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new(gpt.gblib): PDF opener.

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This commit is contained in:
Rodrigo Rodriguez 2024-04-14 12:37:07 -03:00
parent 462297dc75
commit 51107fcd76
1 changed files with 42 additions and 67 deletions
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67
packages/gpt.gblib/services/ChatServices.ts
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@ -99,19 +99,18 @@ export class GBLLMOutputParser extends
lc_namespace = ["langchain", "output_parsers"];
private toolChain: RunnableSequence
private documentChain: RunnableSequence;
private min;
constructor(min, toolChain: RunnableSequence, documentChain: RunnableSequence) {
super();
this.min = min;
this.toolChain = toolChain;
}
async parseResult(
llmOutputs: ChatGeneration[] | Generation[]
): Promise<ExpectedOutput> {
if (!llmOutputs.length) {
throw new OutputParserException(
"Output parser did not receive any generations."
@ -129,33 +128,20 @@ export class GBLLMOutputParser extends
result = llmOutputs[0].text;
}
const naiveJSONFromText = (text) => {
const match = text.match(/\{[\s\S]*\}/);
if (!match) return null;
let res;
try {
return {metadata: JSON.parse(match[0]),
text: text.replace(match, '')};
result = result.replace(/\\n/g, '');
res = JSON.parse(result);
} catch {
return null;
return result;
}
};
if (result) {
const res = naiveJSONFromText(result);
if (res) {
const {metadata, text} = res;
const {url} = await ChatServices.pdfPageAsImage(this.min, metadata.file,
metadata.page);
result = `![alt text](${url})
let { file, page, text } = res;
const { url } = await ChatServices.pdfPageAsImage(this.min, file, page);
text = `![alt text](${url})
${text}`;
return [ result, metadata.file, metadata.page];
}
}
return result;
return {text, file, page};
}
}
@ -167,6 +153,7 @@ export class ChatServices {
const localName = Path.join('work', gbaiName, 'docs', filename);
// Converts the PDF to PNG.
GBLogEx.info(min, `Converting ${filename}, page: ${pageNumber}...`);
const pngPages: PngPageOutput[] = await pdfToPng(localName, {
disableFontFace: true,
@ -216,7 +203,6 @@ export class ChatServices {
return output;
}
private static async findPageForText(pdfPath, searchText) {
const data = new Uint8Array(Fs.readFileSync(pdfPath));
const pdf = await getDocument({ data }).promise;
@ -231,7 +217,7 @@ export class ChatServices {
if (text.includes(searchText)) return i;
}
return -1; // Texto não encontrado
return -1;
}
/**
@ -325,12 +311,19 @@ export class ChatServices {
`
This is a segmented context.
VERY IMPORTANT: When responding, ALWAYS, I said, You must always both include the text and the following information at the end of your message as a VALID standard JSON, just after the text answer: 'file' indicating the PDF filename and 'page' indicating the page number. Example JSON format: "file": "filename.pdf", "page": 3, return valid JSON with brackets. Avoid explaining the context directly to the user; instead, refer to the document source. Double check if the output JSON has brackets.
\n\n{context}\n\n
And based on \n\n{chat_history}\n\n
rephrase the response to the user using the aforementioned context. If you're unsure of the answer, utilize any relevant context provided to answer the question effectively. Don´t output MD images tags url previously shown.
VERY IMPORTANT: ALWAYS return VALID standard JSON with the folowing structure: 'text' as answer,
'file' indicating the PDF filename and 'page' indicating the page number.
Example JSON format: "text": "this is the answer, anything LLM output as text answer shoud be here.",
"file": "filename.pdf", "page": 3,
return valid JSON with brackets. Avoid explaining the context directly
to the user; instead, refer to the document source.
Double check if the output is a valid JSON with brackets. all fields are required: text, file, page.
`
),
new MessagesPlaceholder("chat_history"),
@ -377,20 +370,6 @@ export class ChatServices {
new GBLLMOutputParser(min, null, null)
]);
const conversationalQaChain = RunnableSequence.from([
{
question: (i: { question: string }) => i.question,
chat_history: async () => {
const { chat_history } = await memory.loadMemoryVariables({});
return chat_history;
},
},
questionGeneratorTemplate,
modelWithTools,
new GBLLMOutputParser(min, callToolChain, docsContext?.docstore?._docs.length > 0 ? combineDocumentsChain : null),
new StringOutputParser()
]);
const conversationalToolChain = RunnableSequence.from([
{
question: (i: { question: string }) => i.question,
@ -422,7 +401,7 @@ export class ChatServices {
}
else if (LLMMode === "document") {
[text, file, page] = await combineDocumentsChain.invoke(question);
const {text, file, page} = await combineDocumentsChain.invoke(question);
result = text;
} else if (LLMMode === "function") {
@ -440,7 +419,6 @@ export class ChatServices {
GBLog.info(`Invalid Answer Mode in Config.xlsx: ${LLMMode}.`);
}
await memory.saveContext(
{
input: question,
@ -452,8 +430,6 @@ export class ChatServices {
GBLog.info(`GPT Result: ${result.toString()}`);
return { answer: result.toString(), file, questionId: 0, page };
}
private static getToolsAsText(tools) {
@ -483,7 +459,6 @@ export class ChatServices {
funcObj.schema = eval(jsonSchemaToZod(funcObj.parameters));
functions.push(new DynamicStructuredTool(funcObj));
}
}
});