fix errors

.chainlit/config.toml

@@ -0,0 +1,62 @@
+[project]
+# Whether to enable telemetry (default: true). No personal data is collected.
+enable_telemetry = true
+
+# List of environment variables to be provided by each user to use the app.
+user_env = []
+
+# Duration (in seconds) during which the session is saved when the connection is lost
+session_timeout = 3600
+
+# Enable third parties caching (e.g LangChain cache)
+cache = false
+
+# Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
+# follow_symlink = false
+
+[features]
+# Show the prompt playground
+prompt_playground = true
+
+[UI]
+# Name of the app and chatbot.
+name = "Chatbot"
+
+# Description of the app and chatbot. This is used for HTML tags.
+# description = ""
+
+# Large size content are by default collapsed for a cleaner ui
+default_collapse_content = true
+
+# The default value for the expand messages settings.
+default_expand_messages = false
+
+# Hide the chain of thought details from the user in the UI.
+hide_cot = false
+
+# Link to your github repo. This will add a github button in the UI's header.
+# github = ""
+
+# Override default MUI light theme. (Check theme.ts)
+[UI.theme.light]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.light.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+
+# Override default MUI dark theme. (Check theme.ts)
+[UI.theme.dark]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.dark.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+
+
+[meta]
+generated_by = "0.7.0"

aimakerspace/openai_utils/.chainlit/config.toml

@@ -0,0 +1,62 @@
+[project]
+# Whether to enable telemetry (default: true). No personal data is collected.
+enable_telemetry = true
+
+# List of environment variables to be provided by each user to use the app.
+user_env = []
+
+# Duration (in seconds) during which the session is saved when the connection is lost
+session_timeout = 3600
+
+# Enable third parties caching (e.g LangChain cache)
+cache = false
+
+# Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
+# follow_symlink = false
+
+[features]
+# Show the prompt playground
+prompt_playground = true
+
+[UI]
+# Name of the app and chatbot.
+name = "Chatbot"
+
+# Description of the app and chatbot. This is used for HTML tags.
+# description = ""
+
+# Large size content are by default collapsed for a cleaner ui
+default_collapse_content = true
+
+# The default value for the expand messages settings.
+default_expand_messages = false
+
+# Hide the chain of thought details from the user in the UI.
+hide_cot = false
+
+# Link to your github repo. This will add a github button in the UI's header.
+# github = ""
+
+# Override default MUI light theme. (Check theme.ts)
+[UI.theme.light]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.light.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+
+# Override default MUI dark theme. (Check theme.ts)
+[UI.theme.dark]
+    #background = "#FAFAFA"
+    #paper = "#FFFFFF"
+
+    [UI.theme.dark.primary]
+        #main = "#F80061"
+        #dark = "#980039"
+        #light = "#FFE7EB"
+
+
+[meta]
+generated_by = "0.7.0"

aimakerspace/openai_utils/chatmodel.py

@@ -1,10 +1,10 @@
 import openai
 from dotenv import load_dotenv
 import os
+import chainlit as cl
 
 load_dotenv()
 
-
 class ChatOpenAI:
     def __init__(self, model_name: str = "gpt-3.5-turbo"):
         self.model_name = model_name
@@ -26,9 +26,10 @@ class ChatOpenAI:
 
         return response
 
-    def run_stream(self, messages, settings, chainlit_msg, text_only: bool = True):
-        async for stream_resp in await openai.Completion.acreate(
-            model=self.model_name, prompt=messages, stream=True, **settings
+    async def stream_with_cl_message(self, message_history, chainlit_msg: cl.Message, text_only: bool = True, settings: dict = {}):
+        print("streaming with cl message", message_history);
+        async for stream_resp in await openai.ChatCompletion.acreate(
+            model=self.model_name, messages=message_history, stream=True, **settings
         ):
-            token = stream_resp.get("choices")[0].get("text")
-        await chainlit_msg.stream_token(token)
+            token = stream_resp.choices[0]["delta"].get("content", "")
+            await chainlit_msg.stream_token(token)

app.py

@@ -1,9 +1,9 @@
 from dotenv import load_dotenv
-import openai #importing openai for API usage
-import chainlit as cl #importing chainlit for our app
+import openai
+import chainlit as cl
 from aimakerspace.vectordatabase import VectorDatabase
 from aimakerspace.vectordatabase import asyncio
-from aimakerspace.text_utils import TextFileLoader
+from aimakerspace.text_utils import TextFileLoader, CharacterTextSplitter
 import os
 import openai
 from getpass import getpass
@@ -16,10 +16,9 @@ from aimakerspace.openai_utils.chatmodel import ChatOpenAI
 
 
 load_dotenv()
-
+os.environ["OPENAI_API_KEY"] ="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"
 openai.api_key = os.environ["OPENAI_API_KEY"]
 
-openai.api_key = os.environ["OPENAI_API_KEY"]
 def load(filename):
     text_loader = TextFileLoader(filename)
     documents = text_loader.load_documents()
@@ -27,12 +26,15 @@ def load(filename):
 
 model_name = "gpt-4"
 
-filname = "data/KingLear.txt"
+filename = "data/KingLear.txt"
 
 vector_db = VectorDatabase()
-split_documents = load(filname)
+documents = load(filename)
+text_splitter = CharacterTextSplitter()
+split_documents = text_splitter.split_texts(documents)
 vector_db = asyncio.run(vector_db.abuild_from_list(split_documents))
-chat_openai = ChatOpenAI()
+
+# prompt templates
 user_prompt_template = "{content}"
 user_role_prompt = UserRolePrompt(user_prompt_template)
 system_prompt_template = (
@@ -76,7 +78,7 @@ class RetrievalAugmentedQAPipeline:
 
         return self.llm.run([formatted_system_prompt, formatted_user_prompt])
 
-    def stream_pipeline(self, user_query: str, msg: cl.Message) -> str:
+    async def stream_pipeline(self, user_query: str, message_history: [], msg: cl.Message) -> str:
         context_list = self.vector_db_retriever.search_by_text(user_query, k=4)
 
         context_prompt = ""
@@ -87,7 +89,10 @@ class RetrievalAugmentedQAPipeline:
 
         formatted_user_prompt = user_prompt.create_message(user_query=user_query)
 
-        self.llm.stream([formatted_system_prompt, formatted_user_prompt])
+        message_history.append(formatted_system_prompt)
+        message_history.append(formatted_user_prompt)
+
+        await self.llm.stream_with_cl_message(message_history=message_history, chainlit_msg=msg)
 
 
 @cl.on_chat_start # marks a function that will be executed at the start of a user session
@@ -108,11 +113,12 @@ def start_chat():
 
 @cl.on_message  # this function will be called every time a user inputs a message in the UI
 async def main(message: str):
+    message_history = cl.user_session.get("message_history")
 
-    qaPipeline =  RetrievalAugmentedQAPipeline(vector_db_retriever=vector_db, llm=chat_openai)
+    qaPipeline =  RetrievalAugmentedQAPipeline(vector_db_retriever=vector_db, llm=ChatOpenAI(model_name=model_name))
     msg = cl.Message(content="")
 
-    qaPipeline.stream_pipeline(user_query=message, msg=msg)
+    await qaPipeline.stream_pipeline(user_query=message, message_history=message_history, msg=msg)
     await msg.send()
 
 

chainlit.md

@@ -0,0 +1,14 @@
+# Welcome to Chainlit! 🚀🤖
+
+Hi there, Developer! 👋 We're excited to have you on board. Chainlit is a powerful tool designed to help you prototype, debug and share applications built on top of LLMs.
+
+## Useful Links 🔗
+
+- **Documentation:** Get started with our comprehensive [Chainlit Documentation](https://docs.chainlit.io) 📚
+- **Discord Community:** Join our friendly [Chainlit Discord](https://discord.gg/k73SQ3FyUh) to ask questions, share your projects, and connect with other developers! 💬
+
+We can't wait to see what you create with Chainlit! Happy coding! 💻😊
+
+## Welcome screen
+
+To modify the welcome screen, edit the `chainlit.md` file at the root of your project. If you do not want a welcome screen, just leave this file empty.