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Runtime error
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fix utils complete
Browse files
utils.py
CHANGED
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@@ -1,11 +1,41 @@
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import os
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import re
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from openai import OpenAI
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from groq import Groq
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import anthropic
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# =====================================================
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# DEEPSEEK
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# =====================================================
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@@ -130,25 +160,31 @@ def call_llm(
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max_tokens: int = 2000
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):
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if provider == "deepseek":
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return call_deepseek(
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prompt,
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max_tokens=max_tokens
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)
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elif provider == "groq":
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return call_groq(
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prompt,
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max_tokens=max_tokens
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)
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elif provider == "claude":
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return call_claude(
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prompt,
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max_tokens=max_tokens
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)
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else:
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return "ERREUR: provider inconnu"
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@@ -160,7 +196,8 @@ def smart_call(prompt: str):
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providers = [
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"deepseek",
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"groq"
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]
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for provider in providers:
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@@ -170,21 +207,28 @@ def smart_call(prompt: str):
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provider=provider
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)
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if
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return result
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return "ERREUR: tous les providers ont échoué"
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# =====================================================
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-
# EXTRACTION LATEX
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# =====================================================
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def extract_latex_blocks(text: str):
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pattern = r'\$\$([^\$]+)\$\$|\\\[(.*?)\\\]|\$([^\$]+)\$'
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matches = re.findall(
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equations = []
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@@ -195,23 +239,30 @@ def extract_latex_blocks(text: str):
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if eq and eq.strip():
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equations.append(eq.strip())
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-
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-
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unique = []
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for eq in equations:
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if eq not in seen:
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seen.add(eq)
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unique.append(eq)
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return unique
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# =====================================================
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# EXTRACTION EQUATIONS
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# =====================================================
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def extract_equations_with_llm(
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prompt = f"""
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Tu es un assistant scientifique.
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@@ -219,12 +270,97 @@ Tu es un assistant scientifique.
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Extrais uniquement les équations mathématiques
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présentes dans ce texte.
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Retourne
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Texte :
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{text}
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"""
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response =
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-
return
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import os
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import re
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+
import json
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from openai import OpenAI
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from groq import Groq
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import anthropic
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# =====================================================
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# JSON HELPERS
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# =====================================================
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def clean_json_text(text: str) -> str:
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if not text:
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return ""
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text = text.strip()
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# retire ```json
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text = re.sub(r"^```json", "", text)
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text = re.sub(r"^```", "", text)
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text = re.sub(r"```$", "", text)
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return text.strip()
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def safe_json_loads(text: str):
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try:
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cleaned = clean_json_text(text)
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return json.loads(cleaned)
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except Exception:
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return None
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# =====================================================
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# DEEPSEEK
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# =====================================================
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max_tokens: int = 2000
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):
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provider = provider.lower()
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if provider == "deepseek":
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return call_deepseek(
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prompt,
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max_tokens=max_tokens
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)
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elif provider == "groq":
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return call_groq(
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prompt,
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max_tokens=max_tokens
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)
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elif provider == "claude":
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return call_claude(
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prompt,
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max_tokens=max_tokens
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)
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else:
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return "ERREUR: provider inconnu"
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providers = [
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"deepseek",
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"groq",
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"claude"
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]
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for provider in providers:
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provider=provider
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)
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if (
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isinstance(result, str)
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and not result.startswith("ERREUR")
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):
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return result
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return "ERREUR: tous les providers ont échoué"
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# =====================================================
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# EXTRACTION LATEX SIMPLE
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# =====================================================
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def extract_latex_blocks(text: str):
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pattern = r'\$\$([^\$]+)\$\$|\\\[(.*?)\\\]|\$([^\$]+)\$'
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matches = re.findall(
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pattern,
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text,
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re.DOTALL
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)
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equations = []
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if eq and eq.strip():
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equations.append(eq.strip())
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# remove duplicates
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unique = []
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seen = set()
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for eq in equations:
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if eq not in seen:
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seen.add(eq)
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unique.append(eq)
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return unique
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# =====================================================
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# EXTRACTION EQUATIONS AVEC LLM
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# =====================================================
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def extract_equations_with_llm(
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text: str,
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provider: str = "deepseek"
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):
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prompt = f"""
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Tu es un assistant scientifique.
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Extrais uniquement les équations mathématiques
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présentes dans ce texte.
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Retourne STRICTEMENT un JSON valide
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sous cette forme :
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[
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{{
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"latex": "E = mc^2"
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}}
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]
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Texte :
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{text}
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"""
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response = call_llm(
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prompt,
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provider=provider,
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max_tokens=2000
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)
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data = safe_json_loads(response)
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if data is None:
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return []
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return data
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# =====================================================
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# VALIDATION IR
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# =====================================================
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def validate_ir(ir):
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if not isinstance(ir, dict):
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return False
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if "nodes" not in ir:
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return False
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if "edges" not in ir:
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return False
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return True
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# =====================================================
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# NORMALISATION IR
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# =====================================================
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def normalize_ir(ir):
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if not isinstance(ir, dict):
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return {
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"name": "Invalid IR",
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"strategy": "fallback",
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"nodes": [],
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"edges": []
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}
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ir.setdefault("name", "Unnamed IR")
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ir.setdefault("strategy", "fallback")
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ir.setdefault("nodes", [])
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ir.setdefault("edges", [])
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return ir
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# =====================================================
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# GENERATION IR FALLBACK
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# =====================================================
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def build_fallback_ir(equations):
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nodes = []
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for i, eq in enumerate(equations):
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if isinstance(eq, dict):
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latex = eq.get("latex", "")
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else:
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latex = str(eq)
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nodes.append({
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"id": f"eq_{i}",
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"type": "equation",
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"latex": latex
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})
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return {
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"name": "Fallback Variant 1",
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"strategy": "fallback",
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"nodes": nodes,
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"edges": []
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}
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