more requirements

.gitignore

@@ -0,0 +1 @@
+.streamlit/

app.py

@@ -1,17 +1,57 @@
 import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 from langchain.memory import ConversationBufferMemory
 from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
+from langchain.embeddings import VoyageEmbeddings
+from langchain.vectorstores import SupabaseVectorStore
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
+from st_supabase_connection import SupabaseConnection
 
 msgs = StreamlitChatMessageHistory()
 memory = ConversationBufferMemory(memory_key="history", chat_memory=msgs)
 
-hf = HuggingFacePipeline.from_model_id(
-    model_id="gpt2",
-    task="text-generation",
-    pipeline_kwargs={"max_new_tokens": 10},
+supabase_client = st.connection(
+    name="orbgpt",
+    type=SupabaseConnection,
+    ttl=None,
 )
 
+embeddings = VoyageEmbeddings(model="voyage-01")
+vector_store = SupabaseVectorStore(
+    embedding=embeddings,
+    client=supabase_client,
+    table_name="documents",
+    query_name="match_documents",
+)
+
+
+model_path = "01-ai/Yi-6B-Chat-8bits"
+tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False)
+model = AutoModelForCausalLM.from_pretrained(
+    model_path, device_map="auto", torch_dtype="auto"
+).eval()
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_new_tokens=10,
+    use_fast=False,
+)
+hf = HuggingFacePipeline(pipeline=pipe)
+
+template = """Question: {question}
+
+Answer: Let's think step by step."""
+prompt = PromptTemplate.from_template(template)
+
+chain = prompt | hf
+
+question = "What is electroencephalography?"
+
+st.text(chain.invoke({"question": question}))
+
 st.title("🪩🤖")
 
 if len(msgs.messages) == 0:

requirements.txt

@@ -1,4 +1,10 @@
 streamlit
-torch
 transformers
-langchain
+torch
+sentencepiece
+accelerate
+auto-gptq
+optimum
+langchain
+supabase
+st-supabase-connection