mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-07-01 09:29:38 +02:00
feat: add Docker entrypoints, LLM providers, pipeline hardening, workbench pages
Phase 9 — four parallel workstreams: - Stream A: 14 Docker entrypoints for containerized deployment - Stream B: Pipeline hardening — robust JSON parsing, LLM retry logic, consumer negative-ack, FalkorDB test import fix - Stream C: Azure OpenAI, OpenAI-compatible, and Mistral LLM providers - Stream D: Workbench Prompts, Token Cost, Knowledge Cores pages + Settings feature switches Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
elpresidank
parent
50fb311d2d
commit
c7eefee607
34 changed files with 1457 additions and 112 deletions
6
ts/entrypoints/chunker.mjs
Normal file
6
ts/entrypoints/chunker.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/chunking/service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/doc-embeddings-query.mjs
Normal file
6
ts/entrypoints/doc-embeddings-query.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/query/embeddings/qdrant-doc-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/document-rag.mjs
Normal file
6
ts/entrypoints/document-rag.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/retrieval/document-rag-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/extractor.mjs
Normal file
6
ts/entrypoints/extractor.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/extract/knowledge-extract.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/graph-embeddings-query.mjs
Normal file
6
ts/entrypoints/graph-embeddings-query.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/query/embeddings/qdrant-graph-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/graph-embeddings-store.mjs
Normal file
6
ts/entrypoints/graph-embeddings-store.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/storage/embeddings/graph-embeddings-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/graph-rag.mjs
Normal file
6
ts/entrypoints/graph-rag.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/retrieval/graph-rag-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/pdf-decoder.mjs
Normal file
6
ts/entrypoints/pdf-decoder.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/decoding/pdf-decoder.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/text-completion-azure-openai.mjs
Normal file
6
ts/entrypoints/text-completion-azure-openai.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/model/text-completion/azure-openai.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/text-completion-mistral.mjs
Normal file
6
ts/entrypoints/text-completion-mistral.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/model/text-completion/mistral.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/text-completion-ollama.mjs
Normal file
6
ts/entrypoints/text-completion-ollama.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/model/text-completion/ollama.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/text-completion-openai-compatible.mjs
Normal file
6
ts/entrypoints/text-completion-openai-compatible.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/model/text-completion/openai-compatible.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/triples-query.mjs
Normal file
6
ts/entrypoints/triples-query.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/query/triples/falkordb-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
6
ts/entrypoints/triples-store.mjs
Normal file
6
ts/entrypoints/triples-store.mjs
Normal file
|
|
@ -0,0 +1,6 @@
|
||||||
|
import("../packages/flow/dist/storage/triples/falkordb-service.js")
|
||||||
|
.then((m) => m.run())
|
||||||
|
.catch((err) => {
|
||||||
|
console.error(err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
|
|
@ -30,9 +30,13 @@
|
||||||
"doc-embeddings-query": "tsx scripts/run-doc-embeddings-query.ts",
|
"doc-embeddings-query": "tsx scripts/run-doc-embeddings-query.ts",
|
||||||
"graph-rag": "tsx scripts/run-graph-rag.ts",
|
"graph-rag": "tsx scripts/run-graph-rag.ts",
|
||||||
"document-rag": "tsx scripts/run-document-rag.ts",
|
"document-rag": "tsx scripts/run-document-rag.ts",
|
||||||
"create-test-pdf": "tsx scripts/create-test-pdf.ts"
|
"create-test-pdf": "tsx scripts/create-test-pdf.ts",
|
||||||
|
"llm:azure-openai": "tsx scripts/run-llm-azure-openai.ts",
|
||||||
|
"llm:openai-compat": "tsx scripts/run-llm-openai-compatible.ts",
|
||||||
|
"llm:mistral": "tsx scripts/run-llm-mistral.ts"
|
||||||
},
|
},
|
||||||
"devDependencies": {
|
"devDependencies": {
|
||||||
|
"falkordb": "^5.0.0",
|
||||||
"nats": "^2.29.0",
|
"nats": "^2.29.0",
|
||||||
"pdf-lib": "^1.17.1",
|
"pdf-lib": "^1.17.1",
|
||||||
"tsx": "^4.21.0",
|
"tsx": "^4.21.0",
|
||||||
|
|
|
||||||
|
|
@ -73,8 +73,9 @@ export class Consumer<T> {
|
||||||
|
|
||||||
private async consumeLoop(flow: FlowContext): Promise<void> {
|
private async consumeLoop(flow: FlowContext): Promise<void> {
|
||||||
while (this.running) {
|
while (this.running) {
|
||||||
|
let msg: Message<T> | null = null;
|
||||||
try {
|
try {
|
||||||
const msg = await this.backend!.receive(2000);
|
msg = await this.backend!.receive(2000);
|
||||||
if (!msg) continue;
|
if (!msg) continue;
|
||||||
|
|
||||||
await this.handleWithRetry(msg, flow);
|
await this.handleWithRetry(msg, flow);
|
||||||
|
|
@ -82,7 +83,13 @@ export class Consumer<T> {
|
||||||
} catch (err) {
|
} catch (err) {
|
||||||
if (!this.running) break;
|
if (!this.running) break;
|
||||||
console.error("[Consumer] Error in consume loop:", err);
|
console.error("[Consumer] Error in consume loop:", err);
|
||||||
// Brief pause before retry
|
if (msg) {
|
||||||
|
try {
|
||||||
|
await this.backend!.negativeAcknowledge(msg);
|
||||||
|
} catch (nakErr) {
|
||||||
|
console.error("[Consumer] Failed to nak message:", nakErr);
|
||||||
|
}
|
||||||
|
}
|
||||||
await sleep(1000);
|
await sleep(1000);
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
|
||||||
|
|
@ -18,6 +18,7 @@
|
||||||
"falkordb": "^5.0.0",
|
"falkordb": "^5.0.0",
|
||||||
"fastify": "^5.2.0",
|
"fastify": "^5.2.0",
|
||||||
"ollama": "^0.6.3",
|
"ollama": "^0.6.3",
|
||||||
|
"@mistralai/mistralai": "^1.0.0",
|
||||||
"openai": "^4.85.0",
|
"openai": "^4.85.0",
|
||||||
"pdfjs-dist": "^5.6.205"
|
"pdfjs-dist": "^5.6.205"
|
||||||
},
|
},
|
||||||
|
|
|
||||||
|
|
@ -93,64 +93,71 @@ export class KnowledgeExtractService extends FlowProcessor {
|
||||||
|
|
||||||
// --- Extract relationships ---
|
// --- Extract relationships ---
|
||||||
try {
|
try {
|
||||||
const relPrompt = await promptClient.request({
|
const relPrompt = await promptClient.request(
|
||||||
name: "extract-relationships",
|
{ name: "extract-relationships", variables: { text } },
|
||||||
variables: { text },
|
{ timeoutMs: 10_000 },
|
||||||
});
|
);
|
||||||
|
|
||||||
if (!relPrompt.error) {
|
if (!relPrompt.error) {
|
||||||
const relCompletion = await llmClient.request({
|
let relationships: ExtractedRelationship[] | null = null;
|
||||||
system: relPrompt.system,
|
for (let attempt = 0; attempt < 3; attempt++) {
|
||||||
prompt: relPrompt.prompt,
|
const relCompletion = await llmClient.request(
|
||||||
});
|
{ system: relPrompt.system, prompt: relPrompt.prompt },
|
||||||
|
{ timeoutMs: 120_000 },
|
||||||
|
);
|
||||||
|
|
||||||
if (!relCompletion.error && relCompletion.response) {
|
if (!relCompletion.error && relCompletion.response) {
|
||||||
const relationships = parseJsonResponse<ExtractedRelationship[]>(relCompletion.response);
|
relationships = parseJsonResponse<ExtractedRelationship[]>(relCompletion.response);
|
||||||
|
if (relationships) break;
|
||||||
if (relationships) {
|
console.warn(`[KnowledgeExtract] Relationship parse failed, attempt ${attempt + 1}/3`);
|
||||||
for (const rel of relationships) {
|
} else {
|
||||||
if (!rel.subject || !rel.predicate || !rel.object) continue;
|
break; // LLM error, don't retry
|
||||||
|
|
||||||
const subjectIri = toEntityIri(rel.subject);
|
|
||||||
const predicateIri = toEntityIri(rel.predicate);
|
|
||||||
const objectIri = toEntityIri(rel.object);
|
|
||||||
|
|
||||||
// Main relationship triple
|
|
||||||
allTriples.push({ s: subjectIri, p: predicateIri, o: objectIri });
|
|
||||||
|
|
||||||
// rdfs:label triples for each entity
|
|
||||||
allTriples.push({
|
|
||||||
s: subjectIri,
|
|
||||||
p: iriTerm(RDFS_LABEL),
|
|
||||||
o: literalTerm(rel.subject),
|
|
||||||
});
|
|
||||||
allTriples.push({
|
|
||||||
s: predicateIri,
|
|
||||||
p: iriTerm(RDFS_LABEL),
|
|
||||||
o: literalTerm(rel.predicate),
|
|
||||||
});
|
|
||||||
allTriples.push({
|
|
||||||
s: objectIri,
|
|
||||||
p: iriTerm(RDFS_LABEL),
|
|
||||||
o: literalTerm(rel.object),
|
|
||||||
});
|
|
||||||
|
|
||||||
// Entity contexts for subject and object
|
|
||||||
allEntityContexts.push({
|
|
||||||
entity: subjectIri,
|
|
||||||
context: text,
|
|
||||||
chunkId: msg.documentId,
|
|
||||||
});
|
|
||||||
allEntityContexts.push({
|
|
||||||
entity: objectIri,
|
|
||||||
context: text,
|
|
||||||
chunkId: msg.documentId,
|
|
||||||
});
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log(`[KnowledgeExtract] Extracted ${relationships.length} relationships`);
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
if (relationships) {
|
||||||
|
for (const rel of relationships) {
|
||||||
|
if (!rel.subject || !rel.predicate || !rel.object) continue;
|
||||||
|
|
||||||
|
const subjectIri = toEntityIri(rel.subject);
|
||||||
|
const predicateIri = toEntityIri(rel.predicate);
|
||||||
|
const objectIri = toEntityIri(rel.object);
|
||||||
|
|
||||||
|
// Main relationship triple
|
||||||
|
allTriples.push({ s: subjectIri, p: predicateIri, o: objectIri });
|
||||||
|
|
||||||
|
// rdfs:label triples for each entity
|
||||||
|
allTriples.push({
|
||||||
|
s: subjectIri,
|
||||||
|
p: iriTerm(RDFS_LABEL),
|
||||||
|
o: literalTerm(rel.subject),
|
||||||
|
});
|
||||||
|
allTriples.push({
|
||||||
|
s: predicateIri,
|
||||||
|
p: iriTerm(RDFS_LABEL),
|
||||||
|
o: literalTerm(rel.predicate),
|
||||||
|
});
|
||||||
|
allTriples.push({
|
||||||
|
s: objectIri,
|
||||||
|
p: iriTerm(RDFS_LABEL),
|
||||||
|
o: literalTerm(rel.object),
|
||||||
|
});
|
||||||
|
|
||||||
|
// Entity contexts for subject and object
|
||||||
|
allEntityContexts.push({
|
||||||
|
entity: subjectIri,
|
||||||
|
context: text,
|
||||||
|
chunkId: msg.documentId,
|
||||||
|
});
|
||||||
|
allEntityContexts.push({
|
||||||
|
entity: objectIri,
|
||||||
|
context: text,
|
||||||
|
chunkId: msg.documentId,
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
console.log(`[KnowledgeExtract] Extracted ${relationships.length} relationships`);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
} catch (err) {
|
} catch (err) {
|
||||||
console.error("[KnowledgeExtract] Relationship extraction failed:", err);
|
console.error("[KnowledgeExtract] Relationship extraction failed:", err);
|
||||||
|
|
@ -158,51 +165,58 @@ export class KnowledgeExtractService extends FlowProcessor {
|
||||||
|
|
||||||
// --- Extract definitions ---
|
// --- Extract definitions ---
|
||||||
try {
|
try {
|
||||||
const defPrompt = await promptClient.request({
|
const defPrompt = await promptClient.request(
|
||||||
name: "extract-definitions",
|
{ name: "extract-definitions", variables: { text } },
|
||||||
variables: { text },
|
{ timeoutMs: 10_000 },
|
||||||
});
|
);
|
||||||
|
|
||||||
if (!defPrompt.error) {
|
if (!defPrompt.error) {
|
||||||
const defCompletion = await llmClient.request({
|
let definitions: ExtractedDefinition[] | null = null;
|
||||||
system: defPrompt.system,
|
for (let attempt = 0; attempt < 3; attempt++) {
|
||||||
prompt: defPrompt.prompt,
|
const defCompletion = await llmClient.request(
|
||||||
});
|
{ system: defPrompt.system, prompt: defPrompt.prompt },
|
||||||
|
{ timeoutMs: 120_000 },
|
||||||
|
);
|
||||||
|
|
||||||
if (!defCompletion.error && defCompletion.response) {
|
if (!defCompletion.error && defCompletion.response) {
|
||||||
const definitions = parseJsonResponse<ExtractedDefinition[]>(defCompletion.response);
|
definitions = parseJsonResponse<ExtractedDefinition[]>(defCompletion.response);
|
||||||
|
if (definitions) break;
|
||||||
if (definitions) {
|
console.warn(`[KnowledgeExtract] Definition parse failed, attempt ${attempt + 1}/3`);
|
||||||
for (const def of definitions) {
|
} else {
|
||||||
if (!def.entity || !def.definition) continue;
|
break; // LLM error, don't retry
|
||||||
|
|
||||||
const entityIri = toEntityIri(def.entity);
|
|
||||||
|
|
||||||
// Definition triple
|
|
||||||
allTriples.push({
|
|
||||||
s: entityIri,
|
|
||||||
p: iriTerm(SKOS_DEFINITION),
|
|
||||||
o: literalTerm(def.definition),
|
|
||||||
});
|
|
||||||
|
|
||||||
// Label triple
|
|
||||||
allTriples.push({
|
|
||||||
s: entityIri,
|
|
||||||
p: iriTerm(RDFS_LABEL),
|
|
||||||
o: literalTerm(def.entity),
|
|
||||||
});
|
|
||||||
|
|
||||||
// Entity context
|
|
||||||
allEntityContexts.push({
|
|
||||||
entity: entityIri,
|
|
||||||
context: text,
|
|
||||||
chunkId: msg.documentId,
|
|
||||||
});
|
|
||||||
}
|
|
||||||
|
|
||||||
console.log(`[KnowledgeExtract] Extracted ${definitions.length} definitions`);
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
if (definitions) {
|
||||||
|
for (const def of definitions) {
|
||||||
|
if (!def.entity || !def.definition) continue;
|
||||||
|
|
||||||
|
const entityIri = toEntityIri(def.entity);
|
||||||
|
|
||||||
|
// Definition triple
|
||||||
|
allTriples.push({
|
||||||
|
s: entityIri,
|
||||||
|
p: iriTerm(SKOS_DEFINITION),
|
||||||
|
o: literalTerm(def.definition),
|
||||||
|
});
|
||||||
|
|
||||||
|
// Label triple
|
||||||
|
allTriples.push({
|
||||||
|
s: entityIri,
|
||||||
|
p: iriTerm(RDFS_LABEL),
|
||||||
|
o: literalTerm(def.entity),
|
||||||
|
});
|
||||||
|
|
||||||
|
// Entity context
|
||||||
|
allEntityContexts.push({
|
||||||
|
entity: entityIri,
|
||||||
|
context: text,
|
||||||
|
chunkId: msg.documentId,
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
console.log(`[KnowledgeExtract] Extracted ${definitions.length} definitions`);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
} catch (err) {
|
} catch (err) {
|
||||||
console.error("[KnowledgeExtract] Definition extraction failed:", err);
|
console.error("[KnowledgeExtract] Definition extraction failed:", err);
|
||||||
|
|
@ -245,23 +259,49 @@ function literalTerm(value: string): Term {
|
||||||
|
|
||||||
/**
|
/**
|
||||||
* Parse JSON from LLM output, handling markdown code fences and malformed output.
|
* Parse JSON from LLM output, handling markdown code fences and malformed output.
|
||||||
|
* Uses progressive fallback: direct parse, array extraction, truncated array repair, single object wrap.
|
||||||
*/
|
*/
|
||||||
function parseJsonResponse<T>(raw: string): T | null {
|
function parseJsonResponse<T>(raw: string): T | null {
|
||||||
try {
|
// Attempt 1: direct parse after stripping fences
|
||||||
// Strip markdown code fences
|
let cleaned = raw.trim();
|
||||||
let cleaned = raw.trim();
|
const fenceMatch = cleaned.match(/^```(?:json)?\s*\n?([\s\S]*?)\n?```$/);
|
||||||
|
if (fenceMatch) {
|
||||||
// Remove ```json ... ``` or ``` ... ```
|
cleaned = fenceMatch[1].trim();
|
||||||
const fenceMatch = cleaned.match(/^```(?:json)?\s*\n?([\s\S]*?)\n?```$/);
|
|
||||||
if (fenceMatch) {
|
|
||||||
cleaned = fenceMatch[1].trim();
|
|
||||||
}
|
|
||||||
|
|
||||||
return JSON.parse(cleaned) as T;
|
|
||||||
} catch {
|
|
||||||
console.warn("[KnowledgeExtract] Failed to parse JSON from LLM response:", raw.slice(0, 200));
|
|
||||||
return null;
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
try {
|
||||||
|
return JSON.parse(cleaned) as T;
|
||||||
|
} catch { /* fall through */ }
|
||||||
|
|
||||||
|
// Attempt 2: extract first JSON array from the text
|
||||||
|
const arrayMatch = cleaned.match(/\[[\s\S]*\]/);
|
||||||
|
if (arrayMatch) {
|
||||||
|
try {
|
||||||
|
return JSON.parse(arrayMatch[0]) as T;
|
||||||
|
} catch { /* fall through */ }
|
||||||
|
|
||||||
|
// Attempt 3: try to fix truncated array by closing it after the last complete object
|
||||||
|
const partial = arrayMatch[0];
|
||||||
|
const lastBrace = partial.lastIndexOf('}');
|
||||||
|
if (lastBrace > 0) {
|
||||||
|
const truncated = partial.slice(0, lastBrace + 1) + ']';
|
||||||
|
try {
|
||||||
|
return JSON.parse(truncated) as T;
|
||||||
|
} catch { /* fall through */ }
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// Attempt 4: extract first JSON object, wrap in array
|
||||||
|
const objMatch = cleaned.match(/\{[\s\S]*?\}/);
|
||||||
|
if (objMatch) {
|
||||||
|
try {
|
||||||
|
const obj = JSON.parse(objMatch[0]);
|
||||||
|
return [obj] as unknown as T;
|
||||||
|
} catch { /* fall through */ }
|
||||||
|
}
|
||||||
|
|
||||||
|
console.warn("[KnowledgeExtract] Failed to parse JSON from LLM response:", raw.slice(0, 300));
|
||||||
|
return null;
|
||||||
}
|
}
|
||||||
|
|
||||||
export async function run(): Promise<void> {
|
export async function run(): Promise<void> {
|
||||||
|
|
|
||||||
|
|
@ -79,3 +79,12 @@ export { DocumentRagService } from "./retrieval/document-rag-service.js";
|
||||||
|
|
||||||
// Flow manager service
|
// Flow manager service
|
||||||
export { FlowManagerService } from "./flow-manager/service.js";
|
export { FlowManagerService } from "./flow-manager/service.js";
|
||||||
|
|
||||||
|
// Azure OpenAI text completion
|
||||||
|
export { AzureOpenAIProcessor } from "./model/text-completion/azure-openai.js";
|
||||||
|
|
||||||
|
// OpenAI-compatible text completion
|
||||||
|
export { OpenAICompatibleProcessor } from "./model/text-completion/openai-compatible.js";
|
||||||
|
|
||||||
|
// Mistral text completion
|
||||||
|
export { MistralProcessor } from "./model/text-completion/mistral.js";
|
||||||
|
|
|
||||||
156
ts/packages/flow/src/model/text-completion/azure-openai.ts
Normal file
156
ts/packages/flow/src/model/text-completion/azure-openai.ts
Normal file
|
|
@ -0,0 +1,156 @@
|
||||||
|
/**
|
||||||
|
* Azure OpenAI text completion service.
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* AZURE_TOKEN (required – Azure OpenAI API key)
|
||||||
|
* AZURE_ENDPOINT (required – e.g. https://my-resource.openai.azure.com)
|
||||||
|
* AZURE_MODEL (default: gpt-4o)
|
||||||
|
* AZURE_API_VERSION (default: 2024-12-01-preview)
|
||||||
|
*/
|
||||||
|
|
||||||
|
import { AzureOpenAI } from "openai";
|
||||||
|
import {
|
||||||
|
LlmService,
|
||||||
|
type ProcessorConfig,
|
||||||
|
type LlmResult,
|
||||||
|
type LlmChunk,
|
||||||
|
TooManyRequestsError,
|
||||||
|
} from "@trustgraph/base";
|
||||||
|
|
||||||
|
export class AzureOpenAIProcessor extends LlmService {
|
||||||
|
private client: AzureOpenAI;
|
||||||
|
private readonly defaultModel: string;
|
||||||
|
private readonly defaultTemperature: number;
|
||||||
|
private readonly maxOutput: number;
|
||||||
|
|
||||||
|
constructor(
|
||||||
|
config: ProcessorConfig & {
|
||||||
|
model?: string;
|
||||||
|
apiKey?: string;
|
||||||
|
endpoint?: string;
|
||||||
|
apiVersion?: string;
|
||||||
|
temperature?: number;
|
||||||
|
maxOutput?: number;
|
||||||
|
},
|
||||||
|
) {
|
||||||
|
super(config);
|
||||||
|
|
||||||
|
this.defaultModel = config.model ?? process.env.AZURE_MODEL ?? "gpt-4o";
|
||||||
|
this.defaultTemperature = config.temperature ?? 0.0;
|
||||||
|
this.maxOutput = config.maxOutput ?? 4096;
|
||||||
|
|
||||||
|
const apiKey = config.apiKey ?? process.env.AZURE_TOKEN;
|
||||||
|
if (!apiKey) throw new Error("Azure OpenAI API key not specified");
|
||||||
|
|
||||||
|
const endpoint = config.endpoint ?? process.env.AZURE_ENDPOINT;
|
||||||
|
if (!endpoint) throw new Error("Azure OpenAI endpoint not specified");
|
||||||
|
|
||||||
|
const apiVersion =
|
||||||
|
config.apiVersion ??
|
||||||
|
process.env.AZURE_API_VERSION ??
|
||||||
|
"2024-12-01-preview";
|
||||||
|
|
||||||
|
this.client = new AzureOpenAI({ apiKey, apiVersion, endpoint });
|
||||||
|
|
||||||
|
console.log("[AzureOpenAI] LLM service initialized");
|
||||||
|
}
|
||||||
|
|
||||||
|
async generateContent(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): Promise<LlmResult> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
try {
|
||||||
|
const resp = await this.client.chat.completions.create({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
max_completion_tokens: this.maxOutput,
|
||||||
|
});
|
||||||
|
|
||||||
|
return {
|
||||||
|
text: resp.choices[0].message.content ?? "",
|
||||||
|
inToken: resp.usage?.prompt_tokens ?? 0,
|
||||||
|
outToken: resp.usage?.completion_tokens ?? 0,
|
||||||
|
model: modelName,
|
||||||
|
};
|
||||||
|
} catch (err) {
|
||||||
|
if ((err as any)?.status === 429) {
|
||||||
|
throw new TooManyRequestsError();
|
||||||
|
}
|
||||||
|
throw err;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
override supportsStreaming(): boolean {
|
||||||
|
return true;
|
||||||
|
}
|
||||||
|
|
||||||
|
async *generateContentStream(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): AsyncGenerator<LlmChunk> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
try {
|
||||||
|
const stream = await this.client.chat.completions.create({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
max_completion_tokens: this.maxOutput,
|
||||||
|
stream: true,
|
||||||
|
stream_options: { include_usage: true },
|
||||||
|
});
|
||||||
|
|
||||||
|
let totalInputTokens = 0;
|
||||||
|
let totalOutputTokens = 0;
|
||||||
|
|
||||||
|
for await (const chunk of stream) {
|
||||||
|
if (chunk.choices?.[0]?.delta?.content) {
|
||||||
|
yield {
|
||||||
|
text: chunk.choices[0].delta.content,
|
||||||
|
inToken: null,
|
||||||
|
outToken: null,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: false,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
if (chunk.usage) {
|
||||||
|
totalInputTokens = chunk.usage.prompt_tokens;
|
||||||
|
totalOutputTokens = chunk.usage.completion_tokens;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
yield {
|
||||||
|
text: "",
|
||||||
|
inToken: totalInputTokens,
|
||||||
|
outToken: totalOutputTokens,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: true,
|
||||||
|
};
|
||||||
|
} catch (err) {
|
||||||
|
if ((err as any)?.status === 429) {
|
||||||
|
throw new TooManyRequestsError();
|
||||||
|
}
|
||||||
|
throw err;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export async function run(): Promise<void> {
|
||||||
|
await AzureOpenAIProcessor.launch("text-completion");
|
||||||
|
}
|
||||||
144
ts/packages/flow/src/model/text-completion/mistral.ts
Normal file
144
ts/packages/flow/src/model/text-completion/mistral.ts
Normal file
|
|
@ -0,0 +1,144 @@
|
||||||
|
/**
|
||||||
|
* Mistral text completion service.
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* MISTRAL_TOKEN (required – Mistral API key)
|
||||||
|
* MISTRAL_MODEL (default: ministral-8b-latest)
|
||||||
|
*/
|
||||||
|
|
||||||
|
import { Mistral } from "@mistralai/mistralai";
|
||||||
|
import {
|
||||||
|
LlmService,
|
||||||
|
type ProcessorConfig,
|
||||||
|
type LlmResult,
|
||||||
|
type LlmChunk,
|
||||||
|
TooManyRequestsError,
|
||||||
|
} from "@trustgraph/base";
|
||||||
|
|
||||||
|
export class MistralProcessor extends LlmService {
|
||||||
|
private client: Mistral;
|
||||||
|
private readonly defaultModel: string;
|
||||||
|
private readonly defaultTemperature: number;
|
||||||
|
private readonly maxOutput: number;
|
||||||
|
|
||||||
|
constructor(
|
||||||
|
config: ProcessorConfig & {
|
||||||
|
model?: string;
|
||||||
|
apiKey?: string;
|
||||||
|
temperature?: number;
|
||||||
|
maxOutput?: number;
|
||||||
|
},
|
||||||
|
) {
|
||||||
|
super(config);
|
||||||
|
|
||||||
|
this.defaultModel =
|
||||||
|
config.model ?? process.env.MISTRAL_MODEL ?? "ministral-8b-latest";
|
||||||
|
this.defaultTemperature = config.temperature ?? 0.0;
|
||||||
|
this.maxOutput = config.maxOutput ?? 4096;
|
||||||
|
|
||||||
|
const apiKey = config.apiKey ?? process.env.MISTRAL_TOKEN;
|
||||||
|
if (!apiKey) throw new Error("Mistral API key not specified");
|
||||||
|
|
||||||
|
this.client = new Mistral({ apiKey });
|
||||||
|
|
||||||
|
console.log("[Mistral] LLM service initialized");
|
||||||
|
}
|
||||||
|
|
||||||
|
async generateContent(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): Promise<LlmResult> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
try {
|
||||||
|
const resp = await this.client.chat.complete({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
maxTokens: this.maxOutput,
|
||||||
|
});
|
||||||
|
|
||||||
|
return {
|
||||||
|
text: (resp.choices?.[0]?.message?.content as string) ?? "",
|
||||||
|
inToken: resp.usage?.promptTokens ?? 0,
|
||||||
|
outToken: resp.usage?.completionTokens ?? 0,
|
||||||
|
model: modelName,
|
||||||
|
};
|
||||||
|
} catch (err) {
|
||||||
|
if ((err as any)?.statusCode === 429 || (err as any)?.status === 429) {
|
||||||
|
throw new TooManyRequestsError();
|
||||||
|
}
|
||||||
|
throw err;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
override supportsStreaming(): boolean {
|
||||||
|
return true;
|
||||||
|
}
|
||||||
|
|
||||||
|
async *generateContentStream(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): AsyncGenerator<LlmChunk> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
try {
|
||||||
|
const stream = await this.client.chat.stream({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
maxTokens: this.maxOutput,
|
||||||
|
});
|
||||||
|
|
||||||
|
let totalInputTokens = 0;
|
||||||
|
let totalOutputTokens = 0;
|
||||||
|
|
||||||
|
for await (const chunk of stream) {
|
||||||
|
const delta = chunk.data?.choices?.[0]?.delta;
|
||||||
|
if (delta?.content) {
|
||||||
|
yield {
|
||||||
|
text: delta.content as string,
|
||||||
|
inToken: null,
|
||||||
|
outToken: null,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: false,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
if (chunk.data?.usage) {
|
||||||
|
totalInputTokens = chunk.data.usage.promptTokens ?? 0;
|
||||||
|
totalOutputTokens = chunk.data.usage.completionTokens ?? 0;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
yield {
|
||||||
|
text: "",
|
||||||
|
inToken: totalInputTokens,
|
||||||
|
outToken: totalOutputTokens,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: true,
|
||||||
|
};
|
||||||
|
} catch (err) {
|
||||||
|
if ((err as any)?.statusCode === 429 || (err as any)?.status === 429) {
|
||||||
|
throw new TooManyRequestsError();
|
||||||
|
}
|
||||||
|
throw err;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export async function run(): Promise<void> {
|
||||||
|
await MistralProcessor.launch("text-completion");
|
||||||
|
}
|
||||||
139
ts/packages/flow/src/model/text-completion/openai-compatible.ts
Normal file
139
ts/packages/flow/src/model/text-completion/openai-compatible.ts
Normal file
|
|
@ -0,0 +1,139 @@
|
||||||
|
/**
|
||||||
|
* OpenAI-compatible text completion service (generic local server).
|
||||||
|
*
|
||||||
|
* Works with LM Studio, llama.cpp, vLLM, Ollama OpenAI-compat endpoint, etc.
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* OPENAI_COMPAT_URL (required – e.g. http://localhost:1234/v1)
|
||||||
|
* OPENAI_COMPAT_KEY (default: sk-no-key-required)
|
||||||
|
* OPENAI_COMPAT_MODEL (default: default)
|
||||||
|
*/
|
||||||
|
|
||||||
|
import OpenAI from "openai";
|
||||||
|
import {
|
||||||
|
LlmService,
|
||||||
|
type ProcessorConfig,
|
||||||
|
type LlmResult,
|
||||||
|
type LlmChunk,
|
||||||
|
} from "@trustgraph/base";
|
||||||
|
|
||||||
|
export class OpenAICompatibleProcessor extends LlmService {
|
||||||
|
private client: OpenAI;
|
||||||
|
private readonly defaultModel: string;
|
||||||
|
private readonly defaultTemperature: number;
|
||||||
|
private readonly maxOutput: number;
|
||||||
|
|
||||||
|
constructor(
|
||||||
|
config: ProcessorConfig & {
|
||||||
|
model?: string;
|
||||||
|
apiKey?: string;
|
||||||
|
baseUrl?: string;
|
||||||
|
temperature?: number;
|
||||||
|
maxOutput?: number;
|
||||||
|
},
|
||||||
|
) {
|
||||||
|
super(config);
|
||||||
|
|
||||||
|
this.defaultModel =
|
||||||
|
config.model ?? process.env.OPENAI_COMPAT_MODEL ?? "default";
|
||||||
|
this.defaultTemperature = config.temperature ?? 0.0;
|
||||||
|
this.maxOutput = config.maxOutput ?? 4096;
|
||||||
|
|
||||||
|
const baseURL = config.baseUrl ?? process.env.OPENAI_COMPAT_URL;
|
||||||
|
if (!baseURL)
|
||||||
|
throw new Error(
|
||||||
|
"OpenAI-compatible server URL not specified (set OPENAI_COMPAT_URL)",
|
||||||
|
);
|
||||||
|
|
||||||
|
const apiKey =
|
||||||
|
config.apiKey ?? process.env.OPENAI_COMPAT_KEY ?? "sk-no-key-required";
|
||||||
|
|
||||||
|
this.client = new OpenAI({ baseURL, apiKey });
|
||||||
|
|
||||||
|
console.log("[OpenAI-Compatible] LLM service initialized");
|
||||||
|
}
|
||||||
|
|
||||||
|
async generateContent(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): Promise<LlmResult> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
const resp = await this.client.chat.completions.create({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
max_tokens: this.maxOutput,
|
||||||
|
});
|
||||||
|
|
||||||
|
return {
|
||||||
|
text: resp.choices[0].message.content ?? "",
|
||||||
|
inToken: resp.usage?.prompt_tokens ?? 0,
|
||||||
|
outToken: resp.usage?.completion_tokens ?? 0,
|
||||||
|
model: modelName,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
override supportsStreaming(): boolean {
|
||||||
|
return true;
|
||||||
|
}
|
||||||
|
|
||||||
|
async *generateContentStream(
|
||||||
|
system: string,
|
||||||
|
prompt: string,
|
||||||
|
model?: string,
|
||||||
|
temperature?: number,
|
||||||
|
): AsyncGenerator<LlmChunk> {
|
||||||
|
const modelName = model ?? this.defaultModel;
|
||||||
|
const temp = temperature ?? this.defaultTemperature;
|
||||||
|
|
||||||
|
const stream = await this.client.chat.completions.create({
|
||||||
|
model: modelName,
|
||||||
|
messages: [
|
||||||
|
{ role: "system", content: system },
|
||||||
|
{ role: "user", content: prompt },
|
||||||
|
],
|
||||||
|
temperature: temp,
|
||||||
|
max_tokens: this.maxOutput,
|
||||||
|
stream: true,
|
||||||
|
});
|
||||||
|
|
||||||
|
let totalInputTokens = 0;
|
||||||
|
let totalOutputTokens = 0;
|
||||||
|
|
||||||
|
for await (const chunk of stream) {
|
||||||
|
if (chunk.choices?.[0]?.delta?.content) {
|
||||||
|
yield {
|
||||||
|
text: chunk.choices[0].delta.content,
|
||||||
|
inToken: null,
|
||||||
|
outToken: null,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: false,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
if (chunk.usage) {
|
||||||
|
totalInputTokens = chunk.usage.prompt_tokens;
|
||||||
|
totalOutputTokens = chunk.usage.completion_tokens;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
yield {
|
||||||
|
text: "",
|
||||||
|
inToken: totalInputTokens,
|
||||||
|
outToken: totalOutputTokens,
|
||||||
|
model: modelName,
|
||||||
|
isFinal: true,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
export async function run(): Promise<void> {
|
||||||
|
await OpenAICompatibleProcessor.launch("text-completion");
|
||||||
|
}
|
||||||
|
|
@ -3,6 +3,9 @@ import { RootLayout } from "@/components/layout/root-layout";
|
||||||
import ChatPage from "@/pages/chat";
|
import ChatPage from "@/pages/chat";
|
||||||
import LibraryPage from "@/pages/library";
|
import LibraryPage from "@/pages/library";
|
||||||
import GraphPage from "@/pages/graph";
|
import GraphPage from "@/pages/graph";
|
||||||
|
import PromptsPage from "@/pages/prompts";
|
||||||
|
import TokenCostPage from "@/pages/token-cost";
|
||||||
|
import KnowledgeCoresPage from "@/pages/knowledge-cores";
|
||||||
import FlowsPage from "@/pages/flows";
|
import FlowsPage from "@/pages/flows";
|
||||||
import SettingsPage from "@/pages/settings";
|
import SettingsPage from "@/pages/settings";
|
||||||
import { NotificationToasts } from "@/components/notification-toasts";
|
import { NotificationToasts } from "@/components/notification-toasts";
|
||||||
|
|
@ -16,6 +19,9 @@ export default function App() {
|
||||||
<Route path="/chat" element={<ChatPage />} />
|
<Route path="/chat" element={<ChatPage />} />
|
||||||
<Route path="/library" element={<LibraryPage />} />
|
<Route path="/library" element={<LibraryPage />} />
|
||||||
<Route path="/graph" element={<GraphPage />} />
|
<Route path="/graph" element={<GraphPage />} />
|
||||||
|
<Route path="/prompts" element={<PromptsPage />} />
|
||||||
|
<Route path="/token-cost" element={<TokenCostPage />} />
|
||||||
|
<Route path="/knowledge-cores" element={<KnowledgeCoresPage />} />
|
||||||
<Route path="/flows" element={<FlowsPage />} />
|
<Route path="/flows" element={<FlowsPage />} />
|
||||||
<Route path="/settings" element={<SettingsPage />} />
|
<Route path="/settings" element={<SettingsPage />} />
|
||||||
</Route>
|
</Route>
|
||||||
|
|
|
||||||
|
|
@ -3,6 +3,9 @@ import {
|
||||||
MessageSquareText,
|
MessageSquareText,
|
||||||
LibraryBig,
|
LibraryBig,
|
||||||
Rotate3d,
|
Rotate3d,
|
||||||
|
MessageCircleCode,
|
||||||
|
Coins,
|
||||||
|
BrainCircuit,
|
||||||
Workflow,
|
Workflow,
|
||||||
Settings,
|
Settings,
|
||||||
TestTube2,
|
TestTube2,
|
||||||
|
|
@ -155,6 +158,9 @@ export function Sidebar() {
|
||||||
<NavItem to="/chat" icon={MessageSquareText} label="Chat" />
|
<NavItem to="/chat" icon={MessageSquareText} label="Chat" />
|
||||||
<NavItem to="/library" icon={LibraryBig} label="Library" />
|
<NavItem to="/library" icon={LibraryBig} label="Library" />
|
||||||
<NavItem to="/graph" icon={Rotate3d} label="Graph" />
|
<NavItem to="/graph" icon={Rotate3d} label="Graph" />
|
||||||
|
<NavItem to="/prompts" icon={MessageCircleCode} label="Prompts" />
|
||||||
|
<NavItem to="/token-cost" icon={Coins} label="Token Cost" />
|
||||||
|
<NavItem to="/knowledge-cores" icon={BrainCircuit} label="Knowledge" />
|
||||||
<NavItem to="/flows" icon={Workflow} label="Flows" />
|
<NavItem to="/flows" icon={Workflow} label="Flows" />
|
||||||
<NavItem to="/settings" icon={Settings} label="Settings" />
|
<NavItem to="/settings" icon={Settings} label="Settings" />
|
||||||
</nav>
|
</nav>
|
||||||
|
|
|
||||||
50
ts/packages/workbench/src/hooks/use-prompts.ts
Normal file
50
ts/packages/workbench/src/hooks/use-prompts.ts
Normal file
|
|
@ -0,0 +1,50 @@
|
||||||
|
import { useCallback, useEffect, useState } from "react";
|
||||||
|
import { useSocket } from "@/providers/socket-provider";
|
||||||
|
import { useConnectionState } from "@/providers/socket-provider";
|
||||||
|
|
||||||
|
export function usePrompts() {
|
||||||
|
const socket = useSocket();
|
||||||
|
const connectionState = useConnectionState();
|
||||||
|
const [prompts, setPrompts] = useState<Array<{ id: string; name?: string; description?: string }>>([]);
|
||||||
|
const [systemPrompt, setSystemPrompt] = useState<string>("");
|
||||||
|
const [loading, setLoading] = useState(false);
|
||||||
|
|
||||||
|
const loadPrompts = useCallback(async () => {
|
||||||
|
try {
|
||||||
|
setLoading(true);
|
||||||
|
const list = await socket.config().getPrompts();
|
||||||
|
setPrompts(Array.isArray(list) ? list : []);
|
||||||
|
} catch (err) {
|
||||||
|
console.error("Failed to load prompts:", err);
|
||||||
|
} finally {
|
||||||
|
setLoading(false);
|
||||||
|
}
|
||||||
|
}, [socket]);
|
||||||
|
|
||||||
|
const loadSystemPrompt = useCallback(async () => {
|
||||||
|
try {
|
||||||
|
const sp = await socket.config().getSystemPrompt();
|
||||||
|
setSystemPrompt(typeof sp === "string" ? sp : JSON.stringify(sp, null, 2));
|
||||||
|
} catch (err) {
|
||||||
|
console.error("Failed to load system prompt:", err);
|
||||||
|
}
|
||||||
|
}, [socket]);
|
||||||
|
|
||||||
|
const getPrompt = useCallback(async (id: string) => {
|
||||||
|
return socket.config().getPrompt(id);
|
||||||
|
}, [socket]);
|
||||||
|
|
||||||
|
// Auto-load when connected
|
||||||
|
useEffect(() => {
|
||||||
|
const connected =
|
||||||
|
connectionState.status === "connected" ||
|
||||||
|
connectionState.status === "authenticated" ||
|
||||||
|
connectionState.status === "unauthenticated";
|
||||||
|
if (connected) {
|
||||||
|
loadPrompts();
|
||||||
|
loadSystemPrompt();
|
||||||
|
}
|
||||||
|
}, [connectionState.status, loadPrompts, loadSystemPrompt]);
|
||||||
|
|
||||||
|
return { prompts, systemPrompt, loading, loadPrompts, loadSystemPrompt, getPrompt };
|
||||||
|
}
|
||||||
244
ts/packages/workbench/src/pages/knowledge-cores.tsx
Normal file
244
ts/packages/workbench/src/pages/knowledge-cores.tsx
Normal file
|
|
@ -0,0 +1,244 @@
|
||||||
|
import { useCallback, useEffect, useState } from "react";
|
||||||
|
import {
|
||||||
|
BrainCircuit,
|
||||||
|
Loader2,
|
||||||
|
RefreshCw,
|
||||||
|
Download,
|
||||||
|
Trash2,
|
||||||
|
AlertTriangle,
|
||||||
|
} from "lucide-react";
|
||||||
|
import { cn } from "@/lib/utils";
|
||||||
|
import { useSocket } from "@/providers/socket-provider";
|
||||||
|
import { useConnectionState } from "@/providers/socket-provider";
|
||||||
|
import { useNotification } from "@/providers/notification-provider";
|
||||||
|
import { useSessionStore } from "@/hooks/use-session-store";
|
||||||
|
import { Dialog } from "@/components/ui/dialog";
|
||||||
|
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
// Delete confirmation dialog
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
function DeleteCoreDialog({
|
||||||
|
open,
|
||||||
|
coreId,
|
||||||
|
onClose,
|
||||||
|
onConfirm,
|
||||||
|
}: {
|
||||||
|
open: boolean;
|
||||||
|
coreId: string;
|
||||||
|
onClose: () => void;
|
||||||
|
onConfirm: () => void;
|
||||||
|
}) {
|
||||||
|
return (
|
||||||
|
<Dialog
|
||||||
|
open={open}
|
||||||
|
onClose={onClose}
|
||||||
|
title="Delete Knowledge Core"
|
||||||
|
footer={
|
||||||
|
<>
|
||||||
|
<button
|
||||||
|
onClick={onClose}
|
||||||
|
className="rounded-lg border border-border px-4 py-2 text-sm text-fg-muted hover:bg-surface-200"
|
||||||
|
>
|
||||||
|
Cancel
|
||||||
|
</button>
|
||||||
|
<button
|
||||||
|
onClick={onConfirm}
|
||||||
|
className="rounded-lg bg-error px-4 py-2 text-sm font-medium text-white hover:opacity-90"
|
||||||
|
>
|
||||||
|
Delete
|
||||||
|
</button>
|
||||||
|
</>
|
||||||
|
}
|
||||||
|
>
|
||||||
|
<div className="flex items-start gap-3">
|
||||||
|
<AlertTriangle className="mt-0.5 h-5 w-5 shrink-0 text-error" />
|
||||||
|
<p className="text-sm text-fg-muted">
|
||||||
|
Are you sure you want to delete knowledge core{" "}
|
||||||
|
<span className="font-mono font-medium text-fg">{coreId}</span>?
|
||||||
|
This action cannot be undone.
|
||||||
|
</p>
|
||||||
|
</div>
|
||||||
|
</Dialog>
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
// Knowledge Cores page
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
export default function KnowledgeCoresPage() {
|
||||||
|
const socket = useSocket();
|
||||||
|
const connectionState = useConnectionState();
|
||||||
|
const notify = useNotification();
|
||||||
|
const flowId = useSessionStore((s) => s.flowId);
|
||||||
|
|
||||||
|
const [cores, setCores] = useState<string[]>([]);
|
||||||
|
const [loading, setLoading] = useState(false);
|
||||||
|
const [error, setError] = useState<string | null>(null);
|
||||||
|
const [deleteTarget, setDeleteTarget] = useState<string | null>(null);
|
||||||
|
const [actionInProgress, setActionInProgress] = useState<string | null>(null);
|
||||||
|
|
||||||
|
const loadCores = useCallback(async () => {
|
||||||
|
try {
|
||||||
|
setLoading(true);
|
||||||
|
setError(null);
|
||||||
|
const ids = await socket.knowledge().getKnowledgeCores();
|
||||||
|
setCores(Array.isArray(ids) ? ids : []);
|
||||||
|
} catch (err) {
|
||||||
|
const msg = err instanceof Error ? err.message : String(err);
|
||||||
|
setError(msg);
|
||||||
|
console.error("Failed to load knowledge cores:", err);
|
||||||
|
} finally {
|
||||||
|
setLoading(false);
|
||||||
|
}
|
||||||
|
}, [socket]);
|
||||||
|
|
||||||
|
// Auto-load when connected
|
||||||
|
useEffect(() => {
|
||||||
|
const connected =
|
||||||
|
connectionState.status === "connected" ||
|
||||||
|
connectionState.status === "authenticated" ||
|
||||||
|
connectionState.status === "unauthenticated";
|
||||||
|
if (connected) {
|
||||||
|
loadCores();
|
||||||
|
}
|
||||||
|
}, [connectionState.status, loadCores]);
|
||||||
|
|
||||||
|
const handleLoad = useCallback(
|
||||||
|
async (id: string) => {
|
||||||
|
setActionInProgress(id);
|
||||||
|
try {
|
||||||
|
await socket.knowledge().loadKgCore(id, flowId);
|
||||||
|
notify.success("Core loaded", `Knowledge core "${id}" has been loaded.`);
|
||||||
|
} catch (err) {
|
||||||
|
notify.error(
|
||||||
|
"Failed to load core",
|
||||||
|
err instanceof Error ? err.message : String(err),
|
||||||
|
);
|
||||||
|
} finally {
|
||||||
|
setActionInProgress(null);
|
||||||
|
}
|
||||||
|
},
|
||||||
|
[socket, flowId, notify],
|
||||||
|
);
|
||||||
|
|
||||||
|
const handleDelete = useCallback(async () => {
|
||||||
|
if (!deleteTarget) return;
|
||||||
|
setActionInProgress(deleteTarget);
|
||||||
|
try {
|
||||||
|
await socket.knowledge().deleteKgCore(deleteTarget);
|
||||||
|
notify.success("Core deleted", `Knowledge core "${deleteTarget}" has been deleted.`);
|
||||||
|
await loadCores();
|
||||||
|
} catch (err) {
|
||||||
|
notify.error(
|
||||||
|
"Failed to delete core",
|
||||||
|
err instanceof Error ? err.message : String(err),
|
||||||
|
);
|
||||||
|
} finally {
|
||||||
|
setActionInProgress(null);
|
||||||
|
setDeleteTarget(null);
|
||||||
|
}
|
||||||
|
}, [socket, deleteTarget, notify, loadCores]);
|
||||||
|
|
||||||
|
return (
|
||||||
|
<div className="flex h-full flex-col">
|
||||||
|
{/* Header */}
|
||||||
|
<div className="mb-6 flex items-center justify-between">
|
||||||
|
<div className="flex items-center gap-3">
|
||||||
|
<BrainCircuit className="h-6 w-6 text-brand-400" />
|
||||||
|
<h1 className="text-2xl font-bold text-fg">Knowledge Cores</h1>
|
||||||
|
<span className="ml-2 rounded bg-surface-200 px-2 py-0.5 text-xs text-fg-subtle">
|
||||||
|
{cores.length} core{cores.length !== 1 ? "s" : ""}
|
||||||
|
</span>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
<button
|
||||||
|
onClick={loadCores}
|
||||||
|
disabled={loading}
|
||||||
|
className="flex items-center gap-1.5 rounded-lg border border-border px-3 py-2 text-sm text-fg-muted transition-colors hover:bg-surface-200 disabled:opacity-40"
|
||||||
|
>
|
||||||
|
<RefreshCw className={cn("h-3.5 w-3.5", loading && "animate-spin")} />
|
||||||
|
Refresh
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
{/* Content */}
|
||||||
|
{loading && cores.length === 0 && (
|
||||||
|
<div className="flex items-center justify-center py-12">
|
||||||
|
<Loader2 className="mr-2 h-5 w-5 animate-spin text-fg-subtle" />
|
||||||
|
<span className="text-fg-subtle">Loading knowledge cores...</span>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{error && (
|
||||||
|
<p className="mb-4 rounded-lg bg-error/10 px-4 py-2 text-sm text-error">
|
||||||
|
{error}
|
||||||
|
</p>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{!loading && !error && cores.length === 0 && (
|
||||||
|
<div className="flex flex-1 flex-col items-center justify-center">
|
||||||
|
<BrainCircuit className="mb-3 h-10 w-10 text-fg-subtle opacity-30" />
|
||||||
|
<p className="text-fg-subtle">No knowledge cores available.</p>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{cores.length > 0 && (
|
||||||
|
<div className="overflow-x-auto rounded-lg border border-border">
|
||||||
|
<table className="w-full text-left text-sm">
|
||||||
|
<thead className="border-b border-border bg-surface-100 text-fg-muted">
|
||||||
|
<tr>
|
||||||
|
<th className="px-4 py-3 font-medium">Core ID</th>
|
||||||
|
<th className="px-4 py-3 font-medium text-right">Actions</th>
|
||||||
|
</tr>
|
||||||
|
</thead>
|
||||||
|
<tbody className="divide-y divide-border">
|
||||||
|
{cores.map((id) => (
|
||||||
|
<tr key={id} className="hover:bg-surface-100/50">
|
||||||
|
<td className="px-4 py-3">
|
||||||
|
<span className="font-mono text-sm text-fg">{id}</span>
|
||||||
|
</td>
|
||||||
|
<td className="px-4 py-3 text-right">
|
||||||
|
<div className="flex items-center justify-end gap-1">
|
||||||
|
<button
|
||||||
|
onClick={() => handleLoad(id)}
|
||||||
|
disabled={actionInProgress === id}
|
||||||
|
className="flex items-center gap-1.5 rounded px-2.5 py-1.5 text-xs font-medium text-brand-400 hover:bg-brand-600/10 disabled:opacity-40"
|
||||||
|
title="Load core"
|
||||||
|
>
|
||||||
|
{actionInProgress === id ? (
|
||||||
|
<Loader2 className="h-3.5 w-3.5 animate-spin" />
|
||||||
|
) : (
|
||||||
|
<Download className="h-3.5 w-3.5" />
|
||||||
|
)}
|
||||||
|
Load
|
||||||
|
</button>
|
||||||
|
<button
|
||||||
|
onClick={() => setDeleteTarget(id)}
|
||||||
|
disabled={actionInProgress === id}
|
||||||
|
className="flex items-center gap-1.5 rounded px-2.5 py-1.5 text-xs font-medium text-error hover:bg-error/10 disabled:opacity-40"
|
||||||
|
title="Delete core"
|
||||||
|
>
|
||||||
|
<Trash2 className="h-3.5 w-3.5" />
|
||||||
|
Delete
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
</td>
|
||||||
|
</tr>
|
||||||
|
))}
|
||||||
|
</tbody>
|
||||||
|
</table>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{/* Delete confirmation dialog */}
|
||||||
|
<DeleteCoreDialog
|
||||||
|
open={deleteTarget != null}
|
||||||
|
coreId={deleteTarget ?? ""}
|
||||||
|
onClose={() => setDeleteTarget(null)}
|
||||||
|
onConfirm={handleDelete}
|
||||||
|
/>
|
||||||
|
</div>
|
||||||
|
);
|
||||||
|
}
|
||||||
215
ts/packages/workbench/src/pages/prompts.tsx
Normal file
215
ts/packages/workbench/src/pages/prompts.tsx
Normal file
|
|
@ -0,0 +1,215 @@
|
||||||
|
import { useCallback, useState } from "react";
|
||||||
|
import {
|
||||||
|
MessageCircleCode,
|
||||||
|
Loader2,
|
||||||
|
RefreshCw,
|
||||||
|
ChevronRight,
|
||||||
|
X,
|
||||||
|
FileText,
|
||||||
|
Terminal,
|
||||||
|
} from "lucide-react";
|
||||||
|
import { cn } from "@/lib/utils";
|
||||||
|
import { usePrompts } from "@/hooks/use-prompts";
|
||||||
|
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
// Prompts page
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
type Tab = "templates" | "system";
|
||||||
|
|
||||||
|
export default function PromptsPage() {
|
||||||
|
const { prompts, systemPrompt, loading, loadPrompts, loadSystemPrompt, getPrompt } = usePrompts();
|
||||||
|
|
||||||
|
const [activeTab, setActiveTab] = useState<Tab>("templates");
|
||||||
|
const [selectedPromptId, setSelectedPromptId] = useState<string | null>(null);
|
||||||
|
const [promptDetail, setPromptDetail] = useState<string>("");
|
||||||
|
const [loadingDetail, setLoadingDetail] = useState(false);
|
||||||
|
|
||||||
|
const handleSelectPrompt = useCallback(
|
||||||
|
async (id: string) => {
|
||||||
|
setSelectedPromptId(id);
|
||||||
|
setLoadingDetail(true);
|
||||||
|
try {
|
||||||
|
const detail = await getPrompt(id);
|
||||||
|
setPromptDetail(
|
||||||
|
typeof detail === "string" ? detail : JSON.stringify(detail, null, 2),
|
||||||
|
);
|
||||||
|
} catch (err) {
|
||||||
|
console.error("Failed to load prompt detail:", err);
|
||||||
|
setPromptDetail("Error loading prompt.");
|
||||||
|
} finally {
|
||||||
|
setLoadingDetail(false);
|
||||||
|
}
|
||||||
|
},
|
||||||
|
[getPrompt],
|
||||||
|
);
|
||||||
|
|
||||||
|
const handleRefresh = useCallback(() => {
|
||||||
|
loadPrompts();
|
||||||
|
loadSystemPrompt();
|
||||||
|
}, [loadPrompts, loadSystemPrompt]);
|
||||||
|
|
||||||
|
return (
|
||||||
|
<div className="flex h-full flex-col">
|
||||||
|
{/* Header */}
|
||||||
|
<div className="mb-6 flex items-center justify-between">
|
||||||
|
<div className="flex items-center gap-3">
|
||||||
|
<MessageCircleCode className="h-6 w-6 text-brand-400" />
|
||||||
|
<h1 className="text-2xl font-bold text-fg">Prompts</h1>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
<button
|
||||||
|
onClick={handleRefresh}
|
||||||
|
disabled={loading}
|
||||||
|
className="flex items-center gap-1.5 rounded-lg border border-border px-3 py-2 text-sm text-fg-muted transition-colors hover:bg-surface-200 disabled:opacity-40"
|
||||||
|
>
|
||||||
|
<RefreshCw className={cn("h-3.5 w-3.5", loading && "animate-spin")} />
|
||||||
|
Refresh
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
{/* Tabs */}
|
||||||
|
<div className="mb-4 flex gap-1 rounded-lg bg-surface-100 p-1">
|
||||||
|
<button
|
||||||
|
onClick={() => setActiveTab("templates")}
|
||||||
|
className={cn(
|
||||||
|
"flex items-center gap-2 rounded-md px-4 py-2 text-sm font-medium transition-colors",
|
||||||
|
activeTab === "templates"
|
||||||
|
? "bg-surface-50 text-fg shadow-sm"
|
||||||
|
: "text-fg-muted hover:text-fg",
|
||||||
|
)}
|
||||||
|
>
|
||||||
|
<FileText className="h-3.5 w-3.5" />
|
||||||
|
Templates
|
||||||
|
</button>
|
||||||
|
<button
|
||||||
|
onClick={() => setActiveTab("system")}
|
||||||
|
className={cn(
|
||||||
|
"flex items-center gap-2 rounded-md px-4 py-2 text-sm font-medium transition-colors",
|
||||||
|
activeTab === "system"
|
||||||
|
? "bg-surface-50 text-fg shadow-sm"
|
||||||
|
: "text-fg-muted hover:text-fg",
|
||||||
|
)}
|
||||||
|
>
|
||||||
|
<Terminal className="h-3.5 w-3.5" />
|
||||||
|
System Prompt
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
{/* Templates tab */}
|
||||||
|
{activeTab === "templates" && (
|
||||||
|
<div className="flex flex-1 flex-col gap-4 overflow-hidden">
|
||||||
|
{loading && prompts.length === 0 && (
|
||||||
|
<div className="flex items-center justify-center py-12">
|
||||||
|
<Loader2 className="mr-2 h-5 w-5 animate-spin text-fg-subtle" />
|
||||||
|
<span className="text-fg-subtle">Loading prompts...</span>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{!loading && prompts.length === 0 && (
|
||||||
|
<div className="flex flex-1 flex-col items-center justify-center">
|
||||||
|
<FileText className="mb-3 h-10 w-10 text-fg-subtle opacity-30" />
|
||||||
|
<p className="text-fg-subtle">No prompt templates found.</p>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{prompts.length > 0 && (
|
||||||
|
<div className="flex flex-1 gap-4 overflow-hidden">
|
||||||
|
{/* Prompt list */}
|
||||||
|
<div className="w-80 shrink-0 overflow-y-auto rounded-lg border border-border">
|
||||||
|
<div className="border-b border-border bg-surface-100 px-4 py-3">
|
||||||
|
<h3 className="text-xs font-medium uppercase tracking-wider text-fg-muted">
|
||||||
|
Templates ({prompts.length})
|
||||||
|
</h3>
|
||||||
|
</div>
|
||||||
|
<div className="divide-y divide-border">
|
||||||
|
{prompts.map((p) => {
|
||||||
|
const id = p.id ?? (p as Record<string, unknown>).name ?? String(p);
|
||||||
|
return (
|
||||||
|
<button
|
||||||
|
key={String(id)}
|
||||||
|
onClick={() => handleSelectPrompt(String(id))}
|
||||||
|
className={cn(
|
||||||
|
"flex w-full items-center justify-between px-4 py-3 text-left text-sm transition-colors",
|
||||||
|
selectedPromptId === String(id)
|
||||||
|
? "bg-brand-600/10 text-brand-400"
|
||||||
|
: "text-fg hover:bg-surface-100",
|
||||||
|
)}
|
||||||
|
>
|
||||||
|
<span className="truncate font-mono text-xs">{String(id)}</span>
|
||||||
|
<ChevronRight className="h-3.5 w-3.5 shrink-0 text-fg-subtle" />
|
||||||
|
</button>
|
||||||
|
);
|
||||||
|
})}
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
{/* Prompt detail */}
|
||||||
|
<div className="flex flex-1 flex-col overflow-hidden rounded-lg border border-border">
|
||||||
|
{selectedPromptId ? (
|
||||||
|
<>
|
||||||
|
<div className="flex items-center justify-between border-b border-border bg-surface-100 px-4 py-3">
|
||||||
|
<h3 className="text-sm font-medium text-fg">
|
||||||
|
<span className="font-mono">{selectedPromptId}</span>
|
||||||
|
</h3>
|
||||||
|
<button
|
||||||
|
onClick={() => {
|
||||||
|
setSelectedPromptId(null);
|
||||||
|
setPromptDetail("");
|
||||||
|
}}
|
||||||
|
className="rounded-md p-1 text-fg-subtle hover:bg-surface-200 hover:text-fg"
|
||||||
|
>
|
||||||
|
<X className="h-4 w-4" />
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
<div className="flex-1 overflow-y-auto p-4">
|
||||||
|
{loadingDetail ? (
|
||||||
|
<div className="flex items-center gap-2 py-4 text-fg-subtle">
|
||||||
|
<Loader2 className="h-4 w-4 animate-spin" />
|
||||||
|
Loading...
|
||||||
|
</div>
|
||||||
|
) : (
|
||||||
|
<pre className="whitespace-pre-wrap font-mono text-xs text-fg-muted">
|
||||||
|
{promptDetail}
|
||||||
|
</pre>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
</>
|
||||||
|
) : (
|
||||||
|
<div className="flex flex-1 items-center justify-center text-fg-subtle">
|
||||||
|
Select a template to view its contents.
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{/* System Prompt tab */}
|
||||||
|
{activeTab === "system" && (
|
||||||
|
<div className="flex flex-1 flex-col overflow-hidden rounded-lg border border-border">
|
||||||
|
<div className="border-b border-border bg-surface-100 px-4 py-3">
|
||||||
|
<h3 className="text-xs font-medium uppercase tracking-wider text-fg-muted">
|
||||||
|
System Prompt
|
||||||
|
</h3>
|
||||||
|
</div>
|
||||||
|
<div className="flex-1 overflow-y-auto p-4">
|
||||||
|
{loading ? (
|
||||||
|
<div className="flex items-center gap-2 py-4 text-fg-subtle">
|
||||||
|
<Loader2 className="h-4 w-4 animate-spin" />
|
||||||
|
Loading...
|
||||||
|
</div>
|
||||||
|
) : systemPrompt ? (
|
||||||
|
<pre className="whitespace-pre-wrap font-mono text-xs text-fg-muted">
|
||||||
|
{systemPrompt}
|
||||||
|
</pre>
|
||||||
|
) : (
|
||||||
|
<p className="text-sm text-fg-subtle">No system prompt configured.</p>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
@ -51,7 +51,7 @@ function Section({
|
||||||
// ---------------------------------------------------------------------------
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
export default function SettingsPage() {
|
export default function SettingsPage() {
|
||||||
const { settings, updateSetting } = useSettings();
|
const { settings, updateSetting, updateFeatureSwitches } = useSettings();
|
||||||
const connectionState = useConnectionState();
|
const connectionState = useConnectionState();
|
||||||
const socket = useSocket();
|
const socket = useSocket();
|
||||||
const { flows } = useFlows();
|
const { flows } = useFlows();
|
||||||
|
|
@ -318,6 +318,32 @@ export default function SettingsPage() {
|
||||||
</div>
|
</div>
|
||||||
</Section>
|
</Section>
|
||||||
|
|
||||||
|
{/* Feature Switches */}
|
||||||
|
<Section
|
||||||
|
title="Feature Switches"
|
||||||
|
icon={<SettingsIcon className="h-4 w-4 text-fg-subtle" />}
|
||||||
|
>
|
||||||
|
{Object.entries(settings.featureSwitches).map(([key, enabled]) => (
|
||||||
|
<div key={key} className="flex items-center justify-between">
|
||||||
|
<div>
|
||||||
|
<p className="text-sm text-fg capitalize">{key.replace(/([A-Z])/g, " $1").trim()}</p>
|
||||||
|
</div>
|
||||||
|
<button
|
||||||
|
onClick={() => updateFeatureSwitches({ [key]: !enabled })}
|
||||||
|
className={cn(
|
||||||
|
"relative inline-flex h-6 w-11 items-center rounded-full transition-colors",
|
||||||
|
enabled ? "bg-brand-600" : "bg-surface-300",
|
||||||
|
)}
|
||||||
|
>
|
||||||
|
<span className={cn(
|
||||||
|
"inline-block h-4 w-4 rounded-full bg-white transition-transform",
|
||||||
|
enabled ? "translate-x-6" : "translate-x-1",
|
||||||
|
)} />
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
))}
|
||||||
|
</Section>
|
||||||
|
|
||||||
{/* About */}
|
{/* About */}
|
||||||
<Section
|
<Section
|
||||||
title="About"
|
title="About"
|
||||||
|
|
|
||||||
140
ts/packages/workbench/src/pages/token-cost.tsx
Normal file
140
ts/packages/workbench/src/pages/token-cost.tsx
Normal file
|
|
@ -0,0 +1,140 @@
|
||||||
|
import { useCallback, useEffect, useState } from "react";
|
||||||
|
import { Coins, Loader2, RefreshCw } from "lucide-react";
|
||||||
|
import { cn } from "@/lib/utils";
|
||||||
|
import { useSocket } from "@/providers/socket-provider";
|
||||||
|
import { useConnectionState } from "@/providers/socket-provider";
|
||||||
|
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
// Types
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
interface TokenCost {
|
||||||
|
model: string;
|
||||||
|
input_price: number;
|
||||||
|
output_price: number;
|
||||||
|
}
|
||||||
|
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
// Token Cost page
|
||||||
|
// ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
export default function TokenCostPage() {
|
||||||
|
const socket = useSocket();
|
||||||
|
const connectionState = useConnectionState();
|
||||||
|
const [costs, setCosts] = useState<TokenCost[]>([]);
|
||||||
|
const [loading, setLoading] = useState(false);
|
||||||
|
const [error, setError] = useState<string | null>(null);
|
||||||
|
|
||||||
|
const loadCosts = useCallback(async () => {
|
||||||
|
try {
|
||||||
|
setLoading(true);
|
||||||
|
setError(null);
|
||||||
|
const data = await socket.config().getTokenCosts();
|
||||||
|
setCosts(
|
||||||
|
Array.isArray(data)
|
||||||
|
? data.map((d: Record<string, unknown>) => ({
|
||||||
|
model: String(d.model ?? ""),
|
||||||
|
input_price: Number(d.input_price ?? 0),
|
||||||
|
output_price: Number(d.output_price ?? 0),
|
||||||
|
}))
|
||||||
|
: [],
|
||||||
|
);
|
||||||
|
} catch (err) {
|
||||||
|
const msg = err instanceof Error ? err.message : String(err);
|
||||||
|
setError(msg);
|
||||||
|
console.error("Failed to load token costs:", err);
|
||||||
|
} finally {
|
||||||
|
setLoading(false);
|
||||||
|
}
|
||||||
|
}, [socket]);
|
||||||
|
|
||||||
|
// Auto-load when connected
|
||||||
|
useEffect(() => {
|
||||||
|
const connected =
|
||||||
|
connectionState.status === "connected" ||
|
||||||
|
connectionState.status === "authenticated" ||
|
||||||
|
connectionState.status === "unauthenticated";
|
||||||
|
if (connected) {
|
||||||
|
loadCosts();
|
||||||
|
}
|
||||||
|
}, [connectionState.status, loadCosts]);
|
||||||
|
|
||||||
|
const formatPrice = (price: number) => {
|
||||||
|
if (price == null) return "--";
|
||||||
|
return `$${price.toFixed(2)}`;
|
||||||
|
};
|
||||||
|
|
||||||
|
return (
|
||||||
|
<div className="flex h-full flex-col">
|
||||||
|
{/* Header */}
|
||||||
|
<div className="mb-6 flex items-center justify-between">
|
||||||
|
<div className="flex items-center gap-3">
|
||||||
|
<Coins className="h-6 w-6 text-brand-400" />
|
||||||
|
<h1 className="text-2xl font-bold text-fg">Token Cost</h1>
|
||||||
|
<span className="ml-2 rounded bg-surface-200 px-2 py-0.5 text-xs text-fg-subtle">
|
||||||
|
{costs.length} model{costs.length !== 1 ? "s" : ""}
|
||||||
|
</span>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
<button
|
||||||
|
onClick={loadCosts}
|
||||||
|
disabled={loading}
|
||||||
|
className="flex items-center gap-1.5 rounded-lg border border-border px-3 py-2 text-sm text-fg-muted transition-colors hover:bg-surface-200 disabled:opacity-40"
|
||||||
|
>
|
||||||
|
<RefreshCw className={cn("h-3.5 w-3.5", loading && "animate-spin")} />
|
||||||
|
Refresh
|
||||||
|
</button>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
{/* Content */}
|
||||||
|
{loading && costs.length === 0 && (
|
||||||
|
<div className="flex items-center justify-center py-12">
|
||||||
|
<Loader2 className="mr-2 h-5 w-5 animate-spin text-fg-subtle" />
|
||||||
|
<span className="text-fg-subtle">Loading token costs...</span>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{error && (
|
||||||
|
<p className="mb-4 rounded-lg bg-error/10 px-4 py-2 text-sm text-error">
|
||||||
|
{error}
|
||||||
|
</p>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{!loading && !error && costs.length === 0 && (
|
||||||
|
<div className="flex flex-1 flex-col items-center justify-center">
|
||||||
|
<Coins className="mb-3 h-10 w-10 text-fg-subtle opacity-30" />
|
||||||
|
<p className="text-fg-subtle">No token cost data available.</p>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
|
||||||
|
{costs.length > 0 && (
|
||||||
|
<div className="overflow-x-auto rounded-lg border border-border">
|
||||||
|
<table className="w-full text-left text-sm">
|
||||||
|
<thead className="border-b border-border bg-surface-100 text-fg-muted">
|
||||||
|
<tr>
|
||||||
|
<th className="px-4 py-3 font-medium">Model</th>
|
||||||
|
<th className="px-4 py-3 font-medium text-right">Input Price ($/1M tokens)</th>
|
||||||
|
<th className="px-4 py-3 font-medium text-right">Output Price ($/1M tokens)</th>
|
||||||
|
</tr>
|
||||||
|
</thead>
|
||||||
|
<tbody className="divide-y divide-border">
|
||||||
|
{costs.map((cost) => (
|
||||||
|
<tr key={cost.model} className="hover:bg-surface-100/50">
|
||||||
|
<td className="px-4 py-3">
|
||||||
|
<span className="font-mono text-sm text-fg">{cost.model}</span>
|
||||||
|
</td>
|
||||||
|
<td className="px-4 py-3 text-right text-fg-muted">
|
||||||
|
{formatPrice(cost.input_price)}
|
||||||
|
</td>
|
||||||
|
<td className="px-4 py-3 text-right text-fg-muted">
|
||||||
|
{formatPrice(cost.output_price)}
|
||||||
|
</td>
|
||||||
|
</tr>
|
||||||
|
))}
|
||||||
|
</tbody>
|
||||||
|
</table>
|
||||||
|
</div>
|
||||||
|
)}
|
||||||
|
</div>
|
||||||
|
);
|
||||||
|
}
|
||||||
18
ts/pnpm-lock.yaml
generated
18
ts/pnpm-lock.yaml
generated
|
|
@ -8,6 +8,9 @@ importers:
|
||||||
|
|
||||||
.:
|
.:
|
||||||
devDependencies:
|
devDependencies:
|
||||||
|
falkordb:
|
||||||
|
specifier: ^5.0.0
|
||||||
|
version: 5.0.1
|
||||||
nats:
|
nats:
|
||||||
specifier: ^2.29.0
|
specifier: ^2.29.0
|
||||||
version: 2.29.3
|
version: 2.29.3
|
||||||
|
|
@ -98,6 +101,9 @@ importers:
|
||||||
'@fastify/websocket':
|
'@fastify/websocket':
|
||||||
specifier: ^11.0.0
|
specifier: ^11.0.0
|
||||||
version: 11.2.0
|
version: 11.2.0
|
||||||
|
'@mistralai/mistralai':
|
||||||
|
specifier: ^1.0.0
|
||||||
|
version: 1.15.1
|
||||||
'@qdrant/js-client-rest':
|
'@qdrant/js-client-rest':
|
||||||
specifier: ^1.13.0
|
specifier: ^1.13.0
|
||||||
version: 1.17.0(typescript@5.9.3)
|
version: 1.17.0(typescript@5.9.3)
|
||||||
|
|
@ -667,6 +673,9 @@ packages:
|
||||||
'@jridgewell/trace-mapping@0.3.31':
|
'@jridgewell/trace-mapping@0.3.31':
|
||||||
resolution: {integrity: sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw==}
|
resolution: {integrity: sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw==}
|
||||||
|
|
||||||
|
'@mistralai/mistralai@1.15.1':
|
||||||
|
resolution: {integrity: sha512-fb995eiz3r0KsBGtRjFV+/iLbX+UpfalxpF+YitT3R6ukrPD4PN+FGwwmYcRFhNAzVzDUtTVxQYnjQWEnwV5nw==}
|
||||||
|
|
||||||
'@modelcontextprotocol/sdk@1.29.0':
|
'@modelcontextprotocol/sdk@1.29.0':
|
||||||
resolution: {integrity: sha512-zo37mZA9hJWpULgkRpowewez1y6ML5GsXJPY8FI0tBBCd77HEvza4jDqRKOXgHNn867PVGCyTdzqpz0izu5ZjQ==}
|
resolution: {integrity: sha512-zo37mZA9hJWpULgkRpowewez1y6ML5GsXJPY8FI0tBBCd77HEvza4jDqRKOXgHNn867PVGCyTdzqpz0izu5ZjQ==}
|
||||||
engines: {node: '>=18'}
|
engines: {node: '>=18'}
|
||||||
|
|
@ -2962,6 +2971,15 @@ snapshots:
|
||||||
'@jridgewell/resolve-uri': 3.1.2
|
'@jridgewell/resolve-uri': 3.1.2
|
||||||
'@jridgewell/sourcemap-codec': 1.5.5
|
'@jridgewell/sourcemap-codec': 1.5.5
|
||||||
|
|
||||||
|
'@mistralai/mistralai@1.15.1':
|
||||||
|
dependencies:
|
||||||
|
ws: 8.20.0
|
||||||
|
zod: 3.25.76
|
||||||
|
zod-to-json-schema: 3.25.2(zod@3.25.76)
|
||||||
|
transitivePeerDependencies:
|
||||||
|
- bufferutil
|
||||||
|
- utf-8-validate
|
||||||
|
|
||||||
'@modelcontextprotocol/sdk@1.29.0(zod@3.25.76)':
|
'@modelcontextprotocol/sdk@1.29.0(zod@3.25.76)':
|
||||||
dependencies:
|
dependencies:
|
||||||
'@hono/node-server': 1.19.12(hono@4.12.10)
|
'@hono/node-server': 1.19.12(hono@4.12.10)
|
||||||
|
|
|
||||||
18
ts/scripts/run-llm-azure-openai.ts
Normal file
18
ts/scripts/run-llm-azure-openai.ts
Normal file
|
|
@ -0,0 +1,18 @@
|
||||||
|
/**
|
||||||
|
* Start the Azure OpenAI text-completion service.
|
||||||
|
*
|
||||||
|
* Usage: AZURE_TOKEN=... AZURE_ENDPOINT=... pnpm tsx scripts/run-llm-azure-openai.ts
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* NATS_URL (default: nats://localhost:4222)
|
||||||
|
* AZURE_TOKEN (required)
|
||||||
|
* AZURE_ENDPOINT (required)
|
||||||
|
* AZURE_MODEL (default: gpt-4o)
|
||||||
|
* AZURE_API_VERSION (default: 2024-12-01-preview)
|
||||||
|
*/
|
||||||
|
import { run } from "../packages/flow/src/model/text-completion/azure-openai.js";
|
||||||
|
|
||||||
|
run().catch((err) => {
|
||||||
|
console.error("Azure OpenAI LLM service failed:", err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
16
ts/scripts/run-llm-mistral.ts
Normal file
16
ts/scripts/run-llm-mistral.ts
Normal file
|
|
@ -0,0 +1,16 @@
|
||||||
|
/**
|
||||||
|
* Start the Mistral text-completion service.
|
||||||
|
*
|
||||||
|
* Usage: MISTRAL_TOKEN=... pnpm tsx scripts/run-llm-mistral.ts
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* NATS_URL (default: nats://localhost:4222)
|
||||||
|
* MISTRAL_TOKEN (required)
|
||||||
|
* MISTRAL_MODEL (default: ministral-8b-latest)
|
||||||
|
*/
|
||||||
|
import { run } from "../packages/flow/src/model/text-completion/mistral.js";
|
||||||
|
|
||||||
|
run().catch((err) => {
|
||||||
|
console.error("Mistral LLM service failed:", err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
17
ts/scripts/run-llm-openai-compatible.ts
Normal file
17
ts/scripts/run-llm-openai-compatible.ts
Normal file
|
|
@ -0,0 +1,17 @@
|
||||||
|
/**
|
||||||
|
* Start the OpenAI-compatible text-completion service.
|
||||||
|
*
|
||||||
|
* Usage: OPENAI_COMPAT_URL=http://localhost:1234/v1 pnpm tsx scripts/run-llm-openai-compatible.ts
|
||||||
|
*
|
||||||
|
* Env:
|
||||||
|
* NATS_URL (default: nats://localhost:4222)
|
||||||
|
* OPENAI_COMPAT_URL (required)
|
||||||
|
* OPENAI_COMPAT_KEY (default: sk-no-key-required)
|
||||||
|
* OPENAI_COMPAT_MODEL (default: default)
|
||||||
|
*/
|
||||||
|
import { run } from "../packages/flow/src/model/text-completion/openai-compatible.js";
|
||||||
|
|
||||||
|
run().catch((err) => {
|
||||||
|
console.error("OpenAI-compatible LLM service failed:", err);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
|
|
@ -551,7 +551,12 @@ async function testFullPipeline(): Promise<boolean> {
|
||||||
console.log(` FalkorDB: no nodes found (count=${count})`);
|
console.log(` FalkorDB: no nodes found (count=${count})`);
|
||||||
}
|
}
|
||||||
} catch (err) {
|
} catch (err) {
|
||||||
console.log(` FalkorDB check failed: ${err}`);
|
const errStr = String(err);
|
||||||
|
if (errStr.includes("Cannot find package") || errStr.includes("MODULE_NOT_FOUND")) {
|
||||||
|
console.log(" FalkorDB check skipped: falkordb package not available at workspace root");
|
||||||
|
} else {
|
||||||
|
console.log(` FalkorDB check failed: ${err}`);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// 6. Verify embeddings in Qdrant
|
// 6. Verify embeddings in Qdrant
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue