cleanup 2

.streamlit/config.toml

@@ -1,2 +1,9 @@
 [client]
-showSidebarNavigation = false
+showSidebarNavigation = false
+toolbarMode = "viewer"
+
+[theme]
+primaryColor = "#d93407"
+backgroundColor = "white"
+textColor = "#3e4047"
+font = "serif"

CVReview.py

@@ -54,60 +54,64 @@ def CVReviewPage():
 
     SHARED_STATE = st.session_state.shared_materials
     API_KEY = st.session_state.api_key
-
-    produce_report = st.button("Produce Suitability Report")
-    if produce_report:
-        try:
-            results = {}
-            # We will make 3 calls in parallel, to get various bits of information efficiently
-            with concurrent.futures.ThreadPoolExecutor() as executor:
-
-                futures = {
-                    critique_type: executor.submit(
-                        produce_report,
-                        SHARED_STATE["cv"],
-                        SHARED_STATE["job_posting"],
-                        critique_type,
-                        API_KEY,
-                    )
-                    for critique_type in ["basic", "general", "specific"]
-                }
-
-                for critique_type, future in futures.items():
-                    results[critique_type] = future.result()
-
-        except LocalProtocolError:
-            st.error("You need to enter a Cohere API Key.")
-        except ApiError:
-            st.error("You need a valid Cohere API Key")
-
-        # merge the from our calls, by extracting the json object from the gpt message
-        resultsDict = {}
-        for jsonText in results.values():
-            _, output_report_json = extract_json(jsonText)
-
-            resultsDict.update(output_report_json)
-
-        # store this as the report object
-        SHARED_STATE["report"] = resultsDict
-
-        # if the report object exists
-        if SHARED_STATE["report"]:
-            REPORT = SHARED_STATE["report"]
-
-            # these are used for file naming
-            name = REPORT.get("personName", "MissingPersonName")
-            job_title = REPORT.get("jobTitle", "MissingTitle")
-            company_name = REPORT.get("companyName", "MissingCompany")
-
-            # render markdown report
-            st.markdown(generate_markdown_report(REPORT))
-
-            # Downloadable in json form !
-            st.download_button(
-                label="Download Report JSON",
-                data=json.dumps(REPORT, indent=4),
-                file_name=f"{name}_{job_title}_{company_name}.json",
-                mime="application/json",
-                use_container_width=True,
-            )
+    if not SHARED_STATE["valid_flag"]:
+        st.error("You need to upload a Job Description & CV to use this feature.")
+    else:
+
+        produce_report_button = st.button("Produce Suitability Report")
+
+        if produce_report_button:
+            try:
+                results = {}
+                # We will make 3 calls in parallel, to get various bits of information efficiently
+                with concurrent.futures.ThreadPoolExecutor() as executor:
+
+                    futures = {
+                        critique_type: executor.submit(
+                            produce_report,
+                            SHARED_STATE["cv"],
+                            SHARED_STATE["job_posting"],
+                            critique_type,
+                            API_KEY,
+                        )
+                        for critique_type in ["basic", "general", "specific"]
+                    }
+
+                    for critique_type, future in futures.items():
+                        results[critique_type] = future.result()
+
+            except LocalProtocolError:
+                st.error("You need to enter a Cohere API Key.")
+            except ApiError:
+                st.error("You need a valid Cohere API Key")
+
+            # merge the from our calls, by extracting the json object from the gpt message
+            resultsDict = {}
+            for jsonText in results.values():
+                _, output_report_json = extract_json(jsonText)
+
+                resultsDict.update(output_report_json)
+
+            # store this as the report object
+            SHARED_STATE["report"] = resultsDict
+
+            # if the report object exists
+            if SHARED_STATE["report"]:
+                REPORT = SHARED_STATE["report"]
+
+                # these are used for file naming
+                name = REPORT.get("personName", "MissingPersonName")
+                job_title = REPORT.get("jobTitle", "MissingTitle")
+                company_name = REPORT.get("companyName", "MissingCompany")
+
+                # render markdown report
+                st.markdown(generate_markdown_report(REPORT))
+
+                # Downloadable in json form !
+                st.download_button(
+                    label="Download Report JSON",
+                    data=json.dumps(REPORT, indent=4),
+                    file_name=f"{name}_{job_title}_{company_name}.json",
+                    mime="application/json",
+                    use_container_width=True,
+                )

Interview.py

@@ -31,17 +31,17 @@ def InterviewPage():
     SHARED_STATE = st.session_state.shared_materials
     API_KEY = st.session_state.api_key
 
-    clear_conversation = st.button("Clear Conversation")
-
-    # Clear conversation will clear message state, and initialize with a new random question
-    if clear_conversation:
-        st.session_state["messages"] = [
-            {"role": "assistant", "message": random.choice(initial_questions)}
-        ]
-
     if not SHARED_STATE["valid_flag"]:
         st.error("You need to upload a Job Description & CV to use this feature.")
     else:
+        clear_conversation = st.button("Clear Conversation")
+
+        # Clear conversation will clear message state, and initialize with a new random question
+        if clear_conversation:
+            st.session_state["messages"] = [
+                {"role": "assistant", "message": random.choice(initial_questions)}
+            ]
+
         try:
             # Populate the chat with historic messages
             for msg in MESSAGES:

app.py

@@ -64,7 +64,7 @@ def main():
 
     pg = st.navigation(
         {
-            "Job Search AI Tools": [
+            "Jonah's AI Job Tools": [
                 st.Page(
                     InterviewPage,
                     title="Practice Interview",