upload low-code llm codes

LowCodeLLM/Dockerfile

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+FROM ubuntu:22.04
+
+RUN apt-get -y update
+RUN apt-get install -y git python3.11 python3-pip supervisor
+RUN pip3 install --upgrade pip
+RUN pip3 install --upgrade setuptools
+RUN ln -s /usr/bin/python3 /usr/bin/python
+COPY src/requirements.txt requirements.txt
+RUN pip3 install -r requirements.txt
+
+COPY src /app/src
+
+WORKDIR /app/src
+ENV WORKERS 2
+CMD supervisord -c supervisord.conf

LowCodeLLM/src/app.py

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+import os
+from flask import Flask, request
+from flask_cors import CORS, cross_origin
+from lowCodeLLM import lowCodeLLM
+from flask.logging import default_handler
+import logging
+
+app = Flask('lowcode-llm', static_url_path='', template_folder='')
+app.debug = True
+llm = lowCodeLLM()
+gunicorn_logger = logging.getLogger('gunicorn.error')
+app.logger = gunicorn_logger
+logging_format = logging.Formatter(
+    '%(asctime)s - %(levelname)s - %(filename)s - %(funcName)s - %(lineno)s - %(message)s')
+default_handler.setFormatter(logging_format)
+
+@app.route('/api/get_workflow', methods=['POST'])
+@cross_origin()
+def get_workflow():
+    try:
+        request_content = request.get_json()
+        task_prompt = request_content['task_prompt']
+        workflow = llm.get_workflow(task_prompt)
+        return workflow, 200
+    except Exception as e:
+        app.logger.error(
+            'failed to get_workflow, msg:%s, request data:%s' % (str(e), request.json))
+        return {'errmsg': str(e)}, 500
+
+@app.route('/api/extend_workflow', methods=['POST'])
+@cross_origin()
+def extend_workflow():
+    try:
+        request_content = request.get_json()
+        task_prompt = request_content['task_prompt']
+        current_workflow = request_content['current_workflow']
+        step = request_content['step']
+        sub_workflow = llm.extend_workflow(task_prompt, current_workflow, step)
+        return sub_workflow, 200
+    except Exception as e:
+        app.logger.error(
+            'failed to extend_workflow, msg:%s, request data:%s' % (str(e), request.json))
+        return {'errmsg': str(e)}, 500
+
+@app.route('/api/execute', methods=['POST'])
+@cross_origin()
+def execute():
+    try:
+        request_content = request.get_json()
+        task_prompt = request_content['task_prompt']
+        confirmed_workflow = request_content['confirmed_workflow']
+        curr_input = request_content['curr_input']
+        history = request_content['history']
+        response = llm.execute(task_prompt,confirmed_workflow, history, curr_input)
+        return response, 200
+    except Exception as e:
+        app.logger.error(
+            'failed to execute, msg:%s, request data:%s' % (str(e), request.json))
+        return {'errmsg': str(e)}, 500

LowCodeLLM/src/executingLLM.py

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+from openAIWrapper import OpenAIWrapper
+
+EXECUTING_LLM_PREFIX = """Executing LLM is designed to provide outstanding responses.
+Executing LLM will be given a overall task as the background of the conversation between the Executing LLM and human.
+When providing response, Executing LLM MUST STICTLY follow the provided standard operating procedure (SOP).
+the SOP is formatted as:
+'''
+STEP 1: [step name][step descriptions][[[if 'condition1'][Jump to STEP]], [[if 'condition2'][Jump to STEP]], ...]
+STEP 2: [step name][step descriptions][[[if 'condition1'][Jump to STEP]], [[if 'condition2'][Jump to STEP]], ...]
+'''
+here "[[[if 'condition1'][Jump to STEP n]], [[if 'condition2'][Jump to STEP m]], ...]" is judgmental logic. It means when you're performing this step,
+and if 'condition1' is satisfied, you will perform STEP n next. If 'condition2' is satisfied, you will perform STEP m next.
+
+Remember: 
+Executing LLM is facing a real human, who does not know what SOP is. 
+So, Do not show him/her the SOP steps you are following, or the process and middle results of performing the SOP. It will make him/her confused. Just response the answer.
+"""
+
+EXECUTING_LLM_SUFFIX = """
+Remember: 
+Executing LLM is facing a real human, who does not know what SOP is. 
+So, Do not show him/her the SOP steps you are following, or the process and middle results of performing the SOP. It will make him/her confused. Just response the answer.
+"""
+
+class executingLLM:
+    def __init__(self, temperature) -> None:
+        self.prefix = EXECUTING_LLM_PREFIX
+        self.suffix = EXECUTING_LLM_SUFFIX
+        self.LLM = OpenAIWrapper(temperature)
+        self.messages = [{"role": "system", "content": "You are a helpful assistant."},
+                         {"role": "system", "content": self.prefix}]
+
+    def execute(self, current_prompt, history):
+        ''' provide LLM the dialogue history and the current prompt to get response '''
+        messages = self.messages + history
+        messages.append({'role': 'user', "content": current_prompt + self.suffix})
+        response, status = self.LLM.run(messages)
+        if status:
+            return response
+        else:
+            return "OpenAI API error."