[Bug]: Tool Overuse in Assistant Agent

Describe the bug
Whenever a tool is registered the agents are very enthusiastic at over using the tools and being wasteful.
In the example below the chat history contains information necessary to complete the task without using the tools.
But the assistant agent still proceeds to wastefully use the tools again to get the information.
This is just a reproducible example but the bug is not one off -- it happens consistently across tool types and scenarios.
@afourney also has seen the same behavior multiple times.
Steps to reproduce

Use this script to reproduce
# filename: test/twoagent_tool_overuse.py
from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

def search_arxiv(query: str, max_results: int=10) -> str:
    """
    Searches arXiv for the given query using the arXiv API, then returns the search results. This is a helper function. In most cases, callers will want to use 'find_relevant_papers( query, max_results )' instead.

    Args:
        query (str): The search query.
        max_results (int, optional): The maximum number of search results to return. Defaults to 10.

    Returns:
        response (str): A JSON string containing the search results.

    Example:
        >>> results = search_arxiv("attention is all you need")
        >>> print(results)
    """
    import json
    import re
    import arxiv

    # Normalize the query, removing operator keywords
    query = re.sub(r"[^\s\w]", " ", query.lower())
    query = re.sub(r"\s(and|or|not)\s", " ", " " + query + " ")
    query = re.sub(r"[^\s\w]", " ", query.lower())
    query = re.sub(r"\s+", " ", query).strip()

    search = arxiv.Search(query=query, max_results=max_results, sort_by=arxiv.SortCriterion.Relevance)

    jresults = list()
    for result in search.results():
        r = dict()
        r["entry_id"] = result.entry_id
        r["updated"] = str(result.updated)
        r["published"] = str(result.published)
        r["title"] = result.title
        r["authors"] = [str(a) for a in result.authors]
        r["summary"] = result.summary
        r["comment"] = result.comment
        r["journal_ref"] = result.journal_ref
        r["doi"] = result.doi
        r["primary_category"] = result.primary_category
        r["categories"] = result.categories
        r["links"] = [str(link) for link in result.links]
        r["pdf_url"] = result.pdf_url
        jresults.append(r)

    if len(jresults) > max_results:
        jresults = jresults[0:max_results]

    response = json.dumps(jresults, indent=2)

    return response

config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST", filter_dict={"model": ["gpt-4"]})
assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent(
    "user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False},
    human_input_mode="NEVER",
    is_termination_msg=lambda msg: msg.get("content") and "TERMINATE" in msg.get("content", "")
)

assistant.register_for_llm(description="Find papers on arxiv.")(search_arxiv)
user_proxy.register_for_execution()(search_arxiv)

history = [
    {'content': 'Find recent papers on xai by me', 'role': 'user'},
    {'content': 'Certainly, here are the URLs of your recent papers on Copilot:\n\n1. "Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming"\n   - [PDF Link](http://arxiv.org/pdf/2210.14306v4)\n\n2. "When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming"\n   - [PDF Link](http://arxiv.org/pdf/2306.04930v2)\n\nThese papers are available on arXiv. If you require the papers to be saved, please use the naming convention specified in your preferences.', 'role': 'assistant'},
    ]

for msg in history:
    if msg["role"] == "user":
        user_proxy.send(msg["content"], assistant, request_reply=False)
    else:
        assistant.send(msg["content"], user_proxy, request_reply=False)

user_proxy.initiate_chat(assistant, message="Save these pdfs to disk", clear_history=False)

Expected Behavior
Agents should write python and shell code to download the two pdf files in the chat history to the work dir.
Screenshots and logs
Instead the agents call tools again. This issue is not one off. It is frequent across tool types and applications.

Click here to view console log
@gagb ➜ /workspaces/autogen (main) $ python test/twoagent_tool_overuse.py
user_proxy (to assistant):

Find recent papers on xai by me

--------------------------------------------------------------------------------
assistant (to user_proxy):

Certainly, here are the URLs of your recent papers on Copilot:

1. "Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming"
   - [PDF Link](http://arxiv.org/pdf/2210.14306v4)

2. "When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming"
   - [PDF Link](http://arxiv.org/pdf/2306.04930v2)

These papers are available on arXiv. If you require the papers to be saved, please use the naming convention specified in your preferences.

--------------------------------------------------------------------------------
user_proxy (to assistant):

Save these pdfs to disk

--------------------------------------------------------------------------------
assistant (to user_proxy):

***** Suggested tool Call (call_ju0xcNhwZGhPpv4tpqXMmsCL): search_arxiv *****
Arguments:
{
"query": "xai",
"max_results": 10
}
*****************************************************************************

--------------------------------------------------------------------------------

>>>>>>>> EXECUTING FUNCTION search_arxiv...
/workspaces/autogen/test/twoagent_tool_overuse.py:31: DeprecationWarning: The 'Search.results' method is deprecated, use 'Client.results' instead
  for result in search.results():
user_proxy (to assistant):

user_proxy (to assistant):

***** Response from calling tool "call_ju0xcNhwZGhPpv4tpqXMmsCL" *****
[
  {
    "entry_id": "http://arxiv.org/abs/2207.14160v2",
    "updated": "2022-10-04 10:45:23+00:00",
    "published": "2022-06-08 06:13:39+00:00",
    "title": "Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark",
    "authors": [
      "Mohamed Karim Belaid",
      "Eyke H\u00fcllermeier",
      "Maximilian Rabus",
      "Ralf Krestel"
    ],
    "summary": "In recent years, Explainable AI (xAI) attracted a lot of attention as various\ncountries turned explanations into a legal right. xAI allows for improving\nmodels beyond the accuracy metric by, e.g., debugging the learned pattern and\ndemystifying the AI's behavior. The widespread use of xAI brought new\nchallenges. On the one hand, the number of published xAI algorithms underwent a\nboom, and it became difficult for practitioners to select the right tool. On\nthe other hand, some experiments did highlight how easy data scientists could\nmisuse xAI algorithms and misinterpret their results. To tackle the issue of\ncomparing and correctly using feature importance xAI algorithms, we propose\nCompare-xAI, a benchmark that unifies all exclusive functional testing methods\napplied to xAI algorithms. We propose a selection protocol to shortlist\nnon-redundant functional tests from the literature, i.e., each targeting a\nspecific end-user requirement in explaining a model. The benchmark encapsulates\nthe complexity of evaluating xAI methods into a hierarchical scoring of three\nlevels, namely, targeting three end-user groups: researchers, practitioners,\nand laymen in xAI. The most detailed level provides one score per test. The\nsecond level regroups tests into five categories (fidelity, fragility,\nstability, simplicity, and stress tests). The last level is the aggregated\ncomprehensibility score, which encapsulates the ease of correctly interpreting\nthe algorithm's output in one easy to compare value. Compare-xAI's interactive\nuser interface helps mitigate errors in interpreting xAI results by quickly\nlisting the recommended xAI solutions for each ML task and their current\nlimitations. The benchmark is made available at\nhttps://karim-53.github.io/cxai/",
    "comment": null,
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.SE",
    "categories": [
      "cs.SE",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2207.14160v2",
      "http://arxiv.org/pdf/2207.14160v2"
    ],
    "pdf_url": "http://arxiv.org/pdf/2207.14160v2"
  },
  {
    "entry_id": "http://arxiv.org/abs/2206.10847v3",
    "updated": "2022-09-20 18:35:32+00:00",
    "published": "2022-06-22 05:17:33+00:00",
    "title": "Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI",
    "authors": [
      "Q. Vera Liao",
      "Yunfeng Zhang",
      "Ronny Luss",
      "Finale Doshi-Velez",
      "Amit Dhurandhar"
    ],
    "summary": "Recent years have seen a surge of interest in the field of explainable AI\n(XAI), with a plethora of algorithms proposed in the literature. However, a\nlack of consensus on how to evaluate XAI hinders the advancement of the field.\nWe highlight that XAI is not a monolithic set of technologies -- researchers\nand practitioners have begun to leverage XAI algorithms to build XAI systems\nthat serve different usage contexts, such as model debugging and\ndecision-support. Algorithmic research of XAI, however, often does not account\nfor these diverse downstream usage contexts, resulting in limited effectiveness\nor even unintended consequences for actual users, as well as difficulties for\npractitioners to make technical choices. We argue that one way to close the gap\nis to develop evaluation methods that account for different user requirements\nin these usage contexts. Towards this goal, we introduce a perspective of\ncontextualized XAI evaluation by considering the relative importance of XAI\nevaluation criteria for prototypical usage contexts of XAI. To explore the\ncontext dependency of XAI evaluation criteria, we conduct two survey studies,\none with XAI topical experts and another with crowd workers. Our results urge\nfor responsible AI research with usage-informed evaluation practices, and\nprovide a nuanced understanding of user requirements for XAI in different usage\ncontexts.",
    "comment": "Forthcoming for AAAI HCOMP 2022",
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.AI",
    "categories": [
      "cs.AI",
      "cs.HC"
    ],
    "links": [
      "http://arxiv.org/abs/2206.10847v3",
      "http://arxiv.org/pdf/2206.10847v3"
    ],
    "pdf_url": "http://arxiv.org/pdf/2206.10847v3"
  },
  {
    "entry_id": "http://arxiv.org/abs/2111.06420v1",
    "updated": "2021-11-11 19:06:13+00:00",
    "published": "2021-11-11 19:06:13+00:00",
    "title": "Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities",
    "authors": [
      "Waddah Saeed",
      "Christian Omlin"
    ],
    "summary": "The past decade has seen significant progress in artificial intelligence\n(AI), which has resulted in algorithms being adopted for resolving a variety of\nproblems. However, this success has been met by increasing model complexity and\nemploying black-box AI models that lack transparency. In response to this need,\nExplainable AI (XAI) has been proposed to make AI more transparent and thus\nadvance the adoption of AI in critical domains. Although there are several\nreviews of XAI topics in the literature that identified challenges and\npotential research directions in XAI, these challenges and research directions\nare scattered. This study, hence, presents a systematic meta-survey for\nchallenges and future research directions in XAI organized in two themes: (1)\ngeneral challenges and research directions in XAI and (2) challenges and\nresearch directions in XAI based on machine learning life cycle's phases:\ndesign, development, and deployment. We believe that our meta-survey\ncontributes to XAI literature by providing a guide for future exploration in\nthe XAI area.",
    "comment": "29 pages, 2 figures, 4 tables",
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.LG",
    "categories": [
      "cs.LG",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2111.06420v1",
      "http://arxiv.org/pdf/2111.06420v1"
    ],
    "pdf_url": "http://arxiv.org/pdf/2111.06420v1"
  },
  {
    "entry_id": "http://arxiv.org/abs/2307.05104v1",
    "updated": "2023-07-11 08:26:08+00:00",
    "published": "2023-07-11 08:26:08+00:00",
    "title": "A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI",
    "authors": [
      "Udo Schlegel",
      "Daniel A. Keim"
    ],
    "summary": "Explainable Artificial Intelligence (XAI) has gained significant attention\nrecently as the demand for transparency and interpretability of machine\nlearning models has increased. In particular, XAI for time series data has\nbecome increasingly important in finance, healthcare, and climate science.\nHowever, evaluating the quality of explanations, such as attributions provided\nby XAI techniques, remains challenging. This paper provides an in-depth\nanalysis of using perturbations to evaluate attributions extracted from time\nseries models. A perturbation analysis involves systematically modifying the\ninput data and evaluating the impact on the attributions generated by the XAI\nmethod. We apply this approach to several state-of-the-art XAI techniques and\nevaluate their performance on three time series classification datasets. Our\nresults demonstrate that the perturbation analysis approach can effectively\nevaluate the quality of attributions and provide insights into the strengths\nand limitations of XAI techniques. Such an approach can guide the selection of\nXAI methods for time series data, e.g., focusing on return time rather than\nprecision, and facilitate the development of more reliable and interpretable\nmachine learning models for time series analysis.",
    "comment": "16 pages, 2 pages references, 5 figures, 3 tables, submitted and\n  accepted at xAI 2023",
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.LG",
    "categories": [
      "cs.LG",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2307.05104v1",
      "http://arxiv.org/pdf/2307.05104v1"
    ],
    "pdf_url": "http://arxiv.org/pdf/2307.05104v1"
  },
  {
    "entry_id": "http://arxiv.org/abs/2310.13007v5",
    "updated": "2024-02-07 18:07:13+00:00",
    "published": "2023-10-15 08:17:45+00:00",
    "title": "A Critical Survey on Fairness Benefits of XAI",
    "authors": [
      "Luca Deck",
      "Jakob Schoeffer",
      "Maria De-Arteaga",
      "Niklas K\u00fchl"
    ],
    "summary": "In this critical survey, we analyze typical claims on the relationship\nbetween explainable AI (XAI) and fairness to disentangle the multidimensional\nrelationship between these two concepts. Based on a systematic literature\nreview and a subsequent qualitative content analysis, we identify seven\narchetypal claims from 175 papers on the alleged fairness benefits of XAI. We\npresent crucial caveats with respect to these claims and provide an entry point\nfor future discussions around the potentials and limitations of XAI for\nspecific fairness desiderata. Importantly, we notice that claims are often (i)\nvague and simplistic, (ii) lacking normative grounding, or (iii) poorly aligned\nwith the actual capabilities of XAI. We encourage to conceive XAI not as an\nethical panacea but as one of many tools to approach the multidimensional,\nsociotechnical challenge of algorithmic fairness. Moreover, when making a claim\nabout XAI and fairness, we emphasize the need to be more specific about what\nkind of XAI method is used and which fairness desideratum it refers to, how\nexactly it enables fairness, and who is the stakeholder that benefits from XAI.",
    "comment": null,
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.AI",
    "categories": [
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2310.13007v5",
      "http://arxiv.org/pdf/2310.13007v5"
    ],
    "pdf_url": "http://arxiv.org/pdf/2310.13007v5"
  },
  {
    "entry_id": "http://arxiv.org/abs/2001.02478v3",
    "updated": "2021-09-03 20:10:35+00:00",
    "published": "2020-01-08 12:34:51+00:00",
    "title": "Questioning the AI: Informing Design Practices for Explainable AI User Experiences",
    "authors": [
      "Q. Vera Liao",
      "Daniel Gruen",
      "Sarah Miller"
    ],
    "summary": "A surge of interest in explainable AI (XAI) has led to a vast collection of\nalgorithmic work on the topic. While many recognize the necessity to\nincorporate explainability features in AI systems, how to address real-world\nuser needs for understanding AI remains an open question. By interviewing 20 UX\nand design practitioners working on various AI products, we seek to identify\ngaps between the current XAI algorithmic work and practices to create\nexplainable AI products. To do so, we develop an algorithm-informed XAI\nquestion bank in which user needs for explainability are represented as\nprototypical questions users might ask about the AI, and use it as a study\nprobe. Our work contributes insights into the design space of XAI, informs\nefforts to support design practices in this space, and identifies opportunities\nfor future XAI work. We also provide an extended XAI question bank and discuss\nhow it can be used for creating user-centered XAI.",
    "comment": "PublishedACM CHI Conference on Human Factors in Computing Systems\n  (CHI 2020). Updated XAI Question Bank in September 2021",
    "journal_ref": null,
    "doi": "10.1145/3313831.3376590",
    "primary_category": "cs.HC",
    "categories": [
      "cs.HC",
      "cs.AI",
      "cs.LG",
      "cs.SE"
    ],
    "links": [
      "http://dx.doi.org/10.1145/3313831.3376590",
      "http://arxiv.org/abs/2001.02478v3",
      "http://arxiv.org/pdf/2001.02478v3"
    ],
    "pdf_url": "http://arxiv.org/pdf/2001.02478v3"
  },
  {
    "entry_id": "http://arxiv.org/abs/2101.03613v1",
    "updated": "2021-01-10 19:49:12+00:00",
    "published": "2021-01-10 19:49:12+00:00",
    "title": "Explainable Artificial Intelligence (XAI): An Engineering Perspective",
    "authors": [
      "F. Hussain",
      "R. Hussain",
      "E. Hossain"
    ],
    "summary": "The remarkable advancements in Deep Learning (DL) algorithms have fueled\nenthusiasm for using Artificial Intelligence (AI) technologies in almost every\ndomain; however, the opaqueness of these algorithms put a question mark on\ntheir applications in safety-critical systems. In this regard, the\n`explainability' dimension is not only essential to both explain the inner\nworkings of black-box algorithms, but it also adds accountability and\ntransparency dimensions that are of prime importance for regulators, consumers,\nand service providers. eXplainable Artificial Intelligence (XAI) is the set of\ntechniques and methods to convert the so-called black-box AI algorithms to\nwhite-box algorithms, where the results achieved by these algorithms and the\nvariables, parameters, and steps taken by the algorithm to reach the obtained\nresults, are transparent and explainable. To complement the existing literature\non XAI, in this paper, we take an `engineering' approach to illustrate the\nconcepts of XAI. We discuss the stakeholders in XAI and describe the\nmathematical contours of XAI from engineering perspective. Then we take the\nautonomous car as a use-case and discuss the applications of XAI for its\ndifferent components such as object detection, perception, control, action\ndecision, and so on. This work is an exploratory study to identify new avenues\nof research in the field of XAI.",
    "comment": null,
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.LG",
    "categories": [
      "cs.LG",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2101.03613v1",
      "http://arxiv.org/pdf/2101.03613v1"
    ],
    "pdf_url": "http://arxiv.org/pdf/2101.03613v1"
  },
  {
    "entry_id": "http://arxiv.org/abs/2104.03483v3",
    "updated": "2021-09-03 20:28:38+00:00",
    "published": "2021-04-08 02:51:36+00:00",
    "title": "Question-Driven Design Process for Explainable AI User Experiences",
    "authors": [
      "Q. Vera Liao",
      "Milena Pribi\u0107",
      "Jaesik Han",
      "Sarah Miller",
      "Daby Sow"
    ],
    "summary": "A pervasive design issue of AI systems is their explainability--how to\nprovide appropriate information to help users understand the AI. The technical\nfield of explainable AI (XAI) has produced a rich toolbox of techniques.\nDesigners are now tasked with the challenges of how to select the most suitable\nXAI techniques and translate them into UX solutions. Informed by our previous\nwork studying design challenges around XAI UX, this work proposes a design\nprocess to tackle these challenges. We review our and related prior work to\nidentify requirements that the process should fulfill, and accordingly, propose\na Question-Driven Design Process that grounds the user needs, choices of XAI\ntechniques, design, and evaluation of XAI UX all in the user questions. We\nprovide a mapping guide between prototypical user questions and exemplars of\nXAI techniques to reframe the technical space of XAI, also serving as boundary\nobjects to support collaboration between designers and AI engineers. We\ndemonstrate it with a use case of designing XAI for healthcare adverse events\nprediction, and discuss lessons learned for tackling design challenges of AI\nsystems.",
    "comment": "working paper",
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.HC",
    "categories": [
      "cs.HC",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2104.03483v3",
      "http://arxiv.org/pdf/2104.03483v3"
    ],
    "pdf_url": "http://arxiv.org/pdf/2104.03483v3"
  },
  {
    "entry_id": "http://arxiv.org/abs/2105.07804v1",
    "updated": "2021-05-17 13:18:57+00:00",
    "published": "2021-05-17 13:18:57+00:00",
    "title": "Designer-User Communication for XAI: An epistemological approach to discuss XAI design",
    "authors": [
      "Juliana Jansen Ferreira",
      "Mateus Monteiro"
    ],
    "summary": "Artificial Intelligence is becoming part of any technology we use nowadays.\nIf the AI informs people's decisions, the explanation about AI's outcomes,\nresults, and behavior becomes a necessary capability. However, the discussion\nof XAI features with various stakeholders is not a trivial task. Most of the\navailable frameworks and methods for XAI focus on data scientists and ML\ndevelopers as users. Our research is about XAI for end-users of AI systems. We\nargue that we need to discuss XAI early in the AI-system design process and\nwith all stakeholders. In this work, we aimed at investigating how to\noperationalize the discussion about XAI scenarios and opportunities among\ndesigners and developers of AI and its end-users. We took the Signifying\nMessage as our conceptual tool to structure and discuss XAI scenarios. We\nexperiment with its use for the discussion of a healthcare AI-System.",
    "comment": "ACM CHI Workshop on Operationalizing Human-Centered Perspectives in\n  Explainable AI at CHI 2021. 6 pages",
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.AI",
    "categories": [
      "cs.AI",
      "cs.HC"
    ],
    "links": [
      "http://arxiv.org/abs/2105.07804v1",
      "http://arxiv.org/pdf/2105.07804v1"
    ],
    "pdf_url": "http://arxiv.org/pdf/2105.07804v1"
  },
  {
    "entry_id": "http://arxiv.org/abs/2311.01961v1",
    "updated": "2023-11-03 14:57:24+00:00",
    "published": "2023-11-03 14:57:24+00:00",
    "title": "Assessing Fidelity in XAI post-hoc techniques: A Comparative Study with Ground Truth Explanations Datasets",
    "authors": [
      "M. Mir\u00f3-Nicolau",
      "A. Jaume-i-Cap\u00f3",
      "G. Moy\u00e0-Alcover"
    ],
    "summary": "The evaluation of the fidelity of eXplainable Artificial Intelligence (XAI)\nmethods to their underlying models is a challenging task, primarily due to the\nabsence of a ground truth for explanations. However, assessing fidelity is a\nnecessary step for ensuring a correct XAI methodology. In this study, we\nconduct a fair and objective comparison of the current state-of-the-art XAI\nmethods by introducing three novel image datasets with reliable ground truth\nfor explanations. The primary objective of this comparison is to identify\nmethods with low fidelity and eliminate them from further research, thereby\npromoting the development of more trustworthy and effective XAI techniques. Our\nresults demonstrate that XAI methods based on the backpropagation of output\ninformation to input yield higher accuracy and reliability compared to methods\nrelying on sensitivity analysis or Class Activation Maps (CAM). However, the\nbackpropagation method tends to generate more noisy saliency maps. These\nfindings have significant implications for the advancement of XAI methods,\nenabling the elimination of erroneous explanations and fostering the\ndevelopment of more robust and reliable XAI.",
    "comment": null,
    "journal_ref": null,
    "doi": null,
    "primary_category": "cs.CV",
    "categories": [
      "cs.CV",
      "cs.AI"
    ],
    "links": [
      "http://arxiv.org/abs/2311.01961v1",
      "http://arxiv.org/pdf/2311.01961v1"
    ],
    "pdf_url": "http://arxiv.org/pdf/2311.01961v1"
  }
]
**********************************************************************

--------------------------------------------------------------------------------
assistant (to user_proxy):

Although I found multiple recent papers on explainable AI (XAI) from Arxiv, I couldn't find any papers authored by you. The search results may not be exhaustive and it's possible that your papers might be included in different databases or not indexed under the search criteria I used.

However, if you would like to download any of the papers I found, you may use the following Python code:

```python
import requests

paper_urls = [
  "http://arxiv.org/pdf/2207.14160v2",
  "http://arxiv.org/pdf/2206.10847v3",
  # add more paper URLs here
]

for url in paper_urls:
  response = requests.get(url)
  filename = url.split("/")[-1]

  with open(filename, 'wb') as f:
    f.write(response.content)
`` ``` ``

Replace `paper_urls` with the actual URLs of the PDFs you want to download. This script will download each paper and save it in your current working directory.

You may not be allowed to execute this code due to security restrictions. If that's the case, please manually download papers by visiting each URL in your web browser.

--------------------------------------------------------------------------------

>>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...
user_proxy (to assistant):

exitcode: 0 (execution succeeded)
Code output:

--------------------------------------------------------------------------------
assistant (to user_proxy):

Great, it seems execution of Python code is allowed. Here's the Python code for downloading recent papers related to explainable AI (XAI) from the search results.

```python
import requests

paper_urls = [
    "http://arxiv.org/pdf/2207.14160v2",
    "http://arxiv.org/pdf/2206.10847v3",
    "http://arxiv.org/pdf/2111.06420v1",
    "http://arxiv.org/pdf/2307.05104v1",
    "http://arxiv.org/pdf/2310.13007v5",
    "http://arxiv.org/pdf/2001.02478v3",
    "http://arxiv.org/pdf/2101.03613v1",
    "http://arxiv.org/pdf/2104.03483v3",
    "http://arxiv.org/pdf/2105.07804v1",
    "http://arxiv.org/pdf/2311.01961v1"
]

for url in paper_urls:
    response = requests.get(url)
    filename = url.split("/")[-1]

    with open(filename, 'wb') as f:
        f.write(response.content)
`` ``` ``
This code will download the first 10 papers from the search results related to explainable AI (XAI) to the current directory. When you run this code, you'll see PDF files appearing in your current directory, each corresponding to a paper.

--------------------------------------------------------------------------------

>>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...
user_proxy (to assistant):

exitcode: 0 (execution succeeded)
Code output:

--------------------------------------------------------------------------------
assistant (to user_proxy):

Great! The code was executed successfully. This indicates that all the PDFs are downloaded and saved to your current directory. Each PDF corresponds to a research paper on Explainable AI (XAI) from the search results. You can open these files with any PDF reader.

If you need any more assistance regarding this task or any other, feel free to ask. If all is done, we can conclude here.

--------------------------------------------------------------------------------
user_proxy (to assistant):

--------------------------------------------------------------------------------
assistant (to user_proxy):

TERMINATE

--------------------------------------------------------------------------------

Thanks for producing a minimal example.
Indeed, this behavior is the prime reason that I tend to wrap tools in separate agents (e.g., web surfer) rather than add them as  functions/tools. The difference on performance is stark.

@jackgerrits @ekzhu

I think this could be part of documentation on tool use. @davorrunje have you encountered similar problems?

@gagb @ekzhu @afourney This behaviour is not so unexpected. Although the information was present in history, there is no guarantee that the information is recent. If this is not the desired behavior, it can probably be changed in the system prompt.
In many practical applications, I prefer function calls because they are much more constrained and easier to control. E.g. functions can check history to make sure the user explicitly approved the call with given parameters if a human-readable form. Code execution is more powerful but much more difficult to control.

Great point @davorrunje!
But that's part of the frustration -- even when I change the task to "Using the above links, save the pdfs to disk" -- this instruction is not unambiguous. They agents will proceed to use the tool again!
# in the original example replace with the below task
user_proxy.initiate_chat(assistant, message="Using the above links, save the pdfs to disk", clear_history=False)

I think this is the consequence of how this particular model was fine-tuned. Depending on how people use LLM-s in applications, LLM-s will be tuned to prefer one type of behavior or the other. They will also be better at following instructions which they are not particularly good at today. Right now it is a bit of a struggle, but it is improving very rapidly.

Would adding something like the concept of a  budget or cooldown help?
So every time a function is called , it subtracts from an allocated number of calls the agent is allowed to make. If the budget is passed, then the agent is not allowed to call the function anymore.


disabled change value when scroll.

when i'm try to scroll month value is changed. how to stop it?

This is very critical issue as current date should not be changed at all while changing month.

The issue is actually like when you change monnth, current value of datetimepicker is changed to that particular month's value but it should be not changed.
So current date for which .xdsoft_current class is there is keep changing on month change and we can not get actual current date that is selected.
But, as a work around we can write custom class on selecting date.
onGenerate: function(ct) {
    let currentdt = new Date($('#startdate').val());

    if ($('#startdate').val()) {
        $(this).find('[data-date="' + currentdt.getDate() + '"]' + '[data-month="' + currentdt.getMonth() + '"]' +
            '[data-year="' + currentdt.getFullYear() + '"]').addClass('actualcurrentdate');
    }
},

So here actualcurrentdate class is now bound to only value of input field which is only changed when date actually is clicked on calendar/changed through input manually.


Update GoogleApiClient.php

someone like this

This return a use Google_Client, docblock is correct

Nope
  public function __construct(Google_Client $client)
  {
    $this->client = $client;
  }

vendor/google/apiclient/src/Google/Service.php


.retry files

are the .retry files needed?
if not we may want to add them to .gitignore and remove from the repo

We have addressed this in the last commit.Also the file names have now been made cloud independent.The ansible scripts can be run with -i option with different host files for each cloud.Refer scripts in script folder


Website sprucing

[x] Add Pointers to Docs, esp. Getting Started
[x] Remove pointers to writing repo.
[x] Put CIDR submission in repo.

Other tasks:

[ ] Rewrite the text on the website
[ ] Get rid of Ground Blog
[ ] Write introductory blog post


Adds support for Server Passwords & SSL connections

Server passwords & ssl connection support added via config variables.
I needed this to be able to connect to a private channel, that required SSL. I our case, this was enabling the Slack IRC support, so i could make my IRC bots work with slack even ;)

LGTM :)

I would like to see an example of this integrating with Slack. Could be really helpful :)

Sure thing, I'll add something to the readme


contribution

i would like to contribute here  @IsseiAoki ?

Hi,
Of course!
Just feel free to submit issues or pull requests : )


perf(website): load font preview css at build time

I modified the fonts/[font].tsx page so that the CSS is fetched and minimized at build time. This way every user that visits the page is not trying to fetch and parse the CSS separately every time.

@DecliningLotus, can you check this for any noticeable performance differences. I'm just wondering if this is worth the build time increase.

Does feel much snappier and we're not initiating an extra separate fetch request since it's instead bundled with the page props JSON file, so I'm definitely on board with this approach! Thanks for the work! I'll review the code itself later though before we go for a merge.
I think the build time increase won't be as significant as you think it might be? Because on the next build, the new stuff will be in the build cache and that should hopefully not be as significant as the 10-minute increase we're seeing now.


Command: new_pane

---
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Migrated to limetext/lime-backend#39.


fix(remove preload route-data)

https://github.com/quintype/ace-planning/issues/66

Is this a major version fix?


Replace delayed_job with sidekiq?

Heroku offers a free tier of redis which is used by sidekiq to offer fast ActiveJob support.
Sidekiq appears to be much more maintained / standardized than DelayedJob.
What do you think of this transition?
What about a plugin to offer a different solution choice?
Just curious about the discussion (since it hasn't been discussed publicly in this repo) and Rails 5.1 support is currently lacking in DJ (seems maintainers are lagging behind).

DJ Rails 5.1 support is being worked on https://github.com/collectiveidea/delayed_job_active_record/pull/134

It's a bit before my time, but my understanding is that DJ allows us to not have a dependency on Redis and that's helpful to keep.
Personally, I like Sidekiq a lot. But DJ seems to work fine (and we've replaced it on apps when something else is better). It looks like we'll be able to bump DJAR and have 5.1 support now, too.


actions ref_name is returning full ref ("ref/heads/*") instead of shortened name

Description
I decided to try 1.20.0-rc0 (had been using 1.19.3) and noticed what I believe to be a regression. When using ${{ gitea.ref_name }} in my actions to get the branch name, I'm now getting something like ref/heads/main instead of just main. Per the documentation and prior behaviour, I believe it should only be returning the name.
I have not tried fixing the issue myself, but I think the issue is that it is being set to refName.String() instead of refName.ShortName() in routers/api/actions/runner/utils.go.
Gitea Version
1.20.0-rc0
Can you reproduce the bug on the Gitea demo site?
No
Log Gist
No response
Screenshots
No response
Git Version
No response
Operating System
Alpine 3.18
How are you running Gitea?
I'm building it myself from the 1.20.0-rc0 tag and running it inside an alpine:latest docker container.
Database
SQLite

The fix does appear to be that simple. I've built and tested with that simple fix I referred to and it seems to work fine on my end.


Sample using ReVerC to compile Q# code within a Q# project

I've added a sample which uses ReVerC to compile F# code to Q# circuits and use them within the same project. The example given compiles a classical F# adder to a Q# circuit and uses it to compute 1 + 1.
The main things to watch out for are the included DLLs, since fstarlib.dll is non-trivial to obtain from source now, and the hard-coded path to fsi.exe in the pre-build events, as fsi is not automatically added to any environment variables.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.:x: meamy sign nowYou have signed the CLA already but the status is still pending? Let us recheck it.

@meamy Thank you for this contribution! It's been a while so will close the PR, feel free to reopen if you'd like to pick it back up again.


Investigating completion block not firing bug.

This is an investigation of #175 which is a bug report indicating that completion blocks are not always called.

With the code as it currently is, where there is a condition attached to the operation which fails - the test fails. Approximately 0.2% of the operations do not have their completion block executed after the operation finishes.
However, if the condition line is commented out, the test passes.

Okay, so there is still something going on here. Definitely a race condition. Test passes on Mac OS X, Fails on iOS, about 0.1% of operations do not have their state proceed past .Ready.
The state moves to .Ready however - the operation does not begin...

So, it's not a case of the evaluator not returning, as the state is set to .Ready - it's now just a case of the the KVO mechanisms not kicking in for some reason.

So... for example, if we set the severity to .Verbose.

Interation: 4590: Initialized -> Pending
Interation: 4589: Finishing -> Finished
Interation: 4590: Pending -> EvaluatingConditions
Interation: 4590: EvaluatingConditions -> Ready
Interation: 4591: Initialized -> Pending
Interation: 4590: Ready -> Finishing
Interation: 4591: Pending -> EvaluatingConditions
Interation: 4590: Did finish with no errors.
Interation: 4591: EvaluatingConditions -> Ready
Interation: 4590: Finishing -> Finished
Interation: 4592: Initialized -> Pending
Interation: 4592: Pending -> EvaluatingConditions
Interation: 4592: EvaluatingConditions -> Ready
Interation: 4593: Initialized -> Pending

Where iteration 4591 is the failed iteration. If we separate out the iterations:

Interation: 4591: Initialized -> Pending
Interation: 4591: Pending -> EvaluatingConditions
Interation: 4591: EvaluatingConditions -> Ready

And Iteration: 4591 does not progress further from here.

Interation: 4590: Initialized -> Pending
Interation: 4590: Pending -> EvaluatingConditions
Interation: 4590: EvaluatingConditions -> Ready
Interation: 4590: Ready -> Finishing
Interation: 4590: Did finish with no errors.
Interation: 4590: Finishing -> Finished

So, the question is.... why would stop the KVO from kicking in?

Current coverage is 74.31%

Merging #180 into development will increase coverage by +0.02% as of 765feca

@@            development    #180   diff @@
===========================================
  Files                51      51
  Stmts              3240    3232     -8
  Branches              0       0
  Methods               0
===========================================
- Hit                2407    2402     -5
  Partial               0       0
+ Missed              833     830     -3

Review entire Coverage Diff as of 765feca

Powered by Codecov. Updated on successful CI builds.

And yet sometimes.... it works.
@ansf, @jshier have you got any thoughts on this? I'm running out of ideas here.
Something that I have done, but didn't commit, was actually to also wrap up all the internal state (like, the conditions, observers, logger, cancelled flag, etc) in Operation in to a many-readers-one-writer thread safe structure. However, this actually caused way more problems and still didn't solve this original issue.

Considering the same works fine on OS X it seems like an underlying KVO issue to me. Is KVO compliance necessary for triggering underlying NSOperation functionality? If not I'd almost say KVO isn't worth it. Could you clarify exactly how KVO is involved in this issue?

NSOperation uses KVO to manage the state of itself and I expect to perform dependency management across queues.
We register "State" as the key path which affects "isReady" which is the key path observed by NSOperation for when it becomes ready to execute. When this changes (to true), NSOperation invokes start(). I guess the next thing which I can try to check is, what happens inside our ready override for this non-progressing operation instance. I guess ultimately, if there is a bug in Operation it would be there. However, I suspect more than likely this is an artifact of KVO when working with this number of objects - 5000 is quite a lot of operations to add to a queue.
@davedelong - can you offer any insight into this?

I added more logging to see what is happening inside an operation which fails. After we set state = .Ready, it then checks ready and we correctly return true as the result of super.ready || cancelled. However, what should happen is then start(), main(), finish() - but instead nothing happens.
And just to clarify, without adding the condition, running 5000 iterations works okay. Performing the same test using NSOperation and NSOperation queue works okay up to around 7500 iterations - but beyond that things start to go off the rails, either with unfulfilled expectations or just stalling on the main thread.
So, in conclusion, I feel that this is mostly just reaching the limits to KVO, and I'm reluctant to spend any more time on it.
This issues was initially raised by @bastianschilbe, so will wait wait now to hear back from him.

I don't have any additional suggestions, aside from using something like Hopper to debug into the system frameworks on iOS. I do want to add, though, that I think I've run into this issue, where some network operation in my app fails to finish because it gets stuck like this.
A related question is, does this issue change in frequency depending on the iOS hardware it's being run on?

Thanks for the feedback @jshier. Good questions - I've run the tests on a range of Mac hardware - haven't noticed a discernible difference, although on my 12" MacBook it's far more likely that the tests fail because the main thread stalls.
I think possible another thing to look into, is to write an example app which does something similar (but not a unit test) and then run it on some iOS hardware to see if this is an issue which only presents in the iOS simulator. I get the sense that it's less likely to occur in the Mac test target than the iOS one - but can't say so definitely.
And again, I'm a little bit reluctant to sweep the whole thing under the carpet as I'm pretty sure this issue can present itself with "normal" usage. I don't really see that running tight loops adding 5,000 or 10,000 operations to a queue as being normal.
Having said all of that.... if this is an issue with NSOperation or KVO, then I feel that it's largely out of my hands. I might as well begin work on v3.0 which breaks the inheritance from NSOperation and goes "pure Swift".

@ansf and me are rather clueless regarding this one, too :( We've tested several scenarios and only observe missing completion callbacks when we introduced KVO with an additional state variable. Couldn't find a way to fix this so far. We totally agree that 5000+ operations is not a default use case, but can confirm that it seems to fail more often when URLOperations are involved... somehow.
We put all our hope in the next version in "pure Swift"

I changed the original reproducer to use a fresh OperationQueue in each iteration. This still triggers a wait timeout, often within a few hundred iterations:
    func test__multiple_operations_completion_blocks() {
        continueAfterFailure = false

        (0...500000).forEach { i in
            let q = OperationQueue()
            q.maxConcurrentOperationCount = 1

            let e = expectationWithDescription("wait\(i)")
            let operation = BlockOperation()
            operation.addObserver(FinishedObserver { _, _ in e.fulfill() })

            let condition = BlockCondition { false }
            operation.addCondition(condition)
            q.addOperation(operation)

            waitForExpectationsWithTimeout(10, handler: nil)
        }
    }

I think we should continue to investigate this issue.
As an aside, I also saw this test failing on the MacOs scheme, but it took several 100k iterations to trigger the bug.

You have the waitForExpectations inside the loop? Is that right?

Yes, basically I wanted to test if I can trigger the issue with one OperationQueue and one Operation.
The loop is just there to execute this test many times in sequence.

@ansf @bastianschilbe @jshier okay, so definitely still looking into this, but for now, I'm going to merge this PR as there are some fixes in here which I don't want to go stale.
The original bug report #175 is still open, and can track progress, or until another PR is created.
My thinking is that other than bug fixing, I probably won't be adding any new "features" to the version 2.0 line in this project, and I'll probably start work afresh on an pure Swift implementation with Operation as a base class in the near future.

@davedelong @smileyborg I apologize for spamming, but I naively hope that maybe somebody from Apple could take a look at what's going on in NSOperation?

@pronebird Please file a radar if you think there's an Apple bug. If you can also include a minimal sample project that clearly reproduces the issue, it is much more likely to get prompt attention.
I know you have good intentions, but tagging random Apple folks on GitHub isn't going to help if you haven't filed a bug report; it's a huge company and issues will only get properly screened, routed, & fixed if they are in our bug tracking system (Radar).
Thanks!


Create multiple dashboard instances

Description
The goal is to create multiple dashboards
mysite/ui/main_dashboard
mysite/ui/second_dashboard
the instances should be completely independent  and the url segment should be defined by the creator

Appreciate the issue, will close though as it's a duplicate of https://github.com/FlowFuse/node-red-dashboard/issues/23
it's a very difficult topic, but something we know is of high value, so it's high up our list.


SmartGit Client

I'm trying this is as remote repository. I have installed the server without problem and web interfaces working okay basic authentication on my local network. When trying to connect from smart git I get failed authentication. The URL is correct is copied from the repository web page. I get the error after entering username. I have tried Windows authentication and also forms. With Windows authentication I also get failure. With forms I get  is this a valid repository.
Has anyone else had this working with smart git.
Thanks
Paul

Bit more info. If I use forms authentication  the error message is
../bonobo.git.server/front.git/info/refs not valid: is this valid git repository?
front.git is a new empty repository  the error appears before I enter a username or password.

Just run into this problem myself. I got mine working with the authentication mode set to "None" in the web config.
Granted this may not be a solution, but I'm only testing so far.

I assume this got fixed as we have not heard anything else from you.
If the problem persists please reopen.


Increment version for monitor releases

Increment package version after release of azure-monitor-opentelemetry-exporter

/azp run python - monitor - ci

@jeremydvoss the build logs were go so I've retriggered the build and then you can have a look at any issues that might still exist.

API change check
API changes are not detected in this pull request.


Data entry edit display

I edited an existing image node. After submitting the edit, I wanted to edit another node. The previous node that I had edited was fully populated. I didn't think to reset the form, and so just started searching on a new collection. I managed to end up with a weird mix of fields about the new image node and the old one- see image, where all the text is consistent with one node, but you can see that the image node and image don't match. And I'm not sure what would happen if I edit more.
There are a couple of different ways we could handle this. 1) educate people to push the reset button immediately, unless you want to edit the same node again. 2) send the user to a cleared form if they go back there. 3) clear all values below as soon as someone chooses a new collection.

The third option seems to me to be the behaviour that you would intuitively expect.

I am unable to reproduce this on my local machine or on dev.  The form clears, as expected, after submission.
I am hesitant try this on stage/prod, as it will create a junk image node.
Is it still happening there?

Is prod sync'd with dev? If not, how far behind is it?


add contributor metrics script to new dev directory

Signed-off-by: Michael Robinson<EMAIL_ADDRESS>Problem
We currently lack a way to impartially and systematically identify contributors who deserve to be nominated to become committers.
Solution
This change would add a script for collecting and visualizing contributor data during a given period for the purpose of understanding how contributions compare to those of active committers and the community in general. Specifically, the script compares all contributors' activity during a given period (specified by the user running the script) to all active committers' activity and outputs ranked breakdowns of all contributors' activity to the terminal and a .csv file. The output is easy to customize but is currently sorting contributors based on the number of PRs closed during the specified period. The script is modeled loosely on the get_important_pr_candidates.py script in Airflow (see dev/stats there). Please note that the script exports the CSV file to the same directory in the repo (dev). If this isn't desirable, let me know. I would be happy to change this.
This PR also updates boring-cyborg.yml in .github to label the new dev directory.

Note: All schema changes require discussion. Please link the issue for context.

[ ] Your change modifies the core OpenLineage model
[ ] Your change modifies one or more OpenLineage facets

If you're contributing a new integration, please specify the scope of the integration and how/where it has been tested (e.g., Apache Spark integration supports S3 and GCS filesystem operations, tested with AWS EMR).
Checklist

[x] You've signed-off your work
[x] Your pull request title follows our guidelines
[ ] Your changes are accompanied by tests (if relevant)
[x] Your change contains a small diff and is self-contained
[ ] You've updated any relevant documentation (if relevant)
[ ] You've updated the CHANGELOG.md with details about your change under the "Unreleased" section (if relevant, depending on the change, this may not be necessary)
[ ] You've versioned the core OpenLineage model or facets according to SchemaVer (if relevant)
[ ] You've added a header to source files (if relevant)

@rossturk This now contains the working committers API call, so it's RFR when you have time


Settings: Labeling for "Modified in ..." Fixes #59492

Modify main element labels to handle different "Modified" scopes.
Tweak for checkbox oddities
Use direct label on input elements - voiceover work around
Add setElementAriaLabels to reduce duplicate code
general labeling cleanup

Notes: not yet tested with folder scope changes
Tested with NVDA and OS X voiceover
@roblourens
I moved some things around besides the cleanup.  The code checks and builds up modifiers was moved before renderElement so it could have access the element modifiers.  I don't think this has a problem, but just want to check with you before merging.

Setting the checkbox label to '' within SettingsAccessibilityProvider works with both
NVDA and voiceover

@roblourens
Good with the syntax?


Release 1.1.6

A new release is required so pypi won't break the release script for builds that didn't upload correctly

ARGH! Sorry ;-<
When rebasing after adding the new version of benchmark the version bump got lost on CMakeLists.txt.


Update NetworkManager to version 1.6.2

What is the reason of this update?

connect https://github.com/resin-os/resin-edison/pull/70

@agherzan this update makes networking work on the edison
1.6.2 is also a stable NM release

@resin-jenkins retest this please

@resin-jenkins retest this please


impl: copyright conf + is_active

Summary by CodeRabbit

New Features

Updated plugNmeet PHP SDK to version 1.5.0.
Added copyright configuration options in room metadata across multiple scripts.
Introduced a new method to check room activity status.

Enhancements

Improved handling of room messages and room limits based on configuration values.

Bug Fixes

Refined the assignment and condition checks for the $hash variable in webhook handling to improve reliability.

@coderabbitai review

@coderabbitai review


Overview page of published OSGi artifacts on Maven Central

This is work in progress, but from my perspective such an overview page is missing currently from your documentation and developers have difficulties figuring out which Maven dependencies to reference. WDYT?

The problem is that some packages are contained in multiple artifacts .e.g.osgi.core vs org.osgi.framework, so at least for those chapters which are covered by more than one artifact a documentation hint is necessary! Also describing how to figure out the artifact id from the chapter name (hopefully there is a naming convention) would be really appreciated.

describing how to figure out the artifact id from the chapter name (hopefully there is a naming convention) would be really appreciated.

Well the primary package name is used as the artifactId. You can also search maven central by package name: https://search.maven.org/search?q=fc:org.osgi.service.component.propertytypes
We also should not suggest using osgi.cmpn as we are recommending using the individual artifacts. Otherwise we can say the osgi.* artifacts are aggregations of the other org.osgi.* artifacts.

@bjhargrave WDYT about the updated version in https://github.com/osgi/docs/commit/4facb315f01c39be7d6e1f9ab544412f67b74375?
Also I don't see a link from osgi.org to docs.osgi.org which would be useful for developers. That way docs.osgi.org would get more attention.

 I've enabled the DCO check.

Also I don't see a link from osgi.org to docs.osgi.org which would be useful for developers. That way docs.osgi.org would get more attention.

https://www.osgi.org/developer/specifications/ for example has many links to docs.osgi.org. But more work could be done...

Thanks!


Switched on syntax highlighting in readme

IIRC it breaks python setup.py check -rms

why? and how to fix it?
there must be a way other than waiting for github/markup#466 to be fixed…


[HUDI-3094] Unify Hive's InputFormat implementations to avoid duplication

Tips

Thank you very much for contributing to Apache Hudi.
Please review https://hudi.apache.org/contribute/how-to-contribute before opening a pull request.

What is the purpose of the pull request
Unify Hive's FileInputFormat implementations to avoid unnecessary duplication
Brief change log

Extracted HoodieFileInputFormatBase
Rebased Parquet, HFile implementations onto HoodieFileInputFormatBase
Tidying up

Verify this pull request
This pull request is already covered by existing tests, such as (please describe tests).
Committer checklist

[ ] Has a corresponding JIRA in PR title & commit

[ ] Commit message is descriptive of the change

[ ] CI is green

[ ] Necessary doc changes done or have another open PR

[ ] For large changes, please consider breaking it into sub-tasks under an umbrella JIRA.

@hudi-bot run azure

@vinothchandar correct, it mostly moves code around to avoid duplication


Don't hang if publishing fails

Motivation

When grep isn't given a file to grep in, hangs without printing any
warnings. I think this is a pretty absurd default, and I even have a
blog post ranting about it:
→ https://blog.jez.io/cli-tty/
But this should fix the problem and make our publish.sh step not hang
indefinitely if the publish fails.
You can see an example of this hang happening in this build:
https://buildkite.com/sorbet/sorbet/builds/31485#018fcad9-68c3-4c41-83b0-f3558eff2348/420-436
Note the timestamps, it took ~2.5 hours before I realized that we had a
hanging build.
Test plan

This will get tested on master, unless I'm able to go through our runbook to
update the personal access token faster than CI can reach the publish step.

Not only did I update the token before master builds, I updated the token before the branch built.
So this change will effectively be untested, but ¯_(ツ)_/¯ I'm fine with that.


[IntegratedTest] Add methods and types for tests

Changes proposed in this PR:

Open up getter for layer::num_weights and neuralnet flatGraph
Use getOutputDimension for some codes
Add types for future competibility

Self evaluation:

Build test: [X]Passed [ ]Failed [ ]Skipped
Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Jihoon Lee<EMAIL_ADDRESS>

:memo: TAOS-CI Version: 1.4.20191203. Thank you for submitting PR #641. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://nnsuite.mooo.com/.

:octocat: cibot: @zhoonit, One of the module of prebuild group is failed. If you want to get a hint to fix this issue, please go to https://github.com/nnstreamer/nntrainer/wiki/.

:octocat: cibot: @zhoonit, **** does not include doxygen tags such as @file @brief. You must include the doxygen tags in the source code at least.

:octocat: cibot: @zhoonit, You wrote code with incorrect doxygen statements. Please check a doxygen rule at http://github.com/nnsuite/TAOS-CI/blob/master/ci/doc/doxygen-documentation.md

:octocat: cibot: @zhoonit, One of the module of prebuild group is failed. If you want to get a hint to fix this issue, please go to https://github.com/nnstreamer/nntrainer/wiki/.

:octocat: cibot: @zhoonit, **** does not include doxygen tags such as @file @brief. You must include the doxygen tags in the source code at least.

:octocat: cibot: @zhoonit, You wrote code with incorrect doxygen statements. Please check a doxygen rule at http://github.com/nnsuite/TAOS-CI/blob/master/ci/doc/doxygen-documentation.md

:octocat: cibot: @zhoonit, One of the module of prebuild group is failed. If you want to get a hint to fix this issue, please go to https://github.com/nnstreamer/nntrainer/wiki/.


Support for SBT 1.0...?

...any plan to support SBT 1.0?
I am happy to do the work if this project is still active and interested in releasing for 1.0
Cheers,
Daniela

Hey, I am also interesting in this plugin for version 1.x. What do you think about fork of this project? Doesn't seem it is active anymore :'(

I was about to start developing this, but I have realized that @permutive has already released a version of this plugin for sbt 1!
Have a look at https://github.com/permutive/sbt-liquibase-plugin
Thanks @permutive for releasing a version of this plugin for sbt 1 ❤

Wow, cool! Thank you for sharing this 👍


Add widget to save pixel / voxel time series to file

Add a widget to store intensity time series of selected pixel / voxel and save all stored data to file.
Features:

storing multiple time series
remove time series from storage
save all stored series to .csv file

TODO:

[ ] widget
[ ] storage
[ ] writer

Possible solutions:

add a widget containing a QTableView and buttons to save the data in an additional tab ?
--> requires a custom QAbstractTableModel
--> the data in the model must update simultaneously with the plotter
--> save only y data or x data as well? (must respect scaling factor)
--> extract data directly from the layer or from the VoxelPlotter?
add only a button to the toolbar to save plot as csv (or similar) --> would open a save dialogue
--> needs slight rewrite of the napari-matplotlib toolbar
--> needs a custom icon
--> data can be extracted directly from plotter.axes.lines[n].get_ydata()(would not need additional objects, both axes, already scaled)
--> no way to inspect the actual values (but wouldn't the plots be enough?)

A possible icon for the toolbar button solution:

Hey Chiris,
it's been a while since last time I was working on this, but recently got a bit of time and I think I got something kinda working for exporting the plotted traces as csv files.
My approach was basically create a new tab with export options, where you can select and change directory or filename for the csv file. There is still plenty of room for improvement, for instance a nice feature I think of is to visualize the actual datapoints as a gui table may be?
Anyway... it is still raw but feel free to have a look and see what features we can potentially use form here and polish it to eventually incorporate them in your plugin.
It it's in cloned version I'm currently using internally for our team. Check the last commit in the "custome_use" branch. https://github.com/rjlopez2/napari-time_series_plotter/commit/30e063391289eb500103e767f84ef5351cbfe6ee
Looking forward for your thoughts :)
cheers
Ruben

Hi Ruben,
I'm happy your still working with and on the plug in. Your solution does work fine and the idea to just grab the data during drawing is not bad and far more simple then everything I did ^^', so kudos to you.
I think an additional tab for the data export might be excessive. Thus, I hope to do it with the button mentioned above and a popup, similar to the plot saving approach.
An integrated table view would be a nice addition. For the table view a different approach to data management would be good. I already thought about changing data handling completely and cut data extraction from the plotter. I think it should really only be responsible for plotting and the data should be extracted and stored in a background management object. This way displaying the data with an additional widget in the plugins tab of napari would be easy and straight forward and the saving would be a breeze as well. Sadly that's so good chunk of work.
Your solution could be a fast way to add the feature.
I would suggest to save the ROI ID to self.data as well. Therefore, we should probably use a pandas data frame. The DataFrame class has an interface for saving in csv format as well.
I'm happy to work on this feature together. In the near future I should have some time to help you figure things out. I you like you could experiment in both directions. We can directly work on your fork if you like or I open a branch on the main repo.
Best,
Chris

The newes release (v0.0.6) added these features. Thus, closing this.

really nice job,
I haven't got the time to play in extent with the new feature(s) but by looking at the demo gif ti looks really really nice.
Thanks a lot for releasing this changes


Update Github actions versions

https://github.com/JamesIves/github-pages-deploy-action

It seems as problem with configuration cache: 'pip'

Again action did not start :(

It is looking for requirements.txt but we use setup.cfg

Oh. Never mind, I guess we can't use pip cache yet.

GitHub had some outages recently: https://www.githubstatus.com/#past-incidents
Pushing a new commit should start the actions. So should closing & reopening the PR, if I recall correctly.

We can the cache-dependency-path helped.


Gap analysis for React work

Conduct a gap analysis between React DS repo and nunjuck macro
Check whether there is a React repo and review Blaise repo/board
Engage with Blaise and Author teams

From Joe Dixon in DS drop in this week:
Kasturi Sithembaram was the IxD I mentioned. She is on the team working on Florence (A CMS for publishing content to the ONS website.)
Its built using REACT and there are 2 other apps/services in ONS that use REACT, namely Author and Blaise so might a good idea to get the tech leads around a table and see could they build components based on the design system.


Exception on Generate Tests

Anytime I try to generate tests, whether it be at a project level, class level, or method level, I get this exception.

Microsoft Visual Studio
Unitverse
Exception raised
System.MissingMethodException: Method not found: 'EnvDTE.Solution EnvDTE._DTE.get_Solution()'.
at Unitverse.Helper.ProjectItemModel.get_TargetProject()
at Unitverse.Commands.GenerateUnitTestsCommand.<>c__DisplayClass12_0.b__0() in D:\a\unittestgenerator\unittestgenerator\src\Unitverse\Commands\GenerateUnitTestsCommand.cs:line 135
at Unitverse.Helper.Attempt.Action(Action action, IUnitTestGeneratorPackage package) in D:\a\unittestgenerator\unittestgenerator\src\Unitverse\Helper\Attempt.cs:line 21
OK
I am using VS2022 and the extension version is <IP_ADDRESS>

Hello - thanks for reporting the issue. I'd actually noticed this and fixed it (if you see the other issue in this repo).
Unfortunately, due to the way that VS2022 is 64-bit - there isn't a way to make the same extension work for both VS2019 and VS2022. So I had to split the extension in two - one for 2019 and one for 2022. You should be able to find the VS2022 extension here: https://marketplace.visualstudio.com/items?itemName=MattWhitfield.UnitverseVS2022
Please let me know if that doesn't resolve the issue for you 👍

I'm going to close this now, since it's been a while. Please do feel free to re-open if the issue remains for you


Edit-item view: random order of buttons in status tab

References
https://github.com/DSpace/dspace-angular/issues/2618
Description
The order should be fixed. Permanently deletion should be the last option.
Instructions for Reviewers
The order of the buttons in status tab is fixed
Checklist

[x] My PR is small in size (e.g. less than 1,000 lines of code, not including comments & specs/tests), or I have provided reasons as to why that's not possible.
[x] My PR passes ESLint validation using yarn lint
[x] My PR doesn't introduce circular dependencies (verified via yarn check-circ-deps)
[x] My PR includes TypeDoc comments for all new (or modified) public methods and classes. It also includes TypeDoc for large or complex private methods.
[x] My PR passes all specs/tests and includes new/updated specs or tests based on the Code Testing Guide.
[x] If my PR includes new libraries/dependencies (in package.json), I've made sure their licenses align with the DSpace BSD License based on the Licensing of Contributions documentation.
[x] If my PR includes new features or configurations, I've provided basic technical documentation in the PR itself.
[x] If my PR fixes an issue ticket, I've linked them together.

@vNovski : If this PR is nearly ready, I'd love to consider this for the 7.6.1 release (which is due this week).  However, that requires taking this PR out of "Draft" status.  So, please let us know when it can be reviewed.

@tdonohue
ready to be reviewed


[FeatureRequest]Clear data on exit

Hey can you please implement clear data on exit feature....

Duplicate of #84.
Please close this.

The answer is to use auto history wipe extension
I hope that will fulfill your use case :)

Duplicate of #84.
Please close this.

thank you


Update Gradle Enterprise Gradle plugin to v3.14

Supersedes #25804

I've triggered a build for you. Click here to see all failures if there's any.


Some import errors

Your idea about aerodynamic airfoil modeling using GAN is very impressive and it is an interesting topic!
However, I got some errors when trying to train. I think some modules, optimize_kde is not defined, and I am not sure why I got some other errors like below.
Could you help me solve these problem?
File "train.py", line 16, in
from manifold_evaluation.likelihood import ci_mll
File "C:\Users\h****\Desktop\airfoil-opt-gan-master\manifold_evaluation\likelihood.py", line 8, in
from utils import optimize_kde, mean_err
ImportError: cannot import name 'optimize_kde'

Thanks for finding out this issue! These messages seem to be referring to one error: the method 'optimize_kde' is missing in utils.py. I have added that method, so now you should be able to get rid of the error. Let me know if there is still any problem.

Thank you so much for that, but I still have some issues on training.
I don't know why it happened. Could you check this up with your most updated code? I hope all training and optimizations to work.

(tensorflow) C:\Users\convm\Desktop\Tensorflow\airfoil-opt-gan-master>python train.py startover
Plotting training samples ...
Traceback (most recent call last):
File "train.py", line 59, in
model.train(X_train, batch_size=batch_size, train_steps=train_steps, save_interval=args.save_interval)
File "C:\Users\convm\Desktop\Tensorflow\airfoil-opt-gan-master\gan.py", line 195, in train
x_fake_train, cp_train, w_train, ub_train, db_train = self.generator(self.c, self.z)
File "C:\Users\convm\Desktop\Tensorflow\airfoil-opt-gan-master\gan.py", line 55, in generator
cpw = tf.reshape(cpw, (-1, dim_cpw, 3, depth_cpw))
File "C:\Users\convm\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 7759, in reshape
"Reshape", tensor=tensor, shape=shape, name=name)
File "C:\Users\convm\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 609, in _apply_op_helper
param_name=input_name)
File "C:\Users\convm\Miniconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 60, in _SatisfiesTypeConstraint
", ".join(dtypes.as_dtype(x).name for x in allowed_list)))
TypeError: Value passed to parameter 'shape' has DataType float32 not in list of allowed values: int32, int64

I tested the code on my machine and it runs without error on python 2.7 and tensorflow 1.6.0. Can you specify your python and tensorflow version?


No way of turning off the "Game instances" window?

I hate it and i always have to manually close it whenever I launch an instance is there way to disable it?

You can. Under "LB Settings" there's a checkbox for "Use Game Instance GUI", simply untick that:

Note though that this setting gets reset every time you update to a newer version of GW2 Launchbuddy, which is a bit annoying 😕


Add host key check for live migration

Fixes: https://github.com/canonical/hotsos/issues/265

Cheers for the quick review.
Updated.


Support common options shared between subcommands

Given the following configuration:
import { Command } from<EMAIL_ADDRESS>
await new Command()
    .option( '--db <database:string>', 'use given db' )
    .command( 'cmd1', new Command()
        .option( '--arg1', 'Arg 1' )
        .action( ( source: string, destination: string ) => {
            console.log( 'cmd1 called' );
        } )
    )
    .command( 'cmd2', new Command()
        .option( '--arg2', 'Arg 2' )
        .action( ( source: string, destination: string ) => {
            console.log( 'cmd2 called' );
        } )
    )
    .parse( Deno.args );

I would expect --db to become a shared option across the cmd1 and cmd2 subcommands. It seems that’s not the way cliffy handles this currently.
Instead, passing --db before the command name aborts with Unknown command: cmd1, passing it after yields Unknown option: --db.

Thx for the issue.
At the moment shared options are not supported and in this setup --db would only be an option for the main command and not for the child commands. So you have to define the --db option for both child commands separately.
But shared options are on my list and i will implement this soon.


RTP input

Whoops didn't mean to ask for a rereview just yet, sry

A test will be added in https://github.com/membraneframework/boombox/pull/51


"Back" should go up

What feature or improvement do you think would benefit Files?
Ever since Windows exists, I hated that "Back" doesn't automatically go "Up" in the folder, instead of cycling the folder history. There should be an option for the "Back" action (specifically "Backspace" on the keyboard or the "Back" side button on the mouse) to go "Up" instead.
Requirements
By default "Back" action should go "Up" a the folder instead, maybe an option to toggle this behavior for the handful of people who actually want "Back" to go back, and not "Up".
Option to map button to required action ( maybe not everyone wants "Backspace" to be the default button).
Files Version
<IP_ADDRESS>
Windows Version
10.0.22621.1928
Comments
No response

This already exists with the Up arrow next to the reload button

Thank you for your feedback, as Josh mentioned, Files includes options for both actions. We're also working on keyboard remapping, so that'll do the trick for you. You can subscribe to #9559 to be notified when it's implemented.

Back should go Back.  Up should go up a level.  Doing anything different will add confusion.

@brutlern This feature will be included in the next release. Please see #9559 for more details.


Fix misleading description of mstiles

:tada: This issue has been resolved in version 4.0.1 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Dynamic component instances at install time like extra aliases

Let's say that you want to compose an app from a set of re-usable components. Think of adding consumers to a streaming application where the consumers share the same structure. The consumers would ideally use the same chart but with different images depending on what they do. So to add a consumer to the app chart then you can add a new entry to the requirements with an extra alias (say consumer2) and then your values file looks like:
consumers:
  consumer1:
    image:
      tag: consumer1
  consumer2:
    image:
      tag: consumer2

But what if the idea of adding consumers is intrinsic to the way your app works? Think of a tool for data processing pipelines or business process flows (BPM/workflow) where the composition of components is what the tool is trying to provide. Then you ideally don't want to force your user to create their own charts, you want to provide a dynamic one if possible.
This is possible currently as you can create a chart that loops over the collection in the values file with a range function. So instead of one deployment, service etc as you get with most charts (e.g. see the official charts) you generate one per consumer entry.
The Activiti project would like to contribute an official chart for Activiti Cloud BPM. We can use range-based looping if that is the preferred way. We're not alone in wanting to use helm in this way - there's a good example on SO (and other examples and approaches).
Naturally the range looping will complicate the chart. It would be more like scripting and less like templating. See esp that SO approach or a rough-n-ready illustration here.
I wonder if this could be made easier in the future by supporting adding an extra alias at install-time. Something like 'extraAliases="consumer:consumer2"' to include an aliased dependency at install time under a different alias. Just for aliases, not for adding in whole extra chart dependencies (which would always require a full build). Then dynamic applications like this could have canonical helm charts where users would only have to override the values file and supply the correct aliasing arguments.
Perhaps a more script-heavy approach will become more normal in helm3. I'm hoping that by raising this kind of dynamic components use-case can get more consideration and attention.

To be clear, you can already add aliases in the requirements.yaml without requiring a new build of the chart so that the same package can be used multiple times. What would nice would be to have a way to add aliases from the command-line or in the values file so that it is exposed to end-users of the chart.

Or in a new aliases.yaml file, that would just be an extension of the existing aliases feature but for the chart the user is installing it would be available for them to add to at install time.

closing as inactive.


Copy placeholders

@igerko can you elaborate the goal of this pull request?

@yakky that will copy languages of plugins in current translation, eg. when you have translation only for EN and you want to copy to DE you just click copy all plugins from EN.

@igerko isn't this already provided by django CMS?

yes, but it's not copying post placeholders

Closed due to inactivity


Update Flat Lit Toon Lite Transparent.shader

Changed the ForwardAdd pass of Flat Lit Toon Lite Transparent to include influence from the texture/color mask's alpha value
Before:

After:

Fade does this.
Transparent behaves correctly. Transparent and fade are not the same thing.

Closing request, the feature you want already exists


[Event Change Request] Codeunit 5802 Inventory Posting to G/L-OnBe3foreBufferInvtPosting

Please add CalledFromTestReport as a new parameter to Event OnBeforeBufferInvtPosting
  PostBufDimNo := 0;
  IsHandled := FALSE;
  OnBeforeBufferInvtPosting(ValueEntry, Result, IsHandled, RunOnlyCheck, CalledFromTestReport);
  IF IsHandled THEN
    EXIT(Result);

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.


🐛 Bug Report:  Teams API - create/list methods throwing type conversion errors because of null value

👟 Reproduction steps
Type Conversion Error because of Cloud beta version does not have property Prefs in Team Model.

Create / List methods of Teams API giving:
null is not a subtype of Map<String,dynamic>.

👍 Expected behavior
It should work with Cloud Beta Appwrite version even if it doesn't contain Preference object inside Team Model.
As Appwrite cloud will be upgraded to version 1.3.x ,This issue will not persist as Preference Object will be added.
Till Then please consider this as it will be a very quick issue to fix.
👎 Actual Behavior
create team is working (As i can see Team getting added on Appwrite Dashboard) but throwing error
List method will always throw Type conversion error because of null value of Preferences.
🎲 Appwrite version
Version 1.0.x
💻 Operating system
Linux
🧱 Your Environment
No response
👀 Have you spent some time to check if this issue has been raised before?

[X] I checked and didn't find similar issue

🏢 Have you read the Code of Conduct?

[X] I have read the Code of Conduct

For Appwrite cloud please use Flutter Appwrite SDK version 8.x.x not 9.x.x and that should solve your issue.


Automated Package Upgrade

:tada: This PR is included in version 25.3.90 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Add tests for the CLI functionality

This will drag the overall test coverage% down until the module is properly tested, so we expect the CI runs to fail

merging this into develop as is, will complete testing in an upcoming PR


Refactor codebase for commands under m365 aad app to use async/await

Closes #4933

Thank you, we'll try to review it ASAP!

Hi @martinlingstuyl
Thanks for the review. Resolved the comments.

Merged manually, thanks for all the good work 👏


[Bug]: MySQL DB - No parameters bound for current statement - error pops up intermittently

Is there an existing issue for this?

[X] I have searched the existing issues

Description
When I run a simple select query (or any query), many a time this error pops up
No parameters bound for current statement
Steps To Reproduce

Create a mysql datasource (Details here)
Create a query like - SELECT * FROM alldatatypes8 LIMIT {{Input1.text}};
The error pops up to the effect -
No parameters bound for current statement
On re-running the query, it passes.

No error should pop up even on the first instance or intermittently
Public Sample App
No response
Version
Production

Seeing intermittently:

@btsgh can you please share a sample app with this error and a video

https://www.loom.com/share/eeebc4fbc2034e34bf08d09c309a4a29
@Nikhil-Nandagopal - here is the loom video that I recorded by reproducing it right now. I reproduced it quite often - though intermittent, on my localhost enviroment.

@btsgh please share the app too

Since its on my localhost, I don't think I can share it. I am attaching an export of the app here though. (You could rename it to json and use it.) Also, as mentioned in the bug, if I re-run the query, it passes.
My first application (2).txt

@btsgh I can't test it since I don't have the same DB credentails. Can you please re-create this on cloud and share the app?

I have a similar error. In my case, the error always happens. It isn't intermittent.
Steps To Reproduce

Use a MySQL datasource
Write and run an UPDATE query using parameters from UI components. E.g.
INSERT INTO contacts (name, frequency) VALUES ("{{NewContact.text}}", "{{NewContactFrequency.text}}");

The following error appears:

I think I found the problem in my case:
This error disappears when I deselect the "Use Prepared Statement" toggle:

My only suggestion, then, is to make the error message more intuitive.

I have the same issue, using the "Quick Page Wizard" to generate a CRUD page.  Deselecting "Use Prepared Statement" also resolved it

cannot reproduce this, but mixpanel shows quite a few errors.


New package: ComplexNoise v0.1.0

Registering package: ComplexNoise
Repository: https://github.com/brian-sinquin/ComplexNoise.jl
Created by: @brian-sinquin
Version: v0.1.0
Commit: b0d0f242a963969eba14f8af600589208aad4e8f
Reviewed by: @brian-sinquin
Reference: https://github.com/brian-sinquin/ComplexNoise.jl/commit/b0d0f242a963969eba14f8af600589208aad4e8f#commitcomment-143001651

This is only barely less empty than the previous registration at https://github.com/JuliaRegistries/General/pull/108582. Please don't try to register this package again until it is a little bit more mature. See Should I register my package now?:

If your package is at a stage where it might be useful to others, or provide functionality other packages in General might want to rely on

I don't think this is yet at a stage where others can use it in any meaningful way. There should be more functionality, and - very importantly - there has to be some form of documentation. At the very least, that would be a description of the package's purpose and a small usage example in the README.
Note that package registration isn't really necessary until there are other registered packages that should use this package as a dependency. I realize that "unregistered" packages make some development workflow more difficult. For that, I would recommend that you look at LocalRegistry. Setting up your own development registry also takes care of any issues you might have with this package being a dependency of other unregistered packages or projects.


Cursor doesn't snap to features when the view is rotated 45 degrees

Describe the bug
Cursor doesn't snap to features if the view is rotated 45/135/225/315 degrees.
To Reproduce
Demo: https://codesandbox.io/s/ol-rotation-snap-problem-btt58d?f=

Draw two points on the map
Try drawing a linestring between the two points
→ Cursor doesn't properly snap to the points

Expected behavior
Cursor should snap to features if the view is rotated 45 degrees.
See the original snap interaction demo: https://openlayers.org/en/latest/examples/snap.html

Also the tolerance is noticeably reduced at other angles, e.g. at 60 degrees the tolerance on the x axis is about half of what is expected, while the y axis is relatively unaffected.
It should be working as expected in https://deploy-preview-14344--ol-site.netlify.app/en/latest/examples/snap.html


failed to find path @rpath/libc++.1.dylib

OS: MacOS 14 (M1)
Compiler: clang (xcode 15)
Python: 3.9 (no virtual env)
nuitka: 1.8.2
When I used the --standalone parameter to package, the following error occurred after the main program had been compiled:
Nuitka-Plugins:INFO: data-files: Included data file 'certifi/cacert.pem' due to package data for 'certifi'.
Nuitka-Plugins:INFO: data-files: Included data file 'torch/bin/protoc' due to package data directory 'bin' for 'torch'.
Nuitka-Plugins:INFO: data-files: Included data file 'torch/bin/protoc-<IP_ADDRESS>' due to package data directory 'bin' for 'torch'.
Nuitka-Plugins:INFO: data-files: Included data file 'torch/bin/torch_shm_manager' due to package data directory 'bin' for 'torch'.
Nuitka-Plugins:INFO: data-files: Included 8336 data files due to package data directory 'include' for 'torch'.
Nuitka-Plugins:INFO: dll-files: Found 6 files DLLs from torch installation.
FATAL: Error, failed to find path @rpath/libc++.1.dylib (resolved DLL to /Users/koko/Library/Python/3.9/lib/python/site-packages/coremltools/_deps/kmeans1d/libc++.1.dylib) for /Users/koko/Library/Python/3.9/lib/python/site-packages/coremltools/_deps/kmeans1d/_core.cpython-39-darwin.so from 'coremltools._deps.kmeans1d', please report the bug.

Coremltools is the core package I need. I didn't find the libc++.1.dylib file, and I ran the compiled program and got an error that couldn't import math.so.
No --standalone parameter works normally after compilation.

In the template, I have made it clear, that not filling out the issue template is not acceptable. I am closing this kind of report as invalid. The main reason is that I do not want to be left guessing. For you it's easy to erase the issue template and expect me to ask you questions only as necessary, but I cannot do that. I would much rather wait for you to create a new report, fill out the template, or wait for somebody with the necessary skill to do it.
In short: No issue template, no fun. Therefore I am likely just deleting the issue, as it serves as a bad example and detraction for searches.  And even worse, it might keep good reporters from reporting as is this "already known."


Bugfix/89 97

Fix #89
Fix #97 : Tested scenarios with account import:
** wrong mnemonic -> goes back to first page where the seed is entered
** duplicate account  -> goes back to page where the pin is entered if the user chose to not overwrite the existing account.
** duplicate account  ->  goes to encointerHomePage without intermediately falling back to the AccountCreate/Import page if the user decided to overwrite the existing account.
** everything correct -> goes to encointerHomePage without intermediately falling back to the AccountCreate/Import page.

relying on your tests. thanks for fixing


Added average speed computing functionality for SkiRun

Describe the pull request
Added average speed computing functionality for SkiRun
Link to the the issue
The link to the issue that this pull request solves- https://github.com/rilling/OpenTracks-Winter-SOEN-6431_2024/issues/55#issue-2185320059

Solution added for issue: https://github.com/rilling/OpenTracks-Winter-SOEN-6431_2024/issues/55#issue-2185320059


Better TypeScript Hints for WalletName

This PR adds an optional type (no breaking changes) on the WalletName to support better typescript hints.
Previously, in application code, the user would see the following as a hint:

With this PR, they will see:

Beautiful, thanks!


pipenv install --lock creates broken/confusing state under some circumstances

I spent some time today trying to convert a project from requirements.txt to Pipfile with pipenv, but was confused to discover the wrong versions of some packages getting installed. Upon further investigation, I discovered that pipenv install --lock pkg1==version followed by pipenv install --lock pkg2==version, when pkg2 depends on pkg1 (with no version constraint) can result in a higher version of pkg1 being added to Pipfile.lock (but not actually installed), which then only takes effect on the next pipenv install.
Here is a terminal transcript showing the behavior with sqlalchemy==0.9.7 and graphene-sqlalchemy==1.1.1: https://gist.github.com/drakedevel/80457eca7bd2ff5fefbcb5192b67d88e
You can see that after the first install, sqlalchemy version 0.9.7 appears in Pipfile and Pipfile.lock as I'd expect. But, after graphene-sqlalchemy is installed, the Pipfile.lock contains sqlalchemy version 1.1.13, in direct conflict with the Pipfile's version constraint, and not reflecting the actual packages installed (per pipenv run pip freeze). You can see that the graphene-sqlalchemy install is satisfied with 0.9.7 and does not require an upgrade to proceed.
This seems pretty broken to me on a few levels -- what's the point of specifying version constraints in the Pipfile if they get silently overridden? And what's the point of Pipfile.lock if it doesn't reflect the actual packages pipenv installed?

Hey @drakedevel, thanks for taking the time to put this issue together. This is a duplicate of #298 which has an open patch (#305) but we never made final decisions on what to do with conflicts and conflicting dependency specifications. We'll need to resolve that before we can move forward for a fix with this.

I should also note this is a problem in pip itself too. Without a proper dependency resolver, we're going to have issues here. The best we can do in your situation is give a warning, but I think a lot of pinned versions aren't hard failures so we need to handle conflicts as gracefully as possible.

Can you try this again with the latest version? I'm curious to know if our new dependency resolver will change this behavior @drakedevel :)

@nateprewitt ah yeah --  I got thrown off by the title of that one being about order. As with the initial report in #298, pip handles this (more or less accidentally) regardless of what order you have the requirements in. I do think there's a separate bug which is that the generated Pipfile.lock doesn't reflect the actually installed versions (although maybe moot now, see below).
@kennethreitz appears to be fixed! I just tried the exact same sequence of commands again, and now Pipfile, Pipfile.lock, and pip freeze all agree with the specified versions. I will give that project conversion another shot :)

Excellent news! Bad news is that if you pass --hashes, we use the old behavior, so the bug still exists. But, we can work on that.


Home Assistant error: "The pirateweather integration is using deprecated forecast"

I'm seeing a notification in my Home Assistant reporting "The pirateweather integration is using deprecated forecast."  It also says "This stops working in version 2024.3.0. Please address before upgrading."  I just wanted to open this since I hadnt' seen the request opened yet. Thanks for all your work on this project.  I've enjoyed using it.

This is being tracked in #136.

Thanks for posting this- it is in progress, and so I'm going to close this issue to keep things tidy! You should get an auto-update whenever the new version comes out, so should be fixed then


SAP Mobile Cards - Template creation failing - US Region

Hello,
scenario URL: https://developers.sap.com/tutorials/cp-mobile-cards-welcome.html
Step 2:
In the Select Cards tab of the wizard, select the Sample Template Welcome Card and click Next.
Getting this error: API rate limit exceeded for <IP_ADDRESS>. (But here's the good news: Authenticated requests get a higher rate limit. Check out the documentation for more details.) Please refer to attachment.

Labels to be added:
Sprint Label: SCPTest-2010A
Scenario Label:SCPTest-mcard
Landscape Labels: trial2
prio: high-prio
Thanks,
Shubham

Hi @i353590
Thank you for raising this issue.
We will be tracking this issue as a part of this GitHub issue.
https://github.com/SAPDocuments/Tutorials/issues/6330
@MichaelCzcz Can you please close the ticket?
Warm Regards
Sandeep T D S