Update app.py

app.py

@@ -13,9 +13,10 @@ import streamlit as st
 from io import StringIO
 from llama_index import Document
 from langchain.llms import Anthropic
+from langchain import HuggingFaceHub
 from langchain.chains import RetrievalQA
 from langchain.vectorstores import FAISS
-# from llama_index import LangchainEmbedding
+from llama_index import LangchainEmbedding
 from langchain.chat_models import ChatOpenAI
 from langchain.retrievers import SVMRetriever
 from langchain.chains import QAGenerationChain
@@ -135,12 +136,13 @@ def make_llm(model_version: str):
         chosen_model = ChatOpenAI(model_name=model_version, temperature=0)
     elif model_version == "anthropic":
         chosen_model = Anthropic(temperature=0)
+    elif model_version == "flan-t5-xl":
+        chosen_model = HuggingFaceHub(repo_id="google/flan-t5-xl",model_kwargs={"temperature":0,"max_length":64})
     else:
         st.warning("`Model version not recognized. Using gpt-3.5-turbo`", icon="⚠️")
         chosen_model = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0)
     return chosen_model
 
-
 @st.cache_resource
 def make_retriever(splits, retriever_type, embedding_type, num_neighbors, _llm):
     """
@@ -333,7 +335,12 @@ def run_evaluation(chain, retriever, eval_set, grade_prompt, retriever_type, num
 # Auth
 st.sidebar.image("img/diagnostic.jpg")
 
+oai_api_key = st.sidebar.text_input("`OpenAI API Key:`", type="password")
+ant_api_key = st.sidebar.text_input("`(Optional) Anthropic API Key:`", type="password")
+hf_api_key = st.sidebar.text_input("`(Optional) HuggingFace API Token:`", type="password")
+
 with st.sidebar.form("user_input"):
+
     num_eval_questions = st.select_slider("`Number of eval questions`",
                                           options=[1, 5, 10, 15, 20], value=5)
 
@@ -352,6 +359,8 @@ with st.sidebar.form("user_input"):
                      ("gpt-3.5-turbo",
                       "gpt-4",
                       "anthropic"),
+                      # Error raised by inference API: Model google/flan-t5-xl time out
+                      #"flan-t5-xl"),
                      index=0)
 
     retriever_type = st.radio("`Choose retriever`",
@@ -378,12 +387,14 @@ with st.sidebar.form("user_input"):
 
     submitted = st.form_submit_button("Submit evaluation")
 
+st.sidebar.write("`By:` [@RLanceMartin](https://twitter.com/RLanceMartin)")
+
 # App
 st.header("`Auto-evaluator`")
 st.info(
-    "`I am an evaluation tool for question-answering. Given documents, I will auto-generate a question-answer eval "
+    "`I am an evaluation tool for question-answering built on LangChain. Given documents, I will auto-generate a question-answer eval "
     "set and evaluate using the selected chain settings. Experiments with different configurations are logged. "
-    "Optionally, provide your own eval set (as a JSON, see docs/karpathy-pod-eval.json for an example).`")
+    "Optionally, provide your own eval set (as a JSON, see docs/karpathy-pod-eval.json for an example). If you don't have acess to GPT-4 or Anthropic, you can use our free hosted app here: https://autoevaluator.langchain.com/`")
 
 with st.form(key='file_inputs'):
     uploaded_file = st.file_uploader("`Please upload a file to evaluate (.txt or .pdf):` ",
@@ -396,7 +407,11 @@ with st.form(key='file_inputs'):
 
     submitted = st.form_submit_button("Submit files")
 
-if uploaded_file:
+if uploaded_file and oai_api_key:
+
+    os.environ["OPENAI_API_KEY"] = oai_api_key
+    os.environ["ANTHROPIC_API_KEY"] = ant_api_key
+    os.environ["HUGGINGFACEHUB_API_TOKEN"] = hf_api_key
 
     # Load docs
     text = load_docs(uploaded_file)
@@ -470,3 +485,7 @@ if uploaded_file:
                                              color='expt number',
                                              tooltip=['expt number', 'Retrieval score', 'Latency', 'Answer score'])
     st.altair_chart(c, use_container_width=True, theme="streamlit")
+
+else:
+
+    st.warning("Please input file and API key(s)!")