feat: add logo

README.md

@@ -1,5 +1,5 @@
 ---
-title: InstaNovo De Novo Peptide Sequencing
+title: De Novo Peptide Sequencing With InstaNovo
 emoji: 🚀🧪
 colorFrom: blue
 colorTo: green
@@ -10,7 +10,7 @@ pinned: true
 license: apache-2.0
 ---
 
-# InstaNovo _De Novo_ Peptide Sequencing Demo
+# _De Novo_ Peptide Sequencing With InstaNovo 
 
 This Space provides a web interface for the [InstaNovo](https://github.com/instadeepai/InstaNovo) model for _de novo_ peptide sequencing from mass spectrometry data.
 

app.py

@@ -9,7 +9,6 @@ from pathlib import Path
 from omegaconf import OmegaConf, DictConfig
 
 # --- InstaNovo Imports ---
-# It's good practice to handle potential import issues
 try:
     from instanovo.transformer.model import InstaNovo
     from instanovo.utils import SpectrumDataFrame, ResidueSet, Metrics
@@ -24,10 +23,7 @@ try:
     from instanovo.constants import MASS_SCALE, MAX_MASS
     from torch.utils.data import DataLoader
 except ImportError as e:
-    print(f"Error importing InstaNovo components: {e}")
-    print("Please ensure InstaNovo is installed correctly.")
-    # Optionally, raise the error or exit if InstaNovo is critical
-    # raise e
+    raise ImportError("Failed to import InstaNovo components: {e}")
 
 # --- Configuration ---
 MODEL_ID = "instanovo-v1.1.0" # Use the desired pretrained model ID
@@ -44,6 +40,10 @@ KNAPSACK: Knapsack | None = None
 MODEL_CONFIG: DictConfig | None = None
 RESIDUE_SET: ResidueSet | None = None
 
+# Assets
+gr.set_static_paths(paths=[Path.cwd().absolute()/"assets"])
+
+
 def load_model_and_knapsack():
     """Loads the InstaNovo model and generates/loads the knapsack."""
     global MODEL, KNAPSACK, MODEL_CONFIG, RESIDUE_SET
@@ -63,7 +63,6 @@ def load_model_and_knapsack():
         raise gr.Error(f"Failed to load InstaNovo model: {MODEL_ID}. Error: {e}")
 
     # --- Knapsack Handling ---
-    KNAPSACK_DIR.mkdir(parents=True, exist_ok=True)
     knapsack_exists = (
         (KNAPSACK_DIR / "parameters.pkl").exists() and
         (KNAPSACK_DIR / "masses.npy").exists() and
@@ -116,7 +115,7 @@ def load_model_and_knapsack():
             print("Knapsack saved.")
         except Exception as e:
             print(f"Error generating or saving knapsack: {e}")
-            gr.Warning("Failed to generate Knapsack. Knapsack Beam Search will not be available.")
+            gr.Warning("Failed to generate Knapsack. Knapsack Beam Search will not be available. {e}")
             KNAPSACK = None # Ensure it's None if generation failed
 
 # Load the model and knapsack when the script starts
@@ -405,12 +404,25 @@ css = """
 .gradio-container { font-family: sans-serif; }
 .gr-button { color: white; border-color: black; background: black; }
 footer { display: none !important; }
+/* Optional: Add some margin below the logo */
+.logo-container img { margin-bottom: 1rem; }
 """
 
 with gr.Blocks(css=css, theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue")) as demo:
+    # --- Logo Display ---
+    gr.Markdown(
+        """
+        <div style="text-align: center;" class="logo-container">
+          <img src='/gradio_api/file=assets/instanovo.svg' alt="InstaNovo Logo" width="300" style="display: block; margin: 0 auto;">
+        </div>
+        """,
+        elem_classes="logo-container" # Optional class for CSS targeting
+    )
+
+    # --- App Content ---
     gr.Markdown(
         """
-        # 🚀 InstaNovo _De Novo_ Peptide Sequencing
+        # 🚀 _De Novo_ Peptide Sequencing with InstaNovo 
         Upload your mass spectrometry data file (.mgf, .mzml, or .mzxml) and get peptide sequence predictions using InstaNovo.
         Choose between fast Greedy Search or more accurate but slower Knapsack Beam Search.
         """
@@ -422,13 +434,13 @@ with gr.Blocks(css=css, theme=gr.themes.Default(primary_hue="blue", secondary_hu
                 file_types=[".mgf", ".mzml", ".mzxml"]
             )
             decoding_method = gr.Radio(
-                ["Greedy Search (Fast)", "Knapsack Beam Search (More accurate, but slower)"],
+                ["Greedy Search (Fast, resonably accurate)", "Knapsack Beam Search (More accurate, but slower)"],
                 label="Decoding Method",
-                value="Greedy Search (Fast)" # Default to fast method
+                value="Greedy Search (Fast, resonably accurate)" # Default to fast method
             )
             submit_btn = gr.Button("Predict Sequences", variant="primary")
         with gr.Column(scale=2):
-            output_df = gr.DataFrame(label="Prediction Results", wrap=True)
+            output_df = gr.DataFrame(label="Prediction Results", headers=["scan_number", "precursor_mz", "precursor_charge", "prediction", "log_probability", "delta_mass_ppm"], wrap=True)
             output_file = gr.File(label="Download Full Results (CSV)")
 
     submit_btn.click(
@@ -438,7 +450,8 @@ with gr.Blocks(css=css, theme=gr.themes.Default(primary_hue="blue", secondary_hu
     )
 
     gr.Examples(
-         [["./sample_spectra.mgf", "Knapsack Beam Search (Accurate, 5 Beams)"]], # Requires test data fetched
+         [["assets/sample_spectra.mgf", "Greedy Search (Fast, resonably accurate)" ],
+         ["assets/sample_spectra.mgf", "Knapsack Beam Search (More accurate, but slower)" ]],
          inputs=[input_file, decoding_method],
          outputs=[output_df, output_file],
          fn=predict_peptides,
@@ -451,7 +464,7 @@ with gr.Blocks(css=css, theme=gr.themes.Default(primary_hue="blue", secondary_hu
          **Notes:**
          *   Predictions are based on the [InstaNovo](https://github.com/instadeepai/InstaNovo) model ({MODEL_ID}).
          *   Knapsack Beam Search uses pre-calculated mass constraints and yields better results but takes longer.
-         *   'delta_mass_ppm' shows the lowest absolute precursor mass error (in ppm) across potential isotopes (0-1 neutron).
+         *   `delta_mass_ppm` shows the lowest absolute precursor mass error (in ppm) across potential isotopes (0-1 neutron).
          *   Ensure your input file format is correctly specified. Large files may take time to process.
          """.format(MODEL_ID=MODEL_ID)
     )

sample_spectrum.mgf

@@ -1,33 +0,0 @@
-BEGIN IONS
-TITLE=0
-PEPMASS=451.25348
-CHARGE=2+
-SCANS=F1:2478
-RTINSECONDS=824.574
-SEQ=IAHYNKR
-63.994834899902344 0.0611930787563324
-70.06543731689453 0.06860413402318954
-84.081298828125 0.22455614805221558
-85.08439636230469 0.06763620674610138
-86.09666442871094 0.22344912588596344
-110.07109069824219 0.3034861385822296
-129.1020050048828 0.0932231917977333
-138.06597900390625 0.07667151838541031
-157.13291931152344 0.14716865122318268
-175.1185302734375 0.19198034703731537
-185.1283721923828 0.09717456996440887
-209.10263061523438 0.13139843940734863
-273.1337890625 0.09324286878108978
-301.1282958984375 0.08515828102827072
-303.21221923828125 0.07235292345285416
-304.17529296875 0.07120858132839203
-322.1859130859375 0.15834060311317444
-350.6787414550781 0.07397215068340302
-417.2552185058594 0.14982180297374725
-580.3185424804688 0.31572264432907104
-630.36572265625 0.06255878508090973
-717.376708984375 0.5990896821022034
-753.3748779296875 0.09976936876773834
-788.4207763671875 0.35858696699142456
-866.4544677734375 0.12016354501247406
-END IONS

uv.lock

@@ -801,35 +801,67 @@ wheels = [
 
 [[package]]
 name = "instanovo"
-version = "1.0.0"
-source = { registry = "https://pypi.org/simple" }
+version = "1.1.0"
+source = { path = "../dtu-denovo-sequencing/dist/instanovo-1.1.0-py3-none-any.whl" }
 dependencies = [
-    { name = "click" },
     { name = "datasets" },
+    { name = "gitpython" },
     { name = "hydra-core" },
     { name = "jaxtyping" },
     { name = "jiwer" },
+    { name = "lightning" },
     { name = "matchms" },
     { name = "neptune" },
     { name = "numpy" },
     { name = "omegaconf" },
     { name = "pandas" },
     { name = "polars" },
-    { name = "pyopenms" },
+    { name = "pyteomics" },
     { name = "python-dotenv" },
-    { name = "pytorch-lightning" },
+    { name = "pyyaml" },
+    { name = "requests" },
     { name = "s3fs" },
     { name = "scikit-learn" },
     { name = "spectrum-utils" },
     { name = "tensorboard" },
-    { name = "torch" },
     { name = "tqdm" },
+    { name = "transfusion-asr" },
+    { name = "typer" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/12/a5/e97bec7c26bdd165f23108cb6c048ff50e75c3eced8b08b052c5e0d7ac25/instanovo-1.0.0.tar.gz", hash = "sha256:fd9cfc377d9f8da5272f96b2eb4c14c08b579d7a65466aa402601ec6c4b42672", size = 70720 }
 wheels = [
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+    { filename = "instanovo-1.1.0-py3-none-any.whl", hash = "sha256:388ad39f7d458e790e44a9b5655312664e74cee468ce7268fb52740063af557b" },
 ]
 
+[package.metadata]
+requires-dist = [
+    { name = "datasets", specifier = ">=3.1.0" },
+    { name = "gitpython", specifier = ">=3.1.44" },
+    { name = "hydra-core", specifier = ">=1.3.2" },
+    { name = "jaxtyping", specifier = ">=0.2.34" },
+    { name = "jiwer", specifier = ">=3.0.5" },
+    { name = "lightning", specifier = ">=2.5.1" },
+    { name = "matchms", specifier = ">=0.28.1" },
+    { name = "neptune", specifier = ">=1.13.0" },
+    { name = "numpy", specifier = ">=2.0.2" },
+    { name = "omegaconf", specifier = ">=2.3.0" },
+    { name = "pandas", specifier = ">=2.2.3" },
+    { name = "polars", specifier = ">=1.12.0" },
+    { name = "pyteomics", specifier = ">=4.7.5" },
+    { name = "python-dotenv", specifier = ">=1.0.1" },
+    { name = "pyyaml", specifier = ">=6.0.2" },
+    { name = "requests", specifier = ">=2.32.3" },
+    { name = "s3fs", specifier = ">=2024.9.0" },
+    { name = "scikit-learn", specifier = ">=1.5.2" },
+    { name = "spectrum-utils", specifier = ">=0.4.2" },
+    { name = "tensorboard", specifier = ">=2.18.0" },
+    { name = "torch", marker = "extra == 'cpu'", specifier = ">=2.4.1,<2.5" },
+    { name = "torch", marker = "extra == 'cu124'", specifier = ">=2.4.1,<2.5" },
+    { name = "tqdm", specifier = ">=4.67.0" },
+    { name = "transfusion-asr", specifier = ">=0.1.0" },
+    { name = "typer", specifier = ">=0.15.1" },
+]
+provides-extras = ["cpu", "cu124"]
+
 [[package]]
 name = "instanovo-gradio"
 version = "0.1.0"
@@ -842,7 +874,7 @@ dependencies = [
 [package.metadata]
 requires-dist = [
     { name = "gradio", specifier = ">=5.23.1" },
-    { name = "instanovo", specifier = ">=1.0.0" },
+    { name = "instanovo", path = "../dtu-denovo-sequencing/dist/instanovo-1.1.0-py3-none-any.whl" },
 ]
 
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 ]
 
+[[package]]
+name = "lightning"
+version = "2.5.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "fsspec", extra = ["http"] },
+    { name = "lightning-utilities" },
+    { name = "packaging" },
+    { name = "pytorch-lightning" },
+    { name = "pyyaml" },
+    { name = "torch" },
+    { name = "torchmetrics" },
+    { name = "tqdm" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/39/53/21a834e03317d04cc3db7307d4c19af94c0db43b9001e8fabb8d150c5e69/lightning-2.5.1.tar.gz", hash = "sha256:aca88f8abf3fc38d8b40c1f82ce481f4379c2b181a6eeeb9217db0aba8e40736", size = 630918 }
+wheels = [
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+]
+
 [[package]]
 name = "lightning-utilities"
 version = "0.14.2"
@@ -1876,22 +1928,6 @@ wheels = [
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+[[package]]
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+version = "0.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/0c/61/8b241f67846260f6d24e2f6c10f5a380cc7ede4f0e7619280e18215367c6/transfusion-asr-0.1.0.tar.gz", hash = "sha256:f9026f5450da4ef14be246dc208deefdb857da525092ab182e48c0b8d0a583c5", size = 52935 }
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 version = "3.2.0"