Update PolyAgent/gradio_interface.py

PolyAgent/gradio_interface.py

@@ -84,41 +84,45 @@ DEFAULT_TARGET_BY_PROPERTY = {
 # Run instructions bubble
 # -----------------------------------------------------------------------------
 RUN_INSTRUCTIONS_MD = (
-    "### How to run PolyAgent (one-time setup)\n"
+    "### How to use PolyAgent\n"
     "\n"
-    "**1) Environment**\n"
-    "- Activate your conda/venv where this repository is installed.\n"
-    "- Install required Python packages (project-specific; example):\n"
-    "  - `pip install gradio torch transformers numpy joblib sentencepiece requests beautifulsoup4`\n"
-    "  - If you want PNG visuals and RDKit validation: install RDKit (recommended via conda-forge).\n"
+    "PolyAgent is a web app with three **Tabs** at the top:\n"
+    "- **PolyAgent Console** (main workflow)\n"
+    "- **Tools** (run individual tools)\n"
+    "- **Other LLMs** (baseline LLM-only answers)\n"
     "\n"
-    "**2) Required model/artifact paths**\n"
-    "- Ensure these paths exist and contain the expected artifacts (as configured in `OrchestratorConfig`):\n"
-    "  - `cl_weights_path` (CL encoder weights)\n"
-    "  - `DOWNSTREAM_BESTWEIGHTS_5M_DIR` (property heads)\n"
-    "  - `INVERSE_DESIGN_5M_DIR` (inverse design generator bundles)\n"
-    "  - `spm_5M.model` (SentencePiece model)\n"
+    "#### PolyAgent Console\n"
+    "Use this Tab for the full, end-to-end run.\n"
+    "1) In **Questions**, paste your request (one question or multiple).\n"
+    "2) Click **Run PolyAgent**.\n"
+    "3) Read the results in:\n"
+    "   - **PolyAgent Answer**: the final structured response.\n"
+    "   - **PNG Artifacts**: any available visuals (molecule render, generation grid, explainability heatmap).\n"
     "\n"
-    "**3) Required environment variables**\n"
-    "- `OPENAI_API_KEY` (required for planning + composed answers)\n"
-    "- Optional:\n"
-    "  - `OPENAI_MODEL` (defaults to `gpt-4.1` in config)\n"
-    "  - `HF_TOKEN` (recommended for `materials.selfies-ted` model downloads)\n"
-    "  - `SPRINGER_NATURE_API_KEY`, `SEMANTIC_SCHOLAR_API_KEY` (improves web_search coverage)\n"
+    "**Prompt tips (what PolyAgent detects automatically):**\n"
+    "- **Inverse design / generation**: include words like `generate` or `inverse design` **and** include a numeric target\n"
+    "  (examples: `target_value=60`, `target: 60`, `Tg 60`).\n"
+    "- **Seed polymer**: provide a pSMILES either:\n"
+    "  - inside a fenced code block, or\n"
+    "  - with a keyed prefix like `seed_psmiles:`.\n"
+    "- **Citations**: if you want a specific count, say it explicitly (example: `cite 10 papers`).\n"
     "\n"
-    "**4) Start the interface**\n"
-    "- Run:\n"
-    "  - `python gradio_interface.py --server-name 0.0.0.0 --server-port 7860`\n"
+    "#### Tools (debugging / run one step at a time)\n"
+    "Use this Tab when you want to run a single tool and inspect its raw output.\n"
+    "Each section is a collapsible **Accordion** with its own inputs and a run button:\n"
+    "- **Data Extraction** (parse/canonicalize pSMILES; may also produce PNGs)\n"
+    "- **Property Prediction**\n"
+    "- **Polymer Generation (inverse design)**\n"
+    "- **Web / RAG** (search + retrieval)\n"
+    "- **Explainability**\n"
+    "- **Diagnostics** (health checks, e.g., OpenAI probe)\n"
     "\n"
-    "**5) How to prompt in the Console**\n"
-    "- To trigger inverse design: include a generation intent (e.g., “generate”, “inverse design”) and a target value.\n"
-    "- You can specify `target_value` in text (examples): `target_value=60`, `target: 60`, `Tg 60`.\n"
-    "- To seed with a polymer, include a pSMILES in a code block or via `seed_psmiles:`.\n"
-    "- To control citation count: ask explicitly (e.g., “cite 10 papers”).\n"
+    "Outputs appear as JSON (for tool results) and/or PNGs (for visuals), depending on the tool.\n"
     "\n"
-    "**Notes**\n"
-    "- Tool facts are cited as `[T]`.\n"
-    "- Literature/web/RAG citations appear inline as clickable DOI links (e.g., `[https://doi.org/...](https://doi.org/...)`) next to the claim.\n"
+    "#### Other LLMs (no tools)\n"
+    "Use this Tab to get a direct answer from a selected non-GPT model.\n"
+    "It does **not** run PolyAgent tools (no property prediction, no generation tools, no retrieval).\n"
+    "Pick a model, paste your prompt, and run it.\n"
 )
 
 def pretty_json(x: Any) -> str:
@@ -1261,7 +1265,7 @@ def build_ui() -> gr.Blocks:
     ) as demo:
         state = gr.State({})
 
-        gr.Markdown("## PolyAgent\n")
+        gr.Markdown("## PolyAgent 🧪\n")
 
         # Big bubble shown on load and retained (no dismiss / no state gating).
         gr.Markdown(RUN_INSTRUCTIONS_MD, elem_classes=["info-bubble"])