Create main.py

main.py

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+from fuzzy_json import loads
+from half_json.core import JSONFixer
+from together import Together
+from retry import retry
+import re
+from dotenv import load_dotenv
+import os
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+# Retrieve environment variables
+TOGETHER_API_KEY = "8e4274ffef010b6dd4b4343ed4a3158292691507f02ce99a58e09a0bd5400eab"
+
+SysPromptDefault = "You are an expert AI, complete the given task. Do not add any additional comments."    
+SysPromptList = "You are now in the role of an expert AI who can extract structured information from user request. All elements must be in double quotes. You must respond ONLY with a valid python List. Do not add any additional comments."
+
+# Import FastAPI and other necessary libraries
+
+
+# Define the app
+app = FastAPI()
+
+# Create a Pydantic model to handle the input data
+class TopicInput(BaseModel):
+    user_input: str
+    num_topics: int
+
+@retry(tries=3, delay=1)
+def together_response(message, model = "meta-llama/Llama-3-8b-chat-hf", SysPrompt = SysPromptDefault):
+  client = Together(api_key=TOGETHER_API_KEY)
+
+  messages=[{"role": "system", "content": SysPrompt},{"role": "user", "content": message}]
+
+  response = client.chat.completions.create(
+      model=model,
+      messages=messages,
+      temperature=0.2,
+  )
+  return response.choices[0].message.content
+
+def json_from_text(text):
+    """
+    Extracts JSON from text using regex and fuzzy JSON loading.
+    """
+    match = re.search(r'\{[\s\S]*\}', text)
+    if match:
+      json_out = match.group(0)
+    else:
+      json_out = text
+    try:
+        # Using fuzzy json loader
+        return loads(json_out)
+    except Exception:
+        # Using JSON fixer/ Fixes even half json/ Remove if you need an exception
+        fix_json = JSONFixer()
+        return loads(fix_json.fix(json_out).line)
+    
+SysPromptDefault = "You are an expert AI, complete the given task. Do not add any additional comments."    
+SysPromptList = "You are now in the role of an expert AI who can extract structured information from user request. All elements must be in double quotes. You must respond ONLY with a valid python List. Do not add any additional comments."
+def generate_topics(user_input,num_topics):
+    prompt = f"""create a list of {num_topics} subtopics to follow for conducting {user_input}, RETURN VALID PYTHON LIST"""
+    response_topics = together_response(prompt, model = "meta-llama/Llama-3-8b-chat-hf", SysPrompt = SysPromptList)
+    subtopics = json_from_text(response_topics)
+    return subtopics
+
+@app.post("/generate_topics/")
+async def create_topics(input: TopicInput):
+    topics = generate_topics(input.user_input, input.num_topics)
+    return {"topics": topics}
+