def call_llm()

in bot/code/state_management_bot.py [0:0]

• 21 lines of code
• 7 McCabe index (conditional complexity)

    def call_llm(self, question, chat_history = []):
        data = dict()
        data["question"] = question
        data["chat_history"] = chat_history
        data["categories"] = self.categories
        data["organization_urls"] = self.organization_urls
        data["organization"] = self.organization

        body = str.encode(json.dumps(data))

        # Replace this with the primary/secondary key or AMLToken for the endpoint
        api_key = self.llm_api_key
        if not api_key:
            raise Exception("A key should be provided to invoke the endpoint")

        # The azureml-model-deployment header will force the request to go to a specific deployment.
        # Remove this header to have the request observe the endpoint traffic rules
        headers = {'Content-Type':'application/json', 'Authorization':('Bearer '+ api_key), 'azureml-model-deployment': 'chat-with-website-1' }

        req = urllib.request.Request(self.llm_endpoint, body, headers)

        try:
            response = urllib.request.urlopen(req)

            result = response.read()
            # print(result)
            return result
        except urllib.error.HTTPError as error:
            print("The request failed with status code: " + str(error.code))

            # Print the headers - they include the requert ID and the timestamp, which are useful for debugging the failure
            print(error.info())
            print(error.read().decode("utf8", 'ignore'))