UPDATE: QDRANT

app.py

@@ -14,7 +14,6 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-
 @app.post("/signup")
 async def signup(username: str, password: str):
     try:
@@ -43,23 +42,23 @@ async def login(username: str, password: str):
     return output
 
 
-@app.get("/clear/{vectorstoreName}")
-async def clearVectorStore(vectorStoreName: str):
-    client.table(vectorStoreName).delete().neq("content", "").execute()
+@app.get("/newChatbot/{chatbotName}")
+async def newChatbot(chatbotName: str):
+    createTable(tablename = chatbotName)
     return {
         "output": "SUCCESS"
     }
 
 
 @app.post("/addPDF")
-async def addPDFData(vectorstorename: str, pdf: UploadFile = File(...)):
+async def addPDFData(vectorstore: str, pdf: UploadFile = File(...)):
     try:
         pdf = await pdf.read()
         reader = PdfReader(io.BytesIO(pdf))
         text = ""
         for page in reader.pages:
             text += page.extract_text()
-        addDocuments(text = text, storename = vectorstorename)
+        addDocuments(text = text, vectorstore = vectorstore)
         output = {
             "output": "SUCCESS"
         }
@@ -72,12 +71,13 @@ async def addPDFData(vectorstorename: str, pdf: UploadFile = File(...)):
 
 
 @app.post("/addText")
-async def addText(vectorstorename: str, text: str):
+async def addText(vectorstore: str, text: str):
+    addDocuments(text = text, vectorstore = vectorstore)
     try:
-        addDocuments(text = text, storename = vectorstorename)
         output = {
             "output": "SUCCESS"
         }
+        return output
     except Exception as e:
         output = {
             "error": e
@@ -86,9 +86,9 @@ async def addText(vectorstorename: str, text: str):
 
 
 @app.get("/answerQuery")
-async def answerQuery(query: str, vectorstorename: str, llmModel: str = "llama3-70b-8192"):
+async def answerQuestion(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192"):
     try:
-        response = await answerQuery(query=query, vectorstorename=vectorstorename, llmModel=llmModel)
+        response = answerQuery(query=query, vectorstore=vectorstore, llmModel=llmModel)
         output = {
             "output": response
         }
@@ -96,4 +96,31 @@ async def answerQuery(query: str, vectorstorename: str, llmModel: str = "llama3-
         output = {
             "error": e
         }
-    return output
+    return output
+
+@app.get("/deleteChatbot/{chatbotName}")
+async def delete(chatbotName: str):
+    try:
+        deleteTable(tableName=chatbotName)
+        response = {
+            "output": "SUCCESS"
+        }
+    except Exception as e:
+        response = {
+            "output": e
+        }
+    return response
+
+
+@app.get("/listChatbots/{username}")
+async def delete(username: str):
+    try:
+        chatbots = listTables(username=username)
+        response = {
+            "output": chatbots
+        }
+    except Exception as e:
+        response = {
+            "output": e
+        }
+    return response

functions.py

@@ -5,15 +5,16 @@ from langchain_core.prompts.chat import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_huggingface import HuggingFaceEmbeddings
 from supabase.client import create_client
-from supabase import create_client
+from qdrant_client import QdrantClient
 from langchain_groq import ChatGroq
+from supabase import create_client
 from dotenv import load_dotenv
 import pandas as pd
 import os
 
-
 load_dotenv("secrets.env")
 client = create_client(os.environ["SUPABASE_URL"], os.environ["SUPABASE_KEY"])
+qdrantClient = QdrantClient(url=os.environ["QDRANT_URL"])
 model_kwargs = {"device": "cuda"}
 encode_kwargs = {"normalize_embeddings": True}
 embeddings = HuggingFaceEmbeddings(
@@ -76,7 +77,7 @@ def createTable(tablename: str):
         collection_name=tablename
     )
 
-def addDocuments(text: str, vectorstorename: str):
+def addDocuments(text: str, vectorstore: str):
     global embeddings
     text_splitter = RecursiveCharacterTextSplitter(
         chunk_size = 1024,
@@ -86,7 +87,7 @@ def addDocuments(text: str, vectorstorename: str):
     texts = text_splitter.create_documents([text])
     vectorstore = QdrantVectorStore.from_existing_collection(
         embedding = embeddings,
-        collection_name=vectorstorename,
+        collection_name=vectorstore,
         url=os.environ["QDRANT_URL"],
     )
     vectorstore.add_documents(documents = texts)
@@ -120,4 +121,10 @@ def answerQuery(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192")
 
 
 def deleteTable(tableName: str):
-    pass
+    global qdrantClient
+    qdrantClient.delete_collection(collection_name=tableName)
+
+def listTables(username: str):
+    global qdrantClient
+    qdrantCollections = qdrantClient.get_collections()
+    return [qdrantCollections.collections[x].name for x in qdrantCollections if qdrantCollections.collections[x].name.split("-")[1] == username]