jketreno/backstory
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Just checking in

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This commit is contained in:
James Ketr 2025-04-07 23:51:46 -07:00
parent ba124c1673
commit b3630ebba4
6 changed files with 37 additions and 60 deletions
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9
frontend/src/App.css
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@ -50,6 +50,15 @@ div {
margin: 0 auto;
}
.DocBox {
display: flex;
flex-direction: column;
flex-grow: 1;
max-width: 2048px;
margin: 0 auto;
}
.Controls {
display: flex;
background-color: #F5F5F5;

4
frontend/src/App.tsx
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@ -47,9 +47,7 @@ import '@fontsource/roboto/700.css';
const welcomeMarkdown = `
# Welcome to Backstory
Backstory was written by James Ketrenos in order to provide answers to questions potential employers may have about his work history. In addition to being a RAG enabled expert system, the LLM has access to real-time data.
You can ask things like:
Backstory was written by James Ketrenos in order to provide answers to questions potential employers may have about his work history. In addition to being a RAG enabled expert system, the LLM has access to real-time data. You can ask things like:
<ChatQuery text="What is James Ketrenos' work history?"/>
<ChatQuery text="What programming languages has James used?"/>

17
frontend/src/DocumentViewer.tsx
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@ -136,7 +136,7 @@ const DocumentViewer: React.FC<DocumentViewerProps> = ({generateResume, resume,
value={jobDescription}
onChange={(e) => setJobDescription(e.target.value)}
onKeyDown={handleKeyPress}
placeholder="Enter a job description, then click Generate..."
placeholder="Paste a job description (or URL that resolves to one), then click Generate..."
/>
</Document>
<Button onClick={(e: any) => { triggerGeneration(jobDescription); }}>Generate</Button>
@ -160,9 +160,9 @@ const DocumentViewer: React.FC<DocumentViewerProps> = ({generateResume, resume,
<Typography>Generating resume...</Typography>
</Box>
</>}
<Card sx={{ display: "flex", flexGrow: 1, overflow: "auto", minHeight: "fit-content", p: 1 }}>
{resume !== undefined
? <Typography><b>NOTE:</b> As with all LLMs, hallucination is always a possibility. If this resume seems too good to be true, expand the <b>LLM information for this query</b> section and click the links to the relavent RAG source document to read the details. Or go back to 'Backstory' and ask a question.</Typography>
<Card sx={{ display: "flex", overflow: "auto", minHeight: "fit-content", p: 1 }}>
{resume !== undefined || processing == true
? <Typography><b>NOTE:</b> As with all LLMs, hallucination is always a possibility. If the generated resume seems too good to be true, expand the <b>LLM information for this query</b> section (at the end of the resume) and click the links in the <b>Top RAG</b> matches to view the relavent RAG source document to read the details. Or go back to 'Backstory' and ask a question.</Typography>
: <Typography>Once you click <b>Generate</b> under the <b>Job Description</b>, a resume will be generated based on the user's RAG content and the job description.</Typography>
}
</Card>
@ -193,7 +193,7 @@ const DocumentViewer: React.FC<DocumentViewerProps> = ({generateResume, resume,
value={jobDescription}
onChange={(e) => setJobDescription(e.target.value)}
onKeyDown={handleKeyPress}
placeholder="Enter a job description, then click Generate..."
placeholder="Paste a job description (or URL that resolves to one), then click Generate..."
/>
</Document>
<Tooltip title="Generate">
@ -217,7 +217,12 @@ const DocumentViewer: React.FC<DocumentViewerProps> = ({generateResume, resume,
data-testid="loader"
/>
</Box>
{resume !== undefined && <Card sx={{ display: "flex", flexGrow: 1, overflow: "auto", minHeight: "fit-content", p: 1 }}><Typography><b>NOTE:</b> As with all LLMs, hallucination is always a possibility. If this resume seems too good to be true, expand the <b>LLM information for this query</b> section and click the links to the relavent RAG source document to read the details. Or go back to 'Backstory' and ask a question.</Typography></Card>}
<Card sx={{ display: "flex", overflow: "auto", minHeight: "fit-content", p: 1 }}>
{resume !== undefined || processing == true
? <Typography><b>NOTE:</b> As with all LLMs, hallucination is always a possibility. If the generated resume seems too good to be true, expand the <b>LLM information for this query</b> section (at the end of the resume) and click the links to the relavent RAG source document to read the details. Or go back to 'Backstory' and ask a question.</Typography>
: <Typography>Once you click <b>Generate</b> under the <b>Job Description</b>, a resume will be generated based on the user's RAG content and the job description.</Typography>
}
</Card>
</Box>
</Box>

6
frontend/src/MessageMeta.tsx
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@ -78,7 +78,7 @@ const MessageMeta = ({ metadata }: MessageMetaInterface) => {
</TableContainer>
{
metadata.tools !== undefined && metadata.tools.length !== 0 &&
<Accordion>
<Accordion sx={{ boxSizing: "border-box" }}>
<AccordionSummary expandIcon={<ExpandMoreIcon />}>
<Box sx={{ fontSize: "0.8rem" }}>
Tools queried
@ -88,10 +88,10 @@ const MessageMeta = ({ metadata }: MessageMetaInterface) => {
{metadata.tools.map((tool: any, index: number) => <Box key={index}>
{index !== 0 && <Divider />}
<Box sx={{ fontSize: "0.75rem", display: "flex", flexDirection: "column", mt: 0.5 }}>
<div style={{ display: "flex", paddingRight: "1rem", minWidth: "10rem", whiteSpace: "nowrap" }}>
<div style={{ display: "flex", paddingRight: "1rem", whiteSpace: "nowrap" }}>
{tool.tool}
</div>
<div style={{ display: "flex", padding: "3px", whiteSpace: "pre-wrap", flexGrow: 1, border: "1px solid #E0E0E0", maxHeight: "5rem", overflow: "auto" }}>{JSON.stringify(tool.result, null, 2)}</div>
<div style={{ display: "flex", padding: "3px", whiteSpace: "pre-wrap", flexGrow: 1, border: "1px solid #E0E0E0", wordBreak: "break-all", maxHeight: "5rem", overflow: "auto" }}>{JSON.stringify(tool.result, null, 2)}</div>
</Box>
</Box>)}
</AccordionDetails>

47
frontend/src/ResumeBuilder.tsx
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@ -203,7 +203,7 @@ const ResumeBuilder = ({scrollToBottom, isScrolledToBottom, setProcessing, proce
};
return (
<Box className="ChatBox">
<Box className="DocBox">
<Box className="Conversation">
<DocumentViewer sx={{
display: "flex",
@ -215,51 +215,6 @@ const ResumeBuilder = ({scrollToBottom, isScrolledToBottom, setProcessing, proce
</Box>
</Box>
);
return (<Box className="ChatBox">
<Box className="Conversation">
<TextField
variant="outlined"
fullWidth
multiline
rows="10"
type="text"
value={jobDescription}
onChange={(e) => setJobDescription(e.target.value)}
onKeyDown={handleKeyPress}
placeholder="Enter the job description.."
id="JobDescriptionInput"
/>
<Tooltip title="Generate">
<Button sx={{ m: 1, gap: 1 }} variant="contained" onClick={() => { generateResume(jobDescription); }}>Generate<SendIcon /></Button>
</Tooltip>
<Box sx={{
display: "flex",
flexDirection: "column",
alignItems: "center",
justifyContent: "center",
mb: 1
}}>
<PropagateLoader
size="10px"
loading={processing}
aria-label="Loading Spinner"
data-testid="loader"
/>
{processing === true && countdown > 0 && (
<Box
sx={{
pt: 1,
fontSize: "0.7rem",
color: "darkgrey"
}}
>Estimated response time: {countdown}s</Box>
)}
{generateStatus && <Message isFullWidth={true} message={generateStatus} />}
{/* {resume && <Message isFullWidth={true} message={resume} />} */}
</Box>
</Box>
</Box>);
}

12
src/server.py
View File

@ -137,7 +137,7 @@ When answering queries, follow these steps:
1. First analyze the query to determine if real-time information might be helpful
2. Even when [{context_tag}] is provided, consider whether the tools would provide more current or comprehensive information
3. Use the provided tools whenever they would enhance your response, regardless of whether context is also available
4. When presenting information like weather forecasts, include relevant emojis immediately before the corresponding text. For example, for a sunny day, say \"☀️ Sunny\" or if the forecast says there will be \"rain showers, say \"🌧️ Rain showers\". Use this mapping for weather emojis: Sunny: ☀️, Cloudy: ☁️, Rainy: 🌧️, Snowy: ❄️
4. When presenting weather forecasts, include relevant emojis immediately before the corresponding text. For example, for a sunny day, say \"☀️ Sunny\" or if the forecast says there will be \"rain showers, say \"🌧️ Rain showers\". Use this mapping for weather emojis: Sunny: ☀️, Cloudy: ☁️, Rainy: 🌧️, Snowy: ❄️
4. When both [{context_tag}] and tool outputs are relevant, synthesize information from both sources to provide the most complete answer
5. Always prioritize the most up-to-date and relevant information, whether it comes from [{context_tag}] or tools
6. If [{context_tag}] and tool outputs contain conflicting information, prefer the tool outputs as they likely represent more current data
@ -273,6 +273,9 @@ def is_valid_uuid(value):
def default_tools(tools):
return [{**tool, "enabled": True} for tool in tools]
def find_summarize_tool(tools):
return [{**tool, "enabled": True} for tool in tools if tool.get("name", "") == "AnalyzeSite"]
def llm_tools(tools):
return [tool for tool in tools if tool.get("enabled", False) == True]
@ -846,6 +849,13 @@ class WebServer:
yield {"status": "processing", "message": "Processing request...", "num_ctx": ctx_size}
# Use the async generator in an async for loop
#
# To support URL lookup:
#
# 1. Enable tools in a call to chat() with a simple prompt to invoke the tool to generate the summary if requested.
# 2. If not requested (no tool call,) abort the path
# 3. Otherwise, we know the URL was good and can use that URLs fetched content as context.
#
response = self.client.generate(model=self.model, system=system_generate_resume, prompt=content, options={ 'num_ctx': ctx_size })
metadata["eval_count"] += response['eval_count']
metadata["eval_duration"] += response['eval_duration']