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Update main.py
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main.py
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@@ -46,9 +46,10 @@ def json_from_text(text):
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fix_json = JSONFixer()
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return loads(fix_json.fix(json_out).line)
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def generate_topics(user_input,num_topics,
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subtopics = json_from_text(response_topics)
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return subtopics
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@@ -67,15 +68,14 @@ app.add_middleware(
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class TopicInput(BaseModel):
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user_input: str = Query(default="market research", description="input query to generate subtopics")
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num_topics: int = Query(default=5, description="Number of subtopics to generate (default: 5)")
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@app.get("/",tags=["Home"])
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def api_home():
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return {'detail': 'Welcome to FastAPI Subtopics API!
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@app.post("/generate_topics")
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async def create_topics(input: TopicInput):
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topics = generate_topics(input.user_input, input.num_topics, input.
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return {"topics": topics}
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fix_json = JSONFixer()
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return loads(fix_json.fix(json_out).line)
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def generate_topics(user_input, num_topics, previous_queries):
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previous_context = " -> ".join(previous_queries)
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prompt = f"""create a list of {num_topics} subtopics to follow for conducting {user_input} in the context of {previous_context}, RETURN VALID PYTHON LIST"""
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response_topics = together_response(prompt, model="meta-llama/Llama-3-8b-chat-hf", SysPrompt=None)
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subtopics = json_from_text(response_topics)
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return subtopics
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class TopicInput(BaseModel):
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user_input: str = Query(default="market research", description="input query to generate subtopics")
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num_topics: int = Query(default=5, description="Number of subtopics to generate (default: 5)")
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previous_queries: list[str] = Query(default=[], description="List of previous queries for context")
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@app.get("/", tags=["Home"])
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def api_home():
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return {'detail': 'Welcome to FastAPI Subtopics API! Visit https://pvanand-generate-subtopics.hf.space/docs to test'}
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@app.post("/generate_topics")
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async def create_topics(input: TopicInput):
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topics = generate_topics(input.user_input, input.num_topics, input.previous_queries)
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return {"topics": topics}
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