| import gradio as gr | |
| from paperqa import Docs, SentenceTransformerEmbeddingModel | |
| from langchain_anthropic import ChatAnthropic | |
| MODEL_NAME = "claude-3-5-sonnet-20240620" | |
| class MyChatAnthropic(ChatAnthropic): | |
| model_name = MODEL_NAME | |
| llm = MyChatAnthropic( | |
| model=MODEL_NAME, | |
| temperature=0.2, | |
| max_tokens=4096,) | |
| class MyEmb(SentenceTransformerEmbeddingModel): | |
| async def aembed_documents(self, texts): | |
| return await self.embed_documents(None, texts) | |
| emb = MyEmb(model_name="mixedbread-ai/mxbai-embed-large-v1") | |
| docs = Docs(llm="langchain", | |
| embedding="langchain", | |
| embedding_client=emb, | |
| client=llm) | |
| docs.max_concurrent = 1 | |
| docs.add('knowledge_extraction.csv', disable_check=True) | |
| def respond(message): | |
| return docs.query(messages).answer | |
| """ | |
| For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface | |
| """ | |
| demo = gr.ChatInterface(respond) | |
| if __name__ == "__main__": | |
| demo.launch() |