diff --git a/docs/integration/chainlit.mdx b/docs/integration/chainlit.mdx
index b4a28cff..902f3809 100644
--- a/docs/integration/chainlit.mdx
+++ b/docs/integration/chainlit.mdx
@@ -3,7 +3,9 @@ title: '⛓️ Chainlit'
description: 'Integrate with Chainlit to create LLM chat apps'
---
-In this example, we will learn how to use Chainlit and Embedchain together
+In this example, we will learn how to use Chainlit and Embedchain together.
+
+
## Setup
@@ -64,5 +66,3 @@ chainlit run app.py
## Try it out
Open the app in your browser and start chatting with it!
-
-
diff --git a/docs/integration/streamlit-mistral.mdx b/docs/integration/streamlit-mistral.mdx
index d63b6d47..8d6cbf95 100644
--- a/docs/integration/streamlit-mistral.mdx
+++ b/docs/integration/streamlit-mistral.mdx
@@ -3,108 +3,107 @@ title: '🚀 Streamlit'
description: 'Integrate with Streamlit to plug and play with any LLM'
---
-In this example, we will learn how to use `mistralai/Mistral-7B-v0.1` and Embedchain together with Streamlit to build a simple RAG chatbot.
+In this example, we will learn how to use `mistralai/Mixtral-8x7B-Instruct-v0.1` and Embedchain together with Streamlit to build a simple RAG chatbot.
+
+
## Setup
-
- 1. Install Embedchain and Streamlit
- ```bash
- pip install embedchain
- pip install streamlit
- ```
-
-
- ```python
- import os
- from embedchain import Pipeline as App
- import streamlit as st
+Install Embedchain and Streamlit.
+```bash
+pip install embedchain streamlit
+```
+
+
+ ```python
+ import os
+ from embedchain import Pipeline as App
+ import streamlit as st
- with st.sidebar:
- huggingface_access_token = st.text_input("Hugging face Token", key="chatbot_api_key", type="password")
- "[Get Hugging Face Access Token](https://huggingface.co/settings/tokens)"
- "[View the source code](https://github.com/embedchain/examples/mistral-streamlit)"
+ with st.sidebar:
+ huggingface_access_token = st.text_input("Hugging face Token", key="chatbot_api_key", type="password")
+ "[Get Hugging Face Access Token](https://huggingface.co/settings/tokens)"
+ "[View the source code](https://github.com/embedchain/examples/mistral-streamlit)"
- st.title("💬 Chatbot")
- st.caption("🚀 An Embedchain app powered by Mistral!")
- if "messages" not in st.session_state:
- st.session_state.messages = [
- {
- "role": "assistant",
- "content": """
- Hi! I'm a chatbot. I can answer questions and learn new things!\n
- Ask me anything and if you want me to learn something do `/add `.\n
- I can learn mostly everything. :)
- """,
- }
- ]
+ st.title("💬 Chatbot")
+ st.caption("🚀 An Embedchain app powered by Mistral!")
+ if "messages" not in st.session_state:
+ st.session_state.messages = [
+ {
+ "role": "assistant",
+ "content": """
+ Hi! I'm a chatbot. I can answer questions and learn new things!\n
+ Ask me anything and if you want me to learn something do `/add `.\n
+ I can learn mostly everything. :)
+ """,
+ }
+ ]
- for message in st.session_state.messages:
- with st.chat_message(message["role"]):
- st.markdown(message["content"])
+ for message in st.session_state.messages:
+ with st.chat_message(message["role"]):
+ st.markdown(message["content"])
- if prompt := st.chat_input("Ask me anything!"):
- if not st.session_state.chatbot_api_key:
- st.error("Please enter your Hugging Face Access Token")
- st.stop()
+ if prompt := st.chat_input("Ask me anything!"):
+ if not st.session_state.chatbot_api_key:
+ st.error("Please enter your Hugging Face Access Token")
+ st.stop()
- os.environ["HUGGINGFACE_ACCESS_TOKEN"] = st.session_state.chatbot_api_key
- app = App.from_config(config_path="config.yaml")
+ os.environ["HUGGINGFACE_ACCESS_TOKEN"] = st.session_state.chatbot_api_key
+ app = App.from_config(config_path="config.yaml")
- if prompt.startswith("/add"):
- with st.chat_message("user"):
- st.markdown(prompt)
- st.session_state.messages.append({"role": "user", "content": prompt})
- prompt = prompt.replace("/add", "").strip()
- with st.chat_message("assistant"):
- message_placeholder = st.empty()
- message_placeholder.markdown("Adding to knowledge base...")
- app.add(prompt)
- message_placeholder.markdown(f"Added {prompt} to knowledge base!")
- st.session_state.messages.append({"role": "assistant", "content": f"Added {prompt} to knowledge base!"})
- st.stop()
+ if prompt.startswith("/add"):
+ with st.chat_message("user"):
+ st.markdown(prompt)
+ st.session_state.messages.append({"role": "user", "content": prompt})
+ prompt = prompt.replace("/add", "").strip()
+ with st.chat_message("assistant"):
+ message_placeholder = st.empty()
+ message_placeholder.markdown("Adding to knowledge base...")
+ app.add(prompt)
+ message_placeholder.markdown(f"Added {prompt} to knowledge base!")
+ st.session_state.messages.append({"role": "assistant", "content": f"Added {prompt} to knowledge base!"})
+ st.stop()
- with st.chat_message("user"):
- st.markdown(prompt)
- st.session_state.messages.append({"role": "user", "content": prompt})
+ with st.chat_message("user"):
+ st.markdown(prompt)
+ st.session_state.messages.append({"role": "user", "content": prompt})
- with st.chat_message("assistant"):
- msg_placeholder = st.empty()
- msg_placeholder.markdown("Thinking...")
- full_response = ""
+ with st.chat_message("assistant"):
+ msg_placeholder = st.empty()
+ msg_placeholder.markdown("Thinking...")
+ full_response = ""
- for response in app.chat(prompt):
- msg_placeholder.empty()
- full_response += response
+ for response in app.chat(prompt):
+ msg_placeholder.empty()
+ full_response += response
- msg_placeholder.markdown(full_response)
- st.session_state.messages.append({"role": "assistant", "content": full_response})
- ```
-
-
- ```yaml
- app:
- config:
- name: 'mistral-streamlit-app'
-
- llm:
- provider: huggingface
- config:
- model: 'mistralai/Mistral-7B-v0.1'
- temperature: 0.1
- max_tokens: 250
- top_p: 0.1
- stream: true
-
- embedder:
- provider: huggingface
- config:
- model: 'sentence-transformers/all-mpnet-base-v2'
+ msg_placeholder.markdown(full_response)
+ st.session_state.messages.append({"role": "assistant", "content": full_response})
```
-
-
-
+
+
+ ```yaml
+ app:
+ config:
+ name: 'mistral-streamlit-app'
+
+ llm:
+ provider: huggingface
+ config:
+ model: 'mistralai/Mixtral-8x7B-Instruct-v0.1'
+ temperature: 0.1
+ max_tokens: 250
+ top_p: 0.1
+ stream: true
+
+ embedder:
+ provider: huggingface
+ config:
+ model: 'sentence-transformers/all-mpnet-base-v2'
+ ```
+
+
## To run it locally,