langchain-ai/streamlit-agent
1
0
Fork 0
mirror of https://github.com/langchain-ai/streamlit-agent.git synced 2026-07-01 09:25:05 -04:00
Code Issues 8 Packages Projects Releases Wiki Activity

Not sure how to initialize st.session_state['messages'] in my chat code #5

New Issue
Closed
opened 2026-02-15 19:15:14 -05:00 by yindo · 2 comments
yindo commented 2026-02-15 19:15:14 -05:00
Owner
Copy Link
Copy Source

Originally created by @josoroma on GitHub (Jul 29, 2023).

image

Hitting this error:

Traceback (most recent call last):
  File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 552, in _run_script
    exec(code, module.__dict__)
  File "/Users/josoroma/sites/etl-pipeline-for-langchain-docs/chat.py", line 111, in <module>
    ChatApp().main()
  File "/Users/josoroma/sites/etl-pipeline-for-langchain-docs/chat.py", line 83, in main
    for msg in st.session_state['messages']:
               ~~~~~~~~~~~~~~~~^^^^^^^^^^^^
  File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/state/session_state_proxy.py", line 90, in __getitem__
    return get_session_state()[key]
           ~~~~~~~~~~~~~~~~~~~^^^^^
  File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/state/safe_session_state.py", line 111, in __getitem__
    raise KeyError(key)
KeyError: 'messages'

My code:

import os
import weaviate
import openai
from pydantic import BaseModel
from langchain.callbacks.base import BaseCallbackHandler
# from langchain.chat_models import ChatOpenAI
from langchain.schema import ChatMessage
import streamlit as st

class Document(BaseModel):
    content: str

class QueryResult(BaseModel):
    document: Document

class StreamHandler(BaseCallbackHandler):
    def __init__(self, container, initial_text=""):
        self.container = container
        self.text = initial_text

    def on_llm_new_token(self, token: str, **kwargs) -> None:
        self.text += token
        self.container.markdown(self.text)

class ChatApp:
    def __init__(self):
        self.client = None
        self.get_env_variables()
        self.client = self.get_client()

    def get_env_variable(self, var_name):
        var_value = os.getenv(var_name)
        return var_value

    def get_env_variables(self):
        with st.sidebar:
            self.OPENAI_API_KEY = self.get_env_variable("OPENAI_API_KEY") or st.text_input("OpenAI API Key", type="password")
            self.WEAVIATE_HOST = self.get_env_variable("WEAVIATE_HOST") or st.text_input("Weaviate Host")
            self.WEAVIATE_AUTH_API_KEY = self.get_env_variable("WEAVIATE_AUTH_API_KEY") or st.text_input("Bearer Token", type="password")

        if not self.OPENAI_API_KEY or not self.WEAVIATE_HOST or not self.WEAVIATE_AUTH_API_KEY:
            st.info("Please add your OpenAI API Key, Weaviate Host, and Bearer Token to continue.")
            st.stop()

        openai.api_key = self.OPENAI_API_KEY

    def get_client(self):
        try:
            client = weaviate.Client(
                url=self.WEAVIATE_HOST,
                auth_client_secret=weaviate.AuthApiKey(self.WEAVIATE_AUTH_API_KEY),
                additional_headers={"X-OpenAI-Api-Key": self.OPENAI_API_KEY},
            )
        except Exception as e:
            st.error(f"Error occurred while creating the Weaviate client: {str(e)}")
            st.stop()

        return client

    def client_query(self, question: str):
        generatePrompt = "Respond to the human as helpfully and accurately as possible: {text}"
        nearText = {"concepts": [f"{question}"]}

        try:
            response = (
                self.client.query
                .get("Document", ["content"])
                .with_generate(single_prompt=generatePrompt)
                .with_near_text(nearText)
                .with_limit(1)
                .do()
            )
        except Exception as e:
            st.error(f"Error occurred while querying the Weaviate client: {str(e)}")
            st.stop()

        return response

    def main(self):
        if 'messages' not in st.session_state:
            st.session_state['messages'] = [ChatMessage(role="assistant", content="How can I help you?")]

        for msg in st.session_state['messages']:
            st.chat_message(msg.role).write(msg.content)

        if prompt := st.text_input("Your input:"):
            st.session_state['messages'].append(ChatMessage(role="user", content=prompt))
            st.chat_message("user").write(prompt)

            response = self.client_query(prompt)
            if response:
                try:
                    for document in response['data']['Get']['Document']:
                        try:
                            generativeOpenAI = document['_additional']['generate']["singleResult"]
                            content = document['content']
                        except KeyError as ke:
                            st.markdown(f"Error: Expected keys not found in the document. {ke}")
                            continue

                        if generativeOpenAI:
                            st.session_state['messages'].append(ChatMessage(role="assistant", content=generativeOpenAI))
                            st.chat_message("assistant").write(generativeOpenAI)
                        if content:
                            st.session_state['messages'].append(ChatMessage(role="assistant", content=content))
                            st.chat_message("assistant").write(content)
                except KeyError as ke:
                    st.markdown(f"Error: Expected keys not found in the response. {ke}")

if __name__ == "__main__":
    ChatApp().main()
Originally created by @josoroma on GitHub (Jul 29, 2023). <img width="1090" alt="image" src="https://github.com/langchain-ai/streamlit-agent/assets/128641060/66512225-c75b-44eb-9c96-6b81307842f4"> Hitting this error: ``` Traceback (most recent call last): File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 552, in _run_script exec(code, module.__dict__) File "/Users/josoroma/sites/etl-pipeline-for-langchain-docs/chat.py", line 111, in <module> ChatApp().main() File "/Users/josoroma/sites/etl-pipeline-for-langchain-docs/chat.py", line 83, in main for msg in st.session_state['messages']: ~~~~~~~~~~~~~~~~^^^^^^^^^^^^ File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/state/session_state_proxy.py", line 90, in __getitem__ return get_session_state()[key] ~~~~~~~~~~~~~~~~~~~^^^^^ File "/Users/josoroma/Library/Caches/pypoetry/virtualenvs/etl-Fd0mW_QZ-py3.11/lib/python3.11/site-packages/streamlit/runtime/state/safe_session_state.py", line 111, in __getitem__ raise KeyError(key) KeyError: 'messages' ``` My code: ``` import os import weaviate import openai from pydantic import BaseModel from langchain.callbacks.base import BaseCallbackHandler # from langchain.chat_models import ChatOpenAI from langchain.schema import ChatMessage import streamlit as st class Document(BaseModel): content: str class QueryResult(BaseModel): document: Document class StreamHandler(BaseCallbackHandler): def __init__(self, container, initial_text=""): self.container = container self.text = initial_text def on_llm_new_token(self, token: str, **kwargs) -> None: self.text += token self.container.markdown(self.text) class ChatApp: def __init__(self): self.client = None self.get_env_variables() self.client = self.get_client() def get_env_variable(self, var_name): var_value = os.getenv(var_name) return var_value def get_env_variables(self): with st.sidebar: self.OPENAI_API_KEY = self.get_env_variable("OPENAI_API_KEY") or st.text_input("OpenAI API Key", type="password") self.WEAVIATE_HOST = self.get_env_variable("WEAVIATE_HOST") or st.text_input("Weaviate Host") self.WEAVIATE_AUTH_API_KEY = self.get_env_variable("WEAVIATE_AUTH_API_KEY") or st.text_input("Bearer Token", type="password") if not self.OPENAI_API_KEY or not self.WEAVIATE_HOST or not self.WEAVIATE_AUTH_API_KEY: st.info("Please add your OpenAI API Key, Weaviate Host, and Bearer Token to continue.") st.stop() openai.api_key = self.OPENAI_API_KEY def get_client(self): try: client = weaviate.Client( url=self.WEAVIATE_HOST, auth_client_secret=weaviate.AuthApiKey(self.WEAVIATE_AUTH_API_KEY), additional_headers={"X-OpenAI-Api-Key": self.OPENAI_API_KEY}, ) except Exception as e: st.error(f"Error occurred while creating the Weaviate client: {str(e)}") st.stop() return client def client_query(self, question: str): generatePrompt = "Respond to the human as helpfully and accurately as possible: {text}" nearText = {"concepts": [f"{question}"]} try: response = ( self.client.query .get("Document", ["content"]) .with_generate(single_prompt=generatePrompt) .with_near_text(nearText) .with_limit(1) .do() ) except Exception as e: st.error(f"Error occurred while querying the Weaviate client: {str(e)}") st.stop() return response def main(self): if 'messages' not in st.session_state: st.session_state['messages'] = [ChatMessage(role="assistant", content="How can I help you?")] for msg in st.session_state['messages']: st.chat_message(msg.role).write(msg.content) if prompt := st.text_input("Your input:"): st.session_state['messages'].append(ChatMessage(role="user", content=prompt)) st.chat_message("user").write(prompt) response = self.client_query(prompt) if response: try: for document in response['data']['Get']['Document']: try: generativeOpenAI = document['_additional']['generate']["singleResult"] content = document['content'] except KeyError as ke: st.markdown(f"Error: Expected keys not found in the document. {ke}") continue if generativeOpenAI: st.session_state['messages'].append(ChatMessage(role="assistant", content=generativeOpenAI)) st.chat_message("assistant").write(generativeOpenAI) if content: st.session_state['messages'].append(ChatMessage(role="assistant", content=content)) st.chat_message("assistant").write(content) except KeyError as ke: st.markdown(f"Error: Expected keys not found in the response. {ke}") if __name__ == "__main__": ChatApp().main() ```
yindo closed this issue 2026-02-15 19:15:14 -05:00
yindo commented 2026-02-15 19:15:15 -05:00
Author
Owner
Copy Link
Copy Source

@Muhtasham commented on GitHub (Jul 30, 2023):

Hello are you using correct Streamlit version?

@Muhtasham commented on GitHub (Jul 30, 2023): Hello are you using correct Streamlit version?
yindo commented 2026-02-15 19:15:15 -05:00
Author
Owner
Copy Link
Copy Source

@sfc-gh-jcarroll commented on GitHub (Sep 13, 2023):

Hi, looks like this request is for app code that was not from this repo. Might be a good one to post for help in the forum:

https://discuss.streamlit.io/c/questions/5

@sfc-gh-jcarroll commented on GitHub (Sep 13, 2023): Hi, looks like this request is for app code that was not from this repo. Might be a good one to post for help in the forum: https://discuss.streamlit.io/c/questions/5
Sign in to join this conversation.
No Branch/Tag Specified
Branches Tags
Labels
Clear labels
pull-request
Mirrored from GitHub Pull Request
No Label
Milestone
No items
No Milestone
Projects
Clear projects
No project
Assignees
Clear assignees
yindo
No Assignees
1 Participants
Notifications
Due Date
No due date set.
Dependencies

No dependencies set.

Reference: langchain-ai/streamlit-agent#5
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?