UPDATE: chatHistory

app.py

@@ -81,7 +81,7 @@ async def sign_in(email, password):
  if store_session_check and store_session_check.data:
  store_id = store_session_check.data[0].get("StoreID")
 
- userData = client.table("ConversAI_UserInfo").select("*").filter("user_id", "eq", user_id).execute().data
+ userData = supabase.table("ConversAI_UserInfo").select("*").filter("user_id", "eq", user_id).execute().data
  username = userData[0]["username"]
 
  if not store_id:
@@ -215,13 +215,13 @@ async def oauth(provider):
 @app.post("/newChatbot")
 async def newChatbot(chatbotName: str, username: str):
  currentBotCount = len(listTables(username=username)["output"])
- limit = client.table("ConversAI_UserConfig").select("chatbotLimit").eq("user_id", username).execute().data[0][
+ limit = supabase.table("ConversAI_UserConfig").select("chatbotLimit").eq("user_id", username).execute().data[0][
  "chatbotLimit"]
  if currentBotCount >= int(limit):
  return {
  "output": "CHATBOT LIMIT EXCEEDED"
  }
- client.table("ConversAI_ChatbotInfo").insert({"user_id": username, "chatbotname": chatbotName}).execute()
+ supabase.table("ConversAI_ChatbotInfo").insert({"user_id": username, "chatbotname": chatbotName}).execute()
  chatbotName = f"convai${username}${chatbotName}"
  return createTable(tablename=chatbotName)
 
@@ -238,13 +238,13 @@ async def addPDFData(vectorstore: str, pdf: UploadFile = File(...)):
  textExtraction = time.time()
  os.remove(temp_file_path)
  username, chatbotname = vectorstore.split("$")[1], vectorstore.split("$")[2]
- df = pd.DataFrame(client.table("ConversAI_ChatbotInfo").select("*").execute().data)
+ df = pd.DataFrame(supabase.table("ConversAI_ChatbotInfo").select("*").execute().data)
  currentCount = df[(df["user_id"] == username) & (df["chatbotname"] == chatbotname)]["charactercount"].iloc[0]
- limit = client.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
+ limit = supabase.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
  "tokenLimit"]
  newCount = currentCount + len(text)
  if newCount < int(limit):
- client.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
+ supabase.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
  "chatbotname", chatbotname).execute()
  uploadStart = time.time()
  output = addDocuments(text=text, source=source, vectorstore=vectorstore)
@@ -271,29 +271,46 @@ async def addPDFData(vectorstore: str, pdf: UploadFile = File(...)):
 
 @app.post("/scanAndReturnText")
 async def returnText(pdf: UploadFile = File(...)):
+ source = pdf.filename
  pdf = await pdf.read()
  start = time.time()
  text = getTextFromImagePDF(pdfBytes=pdf)
  end = time.time()
  timeTaken = f"{end - start}s"
  return {
+ "source": source,
  "extractionTime": timeTaken,
  "output": text 
  }
 
 
 @app.post("/addText")
-async def addText(vectorstore: str, text: str):
+async def addText(vectorstore: str, text: str, source: str | None = None):
  username, chatbotname = vectorstore.split("$")[1], vectorstore.split("$")[2]
- df = pd.DataFrame(client.table("ConversAI_ChatbotInfo").select("*").execute().data)
+ df = pd.DataFrame(supabase.table("ConversAI_ChatbotInfo").select("*").execute().data)
  currentCount = df[(df["user_id"] == username) & (df["chatbotname"] == chatbotname)]["charactercount"].iloc[0]
  newCount = currentCount + len(text)
- limit = client.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
+ limit = supabase.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
  "tokenLimit"]
  if newCount < int(limit):
- client.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
+ supabase.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
  "chatbotname", chatbotname).execute()
- return addDocuments(text=text, source="text", vectorstore=vectorstore)
+ uploadStart = time.time()
+ output = addDocuments(text=text, source=source, vectorstore=vectorstore)
+ uploadEnd = time.time()
+ uploadTime = f"VECTOR UPLOAD TIME: {uploadEnd - uploadStart}s" + "\n"
+ tokenCount = f"TOKEN COUNT: {len(text)}" + "\n"
+ tokenizer = nltk.tokenize.RegexpTokenizer(r"\w+")
+ wordCount = f"WORD COUNT: {len(tokenizer.tokenize(text))}" + "\n"
+ newText = ("=" * 75 + "\n").join([uploadTime, wordCount, tokenCount, "TEXT: \n" + text + "\n"])
+ fileId = str(uuid.uuid4())
+ with open(f"{fileId}.txt", "w") as file:
+ file.write(newText)
+ with open(f"{fileId}.txt", "rb") as f:
+ supabase.storage.from_("ConversAI").upload(file = f, path = os.path.join("/", f.name), file_options={"content-type": "text/plain"})
+ os.remove(f"{fileId}.txt")
+ output["supabaseFileName"] = f"{fileId}.txt"
+ return output
  else:
  return {
  "output": "WEBSITE EXCEEDING LIMITS, PLEASE TRY WITH A SMALLER DOCUMENT."
@@ -309,14 +326,14 @@ class AddQAPair(BaseModel):
 @app.post("/addQAPair")
 async def addText(addQaPair: AddQAPair):
  username, chatbotname = addQaPair.vectorstore.split("$")[1], addQaPair.vectorstore.split("$")[2]
- df = pd.DataFrame(client.table("ConversAI_ChatbotInfo").select("*").execute().data)
+ df = pd.DataFrame(supabase.table("ConversAI_ChatbotInfo").select("*").execute().data)
  currentCount = df[(df["user_id"] == username) & (df["chatbotname"] == chatbotname)]["charactercount"].iloc[0]
  qa = f"QUESTION: {addQaPair.question}\tANSWER: {addQaPair.answer}"
  newCount = currentCount + len(qa)
- limit = client.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
+ limit = supabase.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0][
  "tokenLimit"]
  if newCount < int(limit):
- client.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
+ supabase.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
  "chatbotname", chatbotname).execute()
  return addDocuments(text=qa, source="Q&A Pairs", vectorstore=addQaPair.vectorstore)
  else:
@@ -331,12 +348,12 @@ async def addWebsite(vectorstore: str, websiteUrls: list[str]):
  text = extractTextFromUrlList(urls = websiteUrls)
  textExtraction = time.time()
  username, chatbotname = vectorstore.split("$")[1], vectorstore.split("$")[2]
- df = pd.DataFrame(client.table("ConversAI_ChatbotInfo").select("*").execute().data)
+ df = pd.DataFrame(supabase.table("ConversAI_ChatbotInfo").select("*").execute().data)
  currentCount = df[(df["user_id"] == username) & (df["chatbotname"] == chatbotname)]["charactercount"].iloc[0]
  newCount = currentCount + len(text)
- limit = client.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0]["tokenLimit"]
+ limit = supabase.table("ConversAI_UserConfig").select("tokenLimit").eq("user_id", username).execute().data[0]["tokenLimit"]
  if newCount < int(limit):
- client.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
+ supabase.table("ConversAI_ChatbotInfo").update({"charactercount": str(newCount)}).eq("user_id", username).eq(
  "chatbotname", chatbotname).execute()
  uploadStart = time.time()
  output = addDocuments(text=text, source=urlparse(websiteUrls[0]).netloc, vectorstore=vectorstore)
@@ -364,13 +381,20 @@ async def addWebsite(vectorstore: str, websiteUrls: list[str]):
 
 @app.post("/answerQuery")
 async def answerQuestion(query: str, vectorstore: str, llmModel: str = "llama3-70b-8192"):
- return answerQuery(query=query, vectorstore=vectorstore, llmModel=llmModel)
+ username, chatbotName = vectorstore.split("$")[1], vectorstore.split("$")[2]
+ output = answerQuery(query=query, vectorstore=vectorstore, llmModel=llmModel)
+ response = (
+ supabase.table("ConversAI_ChatHistory")
+ .insert({"username": username, "chatbotName": chatbotName, "llmModel": llmModel, "question": query, "response": output["output"]})
+ .execute()
+ )
+ return output
 
 
 @app.post("/deleteChatbot")
 async def delete(chatbotName: str):
  username, chatbotName = chatbotName.split("$")[1], chatbotName.split("$")[2]
- client.table('ConversAI_ChatbotInfo').delete().eq('user_id', username).eq('chatbotname', chatbotName).execute()
+ supabase.table('ConversAI_ChatbotInfo').delete().eq('user_id', username).eq('chatbotname', chatbotName).execute()
  return deleteTable(tableName=chatbotName)
 
 
@@ -389,7 +413,7 @@ async def crawlUrl(baseUrl: str):
 @app.post("/getCurrentCount")
 async def getCount(vectorstore: str):
  username, chatbotName = vectorstore.split("$")[1], vectorstore.split("$")[2]
- df = pd.DataFrame(client.table("ConversAI_ChatbotInfo").select("*").execute().data)
+ df = pd.DataFrame(supabase.table("ConversAI_ChatbotInfo").select("*").execute().data)
  return {
  "currentCount": df[(df['user_id'] == username) & (df['chatbotname'] == chatbotName)]['charactercount'].iloc[0]
  }