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Merge pull request #117 from unkwnownGriot/no-api-key-error500-fixed

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Fix the servor 500 error and show error message to client
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Alex 2023-02-23 18:08:23 +00:00 committed by GitHub
commit 918e1b3bf6
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5 changed files with 161 additions and 102 deletions
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2
.gitignore vendored
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@ -108,7 +108,7 @@ venv/
ENV/ ENV/
env.bak/ env.bak/
venv.bak/ venv.bak/
.flaskenv
# Spyder project settings # Spyder project settings
.spyderproject .spyderproject
.spyproject .spyproject

103
application/app.py
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@ -9,7 +9,7 @@ from langchain import OpenAI, VectorDBQA, HuggingFaceHub, Cohere
from langchain.chains.question_answering import load_qa_chain from langchain.chains.question_answering import load_qa_chain
from langchain.embeddings import OpenAIEmbeddings, HuggingFaceHubEmbeddings, CohereEmbeddings, HuggingFaceInstructEmbeddings from langchain.embeddings import OpenAIEmbeddings, HuggingFaceHubEmbeddings, CohereEmbeddings, HuggingFaceInstructEmbeddings
from langchain.prompts import PromptTemplate from langchain.prompts import PromptTemplate
from error import bad_request
# os.environ["LANGCHAIN_HANDLER"] = "langchain" # os.environ["LANGCHAIN_HANDLER"] = "langchain"
if os.getenv("LLM_NAME") is not None: if os.getenv("LLM_NAME") is not None:
@ -74,6 +74,7 @@ def api_answer():
data = request.get_json() data = request.get_json()
question = data["question"] question = data["question"]
history = data["history"] history = data["history"]
print('-'*5)
if not api_key_set: if not api_key_set:
api_key = data["api_key"] api_key = data["api_key"]
else: else:
@ -83,62 +84,68 @@ def api_answer():
else: else:
embeddings_key = os.getenv("EMBEDDINGS_KEY") embeddings_key = os.getenv("EMBEDDINGS_KEY")
# use try and except to check for exception
try:
# check if the vectorstore is set # check if the vectorstore is set
if "active_docs" in data: if "active_docs" in data:
vectorstore = "vectors/" + data["active_docs"] vectorstore = "vectors/" + data["active_docs"]
if data['active_docs'] == "default": if data['active_docs'] == "default":
vectorstore = ""
else:
vectorstore = "" vectorstore = ""
else:
vectorstore = ""
# loading the index and the store and the prompt template # loading the index and the store and the prompt template
# Note if you have used other embeddings than OpenAI, you need to change the embeddings # Note if you have used other embeddings than OpenAI, you need to change the embeddings
if embeddings_choice == "openai_text-embedding-ada-002": if embeddings_choice == "openai_text-embedding-ada-002":
docsearch = FAISS.load_local(vectorstore, OpenAIEmbeddings(openai_api_key=embeddings_key)) docsearch = FAISS.load_local(vectorstore, OpenAIEmbeddings(openai_api_key=embeddings_key))
elif embeddings_choice == "huggingface_sentence-transformers/all-mpnet-base-v2": elif embeddings_choice == "huggingface_sentence-transformers/all-mpnet-base-v2":
docsearch = FAISS.load_local(vectorstore, HuggingFaceHubEmbeddings()) docsearch = FAISS.load_local(vectorstore, HuggingFaceHubEmbeddings())
elif embeddings_choice == "huggingface_hkunlp/instructor-large": elif embeddings_choice == "huggingface_hkunlp/instructor-large":
docsearch = FAISS.load_local(vectorstore, HuggingFaceInstructEmbeddings()) docsearch = FAISS.load_local(vectorstore, HuggingFaceInstructEmbeddings())
elif embeddings_choice == "cohere_medium": elif embeddings_choice == "cohere_medium":
docsearch = FAISS.load_local(vectorstore, CohereEmbeddings(cohere_api_key=embeddings_key)) docsearch = FAISS.load_local(vectorstore, CohereEmbeddings(cohere_api_key=embeddings_key))
# create a prompt template # create a prompt template
if history: if history:
history = json.loads(history) history = json.loads(history)
template_temp = template_hist.replace("{historyquestion}", history[0]).replace("{historyanswer}", history[1]) template_temp = template_hist.replace("{historyquestion}", history[0]).replace("{historyanswer}", history[1])
c_prompt = PromptTemplate(input_variables=["summaries", "question"], template=template_temp, template_format="jinja2") c_prompt = PromptTemplate(input_variables=["summaries", "question"], template=template_temp, template_format="jinja2")
else: else:
c_prompt = PromptTemplate(input_variables=["summaries", "question"], template=template, template_format="jinja2") c_prompt = PromptTemplate(input_variables=["summaries", "question"], template=template, template_format="jinja2")
if llm_choice == "openai": if llm_choice == "openai":
llm = OpenAI(openai_api_key=api_key, temperature=0) llm = OpenAI(openai_api_key=api_key, temperature=0)
elif llm_choice == "manifest": elif llm_choice == "manifest":
llm = ManifestWrapper(client=manifest, llm_kwargs={"temperature": 0.001, "max_tokens": 2048}) llm = ManifestWrapper(client=manifest, llm_kwargs={"temperature": 0.001, "max_tokens": 2048})
elif llm_choice == "huggingface": elif llm_choice == "huggingface":
llm = HuggingFaceHub(repo_id="bigscience/bloom", huggingfacehub_api_token=api_key) llm = HuggingFaceHub(repo_id="bigscience/bloom", huggingfacehub_api_token=api_key)
elif llm_choice == "cohere": elif llm_choice == "cohere":
llm = Cohere(model="command-xlarge-nightly", cohere_api_key=api_key) llm = Cohere(model="command-xlarge-nightly", cohere_api_key=api_key)
qa_chain = load_qa_chain(llm=llm, chain_type="map_reduce", qa_chain = load_qa_chain(llm=llm, chain_type="map_reduce",
combine_prompt=c_prompt) combine_prompt=c_prompt)
chain = VectorDBQA(combine_documents_chain=qa_chain, vectorstore=docsearch, k=4) chain = VectorDBQA(combine_documents_chain=qa_chain, vectorstore=docsearch, k=4)
# fetch the answer
result = chain({"query": question})
print(result)
# some formatting for the frontend # fetch the answer
result['answer'] = result['result'] result = chain({"query": question})
result['answer'] = result['answer'].replace("\\n", "<br>") print(result)
result['answer'] = result['answer'].replace("SOURCES:", "")
# mock result # some formatting for the frontend
# result = { result['answer'] = result['result']
# "answer": "The answer is 42", result['answer'] = result['answer'].replace("\\n", "<br>")
# "sources": ["https://en.wikipedia.org/wiki/42_(number)", "https://en.wikipedia.org/wiki/42_(number)"] result['answer'] = result['answer'].replace("SOURCES:", "")
# } # mock result
return result # result = {
# "answer": "The answer is 42",
# "sources": ["https://en.wikipedia.org/wiki/42_(number)", "https://en.wikipedia.org/wiki/42_(number)"]
# }
return result
except Exception as e:
print(str(e))
return bad_request(500,str(e))
@app.route("/api/docs_check", methods=["POST"]) @app.route("/api/docs_check", methods=["POST"])

13
application/error.py Normal file
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@ -0,0 +1,13 @@
from flask import jsonify
from werkzeug.http import HTTP_STATUS_CODES
def response_error(code_status,message=None):
payload = {'error':HTTP_STATUS_CODES.get(code_status,"something went wrong")}
if message:
payload['message'] = message
response = jsonify(payload)
response.status_code = code_status
return response
def bad_request(status_code=400,message=''):
return response_error(code_status=status_code,message=message)

118
application/static/src/chat.js
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@ -1,55 +1,73 @@
var el = document.getElementById('message-form'); var form = document.getElementById('message-form');
if (el) { var errorModal = document.getElementById('error-alert')
el.addEventListener("submit", function (event) { document.getElementById('close').addEventListener('click',()=>{
console.log("submitting") errorModal.classList.toggle('hidden')
event.preventDefault() })
var message = document.getElementById("message-input").value;
msg_html = '<div class="bg-blue-500 text-white p-2 rounded-lg mb-2 self-end"><p class="text-sm">'
msg_html += message function submitForm(event){
msg_html += '</p></div>' event.preventDefault()
document.getElementById("messages").innerHTML += msg_html; var message = document.getElementById("message-input").value;
let chatWindow = document.getElementById("messages-container"); console.log(message.length)
chatWindow.scrollTop = chatWindow.scrollHeight; if(message.length === 0){
document.getElementById("message-input").value = ""; return
document.getElementById("button-submit").innerHTML = '<i class="fa fa-circle-o-notch fa-spin"></i> Thinking...'; }
document.getElementById("button-submit").disabled = true; msg_html = '<div class="bg-blue-500 text-white p-2 rounded-lg mb-2 self-end"><p class="text-sm">'
if (localStorage.getItem('activeDocs') == null) { msg_html += message
localStorage.setItem('activeDocs', 'default') msg_html += '</p></div>'
} document.getElementById("messages").innerHTML += msg_html;
let chatWindow = document.getElementById("messages-container");
chatWindow.scrollTop = chatWindow.scrollHeight;
document.getElementById("message-input").value = "";
document.getElementById("button-submit").innerHTML = '<i class="fa fa-circle-o-notch fa-spin"></i> Thinking...';
document.getElementById("button-submit").disabled = true;
if (localStorage.getItem('activeDocs') == null) {
localStorage.setItem('activeDocs', 'default')
}
fetch('/api/answer', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({question: message,
api_key: localStorage.getItem('apiKey'),
embeddings_key: localStorage.getItem('apiKey'),
history: localStorage.getItem('chatHistory'),
active_docs: localStorage.getItem('activeDocs')}),
}).then((response)=> response.json())
.then(data => {
console.log('Success:', data);
if(data.error){
document.getElementById('text-error').textContent = `Error : ${JSON.stringify(data.message)}`
errorModal.classList.toggle('hidden')
}
if(data.answer){
msg_html = '<div class="bg-indigo-500 text-white p-2 rounded-lg mb-2 self-start"><code class="text-sm">'
msg_html += data.answer
msg_html += '</code></div>'
document.getElementById("messages").innerHTML += msg_html;
let chatWindow = document.getElementById("messages-container");
chatWindow.scrollTop = chatWindow.scrollHeight;
}
document.getElementById("button-submit").innerHTML = 'Send';
document.getElementById("button-submit").disabled = false;
let chatHistory = [message, data.answer || ''];
localStorage.setItem('chatHistory', JSON.stringify(chatHistory));
fetch('/api/answer', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({question: message,
api_key: localStorage.getItem('apiKey'),
embeddings_key: localStorage.getItem('apiKey'),
history: localStorage.getItem('chatHistory'),
active_docs: localStorage.getItem('activeDocs')}),
}) })
.then(response => response.json()) .catch((error) => {
.then(data => { console.error('Error:', error);
console.log('Success:', data); // console.log(error);
msg_html = '<div class="bg-indigo-500 text-white p-2 rounded-lg mb-2 self-start"><code class="text-sm">' // document.getElementById("button-submit").innerHTML = 'Send';
msg_html += data.answer // document.getElementById("button-submit").disabled = false;
msg_html += '</code></div>'
document.getElementById("messages").innerHTML += msg_html;
let chatWindow = document.getElementById("messages-container");
chatWindow.scrollTop = chatWindow.scrollHeight;
document.getElementById("button-submit").innerHTML = 'Send';
document.getElementById("button-submit").disabled = false;
let chatHistory = [message, data.answer];
localStorage.setItem('chatHistory', JSON.stringify(chatHistory));
})
.catch((error) => {
console.error('Error:', error);
console.log(error);
document.getElementById("button-submit").innerHTML = 'Send';
document.getElementById("button-submit").disabled = false;
});
});
});
} }
window.addEventListener('submit',submitForm)

23
application/templates/index.html
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@ -28,6 +28,17 @@
{% endif %} {% endif %}
</div> </div>
</header> </header>
<!-- Alert Info -->
<div class="border flex justify-between
w-auto px-4 py-3 rounded relative
hidden" style="background-color: rgb(197, 51, 51);color: white;" id="error-alert" role="alert">
<span class="block sm:inline" id="text-error"></span>
<strong class="text-xl align-center alert-del" style="cursor: pointer;" id="close">&times;</strong>
</div>
<div class="lg:flex ml-2 mr-2"> <div class="lg:flex ml-2 mr-2">
<div class="lg:w-3/4 min-h-screen max-h-screen"> <div class="lg:w-3/4 min-h-screen max-h-screen">
<div class="w-full flex flex-col h-5/6"> <div class="w-full flex flex-col h-5/6">
@ -60,6 +71,8 @@ This will return a new DataFrame with all the columns from both tables, and only
</div> </div>
</div> </div>
</div> </div>
<div class="lg:w-1/4 p-2 sm:max-lg:hidden"> <div class="lg:w-1/4 p-2 sm:max-lg:hidden">
@ -78,10 +91,15 @@ This will return a new DataFrame with all the columns from both tables, and only
<div class="flex items-center justify-center h-full"> <div class="flex items-center justify-center h-full">
</div> </div>
{% if not api_key_set %} {% if not api_key_set %}
<div class="fixed z-10 overflow-y-auto top-0 w-full left-0 hidden" id="modal">
<div class="fixed z-10 overflow-y-auto top-0 w-full left-0 show" id="modal">
<div class="flex items-center justify-center min-height-100vh pt-4 px-4 pb-20 text-center sm:block sm:p-0"> <div class="flex items-center justify-center min-height-100vh pt-4 px-4 pb-20 text-center sm:block sm:p-0">
<div class="fixed inset-0 transition-opacity"> <div class="fixed inset-0 transition-opacity">
<div class="absolute inset-0 bg-gray-900 opacity-75" /> <div class="absolute inset-0 bg-gray-900 opacity-75" />
@ -105,6 +123,9 @@ This will return a new DataFrame with all the columns from both tables, and only
</div> </div>
</div> </div>
{% endif %} {% endif %}
<script> <script>
function docsIndex() { function docsIndex() {
// loads latest index from https://raw.githubusercontent.com/arc53/DocsHUB/main/combined.json // loads latest index from https://raw.githubusercontent.com/arc53/DocsHUB/main/combined.json