Revert "Adding query_llm_robust"

This reverts commit 0f7d899.

Author: prodiggy8

app.py

@@ -3,19 +3,26 @@
 from flask import Flask
 from flask import request, jsonify
 from src.translator import translate_content
-from src.llm_utils import query_llm_robust
 
 app = Flask(__name__)
 
 @app.route("/")
 def translator():
     content = request.args.get("content", default = "", type = str)
-    is_english, translated_content = query_llm_robust(content)
+    is_english, translated_content = translate_content(content)
     return jsonify({
         "is_english": is_english,
         "translated_content": translated_content,
+    })
+@app.route("/translate", methods=["POST"])
+def hardcoded_translate():
+    data = request.get_json()
+    text = data.get("text", "") if data else ""
+    # For P4A, we return a dummy translation response
+    return jsonify({
+        "translated": "Hello, this is a hardcoded translation for P4A",
+        "is_english": False
     }), 200
 
-
 if __name__ == "__main__":
     app.run(debug=True, host="0.0.0.0", port=int(os.environ.get("PORT", 8080)))

requirements.txt

@@ -1,9 +1,3 @@
 Flask==3.0.0
 pytest==7.4.0
 ollama
-torch==2.9.0
-sentence_transformers
-pytest
-ipytest
-pytest-mock
-mock

src/llm_utils.py

@@ -1,40 +1,7 @@
 import ollama
-
-MODEL_NAME = "gemma3:270m"
-
-CLASSIFICATION_CONTEXT = """\
-You are a language identifier.
-Your task is to detect the primary language of the given text input and respond only with the English name of that language.
-
-Rules:
-- Do not translate or explain.
-- Do not guess based on previous examples--decide only from the current input.
-- If the text appears to be random characters, symbols, or nonsense, respond with "English".
-
-Output format: a single word--the English name of the detected language.
-
-Examples:
-INPUT: Bonjour, je m'appelle Sarah
-OUTPUT: French
-
-INPUT: Können Sie mir bitte helfen?
-OUTPUT: German
-
-INPUT: %#$%#%#%#%#%@#!#!@#
-OUTPUT: English"""
-
-TRANSLATION_CONTEXT = """\
-You are a translation model. Your only task is to translate any non-English input into natural, fluent English.
-Do not interpret, paraphrase, or answer the text- -only translate it exactly as written.
-Respond only with the English translation, and nothing else.
-
-Example:
-INPUT: Bonjour, je m'appelle Sarah
-OUTPUT: Hello, my name is Sarah
-
-INPUT: Il fait très chaud aujourd'hui, n'est-ce pas ?
-OUTPUT: It is very hot today, isn't it?
-"""
+MODEL_NAME = "test-model"
+CLASSIFICATION_CONTEXT = "Classify language"
+TRANSLATION_CONTEXT = "Translate to English"
 
 def get_translation(post: str) -> str:
     try: