Chainlit_UI_with_Gemini_API

To integrate Chainlit with the Gemini API, follow these steps: ### Step 1: Install Chainlit First, ensure that you have Chainlit installed. You can install it using pip: ```bash pip install chainlit ``` ### Step 2: Update the Code Here's an updated version of your code that uses the Gemini API instead of the OpenAI API. ```python from langchain.prompts import ChatPromptTemplate from langchain.schema import StrOutputParser from langchain.schema.runnable import Runnable from langchain.schema.runnable.config import RunnableConfig from langchain_google_genai import GoogleGenerativeAI, HarmBlockThreshold, HarmCategory import chainlit as cl import os # Get your API key from the environment variable api_key = os.getenv("API_KEY") @cl.on_chat_start async def on_chat_start(): # Configure the model with your Google API key model = GoogleGenerativeAI( model="gemini-pro", google_api_key=api_key, safety_settings={ HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE, }, ) prompt = ChatPromptTemplate.from_messages( [ ( "system", "You're a very knowledgeable historian who provides accurate and eloquent answers to historical questions.", ), ("human", "{question}"), ] ) runnable = prompt | model | StrOutputParser() cl.user_session.set("runnable", runnable) @cl.on_message async def on_message(message: cl.Message): runnable = cl.user_session.get("runnable") # type: Runnable msg = cl.Message(content="") async for chunk in runnable.astream( {"question": message.content}, config=RunnableConfig(callbacks=[cl.LangchainCallbackHandler()]), ): await msg.stream_token(chunk) await msg.send() ``` ### Step 3: Set Up API Key 1. **Sign Up for Google AI Studio**: Sign up at [Google AI Studio](https://aistudio.google.com/app/apikey) using your Google account to get an API key. 2. **Create an `.env` File**: Create a `.env` file in the root directory of your project and add your API key: ``` API_KEY=your_google_api_key_here ``` 3. **Load the API Key in Your Script**: Ensure that the API key is loaded into your script as shown above. ### Step 4: Run the Application To start your Chainlit app, open a terminal and navigate to the directory containing your `app.py` file. Then run the following command: ```bash chainlit run app.py -w ``` This command will start your Chainlit application and open a web interface where you can interact with the chatbot. ### References For additional details on Chainlit and Langchain integration, refer to the [Chainlit Documentation](https://docs.chainlit.io/integrations/langchain).