getting started": missing hp.conditional_scope()?

"Getting started with KerasTuner" prominently mentions conditional hyperparameters:
https://github.com/keras-team/keras-io/blob/0be9a38b96e8dd85bc525a74babb614f38b179c7/guides/keras_tuner/getting_started.py#L153
But are these "units_0", "units_1","units_2" really conditional? No parent_name is set, directly or via hp.conditional_scope(), so what tells the tuner that f"units_{i}" shall not be explored if i >= hp.get("num_layers")?
Moreover, the next layer (Dropout) is also conditioned on a hyperparameter, and its rate arg begs to be tuned, yet the code does not show how to condition dropout rate on the dropout boolean.
In summary, I can read this 800+ line doc, feel confident about conditional hyperparameters, but never actually learn about setting the parent.

@haifeng-jin

authors: arnoegw jbischof

repo: keras-team/keras-io