Added Qdrant Cloud configuration for deployment environment

Author: siddhi

ai.py

@@ -230,7 +230,17 @@ def review_application(job_description: str) -> ReviewedApplication:
 
 def get_vector_store():
     embeddings = OpenAIEmbeddings(model="text-embedding-3-large", api_key=settings.OPENAI_API_KEY)
-    vector_store = QdrantVectorStore.from_existing_collection(embedding=embeddings, collection_name="resumes", path="qdrant_store")
+    if settings.PRODUCTION:
+        vector_store = QdrantVectorStore.from_existing_collection(
+            embedding=embeddings, 
+            collection_name="resumes", 
+            url=str(settings.QDRANT_URL), 
+            api_key=settings.QDRANT_API_KEY)
+    else:
+        vector_store = QdrantVectorStore.from_existing_collection(
+            embedding=embeddings, 
+            collection_name="resumes", 
+            path="qdrant_store")
     return vector_store
 
 def inmemory_vector_store():

main.py

@@ -111,21 +111,6 @@ async def api_close_job_post(job_post_id, db: Session = Depends(get_db)):
    db.commit()
    return jobPost
 
-@app.get("/api/job-posts/{job_post_id}/recommend")
-async def api_recommend_resume(
-   job_post_id, 
-   db: Session = Depends(get_db),
-   vector_store = Depends(get_vector_store)):
-   
-   job_post = db.get(JobPost, job_post_id)
-   if not job_post:
-      raise HTTPException(status_code=400)
-   job_description = job_post.description
-   recommended_resume = get_recommendation(job_description, vector_store)   
-   application_id = recommended_resume.metadata["_id"]
-   job_application = db.get(JobApplication, application_id)
-   return job_application
-
 class JobPostForm(BaseModel):
    title : str
    description: str