Self-signed SSL certificates

[nagyben]

I followed the instructions to install vectorcode

pipx install vectorcode
vectorcode init

I run Chromadb via docker in another shell (pinning to v0.6.3 as recommended in the docs)

docker run -v ./chroma-data:/data -p 8000:8000 chromadb/chroma:0.6.3

When I try to vectorise my code using

vectorcode vectorise 'src/**/*.py'

I get the following stack trace:

ERROR: vectorcode.main : Traceback (most recent call last):
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/vectorcode/main.py", line 91, in async_main
    return_val = await vectorise(final_configs)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/vectorcode/subcommands/vectorise.py", line 165, in vectorise
    collection = await get_collection(client, configs, True)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/vectorcode/common.py", line 186, in get_collection
    embedding_function = get_embedding_function(configs)
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/vectorcode/common.py", line 152, in get_embedding_function
    return embedding_functions.SentenceTransformerEmbeddingFunction()
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/chromadb/utils/embedding_functions/sentence_transformer_embedding_function.py", line 37, in __init__
    self.models[model_name] = SentenceTransformer(
                              ~~~~~~~~~~~~~~~~~~~^
        model_name, device=device, **kwargs
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/sentence_transformers/SentenceTransformer.py", line 321, in __init__
    modules = self._load_auto_model(
        model_name_or_path,
    ...<7 lines>...
        config_kwargs=config_kwargs,
    )
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/sentence_transformers/SentenceTransformer.py", line 1606, in _load_auto_model
    transformer_model = Transformer(
        model_name_or_path,
    ...<4 lines>...
        backend=self.backend,
    )
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/sentence_transformers/models/Transformer.py", line 80, in __init__
    config, is_peft_model = self._load_config(model_name_or_path, cache_dir, backend, config_args)
                            ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/sentence_transformers/models/Transformer.py", line 145, in _load_config
    return AutoConfig.from_pretrained(model_name_or_path, **config_args, cache_dir=cache_dir), False
           ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/nagyben/.local/pipx/venvs/vectorcode/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1151, in from_pretrained
    raise ValueError(
    ...<3 lines>...
    )
ValueError: Unrecognized model in sentence-transformers/all-MiniLM-L6-v2. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: albert, align, altclip, aria, aria_text, audio-spectrogram-transformer, autoformer, aya_vision, bamba, bark, bart, beit, bert, bert-generation, big_bird, bigbird_pegasus, biogpt, bit, blenderbot, blenderbot-small, blip, blip-2, bloom, bridgetower, bros, camembert, canine, chameleon, chinese_clip, chinese_clip_vision_model, clap, clip, clip_text_model, clip_vision_model, clipseg, clvp, code_llama, codegen, cohere, cohere2, colpali, conditional_detr, convbert, convnext, convnextv2, cpmant, ctrl, cvt, dab-detr, dac, data2vec-audio, data2vec-text, data2vec-vision, dbrx, deberta, deberta-v2, decision_transformer, deepseek_v3, deformable_detr, deit, depth_anything, depth_pro, deta, detr, diffllama, dinat, dinov2, dinov2_with_registers, distilbert, donut-swin, dpr, dpt, efficientformer, efficientnet, electra, emu3, encodec, encoder-decoder, ernie, ernie_m, esm, falcon, falcon_mamba, fastspeech2_conformer, flaubert, flava, fnet, focalnet, fsmt, funnel, fuyu, gemma, gemma2, gemma3, gemma3_text, git, glm, glm4, glpn, got_ocr2, gpt-sw3, gpt2, gpt_bigcode, gpt_neo, gpt_neox, gpt_neox_japanese, gptj, gptsan-japanese, granite, granitemoe, granitemoeshared, granitevision, graphormer, grounding-dino, groupvit, helium, hiera, hubert, ibert, idefics, idefics2, idefics3, idefics3_vision, ijepa, imagegpt, informer, instructblip, instructblipvideo, jamba, jetmoe, jukebox, kosmos-2, layoutlm, layoutlmv2, layoutlmv3, led, levit, lilt, llama, llama4, llama4_text, llava, llava_next, llava_next_video, llava_onevision, longformer, longt5, luke, lxmert, m2m_100, mamba, mamba2, marian, markuplm, mask2former, maskformer, maskformer-swin, mbart, mctct, mega, megatron-bert, mgp-str, mimi, mistral, mistral3, mixtral, mllama, mobilebert, mobilenet_v1, mobilenet_v2, mobilevit, mobilevitv2, modernbert, moonshine, moshi, mpnet, mpt, mra, mt5, musicgen, musicgen_melody, mvp, nat, nemotron, nezha, nllb-moe, nougat, nystromformer, olmo, olmo2, olmoe, omdet-turbo, oneformer, open-llama, openai-gpt, opt, owlv2, owlvit, paligemma, patchtsmixer, patchtst, pegasus, pegasus_x, perceiver, persimmon,phi, phi3, phi4_multimodal, phimoe, pix2struct, pixtral, plbart, poolformer, pop2piano, prompt_depth_anything, prophetnet, pvt, pvt_v2, qdqbert, qwen2, qwen2_5_vl, qwen2_audio, qwen2_audio_encoder, qwen2_moe, qwen2_vl, qwen3, qwen3_moe, rag, realm, recurrent_gemma, reformer, regnet, rembert, resnet, retribert, roberta, roberta-prelayernorm, roc_bert, roformer, rt_detr, rt_detr_resnet, rt_detr_v2, rwkv, sam, sam_vision_model, seamless_m4t, seamless_m4t_v2, segformer, seggpt, sew, sew-d, shieldgemma2, siglip, siglip2, siglip_vision_model, smolvlm, smolvlm_vision, speech-encoder-decoder, speech_to_text, speech_to_text_2, speecht5, splinter, squeezebert, stablelm, starcoder2, superglue, superpoint, swiftformer, swin, swin2sr, swinv2, switch_transformers, t5, table-transformer, tapas, textnet, time_series_transformer, timesformer, timm_backbone, timm_wrapper, trajectory_transformer, transfo-xl, trocr, tvlt, tvp, udop, umt5, unispeech, unispeech-sat, univnet, upernet, van, video_llava, videomae, vilt, vipllava, vision-encoder-decoder, vision-text-dual-encoder, visual_bert, vit, vit_hybrid, vit_mae, vit_msn, vitdet, vitmatte, vitpose, vitpose_backbone, vits, vivit, wav2vec2, wav2vec2-bert, wav2vec2-conformer, wavlm, whisper, xclip, xglm, xlm, xlm-prophetnet, xlm-roberta, xlm-roberta-xl, xlnet, xmod, yolos, yoso, zamba, zamba2, zoedepth

For errors caused by missing dependency, consult the documentation of pipx (or whatever package manager that you installed VectorCode with) for instructions to inject libraries into the virtual environment.

I have also tried without the Chromadb docker and just falling back on the built-in one but I get the same error

Any ideas?

[nagyben]

This may have something to do with a corporate firewall 👀 I tried it on another (personal) machine and it worked fine

[Davidyz]

If this is the case, there isn't much I can do to help. If you're able to at least download the model from huggingface to somewhere on your filesystem, you can use the following config (in the json):

{
  "embedding_params": {
    "model_name": "path_to_your_model",
    "local_files_only": true
  },
}

This makes sentence-transformers load the model from the path you specified, without sending requests to huggingface.

EDIT:
There are also other embedding functions, most of which are just wrappers around some hosted embedding API (but if you don't have access to huggingface, I've no idea whether any of these will be useful to you). If you decide to use a different embedding function and you need an extra dependency for that (for example, openai), you can install the dependency via the pipx inject vectorcode <package_name> command.

[nagyben]

Ok I've narrowed down the problem, it's due to a self-signed cert in the certificate chain

(MaxRetryError("HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /sentence-transformers/all-MiniLM-L6-v2/resolve/main/config.json (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1028)')))"), '(Request ID: 08175f58-5cc5-450a-a4de-ca7ddf1c90d6)')

[nagyben]

The solution in the end was to set REQUESTS_CA_BUNDLE so the underlying requests library uses the correct CA bundle

On MacOS:

export REQUESTS_CA_BUNDLE=/opt/homebrew/etc/ca-certificates/cert.pem 
vectorcode vectorise 'src/*.py'

[Davidyz]

There were actually some CI tests that failed because the runners couldn't connect to huggingface. I never knew why, and rerunning them fixed the problem. This might be the same issue. I can't find a failed run rn but I'll definitely come back to this when it happens again. Thanks!