Spaces:
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Sleeping
| """ | |
| app.py — Topic Modelling Agentic AI | Gradio UI | |
| ═══════════════════════════════════════════════════ | |
| Version: 3.1.0 | April 2026 | |
| Stack: Gradio 5.x + LangGraph + Mistral + BERTopic | |
| Deploy: HuggingFace Spaces (sdk: gradio) | |
| Rules: Zero gr.HTML(). All UI via native Gradio components. | |
| See GRADIO_UI_GUIDELINES_v2.docx for full standards. | |
| ARCHITECTURE — 20 Blocks in 5 Sections | |
| ───────────────────────────────────────── | |
| Section 1: Setup (B1–B3) Imports, agent, theme | |
| Section 2: Helpers (B4–B10) Pure Python functions, no UI | |
| Section 3: UI Layout (B11–B17) gr.Blocks with native components | |
| Section 4: Event Wiring (B18–B19) Connect UI to functions | |
| Section 5: Launch (B20) Start server | |
| BLOCK COMMUNICATION MAP | |
| ───────────────────────── | |
| B6 (respond) ←→ B2 (agent) : invokes agent for chat | |
| B6 (respond) → B4 (output) : scans for download files | |
| B7 (chart) → B17a (display) : loads Plotly JSON → gr.Plot | |
| B8 (table) → B16 (review) : builds rows → gr.Dataframe | |
| B9 (papers) ← B16 (review) : triggered by row click | |
| B10 (submit) → B2 (agent) : sends review edits to agent | |
| B18 (wiring) → B5,B7,B8 : refreshes progress, charts, table | |
| """ | |
| import os | |
| import glob | |
| import json | |
| import plotly.io as pio | |
| import gradio as gr | |
| from langchain_mistralai import ChatMistralAI | |
| from langgraph.prebuilt import create_react_agent | |
| from langgraph.checkpoint.memory import MemorySaver | |
| from agent import SYSTEM_PROMPT, get_local_tools | |
| print(">>> app.py: imports complete") | |
| llm = ChatMistralAI(model="mistral-small-latest", temperature=0, timeout=300) | |
| tools = get_local_tools() | |
| agent = create_react_agent( | |
| model=llm, tools=tools, prompt=SYSTEM_PROMPT, checkpointer=MemorySaver() | |
| ) | |
| print(f">>> app.py: agent ready ({len(tools)} tools)") | |
| _msg_count = 0 # Global message counter (shared across users) | |
| _uploaded = {"path": ""} # Last uploaded CSV path (shared session) | |
| # ── end B2: Agent setup ──────────────────────────────────────── | |
| # ── B3: Theme ─────────────────────────────────────────────────── | |
| # PURPOSE: Define the visual identity of the entire application. | |
| # Uses teal/indigo on zinc — purposeful scientific feel. | |
| # Plus Jakarta Sans: geometric-humanist, modern but not generic. | |
| # Fira Code for monospace elements (phase progress, etc). | |
| # USED BY: B20 (demo.launch) — theme applied at launch time. | |
| # ──────────────────────────────────────────────────────────────── | |
| theme = gr.themes.Default( | |
| primary_hue="teal", | |
| secondary_hue="indigo", | |
| neutral_hue="zinc", | |
| font=gr.themes.GoogleFont("Plus Jakarta Sans"), | |
| font_mono=gr.themes.GoogleFont("Fira Code"), | |
| radius_size="sm", | |
| spacing_size="md", | |
| ).set( | |
| button_primary_background_fill="*primary_600", | |
| button_primary_background_fill_hover="*primary_500", | |
| button_primary_text_color="white", | |
| block_label_text_size="sm", | |
| block_title_text_weight="600", | |
| ) | |
| # ── end B3: Theme ────────────────────────────────────────────── | |
| def _latest_output(): | |
| """Scan /tmp for ALL rq4_* files, sorted by phase order. | |
| Returns list of filepaths for gr.File download component.""" | |
| phase_order = { | |
| "summaries": 1, "labels": 2, "themes": 3, "taxonomy": 4, | |
| "emb": 0, "intertopic": 5, "bars": 6, "hierarchy": 7, | |
| "heatmap": 8, "comparison": 9, "narrative": 10, | |
| } | |
| files = ( | |
| glob.glob("/tmp/rq4_*.csv") | |
| + glob.glob("/tmp/rq4_*.json") | |
| + glob.glob("/tmp/checkpoints/rq4_*.json") | |
| ) | |
| scored = list(map( | |
| lambda f: (sum(v * (k in f) for k, v in phase_order.items()), f), | |
| files, | |
| )) | |
| scored.sort(key=lambda x: x[0]) | |
| return list(map(lambda x: x[1], scored)) or None | |
| # ── end B4: _latest_output ───────────────────────────────────── | |
| def _build_progress(): | |
| """Return emoji progress pipeline. NO HTML — just text + emoji. | |
| Displayed in gr.Markdown component (B14).""" | |
| checks = [ | |
| ("Load", bool(glob.glob("/tmp/checkpoints/rq4_*_summaries.json") | |
| or glob.glob("/tmp/checkpoints/rq4_*_emb.npy"))), | |
| ("Codes", bool(glob.glob("/tmp/checkpoints/rq4_*_labels.json"))), | |
| ("Themes", bool(glob.glob("/tmp/checkpoints/rq4_*_themes.json"))), | |
| ("Review", bool(glob.glob("/tmp/checkpoints/rq4_*_themes.json"))), | |
| ("Names", bool(glob.glob("/tmp/checkpoints/rq4_*_themes.json"))), | |
| ("PAJAIS", bool(glob.glob("/tmp/checkpoints/rq4_*_taxonomy_map.json"))), | |
| ("Report", bool(glob.glob("/tmp/rq4_comparison.csv") | |
| or glob.glob("/tmp/rq4_narrative.txt"))), | |
| ] | |
| return " → ".join(f"{'✅' if done else '⬜'} {name}" for name, done in checks) | |
| # ── end B5: _build_progress ──────────────────────────────────── | |
| def respond(message, chat_history, uploaded_file): | |
| """Handle one chat turn with the LangGraph agent. | |
| Yields twice: progress bubble → final response.""" | |
| global _msg_count | |
| _msg_count += 1 | |
| # Store file path — uses `or` short-circuit instead of if/else | |
| _uploaded["path"] = uploaded_file or _uploaded.get("path", "") | |
| # Tell agent where the CSV is (prevents hallucinated filepaths) | |
| file_note = ( | |
| f"\n[CSV file at: {_uploaded['path']}]" * bool(_uploaded["path"]) | |
| ) or "\n[No CSV uploaded yet — ask user to upload a file first]" | |
| # Tell agent what phase we're in based on existing checkpoint files | |
| phase_context = ( | |
| "\n[Phase context: labels exist]" | |
| * bool(glob.glob("/tmp/checkpoints/rq4_*_labels.json")) | |
| or "\n[Phase context: embeddings exist]" | |
| * bool(glob.glob("/tmp/checkpoints/rq4_*_emb.npy")) | |
| or "\n[Phase context: fresh start]" | |
| ) | |
| text = ((message or "").strip() or "Analyze my Scopus CSV") + file_note + phase_context | |
| print(f"\n{'='*60}\n>>> MSG #{_msg_count}: '{text[:120]}'\n{'='*60}") | |
| # YIELD 1: Show "thinking" bubble immediately | |
| chat_history = chat_history + [ | |
| {"role": "user", "content": (message or "").strip()}, | |
| {"role": "assistant", "content": "🔬 **Working...** _Agent is thinking..._"}, | |
| ] | |
| yield chat_history, "", _latest_output() | |
| # Invoke agent — Mistral brain decides which tools to call | |
| result = agent.invoke( | |
| {"messages": [("human", text)]}, | |
| config={"configurable": {"thread_id": "session"}}, | |
| ) | |
| response = result["messages"][-1].content | |
| print(f">>> Response ({len(response)} chars)") | |
| # YIELD 2: Replace thinking bubble with actual response | |
| chat_history[-1] = {"role": "assistant", "content": response} | |
| gr.Info(f"Agent responded ({len(response)} chars)") | |
| yield chat_history, "", _latest_output() | |
| # ── end B6: respond ──────────────────────────────────────────── | |
| def _load_chart(chart_name): | |
| """Load Plotly chart from JSON file. Returns figure for gr.Plot. | |
| No HTML, no iframe — just a native Plotly figure object.""" | |
| path = f"/tmp/{chart_name}" | |
| (not os.path.exists(path)) and (not None) # guard | |
| return pio.from_json(open(path).read()) * bool(os.path.exists(path)) or None | |
| def _get_chart_choices(): | |
| """Find all rq4_*.json chart files in /tmp.""" | |
| files = sorted(glob.glob("/tmp/rq4_*.json")) | |
| return list(map(os.path.basename, files)) | |
| # ── end B7: _load_chart ─────────────────────────────────────── | |
| def _load_review_table(): | |
| """Build review table from latest checkpoint JSON. | |
| Approve column is bool (renders as checkbox in gr.Dataframe). | |
| Priority: taxonomy_map > themes > labels > summaries.""" | |
| taxonomy_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_taxonomy_map.json")) | |
| theme_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_themes.json")) | |
| label_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_labels.json")) | |
| summary_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_summaries.json")) | |
| # Pick most advanced checkpoint available | |
| path = ( | |
| (taxonomy_files and taxonomy_files[-1]) | |
| or (theme_files and theme_files[-1]) | |
| or (label_files and label_files[-1]) | |
| or (summary_files and summary_files[-1]) | |
| or "" | |
| ) | |
| is_taxonomy = bool(taxonomy_files and taxonomy_files[-1] == path) | |
| data = (os.path.exists(path) and json.load(open(path))) or [] | |
| # For taxonomy: merge with themes to get sentence/paper counts | |
| theme_lookup = {} | |
| (is_taxonomy and theme_files) and theme_lookup.update( | |
| {t.get("label", ""): t for t in json.load(open(theme_files[-1]))} | |
| ) | |
| rows = list(map( | |
| lambda pair: [ | |
| pair[0], # # | |
| pair[1].get("label", pair[1].get("top_words", ""))[:60], # Label | |
| # Evidence: PAJAIS mapping for taxonomy, nearest sentence otherwise | |
| ( | |
| is_taxonomy | |
| and f"→ {pair[1].get('pajais_match', '?')} | {pair[1].get('reasoning', '')}"[:120] | |
| ) or ( | |
| (pair[1].get("nearest", [{}])[0].get("sentence", "")[:120] + "...") | |
| * bool(pair[1].get("nearest")) | |
| ), | |
| # Sentence/paper counts | |
| theme_lookup.get(pair[1].get("label", ""), pair[1]).get( | |
| "sentence_count", pair[1].get("sentence_count", 0)), | |
| theme_lookup.get(pair[1].get("label", ""), pair[1]).get( | |
| "paper_count", pair[1].get("paper_count", 0)), | |
| True, # Approve (bool → checkbox) | |
| "", # Rename To | |
| "", # Reasoning | |
| ], | |
| enumerate(data), | |
| )) | |
| return rows or [[0, "No data yet", "", 0, 0, False, "", ""]] | |
| # ── end B8: _load_review_table ───────────────────────────────── | |
| def _show_papers_by_select(table_data, evt: gr.SelectData): | |
| """Show papers for clicked row. Uses column 0 as topic_id. | |
| Triggered by review_table.select() — no separate Topic # input needed.""" | |
| row_idx = evt.index[0] | |
| # Get topic_id from column 0 of the clicked row (not row index) | |
| topic_id = int(table_data.iloc[row_idx, 0]) if hasattr(table_data, 'iloc') else int(table_data[row_idx][0]) | |
| # Load paper data from checkpoint files | |
| label_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_labels.json")) | |
| summary_files = sorted(glob.glob("/tmp/checkpoints/rq4_*_summaries.json")) | |
| all_files = label_files or summary_files | |
| lines = [] | |
| for f in all_files: | |
| source = os.path.basename(f).split("_")[1] | |
| data = json.load(open(f)) | |
| for t in data: | |
| (t.get("topic_id") == topic_id) and lines.append( | |
| f"═══ {source.upper()} — Topic {topic_id}: " | |
| f"{t.get('label', t.get('top_words', '')[:50])} ═══\n" | |
| f"{t.get('sentence_count', 0)} sentences from {t.get('paper_count', 0)} papers\n" | |
| f"AI Reasoning: {t.get('reasoning', 'not yet labeled')}\n\n" | |
| f"── 5 NEAREST CENTROID SENTENCES (evidence) ──\n" | |
| + "\n".join( | |
| f" {i+1}. \"{t['nearest'][i]['sentence'][:200]}\"\n" | |
| f" Paper: {t['nearest'][i].get('title', '')[:100]}" | |
| for i in range(min(5, len(t.get('nearest', [])))) | |
| ) | |
| + "\n\n── ALL PAPER TITLES ──\n" | |
| + "\n".join( | |
| f" {i+1}. {title}" | |
| for i, title in enumerate(t.get('paper_titles', [])) | |
| ) | |
| ) | |
| return "\n\n".join(lines) or f"Topic {topic_id} not found." | |
| # ── end B9: _show_papers_by_select ───────────────────────────── | |
| def _submit_review(table_data, chat_history): | |
| """Convert review table edits into agent message. | |
| Approve column is bool (checkbox), not string.""" | |
| rows = table_data.values.tolist() | |
| lines = list(map( | |
| lambda r: ( | |
| f"Topic {int(r[0])}: " | |
| + (f"RENAME to '{r[6]}'" * bool(str(r[6]).strip())) | |
| + (f"APPROVE '{r[1]}'" * (not bool(str(r[6]).strip())) * bool(r[5])) | |
| + (f"REJECT" * (not r[5])) | |
| + (f" — reason: {r[7]}" * bool(str(r[7]).strip())) | |
| ), | |
| rows, | |
| )) | |
| review_msg = "Review decisions:\n" + "\n".join(lines) | |
| print(f">>> Review submitted: {review_msg[:200]}") | |
| # YIELD 1: Show processing bubble | |
| chat_history = chat_history + [ | |
| {"role": "user", "content": review_msg}, | |
| {"role": "assistant", "content": "🔬 **Processing review decisions...**"}, | |
| ] | |
| gr.Info("Review submitted to agent") | |
| yield (chat_history, _latest_output(), gr.update(), | |
| gr.update(), gr.update(), _build_progress()) | |
| # Invoke agent with review decisions | |
| result = agent.invoke( | |
| {"messages": [("human", review_msg)]}, | |
| config={"configurable": {"thread_id": "session"}}, | |
| ) | |
| response = result["messages"][-1].content | |
| # YIELD 2: Final response + refreshed table/charts | |
| chat_history[-1] = {"role": "assistant", "content": response} | |
| gr.Info("Review processed — table updated") | |
| yield ( | |
| chat_history, | |
| _latest_output(), | |
| gr.update(choices=_get_chart_choices()), | |
| gr.update(), | |
| gr.update(value=_load_review_table()), | |
| _build_progress(), | |
| ) | |
| print(">>> Building UI...") | |
| with gr.Blocks( | |
| title="Topic Modelling — Agentic AI", | |
| fill_width=True, | |
| css=""" | |
| /* Accent bar at very top of page */ | |
| .gradio-container::before { | |
| content: ""; | |
| display: block; | |
| height: 3px; | |
| background: linear-gradient(90deg, #0d9488, #6366f1); | |
| margin-bottom: 4px; | |
| } | |
| /* Tabs: tighter padding, bolder active state */ | |
| .tab-nav button { | |
| font-size: 13px !important; | |
| font-weight: 500 !important; | |
| letter-spacing: 0.01em; | |
| padding: 6px 16px !important; | |
| } | |
| .tab-nav button.selected { | |
| font-weight: 700 !important; | |
| border-bottom: 2px solid #0d9488 !important; | |
| } | |
| /* Dataframe: subtle zebra rows */ | |
| .table-wrap tr:nth-child(even) td { | |
| background-color: rgba(13, 148, 136, 0.04); | |
| } | |
| /* Chat: teal left-border on assistant bubbles */ | |
| .message.bot { | |
| border-left: 3px solid #0d9488 !important; | |
| } | |
| /* Phase progress: monospace, slightly muted */ | |
| .phase-bar p { | |
| font-family: "Fira Code", monospace; | |
| font-size: 12px; | |
| letter-spacing: 0.03em; | |
| opacity: 0.80; | |
| } | |
| /* Upload area: cleaner dashed border */ | |
| .upload-container { | |
| border-style: dashed !important; | |
| border-width: 1px !important; | |
| } | |
| """, | |
| ) as demo: | |
| # ── B12: Header ──────────────────────────────────────────── | |
| # PURPOSE: Application title and subtitle. | |
| # ─────────────────────────────────────────────────────────── | |
| gr.Markdown( | |
| "# 🔬 Topic Modelling · Agentic AI\n" | |
| "<sub>Mistral · Cosine Clustering · 384d Embeddings · Braun & Clarke Thematic Analysis</sub>" | |
| ) | |
| # ── end B12: Header ──────────────────────────────────────── | |
| # ── B13: Data input ──────────────────────────────────────── | |
| # PURPOSE: CSV file upload area with inline instructions. | |
| # Researcher uploads their Scopus CSV export here. | |
| # On upload, B19 auto-triggers the first analysis. | |
| # COMPONENTS: gr.File (upload) + gr.Markdown (instructions) | |
| # EVENTS: upload.change → B19 (_auto_load_csv) | |
| # ─────────────────────────────────────────────────────────── | |
| gr.Markdown("**① Upload**") | |
| with gr.Row(): | |
| upload = gr.File(label="📂 Scopus CSV", file_types=[".csv"]) | |
| gr.Markdown( | |
| "Upload your Scopus CSV export, then type `run abstract only` in the chat below " | |
| "to begin the analysis pipeline." | |
| ) | |
| # ── end B13: Data input ──────────────────────────────────── | |
| # ── B14: Progress pipeline ───────────────────────────────── | |
| # PURPOSE: Visual indicator of which Braun & Clarke analysis | |
| # phases are complete. Updated after every agent action. | |
| # elem_classes="phase-bar" targets the monospace CSS rule in B11. | |
| # COMPONENT: gr.Markdown — displays emoji string from B5 | |
| # UPDATED BY: B18 (after chat), B10 (after review), B19 (after upload) | |
| # ─────────────────────────────────────────────────────────── | |
| phase_progress = gr.Markdown(value=_build_progress(), elem_classes=["phase-bar"]) | |
| # ── end B14: Progress pipeline ───────────────────────────── | |
| # ── B15: Chatbot + input ─────────────────────────────────── | |
| # PURPOSE: Main conversation interface between researcher and | |
| # the LangGraph agent. | |
| # COMPONENTS: gr.Chatbot (display), gr.Textbox (input), gr.Button (send) | |
| # EVENTS: msg.submit → B18, send.click → B18 | |
| # ─────────────────────────────────────────────────────────── | |
| gr.Markdown("**② Conversation** — follow the guided workflow") | |
| with gr.Group(): | |
| chatbot = gr.Chatbot( | |
| height=320, | |
| show_label=False, | |
| avatar_images=( | |
| None, | |
| "https://api.dicebear.com/7.x/bottts-neutral/svg?seed=bertopic", | |
| ), | |
| placeholder=( | |
| "**Ready.** Upload a Scopus CSV above, then type:\n\n" | |
| "`run abstract only` · `approve all` · `show topic 4 papers` · `done`" | |
| ), | |
| ) | |
| with gr.Row(): | |
| msg = gr.Textbox( | |
| placeholder="run · approve · show topic 4 papers · group 0 1 5 · done", | |
| show_label=False, scale=9, lines=1, max_lines=1, container=False, | |
| ) | |
| send = gr.Button("⏎ Send", variant="primary", scale=1, min_width=80) | |
| # ── end B15: Chatbot + input ─────────────────────────────── | |
| # ── B16: Review table tab ────────────────────────────────── | |
| # PURPOSE: Interactive topic review table where the researcher | |
| # approves, renames, or annotates BERTopic-discovered | |
| # topics. This is the core human-in-the-loop interface. | |
| # | |
| # KEY FEATURES (all native Gradio, no HTML): | |
| # - static_columns=[0,1,2,3,4] — first 5 columns read-only | |
| # - datatype "bool" on column 5 — Approve renders as checkbox | |
| # - pinned_columns=2 — # and Label stay visible when scrolling | |
| # - show_search="filter" — built-in column filtering | |
| # - .select() event — clicking any row auto-loads that topic's papers | |
| # | |
| # COMPONENTS: gr.Dataframe, gr.Button (submit), gr.Textbox (papers) | |
| # EVENTS: review_table.select → B9, submit_review.click → B10 | |
| # ─────────────────────────────────────────────────────────── | |
| gr.Markdown("**③ Review & Export**") | |
| with gr.Tabs(): | |
| with gr.Tab("📋 Topics"): | |
| gr.Markdown( | |
| "*Toggle **Approve**, fill in **Rename To** or **Reasoning**, " | |
| "then click Submit. Click any row to inspect its source papers below.*" | |
| ) | |
| review_table = gr.Dataframe( | |
| headers=[ | |
| "#", "Topic Label", "Top Evidence Sentence", | |
| "Sentences", "Papers", "Approve", "Rename To", "Your Reasoning", | |
| ], | |
| datatype=[ | |
| "number", "str", "str", "number", "number", | |
| "bool", "str", "str", | |
| ], | |
| interactive=True, | |
| column_count=8, | |
| # NOTE: These features need Gradio >=5.23. Uncomment when available: | |
| # static_columns=[0, 1, 2, 3, 4], | |
| # pinned_columns=2, | |
| # show_search="filter", | |
| # show_row_numbers=True, | |
| # show_fullscreen_button=True, | |
| # show_copy_button=True, | |
| # column_widths=["60px","200px","250px","80px","70px","70px","150px","200px"], | |
| ) | |
| submit_review = gr.Button("✅ Submit Review to Agent", variant="primary") | |
| gr.Markdown("---") | |
| gr.Markdown("**📄 Papers in selected topic** *(click any row above)*") | |
| paper_list = gr.Textbox( | |
| label="Papers in selected topic", | |
| lines=8, interactive=False, | |
| ) | |
| # ── end B16: Review table tab ────────────────────────────── | |
| # ── B17a: Charts tab ─────────────────────────────────── | |
| # PURPOSE: Display BERTopic visualization charts rendered | |
| # natively in gr.Plot from Plotly JSON files. | |
| # COMPONENTS: gr.Dropdown (selector), gr.Plot (display) | |
| # EVENTS: chart_selector.change → B7 (_load_chart) | |
| # ─────────────────────────────────────────────────────── | |
| with gr.Tab("📊 Visualise"): | |
| chart_selector = gr.Dropdown( | |
| choices=[], label="Select chart", interactive=True, | |
| ) | |
| chart_display = gr.Plot(label="BERTopic Visualization") | |
| # ── end B17a: Charts tab ─────────────────────────────── | |
| # ── B17b: Download tab ───────────────────────────────── | |
| # PURPOSE: Multi-file download for all pipeline outputs. | |
| # COMPONENTS: gr.Markdown (descriptions), gr.File (download) | |
| # UPDATED BY: B18, B10, B19 — refreshed after each action | |
| # ─────────────────────────────────────────────────────── | |
| with gr.Tab("⬇ Export"): | |
| gr.Markdown( | |
| "**Files by Phase (per run: abstract / title):**\n\n" | |
| "**Phase 2 — Discovery:** `summaries.json` · `emb.npy`\n\n" | |
| "**Phase 2 — Labeling:** `labels.json`\n\n" | |
| "**Phase 2 — Charts:** `intertopic.json` · `bars.json` · " | |
| "`hierarchy.json` · `heatmap.json`\n\n" | |
| "**Phase 3 — Themes:** `themes.json`\n\n" | |
| "**Phase 5.5 — Taxonomy:** `taxonomy_map.json`\n\n" | |
| "**Phase 6 — Report:** `comparison.csv` · `narrative.txt`" | |
| ) | |
| download = gr.File(label="All output files", file_count="multiple") | |
| # ── end B17b: Download tab ───────────────────────────── | |
| chart_selector.change(_load_chart, [chart_selector], [chart_display]) | |
| review_table.select( | |
| _show_papers_by_select, [review_table], [paper_list], | |
| ) | |
| submit_review.click( | |
| _submit_review, [review_table, chatbot], | |
| [chatbot, download, chart_selector, chart_display, | |
| review_table, phase_progress], | |
| ) | |
| def respond_with_viz(message, chat_history, uploaded_file): | |
| """Wrap respond() and update charts + table + progress after each turn.""" | |
| gen = respond(message, chat_history, uploaded_file) | |
| # First yield (progress bubble) | |
| hist, txt, dl = next(gen) | |
| yield (hist, txt, dl, gr.update(choices=_get_chart_choices()), | |
| gr.update(), gr.update(), _build_progress()) | |
| # Second yield (final response + populate table + charts) | |
| hist, txt, dl = next(gen) | |
| choices = _get_chart_choices() | |
| first_chart = (choices and _load_chart(choices[-1])) or gr.update() | |
| table_data = _load_review_table() | |
| yield ( | |
| hist, txt, dl, | |
| gr.update(choices=choices, value=(choices and choices[-1]) or None), | |
| first_chart, | |
| gr.update(value=table_data), | |
| _build_progress(), | |
| ) | |
| msg.submit( | |
| respond_with_viz, [msg, chatbot, upload], | |
| [chatbot, msg, download, chart_selector, chart_display, | |
| review_table, phase_progress], | |
| ) | |
| send.click( | |
| respond_with_viz, [msg, chatbot, upload], | |
| [chatbot, msg, download, chart_selector, chart_display, | |
| review_table, phase_progress], | |
| ) | |
| # ── end B18: respond_with_viz + event bindings ───────────── | |
| # ── B19: _auto_load_csv() ────────────────────────────────── | |
| # PURPOSE: Automatically triggers analysis when a CSV file is | |
| # uploaded. Sends "Analyze my Scopus CSV" as the | |
| # initial message so no manual typing is needed. | |
| # TRIGGERED BY: upload.change event | |
| # CALLS: B6 (respond) with auto-message | |
| # OUTPUTS: chatbot, download, chart_selector, chart_display, | |
| # review_table, phase_progress | |
| # ─────────────────────────────────────────────────────────── | |
| def _auto_load_csv(uploaded_file, chat_history): | |
| """Auto-trigger analysis when CSV is uploaded — no typing needed.""" | |
| gen = respond("Analyze my Scopus CSV", chat_history, uploaded_file) | |
| # First yield (progress) | |
| hist, txt, dl = next(gen) | |
| yield (hist, dl, gr.update(), gr.update(), | |
| gr.update(), _build_progress()) | |
| # Second yield (final + populate everything) | |
| hist, txt, dl = next(gen) | |
| choices = _get_chart_choices() | |
| first_chart = (choices and _load_chart(choices[-1])) or gr.update() | |
| table_data = _load_review_table() | |
| yield ( | |
| hist, dl, | |
| gr.update(choices=choices, value=(choices and choices[-1]) or None), | |
| first_chart, | |
| gr.update(value=table_data), | |
| _build_progress(), | |
| ) | |
| upload.change( | |
| _auto_load_csv, [upload, chatbot], | |
| [chatbot, download, chart_selector, chart_display, | |
| review_table, phase_progress], | |
| ) | |
| # ── end B19: _auto_load_csv ──────────────────────────────── | |
| print(">>> Launching...") | |
| demo.launch( | |
| server_name="0.0.0.0", | |
| server_port=7860, | |
| ssr_mode=False, | |
| theme=theme, # Gradio 6: moved from gr.Blocks() | |
| footer_links=[], # Gradio 6: hides footer, replaces show_api | |
| ) | |
| # ── end B20: Launch ──────────────────────────────────────────── |