Create app.py

app.py

@@ -0,0 +1,119 @@
+# --- Imports ---
+import gradio as gr
+from transformers import pipeline
+import pandas as pd
+import os
+
+# --- Load Model ---
+pipe = pipeline(model="InstaDeepAI/ChatNT", trust_remote_code=True)
+
+# --- Logs ---
+log_file = "logs.txt"
+
+class Log:
+    def __init__(self, log_file):
+        self.log_file = log_file
+
+    def __call__(self):
+        if not os.path.exists(self.log_file):
+            return ""
+        with open(self.log_file, "r") as f:
+            return f.read()
+
+# --- Main Function ---
+def run_chatnt(input_file, custom_question):
+    with open(log_file, "a") as log:
+        log.write("Request started\n")
+
+    if not custom_question or custom_question.strip() == "":
+        return pd.DataFrame(), None
+
+    # Read DNA sequences
+    dna_sequences = []
+    if input_file is not None:
+        with open(input_file.name, "r") as f:
+            lines = f.readlines()
+            for line in lines:
+                if line.startswith(">"):
+                    continue
+                dna_sequences.append(line.strip())
+
+    if not dna_sequences:
+        return pd.DataFrame(), None
+
+    # Build prompt
+    english_sequence = custom_question + " <DNA>"
+
+    # Call model
+    output = pipe(
+        inputs={
+            "english_sequence": english_sequence,
+            "dna_sequences": dna_sequences
+        }
+    )
+
+    # Wrap output
+    results = []
+    if isinstance(output, list):
+        for item in output:
+            results.append({"Result": item})
+    else:
+        results.append({"Result": output})
+
+    df = pd.DataFrame(results)
+    output_file = "output.csv"
+    df.to_csv(output_file, index=False)
+
+    with open(log_file, "a") as log:
+        log.write("Request finished\n")
+
+    return df, output_file
+
+# --- Gradio Interface ---
+css = """
+.gradio-container { font-family: sans-serif; }
+.gr-button { color: white; border-color: black; background: black; }
+footer { display: none !important; }
+"""
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown("# 🧬 ChatNT — DNA Sequence Query Assistant")
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_file = gr.File(
+                label="Upload DNA Sequence File (.fasta or .txt)",
+                file_types=[".fasta", ".fa", ".txt"]
+            )
+            custom_question = gr.Textbox(
+                label="English Question (required)",
+                placeholder="e.g., Does this sequence contain a donor splice site?"
+            )
+
+            submit_btn = gr.Button("Run Query", variant="primary")
+
+        with gr.Column(scale=2):
+            output_df = gr.DataFrame(
+                label="Results",
+                headers=["Result"]
+            )
+            output_file = gr.File(label="Download Results (CSV)")
+
+    submit_btn.click(
+        run_chatnt,
+        inputs=[input_file, custom_question],
+        outputs=[output_df, output_file],
+    )
+
+    gr.Markdown("""
+**Note:** Your question **must** include the `<DNA>` token if needed for multiple sequences.
+    """)
+
+    with gr.Accordion("Logs", open=True):
+        log_display = Log(log_file)
+        gr.Markdown(log_display)
+
+# --- Launch ---
+if __name__ == "__main__":
+    demo.queue()
+    demo.launch(debug=True, show_error=True)