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llm-in-text/backend/__pycache__/llm.cpython-310.pyc

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S5<53>i9<00> @s<>ddlZddlZddlZddlmZddlZddlmZe<06>e<00>dd<05>Ze<00>dd<07>Z e<00>dd <09>Z
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<EFBFBD>Z e<02> d <0B>Zd Zd eeeffdd<0F>Zddd<12>dededed efdd<17>Zddeded efdd<1C>ZdS)<1E>N)<01>datetime)<01> load_dotenv<6E> OLLAMA_MODELz gpt-oss:20b<30> OLLAMA_HOSTzhttp://192.168.0.120:11434<33> VLM_MODELz qwen3-vl:30b)<01>host<73>llmaYou are an OCR and visual-context extractor for markdown writing assistance.
Your output will be embedded inside an HTML comment as hidden context for a text-completion model.
Requirements:
- Keep output compact: maximum 120 words.
- Use plain text only (no markdown code fences).
- Never output <!-- or -->.
- Do not invent unreadable text; mark uncertain characters with ?.
- Preserve original script for recognized text (do not forcibly translate).
Return exactly this format:
TEXT:
<exact transcription of visible text; use " | " for line breaks; write "(none)" if no readable text>
KEY_DETAILS:
- <3-5 short factual bullets about relevant objects/layout>
LANGUAGE:
<dominant language(s) in visible text, e.g. English / Chinese / Mixed>
SUMMARY:
<one short sentence, <= 20 words><3E>returncCs|d}d}t|d<02>r|jr|jjpd}t|jdd<01>pd}||fSt|t<05>r:|<00>di<00>}|<03>dd<01>p1d}|<03>dd<01>p9d}||fS)N<><00>message<67>thinking<6E>content)<07>hasattrr r <00>getattr<74>
isinstance<EFBFBD>dict<63>get)<04>responser r <00>msg<73>r<00>/C:\Users\ydy\Desktop\llm-in-text\backend\llm.py<70>_extract_message*s 
<EFBFBD> r<00>defaultgffffff<66>?)<02>tag<61> temperature<72>promptrrc
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调用 Ollama API 并返回 content 和 thinking。
z<[LLM][%s] request model=%s host=%s prompt_chars=%d temp=%.2f<EFBFBD>user)<02>roler Fg<46><67><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>?)rZrepeat_penalty<74><04>model<65>messages<65>stream<61>optionsN<73><4E>z[LLM][%s] call_time [%s --> %s]<5D>%H:%M:%Sz%[LLM][%s] request failed after %.1fmszP[LLM][%s] response in %.1fms response_type=%s content_chars=%d thinking_chars=%dz)[LLM][%s] empty content returned by model)r r )<13>time<6D> perf_counterr<00>now<6F>logger<65>inforr<00>len<65>client<6E>chat<61> Exception<6F>strftime<6D> exceptionr<00>type<70>__name__<5F>strip<69>warning)
rrr<00>start<72>start_dtr<00>
elapsed_ms<EFBFBD>end_dtr r rrr<00> call_ollama9sh<02><04> 
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r8<00>auto<74> image_bytes<65>languagec
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<EFBFBD><01>t<04>d |t|<04>jt|<07>t|<08><01>|<07><12>s<>t<04>d <0A>|S)Nz>[VLM][ocr] request model=%s host=%s image_bytes=%d language=%sr)rr ZimagesFrg333333<33>?rr#z [VLM][ocr] call_time [%s --> %s]r$z&[VLM][ocr] request failed after %.1fmszQ[VLM][ocr] response in %.1fms response_type=%s content_chars=%d thinking_chars=%dz*[VLM][ocr] empty content returned by model)r%r&rr'r(r)rrr*r+r,<00>VLM_OCR_CONTEXT_PROMPTr-r.r/rr0r1r2r3) r:r;r4r5rr6r7r r rrr<00> call_vlm_ocrusb<02><04><06><10>
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r=)r9)<18>osr%<00>loggingrZollamaZdotenvr<00>getenvrrrZ AsyncClientr+<00> getLoggerr(r<<00>tuple<6C>strr<00>floatrr8<00>bytesr=rrrr<00><module>s       
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