Update app.py

app.py

@@ -1,13 +1,11 @@
-import os
-import json
+import os, json
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# Load prompts
+# Load your tool prompts
 with open("system_prompts.json", encoding="utf-8") as f:
     SYSTEM_PROMPTS = json.load(f)
 
-# Initialize InferenceClient
 client = InferenceClient(model=os.getenv("HF_MODEL"), token=os.getenv("HF_TOKEN"))
 
 def run_model(prompt: str, text: str) -> str:
@@ -18,22 +16,48 @@ def run_model(prompt: str, text: str) -> str:
     )
     return resp.choices[0].message.content
 
-# Build a separate Gradio Interface per tool
-tools = []
-for name, prompt in SYSTEM_PROMPTS.items():
-    tool_name = name.lower().replace(" ", "_")
-    def make_fn(p):
-        def fn(text: str) -> str:
-            """Tool for: """ + name
-            return run_model(p, text)
-        return fn
-    fn = make_fn(prompt)
-    iface = gr.Interface(fn=fn, inputs=gr.Textbox(lines=5), outputs=gr.Textbox(), 
-                         title=name, description=f"{name} tool")
-    tools.append(iface)
-
-# Launch all tools under one app
-demo = gr.TabbedInterface(interface_list=tools, tab_names=list(SYSTEM_PROMPTS.keys()))
+# --- Define one named function per tool prompt ---
+def ecolinguistic_analysis(text: str) -> str:
+    """Ecolinguistic Analysis"""
+    prompt = SYSTEM_PROMPTS["Ecolinguistic Analysis"]
+    return run_model(prompt, text)
+
+def narrative_detection(text: str) -> str:
+    """Narrative Detection"""
+    prompt = SYSTEM_PROMPTS["Narrative Detection"]
+    return run_model(prompt, text)
+
+def critical_discourse_analysis(text: str) -> str:
+    """Critical Discourse Analysis"""
+    prompt = SYSTEM_PROMPTS["Critical Discourse Analysis"]
+    return run_model(prompt, text)
+
+def sfl_analysis(text: str) -> str:
+    """SFL Analysis"""
+    prompt = SYSTEM_PROMPTS["SFL Analysis"]
+    return run_model(prompt, text)
+
+def ecosophy_scoring(text: str) -> str:
+    """Ecosophy Scoring"""
+    prompt = SYSTEM_PROMPTS["Ecosophy Scoring"]
+    return run_model(prompt, text)
+
+# --- Build the Gradio interface with separate interfaces per tool ---
+iface1 = gr.Interface(fn=ecolinguistic_analysis, inputs="text", outputs="text",
+                      title="Ecolinguistic Analysis", description=ecolinguistic_analysis.__doc__)
+iface2 = gr.Interface(fn=narrative_detection, inputs="text", outputs="text",
+                      title="Narrative Detection", description=narrative_detection.__doc__)
+iface3 = gr.Interface(fn=critical_discourse_analysis, inputs="text", outputs="text",
+                      title="Critical Discourse Analysis", description=critical_discourse_analysis.__doc__)
+iface4 = gr.Interface(fn=sfl_analysis, inputs="text", outputs="text",
+                      title="SFL Analysis", description=sfl_analysis.__doc__)
+iface5 = gr.Interface(fn=ecosophy_scoring, inputs="text", outputs="text",
+                      title="Ecosophy Scoring", description=ecosophy_scoring.__doc__)
+
+demo = gr.TabbedInterface(
+    interface_list=[iface1, iface2, iface3, iface4, iface5],
+    tab_names=list(SYSTEM_PROMPTS.keys())
+)
 
 if __name__ == "__main__":
     demo.launch(mcp_server=True, share=True)