updates scoping

app.py

@@ -33,27 +33,30 @@ fig =''
 output_string = ''
 
 
-def prompt_analyze_reporting(prompt):
-    output = openai.ChatCompletion.create(model="gpt-3.5-turbo",temperature = 0.0, messages=[{"role": "user", "content": 
+def prompt_analyze_reporting(prompt, passed_args):
+    data_structure_overview = passed_args['data_structure_overview']
+    data_relationships_overview = passed_args['data_relationships_overview']
+    passed_args['fig'] = ''
+    output = openai.ChatCompletion.create(model="gpt-3.5-turbo",temperature = 0.0, messages=[{"role": "user", "content":
                                                                data_structure_overview},
                                                                        {"role": "user", "content": 
                                                                data_relationships_overview},{"role": "user", "content": 
                                                                f"""Do not attempt to use .csv files in your code."""},
                                                                 {"role": "user", "content": 
-                                                               f"""Only use plotly to output charts, graphs, or figures. Do not use matplotlib or other charting libraries. Name the chart object as 'fig'"""},
+                                                               f"""Only use plotly to output charts, graphs, or figures. Do not use matplotlib or other charting libraries. Name the chart object as 'fig' but do not show it"""},
                                                                        {"role": "user", "content": 
                                                                f"""Create a python script to: {prompt}"""}
-                                                                      ])
-    global parsed_response
+                                                                     ])
     parsed_response = output.choices[0].message.content.strip().split('```python')[len(output.choices[0].message.content.strip().split('```python')) -1 ].split('```')[0]
-    parsed_response_global = f"""global fig 
-global string
-    {parsed_response}"""
-    exec(parsed_response_global)
+    exec(parsed_response,globals(),passed_args)
+    fig = passed_args['fig']
     return fig
 
-def prompt_analyze_questions(prompt):
-    output = openai.ChatCompletion.create(model="gpt-3.5-turbo",temperature = 0.0, messages=[{"role": "user", "content": 
+def prompt_analyze_questions(prompt, passed_args):
+    data_structure_overview = passed_args['data_structure_overview']
+    data_relationships_overview = passed_args['data_relationships_overview']
+    passed_args['output_string']=''
+    output = openai.ChatCompletion.create(model="gpt-3.5-turbo",temperature = 0.0, messages=[{"role": "user", "content":
                                                                data_structure_overview},
                                                                        {"role": "user", "content": 
                                                                data_relationships_overview},{"role": "user", "content": 
@@ -68,18 +71,38 @@ def prompt_analyze_questions(prompt):
                                                                f"""Store the final response as a string variable named output_string"""}
                                                                       ])
 
-    global parsed_response
     parsed_response = output.choices[0].message.content.strip().split('```python')[len(output.choices[0].message.content.strip().split('```python')) -1 ].split('```')[0]
-    parsed_response_global = f"""global fig 
-global string
-{parsed_response}
-globals().update(locals())"""
-    exec(parsed_response_global)
+    exec(parsed_response,globals(),passed_args)
+    output_string = passed_args['output_string']
     return output_string
 
 # Data Retrieval
 
 def getData(tlspc_api_key, openai_api_key):
+    #Get Cert Requests
+    def getCertRequests():
+        currentPage = 0
+        cert_requests_url = "https://api.venafi.cloud/outagedetection/v1/certificaterequestssearch"
+        headers = {
+            "accept": "application/json",
+            "tppl-api-key": tlspc_api_key}
+        payload = {"paging": {
+            "pageNumber": 1,
+            "pageSize": 1000}}
+        response = requests.post(url=cert_requests_url, headers=headers, json=payload)
+        if (response.status_code != 200):
+            raise Exception('Error retrieving certificate requests:' + "\n" + response.text + "\n=============\n")
+        data = response.json()
+        cert_requests = data['certificateRequests']
+        while data['numFound'] > (currentPage * 1000):
+            currentPage += 1
+            print('Getting page ' + str(currentPage) + ': Number remaining - ' + str(
+                data['numFound'] - currentPage * 1000))
+            payload['paging']['pageNumber'] = currentPage
+            response = requests.post(url=cert_requests_url, headers=headers, json=payload)
+            data = response.json()
+            cert_requests += data['certificateRequests']
+        return cert_requests
     try:
         # Store OpenAI API Key
         openai.api_key = openai_api_key
@@ -199,30 +222,6 @@ def getData(tlspc_api_key, openai_api_key):
 
         machine_identities_df.drop(['companyId'],axis=1,inplace=True)
 
-        # Certificate Requests
-        def getCertRequests():
-          currentPage = 0
-          cert_requests_url = "https://api.venafi.cloud/outagedetection/v1/certificaterequestssearch"
-          headers = {
-            "accept": "application/json",
-            "tppl-api-key": tlspc_api_key}
-          payload = { "paging": {
-                "pageNumber": 1,
-                "pageSize": 1000}}
-          response = requests.post(url=cert_requests_url, headers=headers,json=payload)
-          if(response.status_code != 200):
-            raise Exception('Error retrieving certificate requests:' + "\n" + response.text + "\n=============\n")
-          data = response.json()
-          cert_requests = data['certificateRequests']
-          while data['numFound'] > (currentPage * 1000):
-            currentPage+=1
-            print('Getting page ' + str(currentPage) + ': Number remaining - ' + str(data['numFound'] - currentPage*1000))
-            payload['paging']['pageNumber'] = currentPage
-            response = requests.post(url=cert_requests_url, headers=headers,json=payload)
-            data = response.json()
-            cert_requests += data['certificateRequests']
-          return cert_requests
-
         cert_requests_json = getCertRequests()
         cert_requests_df = pd.json_normalize(cert_requests_json).convert_dtypes()
         cert_requests_df.rename(columns = {'id':'cert_request_id', 'creationDate':'cert_request_creationDate'}, inplace = True)
@@ -275,11 +274,13 @@ def getData(tlspc_api_key, openai_api_key):
         The column values in the 'certificateOwnerUserId' column in cert_requests_df match the column values in the 'user_id' column in users_df.
         The column values in the 'certificateIssuingTemplateId' column in certs_request_df match the column values in the 'issuing_template_id' column in issuing_templates_df.
         """
-        
-        # Store variables for use in other portions of the application
-        globals().update(locals())
-        
-        return 'Data successfully loaded!'
+        passed_args = {'application_df': application_df, 'users_df': users_df, 'certs_df': certs_df,
+                       'teams_df': teams_df, 'machines_df': machines_df, 'machine_identities_df': machine_identities_df,
+                       'cert_requests_df': cert_requests_df, 'issuing_templates_df': issuing_templates_df,
+                       'data_structure_overview': data_structure_overview,
+                       'data_relationships_overview': data_relationships_overview}
+
+        return 'Data successfully loaded!', passed_args
     
     except:
         
@@ -322,10 +323,10 @@ with gr.Blocks(theme='aliabid94/new-theme') as demo:
         chart_button = gr.Button("Submit")
     gr.Markdown("<sup><sub>Reminder: This is an experimental project to test new capabilities. Take care and understand risks of using API keys and accessing data especially if running from Hugging Face. Rotate keys after use.</sup></sub>")
 
+    passed_args = gr.State([])
 
-
-    text_button.click(prompt_analyze_questions, inputs=prompt_questions, outputs=text_output)
-    chart_button.click(prompt_analyze_reporting, inputs=prompt_reporting, outputs=chart_output)
-    load_button.click(getData, inputs=[tlspc_api_key, openai_api_key], outputs=api_key_output)
+    text_button.click(prompt_analyze_questions, inputs=[prompt_questions,passed_args], outputs=text_output)
+    chart_button.click(prompt_analyze_reporting, inputs=[prompt_reporting,passed_args], outputs=chart_output)
+    load_button.click(getData, inputs=[tlspc_api_key, openai_api_key], outputs=[api_key_output,passed_args])
 
 demo.launch()