jketreno/backstory
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Lots of improvements to tunables and feedback

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This commit is contained in:
James Ketr 2025-04-02 15:29:50 -07:00
parent 030806c34f
commit 847de136cf
2 changed files with 8 additions and 7 deletions
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10
src/ketr-chat/src/App.tsx
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@ -62,11 +62,11 @@ This LLM agent was built by James Ketrenos in order to provide answers to any qu
In addition to being a RAG enabled expert system, the LLM is configured with real-time access to weather, stocks, the current time, and can answer questions about the contents of a website. In addition to being a RAG enabled expert system, the LLM is configured with real-time access to weather, stocks, the current time, and can answer questions about the contents of a website.
You can ask things like: You can ask things like:
* <ChatQuery text="What are the headlines from CNBC?"/>
* <ChatQuery text="What is the weather where James is from?"/>
* <ChatQuery text="What is James Ketrenos' work history?"/> * <ChatQuery text="What is James Ketrenos' work history?"/>
* <ChatQuery text="What are the stock value of the most traded companies?"/>
* <ChatQuery text="What programming languages has James used?"/> * <ChatQuery text="What programming languages has James used?"/>
* <ChatQuery text="What is the weather where James is from?"/>
* <ChatQuery text="What are the headlines from CNBC?"/>
* <ChatQuery text="What are the stock value of the most traded companies?"/>
Or click the text above to submit that query. Or click the text above to submit that query.
@ -451,7 +451,7 @@ interface ChatQueryInterface {
} }
const ChatQuery = ({ text, submitQuery }: ChatQueryInterface) => { const ChatQuery = ({ text, submitQuery }: ChatQueryInterface) => {
return (<Button onClick={(e: any) => { console.log(text); submitQuery(text); }}>{text}</Button>); return (<Button size="small" variant="outlined" sx={{ mb: 1 }} onClick={(e: any) => { console.log(text); submitQuery(text); }}>{text}</Button>);
} }
const Message = ({ message, submitQuery }: MessageInterface) => { const Message = ({ message, submitQuery }: MessageInterface) => {
@ -532,7 +532,7 @@ const App = () => {
const [lastEvalTPS, setLastEvalTPS] = useState<number>(35); const [lastEvalTPS, setLastEvalTPS] = useState<number>(35);
const [lastPromptTPS, setLastPromptTPS] = useState<number>(430); const [lastPromptTPS, setLastPromptTPS] = useState<number>(430);
const [countdown, setCountdown] = useState<number>(0); const [countdown, setCountdown] = useState<number>(0);
const [messageHistoryLength, setMessageHistoryLength] = useState<number>(0); const [messageHistoryLength, setMessageHistoryLength] = useState<number>(5);
const timerRef = useRef<any>(null); const timerRef = useRef<any>(null);

5
src/server.py
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@ -144,6 +144,7 @@ LOG_LEVEL="info"
USE_TLS=False USE_TLS=False
WEB_HOST="0.0.0.0" WEB_HOST="0.0.0.0"
WEB_PORT=5000 WEB_PORT=5000
DEFAULT_HISTORY_LENGTH=5
# %% # %%
# Globals # Globals
@ -391,8 +392,8 @@ class WebServer:
context["context_tokens"] = round(len(str(context["system"])) * 3 / 4) # Estimate context usage context["context_tokens"] = round(len(str(context["system"])) * 3 / 4) # Estimate context usage
response["context_used"] = context["context_tokens"] response["context_used"] = context["context_tokens"]
case "message-history-length": case "message-history-length":
context["message_history_length"] = 5 context["message_history_length"] = DEFAULT_HISTORY_LENGTH
response["message-history-length"] = 5 response["message-history-length"] = DEFAULT_HISTORY_LENGTH
if not response: if not response:
return JSONResponse({ "error": "Usage: { reset: rags|tools|history|system-prompt}"}) return JSONResponse({ "error": "Usage: { reset: rags|tools|history|system-prompt}"})