Claude UI Feature Request
2 by simon_acca | 0 comments on Hacker News.
Putting this here in the hope that someone at Anthropic reads it. Searching through old conversations is difficult with the current app and web interface. Could you have the model provide a bunch of tags relevant to the conversation like “cooking” or “purchase advice” or “music”, so that we are able to browse conversations by topic? Thanks!
Hack Nux
Watch the number of websites being hacked today, one by one on a page, increasing in real time.
New Show Hacker News story: Show HN: Coelanox – auditable inference runtime in Rust (BERT runs today)
Show HN: Coelanox – auditable inference runtime in Rust (BERT runs today)
2 by Shark1n4Suit | 0 comments on Hacker News.
PyTorch and ONNX Runtime tell you what came out. They can't tell you what actually ran to get there — which ops executed, in what order, on what inputs. A model gets packaged into a sealed .cnox container. SHA-256 is verified before a single op executes. Inference walks a fixed plan over a minimal opset. Every run can emit a per-op audit log: op type, output tensor hash, output sample — cryptographically linked to the exact container and input that produced it. If something goes wrong in production, you have a trail. Scalar backend today — reference implementation and permanent fallback when hardware acceleration isn't available. Audit and verification is identical across all backends. SIMD next, GPU after that. Input below is synthetic (all-ones) — pipeline is identical with real inputs. github.com/Coelanox/CLF Audit example: { "schema": 2, "run": { "run_id": "59144ede-5a27-4dff-bc25-94abade5b215", "started_at_unix_ms": 1776535116721, "container_path": "/home/shark/cnox/models/output/bert_base_uncased.cnox", "container_sha256_hex": "184c291595536e3ef69b9a6a324ad5ee4d0cef21cc95188e4cfdedb7f1f82740", "backend": "scalar" }, "input": { "len": 98304, "sha256_hex": "54ac99d2a36ac55b4619119ee26c36ec2868552933d27d519e0f9fd128b7319f", "sample_head": [ 1.0, 1.0, 1.0, 1.0 ] }, "ops": [ { "op_index": 0, "op_type": "Add", "out_len": 98304, "out_sample_head": [ 0.12242669, -4.970478, 2.8673656, 5.450008 ], "out_sha256_hex": "19f8aa0a618e5513aed4603a7aae2a333c3287368050e76d4aca0f83fb220e78" }, { "op_index": 1, "op_type": "Add", "out_len": 98304, "out_sample_head": [ 0.9650015, 0.23414998, 1.539839, 0.30231553 ], "out_sha256_hex": "7ae2f025c8acf67b8232e694dd43caf3b479eb078366787e4fdc16d651450ad4" }, { "op_index": 2, "op_type": "MatMul", "out_len": 98304, "out_sample_head": [ 1.0307425, 0.19207191, 1.5278282, 0.3000223 ], "out_sha256_hex": "44c28e64441987b8f0516d77f45ad892750b3e5b3916770d3baa5f2289e41bdd" }, { "op_index": 3, "op_type": "Gelu", "out_len": 393216, "out_sample_head": [ 0.68828076, -0.0033473556, 1.591219, -0.16837223 ], "audit_elided": "hash_skipped: len 393216 > max 262144" }
2 by Shark1n4Suit | 0 comments on Hacker News.
PyTorch and ONNX Runtime tell you what came out. They can't tell you what actually ran to get there — which ops executed, in what order, on what inputs. A model gets packaged into a sealed .cnox container. SHA-256 is verified before a single op executes. Inference walks a fixed plan over a minimal opset. Every run can emit a per-op audit log: op type, output tensor hash, output sample — cryptographically linked to the exact container and input that produced it. If something goes wrong in production, you have a trail. Scalar backend today — reference implementation and permanent fallback when hardware acceleration isn't available. Audit and verification is identical across all backends. SIMD next, GPU after that. Input below is synthetic (all-ones) — pipeline is identical with real inputs. github.com/Coelanox/CLF Audit example: { "schema": 2, "run": { "run_id": "59144ede-5a27-4dff-bc25-94abade5b215", "started_at_unix_ms": 1776535116721, "container_path": "/home/shark/cnox/models/output/bert_base_uncased.cnox", "container_sha256_hex": "184c291595536e3ef69b9a6a324ad5ee4d0cef21cc95188e4cfdedb7f1f82740", "backend": "scalar" }, "input": { "len": 98304, "sha256_hex": "54ac99d2a36ac55b4619119ee26c36ec2868552933d27d519e0f9fd128b7319f", "sample_head": [ 1.0, 1.0, 1.0, 1.0 ] }, "ops": [ { "op_index": 0, "op_type": "Add", "out_len": 98304, "out_sample_head": [ 0.12242669, -4.970478, 2.8673656, 5.450008 ], "out_sha256_hex": "19f8aa0a618e5513aed4603a7aae2a333c3287368050e76d4aca0f83fb220e78" }, { "op_index": 1, "op_type": "Add", "out_len": 98304, "out_sample_head": [ 0.9650015, 0.23414998, 1.539839, 0.30231553 ], "out_sha256_hex": "7ae2f025c8acf67b8232e694dd43caf3b479eb078366787e4fdc16d651450ad4" }, { "op_index": 2, "op_type": "MatMul", "out_len": 98304, "out_sample_head": [ 1.0307425, 0.19207191, 1.5278282, 0.3000223 ], "out_sha256_hex": "44c28e64441987b8f0516d77f45ad892750b3e5b3916770d3baa5f2289e41bdd" }, { "op_index": 3, "op_type": "Gelu", "out_len": 393216, "out_sample_head": [ 0.68828076, -0.0033473556, 1.591219, -0.16837223 ], "audit_elided": "hash_skipped: len 393216 > max 262144" }
New Show Hacker News story: Show HN: Sostactic – polynomial inequalities using sums-of-squares in Lean
Show HN: Sostactic – polynomial inequalities using sums-of-squares in Lean
2 by mmaaz | 0 comments on Hacker News.
Current support for nonlinear inequalities in Lean is quite limited. This package attempts to solve this. It contains a collection of Lean4 tactics for proving polynomial inequalities via sum-of-squares (SOS) decompositions, powered by a Python backend. You can use it via Python or Lean. These tactics are significantly more powerful than `nlinarith` and `positivity` -- i.e., they can prove inequalities they cannot. In theory, they can be used to prove any of the following types of statements - prove that a polynomial is nonnegative globally - prove that a polynomial is nonnegative over a semialgebraic set (i.e., defined by a set of polynomial inequalities) - prove that a semialgebraic set is empty, i.e., that a system of polynomial inequalities is infeasible The underlying theory is based on the following observation: if a polynomial can be written as a sum of squares of other polynomials, then it is nonnegative everywhere. Theorems proving the existence of such decompositions were one of the landmark achievements of real algebraic geometry in the 20th century, and its connection to semidefinite programming in the 21st century made it a practical computational tool, and is what this software does in the background.
2 by mmaaz | 0 comments on Hacker News.
Current support for nonlinear inequalities in Lean is quite limited. This package attempts to solve this. It contains a collection of Lean4 tactics for proving polynomial inequalities via sum-of-squares (SOS) decompositions, powered by a Python backend. You can use it via Python or Lean. These tactics are significantly more powerful than `nlinarith` and `positivity` -- i.e., they can prove inequalities they cannot. In theory, they can be used to prove any of the following types of statements - prove that a polynomial is nonnegative globally - prove that a polynomial is nonnegative over a semialgebraic set (i.e., defined by a set of polynomial inequalities) - prove that a semialgebraic set is empty, i.e., that a system of polynomial inequalities is infeasible The underlying theory is based on the following observation: if a polynomial can be written as a sum of squares of other polynomials, then it is nonnegative everywhere. Theorems proving the existence of such decompositions were one of the landmark achievements of real algebraic geometry in the 20th century, and its connection to semidefinite programming in the 21st century made it a practical computational tool, and is what this software does in the background.
New ask Hacker News story: Ask HN: How do you search the web programmatically these days?
Ask HN: How do you search the web programmatically these days?
2 by coreyp_1 | 2 comments on Hacker News.
For the first time in a long time, I need to query a search engine programmatically, and found that most of them block the use of curl, etc. So, my question is simple: how do you solve the problem? I've tried searxng with mediocre success, but it seems a bit heavy to have to be running a complete separate service for this one thing that I only need every once in a while. I haven't tried using a service that requires an API key, simply because I'm not sure which direction to go or who to go with. Just thought I would ask here first.
2 by coreyp_1 | 2 comments on Hacker News.
For the first time in a long time, I need to query a search engine programmatically, and found that most of them block the use of curl, etc. So, my question is simple: how do you solve the problem? I've tried searxng with mediocre success, but it seems a bit heavy to have to be running a complete separate service for this one thing that I only need every once in a while. I haven't tried using a service that requires an API key, simply because I'm not sure which direction to go or who to go with. Just thought I would ask here first.
New ask Hacker News story: Gmail label bridge on Claude Cowork just broke
Gmail label bridge on Claude Cowork just broke
2 by mangoe | 2 comments on Hacker News.
Hello, a first time poster here - encountering an issue with my email triage system through claude after a connector update overnight. curious whether anyone else landed here? about a month ago i was trying to figure out a way to get intuitive ai filtering on my gmail without full labeling integration. with help from claude i worked out a system where claude can auto draft my email responses, and enter a little code for the appropriate label in the top of the draft..... then a Google Apps Script trigger runs every five minutes to read the code, apply the matching label to the parent thread, archive it and delete the draft. This system ran cleanly for weeks, but this morning an upgrade removed threadId from create_draft, so drafts now land as standalone messages rather than threaded replies. Did anyone on here have a similar workaround? any recommendations? i think im going to have to resort to a third party MCP, but would prefer not to as im being overly cautious of vulnerabilities right now. Thanks so much! - Robert
2 by mangoe | 2 comments on Hacker News.
Hello, a first time poster here - encountering an issue with my email triage system through claude after a connector update overnight. curious whether anyone else landed here? about a month ago i was trying to figure out a way to get intuitive ai filtering on my gmail without full labeling integration. with help from claude i worked out a system where claude can auto draft my email responses, and enter a little code for the appropriate label in the top of the draft..... then a Google Apps Script trigger runs every five minutes to read the code, apply the matching label to the parent thread, archive it and delete the draft. This system ran cleanly for weeks, but this morning an upgrade removed threadId from create_draft, so drafts now land as standalone messages rather than threaded replies. Did anyone on here have a similar workaround? any recommendations? i think im going to have to resort to a third party MCP, but would prefer not to as im being overly cautious of vulnerabilities right now. Thanks so much! - Robert
New Show Hacker News story: Show HN: Pyra – a Python toolchain experiment inspired by uv and Bun
Show HN: Pyra – a Python toolchain experiment inspired by uv and Bun
3 by trey-orr | 0 comments on Hacker News.
I’ve been working on Pyra for the past few months and wanted to start sharing it in public. Right now it’s focused on the core package/project management workflow: Python installs, init, add/remove, lockfiles, env sync, and running commands in the managed env. The bigger thing I’m exploring is whether Python could eventually support a more cohesive toolchain story overall, more in the direction of Bun: not just packaging, but maybe over time testing, tasks, notebooks, and other common workflow tools feeling like one system instead of a bunch of separate pieces. It’s still early, and I’m definitely not claiming it’s as mature as uv. I’m mostly sharing it now because I want honest feedback on whether the direction feels interesting or misguided.
3 by trey-orr | 0 comments on Hacker News.
I’ve been working on Pyra for the past few months and wanted to start sharing it in public. Right now it’s focused on the core package/project management workflow: Python installs, init, add/remove, lockfiles, env sync, and running commands in the managed env. The bigger thing I’m exploring is whether Python could eventually support a more cohesive toolchain story overall, more in the direction of Bun: not just packaging, but maybe over time testing, tasks, notebooks, and other common workflow tools feeling like one system instead of a bunch of separate pieces. It’s still early, and I’m definitely not claiming it’s as mature as uv. I’m mostly sharing it now because I want honest feedback on whether the direction feels interesting or misguided.