Latex incoming changes

ai_functions.py

@@ -133,7 +133,7 @@ def num_tokens_from_string(message, model):
 
 
 async def handle_response(
-    prompt, vykidailo, bartender, history, username, request_type, algorithm="gpt-4o"
+    prompt, vykidailo, bartender, history, username, request_type, algorithm="gpt-4o", none_request=""
 ):
     """
     Handle responses by appending them to a history, use OpenAI to
@@ -189,60 +189,63 @@ async def handle_response(
             # convert back to json.
             json.dump(file_data, file_memory, indent=4)
     history = []
-    history.append(GPT_SETTINGS[0])
-    chat_gpt_config_request_size = num_tokens_from_string(GPT_SETTINGS[0], "gpt-4")
+    if request_type != "NONE":
+        history.append(GPT_SETTINGS[0])
+        chat_gpt_config_request_size = num_tokens_from_string(GPT_SETTINGS[0], "gpt-4")
 
-    for slowo, reakcja in WORD_REACTIONS.items():
-        if not reakcja[3]:
-            content = (
-                "Kiedy słyszysz "
-                + slowo
-                + " to reagujesz lub dzieje się to "
-                + reakcja[0]
-            )
-            temp = {"role": "system", "content": content}
-            chat_gpt_config_request_size += num_tokens_from_string(temp, "gpt-4")
-            history.append(temp)
+        for slowo, reakcja in WORD_REACTIONS.items():
+            if not reakcja[3]:
+                content = (
+                    "Kiedy słyszysz "
+                    + slowo
+                    + " to reagujesz lub dzieje się to "
+                    + reakcja[0]
+                )
+                temp = {"role": "system", "content": content}
+                chat_gpt_config_request_size += num_tokens_from_string(temp, "gpt-4")
+                history.append(temp)
 
-    final_prompt = username + ":" + prompt
-    logger.debug(
-        "Rozmiar zapytania przed dodaniem historii %s", chat_gpt_config_request_size
-    )
-    if request_type == "MUSIC":
-        table = MESSAGE_TABLE_MUZYKA
-        token_amount = 10700
-    elif request_type == "RANDOM":
-        table = MESSAGE_TABLE
-        token_amount = 10700
-    elif request_type == "GENERAL":
-        table = MESSAGE_TABLE
-        token_amount = 10700
-    else:
-        table = []
-        token_amount = 10000
-
-
-    prompt_gpt_request_size = num_tokens_from_string(
-        {"role": "user", "content": final_prompt}, "gpt-4"
-    )
-    temptable = []
-    for i in reversed(table):
-        temp_token = num_tokens_from_string(i, "gpt-4")
+        final_prompt = username + ":" + prompt
         logger.debug(
-            "Rozmiar zapytania %s prompt %s temp %s",
-            chat_gpt_config_request_size,
-            prompt_gpt_request_size,
-            temp_token,
+            "Rozmiar zapytania przed dodaniem historii %s", chat_gpt_config_request_size
         )
-        if (
-            chat_gpt_config_request_size
-            < token_amount + prompt_gpt_request_size + temp_token
-        ):
-            temptable.insert(1, i)
-            chat_gpt_config_request_size += temp_token
-    history.extend(temptable)
-    temp = {"role": "user", "content": final_prompt}
-    history.append(temp)
+        if request_type == "MUSIC":
+            table = MESSAGE_TABLE_MUZYKA
+            token_amount = 10700
+        elif request_type == "RANDOM":
+            table = MESSAGE_TABLE
+            token_amount = 10700
+        elif request_type == "GENERAL":
+            table = MESSAGE_TABLE
+            token_amount = 10700
+        else:
+            table = []
+            token_amount = 10000
+
+
+        prompt_gpt_request_size = num_tokens_from_string(
+            {"role": "user", "content": final_prompt}, "gpt-4"
+        )
+        temptable = []
+        for i in reversed(table):
+            temp_token = num_tokens_from_string(i, "gpt-4")
+            logger.debug(
+                "Rozmiar zapytania %s prompt %s temp %s",
+                chat_gpt_config_request_size,
+                prompt_gpt_request_size,
+                temp_token,
+            )
+            if (
+                chat_gpt_config_request_size
+                < token_amount + prompt_gpt_request_size + temp_token
+            ):
+                temptable.insert(1, i)
+                chat_gpt_config_request_size += temp_token
+        history.extend(temptable)
+        temp = {"role": "user", "content": final_prompt}
+        history.append(temp)
+    else:
+        history = none_request
     logger.info("Rozmiar zapytania po wyslaniu %s", chat_gpt_config_request_size)
     try:
         # ...przygotowanie messages/system prompt/itp. jak masz...
@@ -256,9 +259,9 @@ async def handle_response(
 
     except openai.APITimeoutError as e:
         # Handle timeout error, e.g. retry or log
-        result = f"*Kondziu patrzy na terminal, czeka, czeka, czeka,.... Jeszcze chwile czeka Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai spróbuj od nowa. *Na ekranie pojawia się*: {e}"
+        response = f"*Kondziu patrzy na terminal, czeka, czeka, czeka,.... Jeszcze chwile czeka Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai spróbuj od nowa. *Na ekranie pojawia się*: {e}"
     except openai.APIConnectionError as e:
-        result = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai. *Na ekranie pojawia się*: {e}"
+        response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai. *Na ekranie pojawia się*: {e}"
     except openai.BadRequestError as e:
         # Handle invalid request error, e.g. validate parameters or log
         resp, _ = await handle_response(
@@ -269,7 +272,7 @@ async def handle_response(
             username,
             "RANDOM",
         )
-        result = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
+        response = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
     except openai.APIResponseValidationError as e:
         # Handle invalid request error, e.g. validate parameters or log
         resp, _ = await handle_response(
@@ -280,20 +283,20 @@ async def handle_response(
             username,
             "RANDOM",
         )
-        result = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
+        response = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
     except openai.AuthenticationError as e:
         # Handle authentication error, e.g. check credentials or log
-        result = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z hasłem zjebało. *Na terminalu pojawia się:* {e}"
+        response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z hasłem zjebało. *Na terminalu pojawia się:* {e}"
     except openai.PermissionDeniedError as e:
         # Handle permission error, e.g. check scope or log
-        result = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z uprawnieniami zjebało. *Na terminalu pojawia się:* {e}"
+        response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z uprawnieniami zjebało. *Na terminalu pojawia się:* {e}"
     except openai.RateLimitError as e:
-        result = f"*Kondziu patrzy na terminal* Wołaj szefa. Zapłacić rachunki za AI trzeba. Jak chcesz to się na #zebranie dorzuć. {e}"
+        response = f"*Kondziu patrzy na terminal* Wołaj szefa. Zapłacić rachunki za AI trzeba. Jak chcesz to się na #zebranie dorzuć. {e}"
     except openai.UnprocessableEntityError as e:
-        result = f"*Kondziu patrzy na terminal. Potem na to co każesz mu wysłać....* Ja wiem że jesteśmy w barze BDSM - ale nie da się włożyć TEGO w TO. *Za jego plecami na terminalu pojawia się:* {e}"
+        response = f"*Kondziu patrzy na terminal. Potem na to co każesz mu wysłać....* Ja wiem że jesteśmy w barze BDSM - ale nie da się włożyć TEGO w TO. *Za jego plecami na terminalu pojawia się:* {e}"
     except openai.APIError as e:
         # Handle API error, e.g. retry or log
-        result = f"*Kondziu nurkuje za bar, terminal wybucha. Przed tobą ląduje pergamin zapisany pięknym gotykiem a na nim*: {e}"
+        response = f"*Kondziu nurkuje za bar, terminal wybucha. Przed tobą ląduje pergamin zapisany pięknym gotykiem a na nim*: {e}"
 
     logger.info("Historia wysłana:")
     logger.info(history)

latex_commands.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 import io
 from typing import Optional, List
+import logging
 
 import discord
 from discord import app_commands
@@ -128,5 +129,7 @@ class LatexModule(commands.Cog):
             self.logger.debug("BATCH failed: %s", ", ".join(failed))
         await interaction.followup.send("✅ Gotowe (ZIP w załączniku)." + (f" ❌ Błędy: {len(failed)}" if failed else ""), files=[discord.File(bio, filename=bio.name)])
 
-async def setup(bot: commands.Bot):
+async def setup(bot):
+    logger = logging.getLogger("discord")
     await bot.add_cog(LatexModule(bot, logger_name="latex"))
+    logger.info("Loading kinky latex module done")

latex_functions.py

@@ -1,76 +1,122 @@
 # latex_functions.py
 # -*- coding: utf-8 -*-
 from __future__ import annotations
-import asyncio, os, re, shlex, tempfile, zipfile
-from pathlib import Path
-from typing import Tuple, List, Dict, Optional
 
-from openai import OpenAI
+import asyncio
+import re
+import shlex
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple
+
+from ai_functions import handle_response
 
 SAFE_TEX_NAME = re.compile(r"^[\w\-. ]+\.tex$", re.IGNORECASE)
 
+
 def is_safe_tex_name(name: str) -> bool:
     return bool(SAFE_TEX_NAME.match(name or "")) and name.lower().endswith(".tex")
 
+
 def is_tex_attachment(att, max_mb: int) -> bool:
     """Filtruje discord.Attachment: tylko .tex + limit MB + nazwa bezpieczna."""
     return bool(
-        getattr(att, "filename", "") and
-        is_safe_tex_name(att.filename) and
-        getattr(att, "size", 0) <= max_mb * 1024 * 1024
+        getattr(att, "filename", "")
+        and is_safe_tex_name(att.filename)
+        and getattr(att, "size", 0) <= max_mb * 1024 * 1024
     )
 
-async def run_latex_two_passes(tex_filename: str, workdir: Path, tex_engine: str, timeout_sec: int, logger=None) -> Tuple[bool, str, Path]:
-    cmd = f'{tex_engine} -interaction=nonstopmode -halt-on-error -file-line-error -no-shell-escape {shlex.quote(tex_filename)}'
-    if logger: logger.debug("LaTeX cmd: %s (cwd=%s)", cmd, workdir)
+
+async def run_latex_two_passes(
+    tex_filename: str, workdir: Path, tex_engine: str, timeout_sec: int, logger=None
+) -> Tuple[bool, str, Path]:
+    cmd = f"{tex_engine} -interaction=nonstopmode -halt-on-error -file-line-error -no-shell-escape {shlex.quote(tex_filename)}"
+    if logger:
+        logger.debug("LaTeX cmd: %s (cwd=%s)", cmd, workdir)
 
     async def _run_once() -> Tuple[int, str]:
         proc = await asyncio.create_subprocess_shell(
-            cmd, cwd=str(workdir),
-            stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.STDOUT
+            cmd,
+            cwd=str(workdir),
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.STDOUT,
         )
         try:
             out_b, _ = await asyncio.wait_for(proc.communicate(), timeout=timeout_sec)
             out_t = (out_b or b"").decode("utf-8", errors="replace")
             return proc.returncode or 0, out_t
         except asyncio.TimeoutError:
-            try: proc.kill()
-            except Exception: pass
+            try:
+                proc.kill()
+            except Exception:
+                pass
             return 124, f"[Timeout] Compilation exceeded {timeout_sec}s.\n"
 
     logs: List[str] = []
-    rc1, out1 = await _run_once(); logs.append(out1)
+    rc1, out1 = await _run_once()
+    logs.append(out1)
     if rc1 != 0:
         log_text = "".join(logs)
-        if logger: logger.debug("LaTeX pass1 FAIL %s\n%s", tex_filename, log_text[-2000:])
+        if logger:
+            logger.debug("LaTeX pass1 FAIL %s\n%s", tex_filename, log_text[-2000:])
         return False, log_text, workdir / (Path(tex_filename).stem + ".pdf")
 
-    rc2, out2 = await _run_once(); logs.append(out2)
+    rc2, out2 = await _run_once()
+    logs.append(out2)
     log_text = "".join(logs)
     pdf = workdir / (Path(tex_filename).stem + ".pdf")
     ok = (rc2 == 0) and pdf.exists()
-    if logger: logger.debug("LaTeX pass2 %s ok=%s\n%s", tex_filename, ok, log_text[-2000:])
+    if logger:
+        logger.debug("LaTeX pass2 %s ok=%s\n%s", tex_filename, ok, log_text[-2000:])
     return ok, log_text, pdf
 
-async def compile_single_tex_bytes(tex_bytes: bytes, filename: str, tex_engine: str, timeout_sec: int, logger=None) -> Dict[str, Optional[object]]:
+
+async def compile_single_tex_bytes(
+    tex_bytes: bytes, filename: str, tex_engine: str, timeout_sec: int, logger=None
+) -> Dict[str, Optional[object]]:
     if not is_safe_tex_name(filename):
-        return {'ok': False, 'pdf_bytes': None, 'log_text': 'Invalid .tex filename', 'pdf_name': None}
+        return {
+            "ok": False,
+            "pdf_bytes": None,
+            "log_text": "Invalid .tex filename",
+            "pdf_name": None,
+        }
     with tempfile.TemporaryDirectory(prefix="latex_one_") as td:
         wd = Path(td)
         tex_path = wd / filename
         tex_path.write_bytes(tex_bytes)
-        ok, log_text, pdf_path = await run_latex_two_passes(filename, wd, tex_engine, timeout_sec, logger=logger)
+        ok, log_text, pdf_path = await run_latex_two_passes(
+            filename, wd, tex_engine, timeout_sec, logger=logger
+        )
         if ok and pdf_path.exists():
-            return {'ok': True, 'pdf_bytes': pdf_path.read_bytes(), 'log_text': log_text, 'pdf_name': pdf_path.name}
-        return {'ok': False, 'pdf_bytes': None, 'log_text': log_text, 'pdf_name': pdf_path.name}
+            return {
+                "ok": True,
+                "pdf_bytes": pdf_path.read_bytes(),
+                "log_text": log_text,
+                "pdf_name": pdf_path.name,
+            }
+        return {
+            "ok": False,
+            "pdf_bytes": None,
+            "log_text": log_text,
+            "pdf_name": pdf_path.name,
+        }
 
-async def compile_zip_to_zip(zip_bytes: bytes, tex_engine: str, timeout_sec: int, logger=None) -> Tuple[bytes, List[str]]:
-    failed: List[str] = []; out_pdf_paths: List[Path] = []
+
+async def compile_zip_to_zip(
+    zip_bytes: bytes, tex_engine: str, timeout_sec: int, logger=None
+) -> Tuple[bytes, List[str]]:
+    failed: List[str] = []
+    out_pdf_paths: List[Path] = []
     with tempfile.TemporaryDirectory(prefix="latex_zip_") as td:
         td_path = Path(td)
-        in_zip = td_path / "in.zip"; in_zip.write_bytes(zip_bytes)
-        extract_dir = td_path / "in"; extract_dir.mkdir(parents=True, exist_ok=True)
-        with zipfile.ZipFile(in_zip, 'r') as zf: zf.extractall(extract_dir)
+        in_zip = td_path / "in.zip"
+        in_zip.write_bytes(zip_bytes)
+        extract_dir = td_path / "in"
+        extract_dir.mkdir(parents=True, exist_ok=True)
+        with zipfile.ZipFile(in_zip, "r") as zf:
+            zf.extractall(extract_dir)
 
         tex_files = [p for p in extract_dir.rglob("*.tex") if is_safe_tex_name(p.name)]
         if not tex_files:
@@ -78,17 +124,23 @@ async def compile_zip_to_zip(zip_bytes: bytes, tex_engine: str, timeout_sec: int
 
         for tex in tex_files:
             try:
-                work = td_path / f"build_{tex.stem}"; work.mkdir(parents=True, exist_ok=True)
-                target_tex = work / tex.name; target_tex.write_bytes(tex.read_bytes())
-                ok, log_text, pdf_path = await run_latex_two_passes(target_tex.name, work, tex_engine, timeout_sec, logger=logger)
+                work = td_path / f"build_{tex.stem}"
+                work.mkdir(parents=True, exist_ok=True)
+                target_tex = work / tex.name
+                target_tex.write_bytes(tex.read_bytes())
+                ok, log_text, pdf_path = await run_latex_two_passes(
+                    target_tex.name, work, tex_engine, timeout_sec, logger=logger
+                )
                 if ok and pdf_path.exists():
                     out_pdf_paths.append(pdf_path)
                 else:
                     failed.append(tex.name)
-                    if logger: logger.debug("BATCH FAIL %s\n%s", tex.name, log_text[-1500:])
+                    if logger:
+                        logger.debug("BATCH FAIL %s\n%s", tex.name, log_text[-1500:])
             except Exception as e:
                 failed.append(f"{tex.name} (exception: {e})")
-                if logger: logger.debug("BATCH EXC %s: %s", tex.name, e)
+                if logger:
+                    logger.debug("BATCH EXC %s: %s", tex.name, e)
 
         out_zip = td_path / "compiled_pdfs.zip"
         with zipfile.ZipFile(out_zip, "w", compression=zipfile.ZIP_DEFLATED) as zf:
@@ -97,25 +149,27 @@ async def compile_zip_to_zip(zip_bytes: bytes, tex_engine: str, timeout_sec: int
 
         return out_zip.read_bytes(), failed
 
-async def ask_openai_diagnosis(log_text: str, tex_excerpt: str, api_key: str, model: str, logger=None) -> str:
-    if not api_key:
-        return "⚠️ Brak OPENAI_API_KEY — pomijam diagnozę."
-    client = OpenAI(api_key=api_key)
-    sys = ("You are a LaTeX build diagnostician. Analyze pdflatex log and return:\n"
-           "1) Root causes (bullets)\n2) Minimal working fix (code block)\n3) Alternative fix")
+
+async def ask_openai_diagnosis(
+    log_text: str, tex_excerpt: str, api_key: str, model: str, logger=None
+) -> str:
+    sys = (
+        "You are a LaTeX build diagnostician. Analyze pdflatex log and return:\n"
+        "1) Root causes (bullets)\n2) Minimal working fix (code block)\n3) Alternative fix"
+    )
     usr = f"---LOG---\n{log_text[-9000:]}\n---END LOG---"
     if tex_excerpt:
         usr += f"\n---TEX EXCERPT---\n{tex_excerpt[:4000]}\n---END EXCERPT---"
-    try:
-        if model.startswith("gpt-3.5"):
-            def _legacy():
-                resp = client.chat.completions.create(model=model, messages=[{"role":"system","content":sys},{"role":"user","content":usr}], temperature=0.1)
-                return resp.choices[0].message.content.strip()
-            return await asyncio.to_thread(_legacy)
-        def _resp():
-            r = client.responses.create(model=model, temperature=0.1, input=[{"role":"system","content":sys},{"role":"user","content":usr}])
-            return (getattr(r,"output_text",None) or "").strip() or str(r)
-        return await asyncio.to_thread(_resp)
-    except Exception as e:
-        if logger: logger.debug("OpenAI error: %s", e)
-        return f"⚠️ OpenAI API error: {e}"
+        prompt = [{"role": sys, "content": "none"}, {"role": "user", "content": usr}]
+
+        response, _ = await handle_response(
+            prompt,
+            None,
+            None,
+            prompt,
+            "latex_diagnosis",
+            "NONE",
+            algorithm=model,
+            none_request=prompt,
+        )
+    return response

thin_client.py

@@ -69,6 +69,7 @@ async def on_ready():
     await client.load_extension("other_commands")
     await client.load_extension("voice_recognition_commands")
     await client.load_extension("file_search_commands")
+    await client.load_extension("latex_commands")
     logger.info("Sensors: online")
 
     logger.info(client.cogs)