Update app.py

app.py

@@ -1,62 +1,34 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
+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,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+demo = gr.ChatInterface(respond)
 
 
 if __name__ == "__main__":