Spaces:
Sleeping
Sleeping
UPDATE: QDRANT
Browse files- app.py +8 -42
- functions.py +105 -55
app.py
CHANGED
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@@ -17,28 +17,18 @@ app.add_middleware(
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@app.post("/signup")
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async def signup(username: str, password: str):
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response = createUser(username = username, password = password)
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"output": response
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}
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return output
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@app.post("/login")
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async def login(username: str, password: str):
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response = matchPassword(username = username, password = password)
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"output": response
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}
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return output
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@app.get("/newChatbot/{chatbotName}")
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async def newChatbot(chatbotName: str):
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createTable(tablename = chatbotName)
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return {
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"output": "SUCCESS"
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}
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@app.post("/addPDF")
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@@ -48,47 +38,23 @@ async def addPDFData(vectorstore: str, pdf: UploadFile = File(...)):
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text = ""
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for page in reader.pages:
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text += page.extract_text()
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addDocuments(text = text, vectorstore = vectorstore)
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output = {
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"output": "SUCCESS"
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}
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return output
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@app.post("/addText")
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async def addText(vectorstore: str, text: str):
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addDocuments(text = text, vectorstore = vectorstore)
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output = {
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"output": "SUCCESS"
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}
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return output
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@app.get("/answerQuery")
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async def answerQuestion(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192"):
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output = {
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"output": response
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}
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return output
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@app.get("/deleteChatbot/{chatbotName}")
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async def delete(chatbotName: str):
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deleteTable(tableName=chatbotName)
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response = {
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"output": "SUCCESS"
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}
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return response
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@app.get("/listChatbots/{username}")
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async def delete(username: str):
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response = {
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"output": chatbots
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}
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return response
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@app.post("/signup")
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async def signup(username: str, password: str):
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response = createUser(username = username, password = password)
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return response
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@app.post("/login")
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async def login(username: str, password: str):
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response = matchPassword(username = username, password = password)
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return response
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@app.get("/newChatbot/{chatbotName}")
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async def newChatbot(chatbotName: str):
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return createTable(tablename = chatbotName)
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@app.post("/addPDF")
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text = ""
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for page in reader.pages:
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text += page.extract_text()
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return addDocuments(text = text, vectorstore = vectorstore)
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@app.post("/addText")
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async def addText(vectorstore: str, text: str):
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return addDocuments(text = text, vectorstore = vectorstore)
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@app.get("/answerQuery")
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async def answerQuestion(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192"):
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return answerQuery(query=query, vectorstore=vectorstore, llmModel=llmModel)
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@app.get("/deleteChatbot/{chatbotName}")
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async def delete(chatbotName: str):
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return deleteTable(tableName=chatbotName)
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@app.get("/listChatbots/{username}")
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async def delete(username: str):
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return listTables(username=username)
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functions.py
CHANGED
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@@ -14,7 +14,7 @@ import os
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load_dotenv("secrets.env")
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client = create_client(os.environ["SUPABASE_URL"], os.environ["SUPABASE_KEY"])
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qdrantClient = QdrantClient(url=os.environ["QDRANT_URL"])
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model_kwargs = {"device": "cuda"}
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encode_kwargs = {"normalize_embeddings": True}
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embeddings = HuggingFaceEmbeddings(
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@@ -43,16 +43,25 @@ prompt = ChatPromptTemplate.from_template(prompt)
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def createUser(username: str, password: str) -> None:
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def matchPassword(username: str, password: str) -> str:
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@@ -62,34 +71,54 @@ def matchPassword(username: str, password: str) -> str:
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.eq("username", username)
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.execute()
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)
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try: return
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def createTable(tablename: str):
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def addDocuments(text: str, vectorstore: str):
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def format_docs(docs: str):
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@@ -99,31 +128,52 @@ def format_docs(docs: str):
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else: pass
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return context
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def answerQuery(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192") -> str:
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retriever = vectorstore.as_retriever()
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chain = (
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{"context": retriever | RunnableLambda(format_docs), "question": RunnablePassthrough(query)}
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| prompt
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| ChatGroq(model = llmModel, temperature = 0.3, max_tokens = 512)
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| StrOutputParser()
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)
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def deleteTable(tableName: str):
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def listTables(username: str):
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load_dotenv("secrets.env")
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client = create_client(os.environ["SUPABASE_URL"], os.environ["SUPABASE_KEY"])
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qdrantClient = QdrantClient(url=os.environ["QDRANT_URL"], api_key=os.environ["QDRANT_API_KEY"])
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model_kwargs = {"device": "cuda"}
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encode_kwargs = {"normalize_embeddings": True}
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embeddings = HuggingFaceEmbeddings(
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def createUser(username: str, password: str) -> None:
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try:
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userData = client.table("ConversAI_UserInfo").select("*").execute().data
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if username not in [userData[x]["username"] for x in range(len(userData))]:
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response = (
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client.table("ConversAI_UserInfo")
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.insert({"username": username, "password": password})
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.execute()
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)
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return {
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"output": "SUCCESS"
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}
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else:
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return {
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"output": "USER ALREADY EXISTS"
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}
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except Exception as e:
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return {
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"error": e
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}
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def matchPassword(username: str, password: str) -> str:
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.eq("username", username)
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.execute()
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)
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try: return {
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"output": password == response.data[0]["password"]
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}
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except: return {
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"output": "USER DOESN'T EXIST"
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}
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def createTable(tablename: str):
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try:
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qdrant = QdrantVectorStore.from_documents(
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[],
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embeddings,
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url=os.environ["QDRANT_URL"],
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prefer_grpc=True,
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api_key=os.environ["QDRANT_API_KEY"],
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collection_name=tablename
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)
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return {
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"output": "SUCCESS"
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}
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except Exception as e:
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return {
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"error": e
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}
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def addDocuments(text: str, vectorstore: str):
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try:
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global embeddings
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text_splitter = RecursiveCharacterTextSplitter(
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chunk_size = 1024,
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chunk_overlap = 200,
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add_start_index = True
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)
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texts = text_splitter.create_documents([text])
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vectorstore = QdrantVectorStore.from_existing_collection(
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embedding = embeddings,
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collection_name=vectorstore,
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url=os.environ["QDRANT_URL"],
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)
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vectorstore.add_documents(documents = texts)
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return {
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"output": "SUCCESS"
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}
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except Exception as e:
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return {
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"error": e
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}
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def format_docs(docs: str):
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else: pass
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return context
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def answerQuery(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192") -> str:
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try:
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global prompt
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global client
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global embeddings
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vectorstore = QdrantVectorStore.from_existing_collection(
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embedding = embeddings,
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collection_name=vectorstore,
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url=os.environ["QDRANT_URL"],
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)
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retriever = vectorstore.as_retriever()
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chain = (
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{"context": retriever | RunnableLambda(format_docs), "question": RunnablePassthrough(query)}
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| prompt
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| ChatGroq(model = llmModel, temperature = 0.3, max_tokens = 512)
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| StrOutputParser()
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)
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return {
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"output": chain.invoke(query)
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}
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except Exception as e:
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return {
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"error": e
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}
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def deleteTable(tableName: str):
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try:
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global qdrantClient
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qdrantClient.delete_collection(collection_name=tableName)
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return {
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"output": "SUCCESS"
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}
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except Exception as e:
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return {
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"error": e
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}
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def listTables(username: str):
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try:
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global qdrantClient
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qdrantCollections = qdrantClient.get_collections()
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return {
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"output": [qdrantCollections.collections[x].name for x in qdrantCollections if qdrantCollections.collections[x].name.split("-")[1] == username]
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}
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except Exception as e:
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return {
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"error": e
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}
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