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  1. .chainlit/config.toml +97 -0
  2. Dockerfile +11 -0
  3. README.md +19 -4
  4. app.py +40 -0
  5. chainlit.md +14 -0
  6. requirements.txt +7 -0
  7. storage_mini/default__vector_store.json +0 -0
  8. storage_mini/docstore.json +0 -0
  9. storage_mini/index_store.json +1 -0
.chainlit/config.toml ADDED
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+ [project]
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+ # Whether to enable telemetry (default: true). No personal data is collected.
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+ enable_telemetry = true
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+
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+
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+ # List of environment variables to be provided by each user to use the app.
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+ user_env = []
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+
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+ # Duration (in seconds) during which the session is saved when the connection is lost
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+ session_timeout = 3600
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+
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+ # Enable third parties caching (e.g LangChain cache)
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+ cache = false
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+
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+ # Authorized origins
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+ allow_origins = ["*"]
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+
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+ # Follow symlink for asset mount (see https://github.com/Chainlit/chainlit/issues/317)
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+ # follow_symlink = false
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+
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+ [features]
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+ # Show the prompt playground
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+ prompt_playground = true
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+
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+ # Process and display HTML in messages. This can be a security risk (see https://stackoverflow.com/questions/19603097/why-is-it-dangerous-to-render-user-generated-html-or-javascript)
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+ unsafe_allow_html = false
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+
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+ # Process and display mathematical expressions. This can clash with "$" characters in messages.
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+ latex = false
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+
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+ # Authorize users to upload files with messages
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+ multi_modal = true
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+
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+ # Allows user to use speech to text
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+ [features.speech_to_text]
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+ enabled = false
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+ # See all languages here https://github.com/JamesBrill/react-speech-recognition/blob/HEAD/docs/API.md#language-string
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+ # language = "en-US"
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+
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+ [UI]
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+ # Name of the app and chatbot.
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+ name = "Chatbot"
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+
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+ # Show the readme while the thread is empty.
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+ show_readme_as_default = true
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+
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+ # Description of the app and chatbot. This is used for HTML tags.
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+ # description = ""
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+
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+ # Large size content are by default collapsed for a cleaner ui
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+ default_collapse_content = true
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+
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+ # The default value for the expand messages settings.
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+ default_expand_messages = false
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+
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+ # Hide the chain of thought details from the user in the UI.
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+ hide_cot = false
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+
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+ # Link to your github repo. This will add a github button in the UI's header.
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+ # github = ""
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+
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+ # Specify a CSS file that can be used to customize the user interface.
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+ # The CSS file can be served from the public directory or via an external link.
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+ # custom_css = "/public/test.css"
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+
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+ # Specify a Javascript file that can be used to customize the user interface.
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+ # The Javascript file can be served from the public directory.
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+ # custom_js = "/public/test.js"
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+
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+ # Specify a custom font url.
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+ # custom_font = "https://fonts.googleapis.com/css2?family=Inter:wght@400;500;700&display=swap"
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+
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+ # Override default MUI light theme. (Check theme.ts)
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+ [UI.theme]
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+ #font_family = "Inter, sans-serif"
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+ [UI.theme.light]
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+ #background = "#FAFAFA"
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+ #paper = "#FFFFFF"
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+
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+ [UI.theme.light.primary]
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+ #main = "#F80061"
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+ #dark = "#980039"
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+ #light = "#FFE7EB"
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+
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+ # Override default MUI dark theme. (Check theme.ts)
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+ [UI.theme.dark]
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+ #background = "#FAFAFA"
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+ #paper = "#FFFFFF"
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+
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+ [UI.theme.dark.primary]
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+ #main = "#F80061"
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+ #dark = "#980039"
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+ #light = "#FFE7EB"
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+
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+
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+ [meta]
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+ generated_by = "1.0.401"
Dockerfile ADDED
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+ FROM python:3.9
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+ RUN useradd -m -u 1000 user
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+ USER user
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+ ENV HOME=/home/user \
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+ PATH=/home/user/.local/bin:$PATH
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+ WORKDIR $HOME/app
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+ COPY --chown=user . $HOME/app
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+ COPY ./requirements.txt ~/app/requirements.txt
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+ RUN pip install -r requirements.txt
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+ COPY . .
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+ CMD ["chainlit", "run", "app.py", "--port", "7860"]
README.md CHANGED
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- ---
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- license: mit
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- title: Finance Knowledge Bot
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ RAG use-case implementation using Llamaindex
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+
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+ Supercharge your RAG pipeline with the following:
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+
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+ - Framework -> [Llamaindex](https://docs.llamaindex.ai/en/stable/index.html)
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+ - Loader -> [SimpleDirectoryLoader](https://docs.llamaindex.ai/en/stable/module_guides/loading/simpledirectoryreader.html)
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+ - Chunking -> [Semantic Chunking](https://docs.llamaindex.ai/en/stable/examples/node_parsers/semantic_chunking.html)
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+ - Embeddings -> [Gemini Embeddings](https://docs.llamaindex.ai/en/stable/examples/node_parsers/semantic_chunking.html)
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+ - Reranking -> [Cohere Rerank Model](https://docs.llamaindex.ai/en/stable/examples/node_postprocessor/CohereRerank.html)
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+ - LLM -> [Groq Mistral](https://docs.llamaindex.ai/en/stable/examples/llm/groq.html#groq)
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+
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+ For index creation follow notebook file ```rag.ipynb```
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+
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+ To run application:
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+
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+ ```
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+ pip install -r requirements.txt
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+ chainlit run app.py
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+ ```
app.py ADDED
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+ from llama_index.core import StorageContext, ServiceContext, load_index_from_storage
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+ from llama_index.core.callbacks.base import CallbackManager
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+ from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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+ from llama_index.llms.groq import Groq
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+ import os
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+ from dotenv import load_dotenv
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+ load_dotenv()
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+ import chainlit as cl
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+
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+ GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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+
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+ @cl.on_chat_start
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+ async def factory():
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+ storage_context = StorageContext.from_defaults(persist_dir="./storage_mini")
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+
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+ embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
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+
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+ llm = Groq(model="llama3-70b-8192", api_key=GROQ_API_KEY)
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+
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+ service_context = ServiceContext.from_defaults(embed_model=embed_model, llm=llm,
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+ callback_manager=CallbackManager([cl.LlamaIndexCallbackHandler()]),
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+ )
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+
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+ index = load_index_from_storage(storage_context, service_context=service_context)
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+
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+ chat_engine = index.as_chat_engine(service_context=service_context)
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+
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+ cl.user_session.set("chat_engine", chat_engine)
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+
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+ @cl.on_message
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+ async def main(message: cl.Message):
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+ chat_engine = cl.user_session.get("chat_engine")
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+ response = await cl.make_async(chat_engine.chat)(message.content)
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+
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+ response_message = cl.Message(content="")
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+
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+ for token in response.response:
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+ await response_message.stream_token(token=token)
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+
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+ await response_message.send()
chainlit.md ADDED
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+ # Welcome to Chainlit! 🚀🤖
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+
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+ 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.
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+
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+ ## Useful Links 🔗
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+
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+ - **Documentation:** Get started with our comprehensive [Chainlit Documentation](https://docs.chainlit.io) 📚
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+ - **Discord Community:** Join our friendly [Chainlit Discord](https://discord.gg/k73SQ3FyUh) to ask questions, share your projects, and connect with other developers! 💬
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+
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+ We can't wait to see what you create with Chainlit! Happy coding! 💻😊
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+
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+ ## Welcome screen
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+
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+ 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.
requirements.txt ADDED
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+ llama-index==0.10.18
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+ llama-index-llms-groq==0.1.3
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+ chainlit==1.0.401
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+ groq==0.4.2
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+ python-dotenv==1.0.1
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+ llama-index-embeddings-gemini==0.1.4
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+ llama-index-postprocessor-cohere-rerank==0.1.2
storage_mini/default__vector_store.json ADDED
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storage_mini/docstore.json ADDED
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storage_mini/index_store.json ADDED
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