Major update. Support for 15 LLMs, World Flora Online taxonomy validation, geolocation, 2 OCR methods, significant UI changes, stability improvements, consistent JSON parsing

app.py

@@ -1427,8 +1427,11 @@ def display_api_key_status():
 
 
 def check_api_key_status():
-    path_cfg_private = os.path.join(st.session_state.dir_home, 'PRIVATE_DATA.yaml')
-    cfg_private = get_cfg_from_full_path(path_cfg_private)
+    try:
+        path_cfg_private = os.path.join(st.session_state.dir_home, 'PRIVATE_DATA.yaml')
+        cfg_private = get_cfg_from_full_path(path_cfg_private)
+    except:
+        cfg_private = None
 
     API_Validator = APIvalidation(cfg_private, st.session_state.dir_home)
     present_keys, missing_keys, date_of_check = API_Validator.report_api_key_status()  # Assuming this function returns two lists

vouchervision/API_validation.py

@@ -34,7 +34,11 @@ class APIvalidation:
             return False
             
     def check_openai_api_key(self):
-        openai.api_key = self.cfg_private['openai']['OPENAI_API_KEY']
+        if self.cfg_private:
+            openai.api_key = self.cfg_private['openai']['OPENAI_API_KEY']
+        else:
+            openai.api_key = os.getenv('OPENAI_API_KEY')
+
         try:
             openai.models.list()
             return True
@@ -66,32 +70,63 @@ class APIvalidation:
             return False
         
     def check_azure_openai_api_key(self):
-        try:
-            # Initialize the Azure OpenAI client
-            model = AzureChatOpenAI(
-                deployment_name = 'gpt-35-turbo',#'gpt-35-turbo',
-                openai_api_version = self.cfg_private['openai_azure']['api_version'],
-                openai_api_key = self.cfg_private['openai_azure']['openai_api_key'],
-                azure_endpoint = self.cfg_private['openai_azure']['openai_api_base'],
-                openai_organization = self.cfg_private['openai_azure']['openai_organization'],
-            )
-            msg = HumanMessage(content="hello")
-            # self.llm_object.temperature = self.config.get('temperature')
-            response = model([msg])
+        if self.cfg_private:
+            try:
+                # Initialize the Azure OpenAI client
+                model = AzureChatOpenAI(
+                    deployment_name = 'gpt-35-turbo',#'gpt-35-turbo',
+                    openai_api_version = self.cfg_private['openai_azure']['api_version'],
+                    openai_api_key = self.cfg_private['openai_azure']['openai_api_key'],
+                    azure_endpoint = self.cfg_private['openai_azure']['openai_api_base'],
+                    openai_organization = self.cfg_private['openai_azure']['openai_organization'],
+                )
+                msg = HumanMessage(content="hello")
+                # self.llm_object.temperature = self.config.get('temperature')
+                response = model([msg])
 
-            # Check the response content (you might need to adjust this depending on how your AzureChatOpenAI class handles responses)
-            if response:
-                return True
-            else:
+                # Check the response content (you might need to adjust this depending on how your AzureChatOpenAI class handles responses)
+                if response:
+                    return True
+                else:
+                    return False
+
+            except Exception as e:  # Use a more specific exception if possible
                 return False
+        else:
+            try:
+                azure_api_version = os.getenv('AZURE_API_VERSION')
+                azure_api_key = os.getenv('AZURE_API_KEY')
+                azure_api_base = os.getenv('AZURE_API_BASE')
+                azure_organization = os.getenv('AZURE_ORGANIZATION')
+                # Initialize the Azure OpenAI client
+                model = AzureChatOpenAI(
+                    deployment_name = 'gpt-35-turbo',#'gpt-35-turbo',
+                    openai_api_version = azure_api_version,
+                    openai_api_key = azure_api_key,
+                    azure_endpoint = azure_api_base,
+                    openai_organization = azure_organization,
+                )
+                msg = HumanMessage(content="hello")
+                # self.llm_object.temperature = self.config.get('temperature')
+                response = model([msg])
 
-        except Exception as e:  # Use a more specific exception if possible
-            return False
+                # Check the response content (you might need to adjust this depending on how your AzureChatOpenAI class handles responses)
+                if response:
+                    return True
+                else:
+                    return False
+
+            except Exception as e:  # Use a more specific exception if possible
+                return False
         
     def check_mistral_api_key(self):
+        if self.cfg_private:
+            client = MistralClient(api_key=self.cfg_private['mistral']['mistral_key'])
+        else:
+            client = MistralClient(api_key=os.getenv('MISTRAL_API_KEY'))
+
         try:
             # Initialize the Mistral Client with the API key
-            client = MistralClient(api_key=self.cfg_private['mistral']['mistral_key'])
 
             # Create a simple message
             messages = [ChatMessage(role="user", content="hello")]
@@ -112,46 +147,98 @@ class APIvalidation:
         
     def check_google_vertex_genai_api_key(self):
         results = {"palm2": False, "gemini": False}
-        try:
-            # Assuming genai and vertexai are clients for Google services
-            os.environ["GOOGLE_API_KEY"] = self.cfg_private['google_palm']['google_palm_api']
-            # genai.configure(api_key=self.cfg_private['google_palm']['google_palm_api'])
-            vertexai.init(project= self.cfg_private['google_palm']['project_id'], location=self.cfg_private['google_palm']['location'])
-
+        if self.cfg_private:
             try:
-                model = TextGenerationModel.from_pretrained("text-bison@001")
-                response = model.predict("Hello")
-                test_response_palm = response.text
-                # llm_palm = ChatGoogleGenerativeAI(model="text-bison@001")
-                # test_response_palm = llm_palm.invoke("Hello")
-                if test_response_palm:
-                    results["palm2"] = True
-            except Exception as e:  
-                pass
+                # Assuming genai and vertexai are clients for Google services
+                os.environ["GOOGLE_API_KEY"] = self.cfg_private['google_palm']['google_palm_api']
+                # genai.configure(api_key=self.cfg_private['google_palm']['google_palm_api'])
+                vertexai.init(project= self.cfg_private['google_palm']['project_id'], location=self.cfg_private['google_palm']['location'])
 
+                try:
+                    model = TextGenerationModel.from_pretrained("text-bison@001")
+                    response = model.predict("Hello")
+                    test_response_palm = response.text
+                    # llm_palm = ChatGoogleGenerativeAI(model="text-bison@001")
+                    # test_response_palm = llm_palm.invoke("Hello")
+                    if test_response_palm:
+                        results["palm2"] = True
+                except Exception as e:  
+                    pass
+
+                try:
+                    model = GenerativeModel("gemini-pro")
+                    response = model.generate_content("Hello")
+                    test_response_gemini = response.text
+                    # llm_gemini = ChatGoogleGenerativeAI(model="gemini-pro")
+                    # test_response_gemini = llm_gemini.invoke("Hello")
+                    if test_response_gemini:
+                        results["gemini"] = True
+                except Exception as e:  
+                    pass
+
+                return results
+            except Exception as e:  # Replace with a more specific exception if possible
+                return results
+        else:
             try:
-                model = GenerativeModel("gemini-pro")
-                response = model.generate_content("Hello")
-                test_response_gemini = response.text
-                # llm_gemini = ChatGoogleGenerativeAI(model="gemini-pro")
-                # test_response_gemini = llm_gemini.invoke("Hello")
-                if test_response_gemini:
-                    results["gemini"] = True
-            except Exception as e:  
-                pass
-
-            return results
-        except Exception as e:  # Replace with a more specific exception if possible
-            return results
-            
+                # Assuming genai and vertexai are clients for Google services
+                os.environ["GOOGLE_API_KEY"] = os.getenv('PALM_API_KEY')
+                # genai.configure(api_key=self.cfg_private['google_palm']['google_palm_api'])
+                vertexai.init(project= os.getenv('GOOGLE_PROJECT_ID'), location=os.getenv('GOOGLE_LOCATION'))
+
+                try:
+                    model = TextGenerationModel.from_pretrained("text-bison@001")
+                    response = model.predict("Hello")
+                    test_response_palm = response.text
+                    # llm_palm = ChatGoogleGenerativeAI(model="text-bison@001")
+                    # test_response_palm = llm_palm.invoke("Hello")
+                    if test_response_palm:
+                        results["palm2"] = True
+                except Exception as e:  
+                    pass
+
+                try:
+                    model = GenerativeModel("gemini-pro")
+                    response = model.generate_content("Hello")
+                    test_response_gemini = response.text
+                    # llm_gemini = ChatGoogleGenerativeAI(model="gemini-pro")
+                    # test_response_gemini = llm_gemini.invoke("Hello")
+                    if test_response_gemini:
+                        results["gemini"] = True
+                except Exception as e:  
+                    pass
+
+                return results
+            except Exception as e:  # Replace with a more specific exception if possible
+                return results
 
     def report_api_key_status(self):
         missing_keys = []
         present_keys = []
 
+        if self.cfg_private:
+            k_OPENAI_API_KEY = self.cfg_private['openai']['OPENAI_API_KEY']
+            k_openai_azure = self.cfg_private['openai_azure']['api_version']
+            k_google_palm_api = self.cfg_private['google_palm']['google_palm_api']
+            k_project_id = self.cfg_private['google_palm']['project_id']
+            k_location = self.cfg_private['google_palm']['location']
+            k_mistral = self.cfg_private['mistral']['mistral_key']
+            k_here = self.cfg_private['here']['api_key']
+            k_opencage = self.cfg_private['open_cage_geocode']['api_key']
+        else:
+            k_OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+            k_openai_azure = os.getenv('AZURE_API_VERSION')
+            k_google_palm_api = os.getenv('PALM_API_KEY')
+            k_project_id = os.getenv('GOOGLE_PROJECT_ID')
+            k_location = os.getenv('GOOGLE_LOCATION')
+            k_mistral = os.getenv('MISTRAL_API_KEY')
+            k_here = os.getenv('here_api_key')
+            k_opencage = os.getenv('open_cage_geocode')
+
+
         # Check each key and add to the respective list
         # OpenAI key check
-        if self.has_API_key(self.cfg_private['openai']['OPENAI_API_KEY']):
+        if self.has_API_key(k_OPENAI_API_KEY):
             is_valid = self.check_openai_api_key()
             if is_valid:
                 present_keys.append('OpenAI (Valid)')
@@ -161,7 +248,7 @@ class APIvalidation:
             missing_keys.append('OpenAI')
 
         # Azure OpenAI key check
-        if self.has_API_key(self.cfg_private['openai_azure']['api_version']):
+        if self.has_API_key(k_openai_azure):
             is_valid = self.check_azure_openai_api_key()
             if is_valid:
                 present_keys.append('Azure OpenAI (Valid)')
@@ -171,7 +258,7 @@ class APIvalidation:
             missing_keys.append('Azure OpenAI')
 
         # Google PALM2/Gemini key check
-        if self.has_API_key(self.cfg_private['google_palm']['google_palm_api']) and self.has_API_key(self.cfg_private['google_palm']['project_id']) and self.has_API_key(self.cfg_private['google_palm']['location']):
+        if self.has_API_key(k_google_palm_api) and self.has_API_key(k_project_id) and self.has_API_key(k_location):
             google_results = self.check_google_vertex_genai_api_key()
             if google_results['palm2']:
                 present_keys.append('Palm2 (Valid)')
@@ -185,7 +272,7 @@ class APIvalidation:
             missing_keys.append('Google VertexAI/GenAI')
 
         # Google OCR key check
-        if self.has_API_key(self.cfg_private['google_palm']['google_palm_api']) and self.has_API_key(self.cfg_private['google_palm']['project_id']) and self.has_API_key(self.cfg_private['google_palm']['location']):
+        if self.has_API_key(k_google_palm_api) and self.has_API_key(k_project_id) and self.has_API_key(k_location):
             is_valid = self.check_google_ocr_api_key()
             if is_valid:
                 present_keys.append('Google OCR (Valid)')
@@ -195,8 +282,8 @@ class APIvalidation:
             missing_keys.append('Google OCR')
 
         # Mistral key check
-        if self.has_API_key(self.cfg_private['mistral']['mistral_key']):
-            is_valid = self.check_mistral_api_key()
+        if self.has_API_key():
+            is_valid = self.check_mistral_api_key(k_mistral)
             if is_valid:
                 present_keys.append('Mistral (Valid)')
             else:
@@ -205,12 +292,12 @@ class APIvalidation:
             missing_keys.append('Mistral')
 
 
-        if self.has_API_key(self.cfg_private['here']['api_key']):
+        if self.has_API_key(k_here):
             present_keys.append('HERE Geocode (Valid)')
         else:
             missing_keys.append('HERE Geocode (Invalid)')
 
-        if self.has_API_key(self.cfg_private['open_cage_geocode']['api_key']):
+        if self.has_API_key(k_opencage):
             present_keys.append('OpenCage Geocode (Valid)')
         else:
             missing_keys.append('OpenCage Geocode (Invalid)')