Update question_generation.py

question_generation.py

@@ -1,100 +1,100 @@
-import os
-import json
-from dotenv import load_dotenv
-from pydantic import BaseModel, ValidationError
-from typing import List
-from prompts import PROMPTS
-import google.generativeai as genai
-from fastapi import FastAPI, HTTPException
+import os
+import json
+from dotenv import load_dotenv
+from pydantic import BaseModel, ValidationError
+from typing import List
+from prompts import PROMPTS
+import google.generativeai as genai
+from fastapi import FastAPI, HTTPException
 import uvicorn
-
-# Setup
-load_dotenv()
-google_api_key = os.getenv("GOOGLE_API_KEY")
-genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
-model = genai.GenerativeModel(os.getenv("LLM_MODEL", "gemini-pro"))
-
-# Models
-class TopicRequest(BaseModel):
-    topic: str
-    num_questions: int = 10
-
-class GeneratedQuestionModel(BaseModel):
-    question_language: str
-    question_list: List[str]
-
-# Functions
-def chat_with_model(prompt: str) -> str:
-    try:
-        response = model.generate_content(prompt)
-        return response.text if response.text else "Error: Empty response"
-    except Exception as e:
-        return f"Error: {e}"
-
-def clean_json_text(text: str) -> str:
-    if text.startswith("Error:"):
-        return text
-    if text.startswith("```"):
-        lines = text.split('\n')
-        text = '\n'.join(lines[1:-1]) if len(lines) > 2 else text.strip("`").replace("json", "", 1).strip()
-    first, last = text.find("{"), text.rfind("}")
-    return text[first:last+1] if first != -1 and last != -1 else text
-
-def validate_answer(raw_output: str):
-    cleaned = clean_json_text(raw_output)
-    if cleaned.startswith("Error:"):
-        return {"error": cleaned, "question_language": "Odia", "question_list": []}
-    try:
-        return GeneratedQuestionModel.model_validate_json(cleaned).model_dump()
-    except ValidationError:
-        try:
-            return GeneratedQuestionModel(**json.loads(cleaned)).model_dump()
-        except:
-            return {"error": "Invalid JSON", "question_language": "Odia", "question_list": []}
-
-def final_pipeline(user_input: str, num_questions: int = 10):
-    prompt = PROMPTS["questions_only"].format(language="Odia", topic=user_input, num_questions=num_questions)
-    return validate_answer(chat_with_model(prompt))
-
-# API
-app = FastAPI()
-
-@app.get("/health")
-async def health_check():
-    try:
-        # Test model connectivity
-        test_response = model.generate_content("Test")
-        return {
-            "status": "healthy",
-            "model": os.getenv("LLM_MODEL", "gemini-pro"),
-            "api_configured": bool(google_api_key)
-        }
-    except Exception as e:
-        return {
-            "status": "unhealthy",
-            "error": str(e),
-            "api_configured": bool(google_api_key)
-        }
-@app.get("/")
-async def root():
-    return {"message": "Odia Question Generating API is running", "status": "healthy"}
-
-
-@app.post("/generate-questions")
-async def generate_questions(request: TopicRequest):
-    if not request.topic.strip():
-        raise HTTPException(status_code=400, detail="Topic cannot be empty")
-    if not 1 <= request.num_questions <= 50:
-        raise HTTPException(status_code=400, detail="Questions must be between 1-50")
-    
-    result = final_pipeline(request.topic.strip(), request.num_questions)
-    
-    if "error" in result and "Error:" in result["error"]:
-        raise HTTPException(status_code=500, detail=result["error"])
-    
-    return {"success": True, "data": result}
-
+
+# Setup
+load_dotenv()
+google_api_key = os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+model = genai.GenerativeModel(os.getenv("LLM_MODEL", "gemini-pro"))
+
+# Models
+class TopicRequest(BaseModel):
+    topic: str
+    num_questions: int = 10
+
+class GeneratedQuestionModel(BaseModel):
+    question_language: str
+    question_list: List[str]
+
+# Functions
+def chat_with_model(prompt: str) -> str:
+    try:
+        response = model.generate_content(prompt)
+        return response.text if response.text else "Error: Empty response"
+    except Exception as e:
+        return f"Error: {e}"
+
+def clean_json_text(text: str) -> str:
+    if text.startswith("Error:"):
+        return text
+    if text.startswith("```"):
+        lines = text.split('\n')
+        text = '\n'.join(lines[1:-1]) if len(lines) > 2 else text.strip("`").replace("json", "", 1).strip()
+    first, last = text.find("{"), text.rfind("}")
+    return text[first:last+1] if first != -1 and last != -1 else text
+
+def validate_answer(raw_output: str):
+    cleaned = clean_json_text(raw_output)
+    if cleaned.startswith("Error:"):
+        return {"error": cleaned, "question_language": "Odia", "question_list": []}
+    try:
+        return GeneratedQuestionModel.model_validate_json(cleaned).model_dump()
+    except ValidationError:
+        try:
+            return GeneratedQuestionModel(**json.loads(cleaned)).model_dump()
+        except:
+            return {"error": "Invalid JSON", "question_language": "Odia", "question_list": []}
+
+def final_pipeline(user_input: str, num_questions: int = 10):
+    prompt = PROMPTS["questions_only"].format(language="Odia", topic=user_input, num_questions=num_questions)
+    return validate_answer(chat_with_model(prompt))
+
+# API
+app = FastAPI()
+
+@app.get("/health")
+async def health_check():
+    try:
+        # Test model connectivity
+        test_response = model.generate_content("Test")
+        return {
+            "status": "healthy",
+            "model": os.getenv("LLM_MODEL", "gemini-pro"),
+            "api_configured": bool(google_api_key)
+        }
+    except Exception as e:
+        return {
+            "status": "unhealthy",
+            "error": str(e),
+            "api_configured": bool(google_api_key)
+        }
+@app.get("/")
+async def root():
+    return {"message": "Odia Question Generating API is running", "status": "healthy"}
+
+
+@app.post("/generate-questions")
+async def generate_questions(request: TopicRequest):
+    if not request.topic.strip():
+        raise HTTPException(status_code=400, detail="Topic cannot be empty")
+    if not 1 <= request.num_questions <= 50:
+        raise HTTPException(status_code=400, detail="Questions must be between 1-50")
+    
+    result = final_pipeline(request.topic.strip(), request.num_questions)
+    
+    if "error" in result and "Error:" in result["error"]:
+        raise HTTPException(status_code=500, detail=result["error"])
+    
+    return {"success": True, "data": result}
+
 if __name__ == "__main__":
     host = os.getenv("QUESTION_SERVICE_HOST", "0.0.0.0")
     port = int(os.getenv("QUESTION_SERVICE_PORT", "8000"))
-    uvicorn.run(app, host=host, port=port)
+    uvicorn.run(app, host=0.0.0.0, port=8000)