Update app.py

app.py

@@ -25,7 +25,6 @@ from sklearn.metrics.pairwise import cosine_similarity
 # Initialize Groq Client
 client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
-
 # ---------------------- Base Classes and Schemas ---------------------------
 class ResearchInput(BaseModel):
     """Base schema for research tool inputs"""
@@ -287,7 +286,7 @@ class BasicTreatmentRecommendation(TreatmentRecommendation):
 class MedicalKnowledgeBase():
   """Abstract class for Medical Knowledge"""
   @abstractmethod
-  def search_medical_info(self, query: str) -> str:
+  def search_medical_info(self, query: str, pub_email:str="") -> str:
     pass
 
 class SimpleMedicalKnowledge(MedicalKnowledgeBase):
@@ -534,6 +533,7 @@ def main():
     if 'pub_email' not in st.session_state:
         st.session_state.pub_email = st.secrets.get("PUB_EMAIL", "")  # Load PUB_EMAIL from secrets
   
+
     # Sidebar for Data Management
     with st.sidebar:
         st.header("⚙️ Data Management")
@@ -706,4 +706,52 @@ def main():
                           st.json(result)
             with insights_tab:
                 if selected_data_key:
-                  
+                    data = st.session_state.data[selected_data_key]
+                    available_analysis = ["EDA", "temporal", "distribution", "hypothesis", "model"]
+                    selected_analysis = st.multiselect("Select Analysis", available_analysis)
+                    if st.button("Generate Automated Insights"):
+                        with st.spinner("Generating Insights"):
+                            results = st.session_state.automated_insights.generate_insights(data, analysis_names=selected_analysis)
+                            st.json(results)
+                    st.subheader("Diagnosis Support")
+                    target_col = st.selectbox("Select Target Variable for Diagnosis", data.columns.tolist())
+                    num_cols = data.select_dtypes(include=np.number).columns.tolist()
+                    selected_cols_diagnosis = st.multiselect("Select Feature Variables for Diagnosis", num_cols)
+                    if st.button("Generate Diagnosis"):
+                        if target_col
+                                                        if target_col and selected_cols_diagnosis:
+                                    with st.spinner("Generating Diagnosis"):
+                                        result = st.session_state.diagnosis_support.diagnose(data, target_col=target_col, columns=selected_cols_diagnosis, diagnosis_key="diagnosis_result")
+                                        st.json(result)
+
+                    st.subheader("Treatment Recommendation")
+                    condition_col = st.selectbox("Select Condition Column for Treatment Recommendation", data.columns.tolist())
+                    treatment_col = st.selectbox("Select Treatment Column for Treatment Recommendation", data.columns.tolist())
+                    if st.button("Generate Treatment Recommendation"):
+                        if condition_col and treatment_col:
+                            with st.spinner("Generating Treatment Recommendation"):
+                                result = st.session_state.treatment_recommendation.recommend(data, condition_col = condition_col, treatment_col = treatment_col, recommendation_key="treatment_recommendation")
+                                st.json(result)
+
+            with reports_tab:
+                 st.header("Reports")
+                 report_name = st.text_input("Report Name")
+                 report_def = st.text_area("Report definition")
+                 if st.button("Create Report Definition"):
+                   st.session_state.automated_reports.create_report_definition(report_name, report_def)
+                   st.success("Report definition created")
+                 if selected_data_key:
+                   data = st.session_state.data
+                   if st.button("Generate Report"):
+                     with st.spinner("Generating Report..."):
+                       report = st.session_state.automated_reports.generate_report(report_name, data)
+            with knowledge_tab:
+              st.header("Medical Knowledge")
+              query = st.text_input("Enter your medical question here:")
+              if st.button("Search"):
+                  with st.spinner("Searching..."):
+                      result = st.session_state.knowledge_base.search_medical_info(query, pub_email=st.session_state.pub_email)
+                      st.write(result)
+
+if __name__ == "__main__":
+    main()