diff --git a/requirements.txt b/requirements.txt index 9f41679..d28a267 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,4 +4,3 @@ youtube-transcript-api>=0.6 google-api-python-client>=2.0.0 python-dotenv>=0.19.0 requests>=2.31.0 -sentence-transformers>=2.7.0 diff --git a/search_app.py b/search_app.py index f01a2ba..8c32be3 100644 --- a/search_app.py +++ b/search_app.py @@ -4,10 +4,8 @@ Flask application exposing search, graph, and transcript endpoints for TLC. Routes: GET / -> static HTML search page. GET /graph -> static reference graph UI. - GET /vector-search -> experimental Qdrant vector search UI. GET /api/channels -> channels aggregation. GET /api/search -> Elasticsearch keyword search. - POST /api/vector-search -> Qdrant vector similarity query. GET /api/graph -> reference graph API. GET /api/transcript -> transcript JSON payload. """ @@ -27,13 +25,6 @@ from datetime import datetime from flask import Flask, jsonify, request, send_from_directory -import requests - -try: - from sentence_transformers import SentenceTransformer # type: ignore -except ImportError: # pragma: no cover - optional dependency - SentenceTransformer = None - from .config import CONFIG, AppConfig try: @@ -44,14 +35,11 @@ except ImportError: # pragma: no cover - dependency optional BadRequestError = Exception # type: ignore LOGGER = logging.getLogger(__name__) -_EMBED_MODEL = None -_EMBED_MODEL_NAME: Optional[str] = None # Security constants MAX_QUERY_SIZE = 100 MAX_OFFSET = 10000 -ALLOWED_QDRANT_FILTER_FIELDS = {"channel_id", "date", "video_status", "external_reference"} - +DEFAULT_ELASTIC_TIMEOUT = int(os.environ.get("ELASTIC_TIMEOUT_SECONDS", "30")) def sanitize_query_string(query: str) -> str: """ @@ -74,47 +62,6 @@ def sanitize_query_string(query: str) -> str: return sanitized.strip() or "*" -def validate_qdrant_filter(filters: Any) -> Dict[str, Any]: - """ - Validate and sanitize Qdrant filter objects. - Only allows whitelisted fields to prevent filter injection. - """ - if not isinstance(filters, dict): - return {} - validated: Dict[str, Any] = {} - for key, value in filters.items(): - if key in ALLOWED_QDRANT_FILTER_FIELDS: - validated[key] = value - return validated - - -def _ensure_embedder(model_name: str) -> "SentenceTransformer": - global _EMBED_MODEL, _EMBED_MODEL_NAME - if SentenceTransformer is None: # pragma: no cover - optional dependency - raise RuntimeError( - "sentence-transformers is required for vector search. Install via pip install sentence-transformers." - ) - if _EMBED_MODEL is None or _EMBED_MODEL_NAME != model_name: - LOGGER.info("Loading embedding model: %s", model_name) - _EMBED_MODEL = SentenceTransformer(model_name) - _EMBED_MODEL_NAME = model_name - return _EMBED_MODEL - - -def embed_query(text: str, *, model_name: str, expected_dim: int) -> List[float]: - embedder = _ensure_embedder(model_name) - vector = embedder.encode( - [f"query: {text}"], - show_progress_bar=False, - normalize_embeddings=True, - )[0].tolist() - if len(vector) != expected_dim: - raise RuntimeError( - f"Embedding dimension mismatch (expected {expected_dim}, got {len(vector)})" - ) - return vector - - def _ensure_client(config: AppConfig) -> "Elasticsearch": if Elasticsearch is None: raise RuntimeError( @@ -286,7 +233,7 @@ def elastic_metrics_payload( "Elasticsearch metrics request: %s", json.dumps({"index": index, "body": body}, indent=2), ) - response = client.search(index=index, body=body) + response = client.search(index=index, body=body, request_timeout=30) break except BadRequestError as exc: last_error = exc @@ -857,7 +804,7 @@ def build_full_graph_payload( scroll_id: Optional[str] = None try: body = {"query": query, "_source": source_fields, "sort": ["_doc"]} - response = client.search(index=index, body=body, size=batch_size, scroll="1m") + response = client.search(index=index, body=body, size=batch_size, scroll="1m", request_timeout=60) scroll_id = response.get("_scroll_id") stop_fetch = False while not stop_fetch: @@ -957,11 +904,6 @@ def create_app(config: AppConfig = CONFIG) -> Flask: client = _ensure_client(config) index = config.elastic.index - qdrant_url = config.qdrant_url - qdrant_collection = config.qdrant_collection - qdrant_vector_name = config.qdrant_vector_name - qdrant_vector_size = config.qdrant_vector_size - qdrant_embed_model = config.qdrant_embed_model @app.route("/") def index_page(): @@ -971,10 +913,6 @@ def create_app(config: AppConfig = CONFIG) -> Flask: def graph_page(): return send_from_directory(app.static_folder, "graph.html") - @app.route("/vector-search") - def vector_search_page(): - return send_from_directory(app.static_folder, "vector.html") - @app.route("/static/") def static_files(filename: str): return send_from_directory(app.static_folder, filename) @@ -1260,6 +1198,7 @@ def create_app(config: AppConfig = CONFIG) -> Flask: from_=start, size=size, body=payload, + request_timeout=30, ) if config.elastic.debug: LOGGER.info( @@ -1550,145 +1489,6 @@ def create_app(config: AppConfig = CONFIG) -> Flask: def frequency_page(): return send_from_directory(app.static_folder, "frequency.html") - @app.route("/api/vector-search", methods=["POST"]) - def api_vector_search(): - payload = request.get_json(silent=True) or {} - query_text = (payload.get("query") or "").strip() - filters = validate_qdrant_filter(payload.get("filters")) - limit = min(max(int(payload.get("size", 10)), 1), MAX_QUERY_SIZE) - offset = min(max(int(payload.get("offset", 0)), 0), MAX_OFFSET) - - if not query_text: - return jsonify( - {"items": [], "totalResults": 0, "offset": offset, "error": "empty_query"} - ) - - try: - query_vector = embed_query( - query_text, model_name=qdrant_embed_model, expected_dim=qdrant_vector_size - ) - except Exception as exc: # pragma: no cover - runtime dependency - LOGGER.error("Embedding failed: %s", exc, exc_info=config.elastic.debug) - return jsonify({"error": "embedding_unavailable"}), 500 - - qdrant_vector_payload: Any - if qdrant_vector_name: - qdrant_vector_payload = {qdrant_vector_name: query_vector} - else: - qdrant_vector_payload = query_vector - - qdrant_body: Dict[str, Any] = { - "vector": qdrant_vector_payload, - "limit": limit, - "offset": offset, - "with_payload": True, - "with_vectors": False, - } - if filters: - qdrant_body["filter"] = filters - - try: - response = requests.post( - f"{qdrant_url}/collections/{qdrant_collection}/points/search", - json=qdrant_body, - timeout=20, - ) - response.raise_for_status() - data = response.json() - except Exception as exc: - LOGGER.error("Vector search failed: %s", exc, exc_info=config.elastic.debug) - return jsonify({"error": "vector_search_unavailable"}), 502 - - points = data.get("result", []) if isinstance(data, dict) else [] - items: List[Dict[str, Any]] = [] - missing_channel_ids: Set[str] = set() - for point in points: - payload = point.get("payload", {}) or {} - raw_highlights = payload.get("highlights") or [] - highlight_entries: List[Dict[str, str]] = [] - for entry in raw_highlights: - if isinstance(entry, dict): - html_value = entry.get("html") or entry.get("text") - else: - html_value = str(entry) - if not html_value: - continue - highlight_entries.append({"html": html_value, "source": "primary"}) - - channel_label = ( - payload.get("channel_name") - or payload.get("channel_title") - or payload.get("channel_id") - ) - items.append( - { - "video_id": payload.get("video_id"), - "channel_id": payload.get("channel_id"), - "channel_name": channel_label, - "title": payload.get("title"), - "titleHtml": payload.get("title"), - "description": payload.get("description"), - "descriptionHtml": payload.get("description"), - "date": payload.get("date"), - "url": payload.get("url"), - "chunkText": payload.get("text") - or payload.get("chunk_text") - or payload.get("chunk") - or payload.get("content"), - "chunkTimestamp": payload.get("timestamp") - or payload.get("start_seconds") - or payload.get("start"), - "toHighlight": highlight_entries, - "highlightSource": { - "primary": bool(highlight_entries), - "secondary": False, - }, - "distance": point.get("score"), - "internal_references_count": payload.get("internal_references_count", 0), - "internal_references": payload.get("internal_references", []), - "referenced_by_count": payload.get("referenced_by_count", 0), - "referenced_by": payload.get("referenced_by", []), - "video_status": payload.get("video_status"), - "duration": payload.get("duration"), - } - ) - if (not channel_label) and payload.get("channel_id"): - missing_channel_ids.add(str(payload.get("channel_id"))) - - if missing_channel_ids: - try: - es_lookup = client.search( - index=index, - body={ - "size": len(missing_channel_ids) * 2, - "_source": ["channel_id", "channel_name"], - "query": {"terms": {"channel_id.keyword": list(missing_channel_ids)}}, - }, - ) - hits = es_lookup.get("hits", {}).get("hits", []) - channel_lookup = {} - for hit in hits: - src = hit.get("_source", {}) or {} - cid = src.get("channel_id") - cname = src.get("channel_name") - if cid and cname and cid not in channel_lookup: - channel_lookup[cid] = cname - for item in items: - if not item.get("channel_name"): - cid = item.get("channel_id") - if cid and cid in channel_lookup: - item["channel_name"] = channel_lookup[cid] - except Exception as exc: - LOGGER.debug("Vector channel lookup failed: %s", exc) - - return jsonify( - { - "items": items, - "totalResults": len(items), - "offset": offset, - } - ) - @app.route("/api/transcript") def transcript(): video_id = request.args.get("video_id", type=str) diff --git a/static/app.js b/static/app.js index f914598..69e9205 100644 --- a/static/app.js +++ b/static/app.js @@ -1340,10 +1340,12 @@ async function updateFrequencyChart(term, channels, year, queryMode, toggles = { } const el = document.createElement("div"); el.className = "item"; + const rawTitle = item.title || "Untitled"; + const rawDescription = item.description || ""; const titleHtml = - item.titleHtml || escapeHtml(item.title || "Untitled"); + item.titleHtml || escapeHtml(rawTitle); const descriptionHtml = - item.descriptionHtml || escapeHtml(item.description || ""); + item.descriptionHtml || escapeHtml(rawDescription); const header = document.createElement("div"); header.className = "result-header"; @@ -1395,7 +1397,11 @@ async function updateFrequencyChart(term, channels, year, queryMode, toggles = { } const titleEl = document.createElement("strong"); - titleEl.innerHTML = titleHtml; + if (item.titleHtml) { + titleEl.innerHTML = titleHtml; + } else { + titleEl.textContent = rawTitle; + } headerMain.appendChild(titleEl); const metaLine = document.createElement("div"); @@ -1519,7 +1525,11 @@ async function updateFrequencyChart(term, channels, year, queryMode, toggles = { if (descriptionHtml) { const desc = document.createElement("div"); desc.className = "muted description-block"; - desc.innerHTML = descriptionHtml; + if (item.descriptionHtml) { + desc.innerHTML = descriptionHtml; + } else { + desc.textContent = rawDescription; + } el.appendChild(desc); } diff --git a/static/index.html b/static/index.html index cc1d437..37b3be5 100644 --- a/static/index.html +++ b/static/index.html @@ -5,9 +5,9 @@ TLC Search - + - +
@@ -22,10 +22,6 @@

Enter a phrase to query title, description, and transcript text.

-

- Looking for semantic matches? Try the - vector search beta. -

Search diff --git a/static/vector.html b/static/vector.html deleted file mode 100644 index 2f9fc5f..0000000 --- a/static/vector.html +++ /dev/null @@ -1,46 +0,0 @@ - - - - - - TLC Vector Search - - - - - -
-
-
Vector Search (Experimental)
-
- ⬅ Back to Search -
-
-
-

Enter a natural language prompt; results come from the Qdrant vector index.

- -
- Vector Query -
- - - -
-
- -
- -
- Results -
-
-
- -
-

Experimental mode • Qdrant

-
-
- - - - diff --git a/static/vector.js b/static/vector.js deleted file mode 100644 index ce91865..0000000 --- a/static/vector.js +++ /dev/null @@ -1,423 +0,0 @@ -(() => { - const queryInput = document.getElementById("vectorQuery"); - const searchBtn = document.getElementById("vectorSearchBtn"); - const resultsDiv = document.getElementById("vectorResults"); - const metaDiv = document.getElementById("vectorMeta"); - const transcriptCache = new Map(); - - if (!queryInput || !searchBtn || !resultsDiv || !metaDiv) { - console.error("Vector search elements missing"); - return; - } - - /** Utility helpers **/ - const escapeHtml = (str) => - (str || "").replace(/[&<>"']/g, (ch) => { - switch (ch) { - case "&": - return "&"; - case "<": - return "<"; - case ">": - return ">"; - case '"': - return """; - case "'": - return "'"; - default: - return ch; - } - }); - - const fmtDate = (value) => { - try { - return (value || "").split("T")[0]; - } catch { - return value; - } - }; - - const fmtSimilarity = (score) => { - if (typeof score !== "number" || Number.isNaN(score)) return ""; - return score.toFixed(3); - }; - - const getVideoStatus = (item) => - (item && item.video_status ? String(item.video_status).toLowerCase() : ""); - const isLikelyDeleted = (item) => getVideoStatus(item) === "deleted"; - - const formatTimestamp = (seconds) => { - if (!seconds && seconds !== 0) return "00:00"; - const hours = Math.floor(seconds / 3600); - const mins = Math.floor((seconds % 3600) / 60); - const secs = Math.floor(seconds % 60); - if (hours > 0) { - return `${hours}:${mins.toString().padStart(2, "0")}:${secs - .toString() - .padStart(2, "0")}`; - } - return `${mins}:${secs.toString().padStart(2, "0")}`; - }; - - const formatSegmentTimestamp = (segment) => { - if (!segment) return ""; - if (segment.timestamp) return segment.timestamp; - const fields = [ - segment.start_seconds, - segment.start, - segment.offset, - segment.time, - ]; - for (const value of fields) { - if (value == null) continue; - const num = parseFloat(value); - if (!Number.isNaN(num)) { - return formatTimestamp(num); - } - } - return ""; - }; - - const serializeTranscriptSection = (label, parts, fullText) => { - let content = ""; - if (typeof fullText === "string" && fullText.trim()) { - content = fullText.trim(); - } else if (Array.isArray(parts) && parts.length) { - content = parts - .map((segment) => { - const ts = formatSegmentTimestamp(segment); - const text = segment && segment.text ? segment.text : ""; - return ts ? `[${ts}] ${text}` : text; - }) - .join("\n") - .trim(); - } - if (!content) return ""; - return `${label}\n${content}\n`; - }; - - const fetchTranscriptData = async (videoId) => { - if (!videoId) return null; - if (transcriptCache.has(videoId)) { - return transcriptCache.get(videoId); - } - const res = await fetch(`/api/transcript?video_id=${encodeURIComponent(videoId)}`); - if (!res.ok) { - throw new Error(`Transcript fetch failed (${res.status})`); - } - const data = await res.json(); - transcriptCache.set(videoId, data); - return data; - }; - - const buildTranscriptDownloadText = (item, transcriptData) => { - const lines = []; - lines.push(`Title: ${item.title || "Untitled"}`); - if (item.channel_name) lines.push(`Channel: ${item.channel_name}`); - if (item.date) lines.push(`Published: ${item.date}`); - if (item.url) lines.push(`URL: ${item.url}`); - lines.push(""); - - const primaryText = serializeTranscriptSection( - "Primary Transcript", - transcriptData.transcript_parts, - transcriptData.transcript_full - ); - const secondaryText = serializeTranscriptSection( - "Secondary Transcript", - transcriptData.transcript_secondary_parts, - transcriptData.transcript_secondary_full - ); - - if (primaryText) lines.push(primaryText); - if (secondaryText) lines.push(secondaryText); - if (!primaryText && !secondaryText) { - lines.push("No transcript available."); - } - return lines.join("\n").trim() + "\n"; - }; - - const flashButtonMessage = (button, message, duration = 1800) => { - if (!button) return; - const original = button.dataset.originalLabel || button.textContent; - button.dataset.originalLabel = original; - button.textContent = message; - setTimeout(() => { - button.textContent = button.dataset.originalLabel || original; - }, duration); - }; - - const handleTranscriptDownload = async (item, button) => { - if (!item.video_id) return; - button.disabled = true; - try { - const transcriptData = await fetchTranscriptData(item.video_id); - if (!transcriptData) throw new Error("Transcript unavailable"); - const text = buildTranscriptDownloadText(item, transcriptData); - const blob = new Blob([text], { type: "text/plain" }); - const url = URL.createObjectURL(blob); - const link = document.createElement("a"); - link.href = url; - link.download = `${item.video_id}.txt`; - document.body.appendChild(link); - link.click(); - document.body.removeChild(link); - URL.revokeObjectURL(url); - flashButtonMessage(button, "Downloaded"); - } catch (err) { - console.error("Download failed", err); - alert("Unable to download transcript right now."); - } finally { - button.disabled = false; - } - }; - - const formatMlaDate = (value) => { - if (!value) return "n.d."; - const parsed = new Date(value); - if (Number.isNaN(parsed.valueOf())) return value; - const months = [ - "Jan.", "Feb.", "Mar.", "Apr.", "May", "June", - "July", "Aug.", "Sept.", "Oct.", "Nov.", "Dec.", - ]; - return `${parsed.getDate()} ${months[parsed.getMonth()]} ${parsed.getFullYear()}`; - }; - - const buildMlaCitation = (item) => { - const channel = (item.channel_name || item.channel_id || "Unknown").trim(); - const title = (item.title || "Untitled").trim(); - const url = item.url || ""; - const publishDate = formatMlaDate(item.date); - const today = formatMlaDate(new Date().toISOString().split("T")[0]); - return `${channel}. "${title}." YouTube, uploaded by ${channel}, ${publishDate}, ${url}. Accessed ${today}.`; - }; - - const handleCopyCitation = async (item, button) => { - const citation = buildMlaCitation(item); - try { - if (navigator.clipboard && window.isSecureContext) { - await navigator.clipboard.writeText(citation); - } else { - const textarea = document.createElement("textarea"); - textarea.value = citation; - textarea.style.position = "fixed"; - textarea.style.opacity = "0"; - document.body.appendChild(textarea); - textarea.select(); - document.execCommand("copy"); - document.body.removeChild(textarea); - } - flashButtonMessage(button, "Copied!"); - } catch (err) { - console.error("Citation copy failed", err); - alert(citation); - } - }; - - /** Rendering helpers **/ - const createHighlightRows = (entries) => { - if (!Array.isArray(entries) || !entries.length) return null; - const container = document.createElement("div"); - container.className = "transcript highlight-list"; - entries.forEach((entry) => { - if (!entry) return; - const row = document.createElement("div"); - row.className = "highlight-row"; - const textBlock = document.createElement("div"); - textBlock.className = "highlight-text"; - const html = entry.html || entry.text || entry; - textBlock.innerHTML = html || ""; - row.appendChild(textBlock); - const indicator = document.createElement("span"); - indicator.className = "highlight-source-indicator highlight-source-indicator--primary"; - indicator.title = "Vector highlight"; - row.appendChild(indicator); - container.appendChild(row); - }); - return container; - }; - - const createActions = (item) => { - const actions = document.createElement("div"); - actions.className = "result-actions"; - const downloadBtn = document.createElement("button"); - downloadBtn.type = "button"; - downloadBtn.className = "result-action-btn"; - downloadBtn.textContent = "Download transcript"; - downloadBtn.addEventListener("click", () => handleTranscriptDownload(item, downloadBtn)); - actions.appendChild(downloadBtn); - - const citationBtn = document.createElement("button"); - citationBtn.type = "button"; - citationBtn.className = "result-action-btn"; - citationBtn.textContent = "Copy citation"; - citationBtn.addEventListener("click", () => handleCopyCitation(item, citationBtn)); - actions.appendChild(citationBtn); - - const graphBtn = document.createElement("button"); - graphBtn.type = "button"; - graphBtn.className = "result-action-btn graph-launch-btn"; - graphBtn.textContent = "Graph"; - graphBtn.disabled = !item.video_id; - graphBtn.addEventListener("click", () => { - if (!item.video_id) return; - const target = `/graph?video_id=${encodeURIComponent(item.video_id)}`; - window.open(target, "_blank", "noopener"); - }); - actions.appendChild(graphBtn); - - return actions; - }; - - const renderVectorResults = (payload) => { - resultsDiv.innerHTML = ""; - const items = payload.items || []; - if (!items.length) { - metaDiv.textContent = "No vector matches for this prompt."; - return; - } - metaDiv.textContent = `Matches: ${items.length} (vector mode)`; - - items.forEach((item) => { - const el = document.createElement("div"); - el.className = "item"; - const header = document.createElement("div"); - header.className = "result-header"; - const headerMain = document.createElement("div"); - headerMain.className = "result-header-main"; - const titleEl = document.createElement("strong"); - titleEl.innerHTML = item.titleHtml || escapeHtml(item.title || "Untitled"); - headerMain.appendChild(titleEl); - - const metaLine = document.createElement("div"); - metaLine.className = "muted result-meta"; - const channelLabel = item.channel_name || item.channel_id || "Unknown"; - const dateLabel = fmtDate(item.date); - let durationSeconds = null; - if (typeof item.duration === "number") { - durationSeconds = item.duration; - } else if (typeof item.duration === "string" && item.duration.trim()) { - const parsed = parseFloat(item.duration); - if (!Number.isNaN(parsed)) { - durationSeconds = parsed; - } - } - const durationLabel = durationSeconds != null ? ` • ${formatTimestamp(durationSeconds)}` : ""; - metaLine.textContent = channelLabel ? `${channelLabel} • ${dateLabel}${durationLabel}` : `${dateLabel}${durationLabel}`; - if (isLikelyDeleted(item)) { - metaLine.appendChild(document.createTextNode(" ")); - const statusEl = document.createElement("span"); - statusEl.className = "result-status result-status--deleted"; - statusEl.textContent = "Likely deleted"; - metaLine.appendChild(statusEl); - } - headerMain.appendChild(metaLine); - - if (item.url) { - const linkLine = document.createElement("div"); - linkLine.className = "muted"; - const anchor = document.createElement("a"); - anchor.href = item.url; - anchor.target = "_blank"; - anchor.rel = "noopener"; - anchor.textContent = "Open on YouTube"; - linkLine.appendChild(anchor); - headerMain.appendChild(linkLine); - } - - if (typeof item.distance === "number") { - const scoreLine = document.createElement("div"); - scoreLine.className = "muted"; - scoreLine.textContent = `Similarity score: ${fmtSimilarity(item.distance)}`; - headerMain.appendChild(scoreLine); - } - - header.appendChild(headerMain); - header.appendChild(createActions(item)); - el.appendChild(header); - - if (item.descriptionHtml || item.description) { - const desc = document.createElement("div"); - desc.className = "muted description-block"; - desc.innerHTML = item.descriptionHtml || escapeHtml(item.description); - el.appendChild(desc); - } - - if (item.chunkText) { - const chunkBlock = document.createElement("div"); - chunkBlock.className = "vector-chunk"; - if (item.chunkTimestamp && item.url) { - const tsObj = - typeof item.chunkTimestamp === "object" - ? item.chunkTimestamp - : { timestamp: item.chunkTimestamp }; - const ts = formatSegmentTimestamp(tsObj); - const tsLink = document.createElement("a"); - const paramValue = - typeof item.chunkTimestamp === "number" - ? Math.floor(item.chunkTimestamp) - : item.chunkTimestamp; - tsLink.href = `${item.url}${item.url.includes("?") ? "&" : "?"}t=${encodeURIComponent( - paramValue - )}`; - tsLink.target = "_blank"; - tsLink.rel = "noopener"; - tsLink.textContent = ts ? `[${ts}]` : "[timestamp]"; - chunkBlock.appendChild(tsLink); - chunkBlock.appendChild(document.createTextNode(" ")); - } - const chunkTextSpan = document.createElement("span"); - chunkTextSpan.textContent = item.chunkText; - chunkBlock.appendChild(chunkTextSpan); - el.appendChild(chunkBlock); - } - - const highlights = createHighlightRows(item.toHighlight); - if (highlights) { - el.appendChild(highlights); - } - - resultsDiv.appendChild(el); - }); - }; - - /** Search handler **/ - const runVectorSearch = async () => { - const query = queryInput.value.trim(); - if (!query) { - alert("Please enter a query."); - return; - } - metaDiv.textContent = "Searching vector index…"; - resultsDiv.innerHTML = ""; - searchBtn.disabled = true; - try { - const res = await fetch("/api/vector-search", { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify({ query }), - }); - if (!res.ok) { - throw new Error(`Vector search failed (${res.status})`); - } - const data = await res.json(); - if (data.error) { - metaDiv.textContent = "Vector search unavailable."; - return; - } - renderVectorResults(data); - } catch (err) { - console.error(err); - metaDiv.textContent = "Vector search unavailable."; - } finally { - searchBtn.disabled = false; - } - }; - - searchBtn.addEventListener("click", runVectorSearch); - queryInput.addEventListener("keypress", (event) => { - if (event.key === "Enter") { - runVectorSearch(); - } - }); -})();