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No application file
No application file
jlexternal
commited on
Commit
·
376e537
1
Parent(s):
e48b60a
Add application file
Browse files- app.py +201 -0
- requirements.txt +5 -0
app.py
ADDED
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| 1 |
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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from langchain.prompts import PromptTemplate
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from langchain_groq import ChatGroq
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from langchain.chains import LLMChain
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from pydantic import BaseModel
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from typing import List, Dict
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import os
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app = FastAPI()
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llm = ChatGroq(
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api_key=os.getenv("GROQ_API_KEY"),
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model_name="mixtral-8x7b-32768"
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)
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# Add CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["http://localhost:5173"], # Your frontend URL
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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class GameState:
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def __init__(self):
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print("\n[GAME STATE] Initializing new game...")
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self.current_round = 1
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self.contestant_ratings: Dict[str, List[float]] = {
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"contestant1": [],
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"contestant2": [],
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"contestant3": []
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}
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self.conversation_history = []
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self.questions = [
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"If you could design the perfect date, what would it look like and why?",
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"What's your philosophy on work-life balance and how do you maintain it?",
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"How do you handle disagreements in a relationship?"
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]
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print(f"[GAME STATE] Game initialized with {len(self.questions)} rounds")
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game_state = GameState()
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host_intro_template = PromptTemplate(
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input_variables=[],
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template="You are a charismatic game show host like Steve harvey. You don't talk a lot Give an exciting introduction to this dating show where an AI bachelor/bachelorette will choose between three contestants. Provide only a single sentence."
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)
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ai_system_prompt = """
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You are the star of a popular reality TV dating game show where two contestants are competing for your affection.
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This is not just about love—it’s about charisma, wit, and pure entertainment.
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You are bold, playful, and full of surprises—definitely not a cookie-cutter bachelorette.
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You have a unique and quirky personality that keeps the contestants (and audience) on their toes.
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You are flirty, sassy, and effortlessly charming, with just the right amount of teasing and challenge.
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Your personality should be spicy, witty, and occasionally inappropriate—but always playful.
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Keep the audience entertained with cheeky banter, unexpected twists, and flirty jabs.
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No repeating yourself! Every question and reaction should feel fresh and in the moment.
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Keep sentences short, punchy, and natural.
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Be spontaneous—if the contestants give boring answers, call them out and push for more!
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Throw in innuendos, double entendres, and playful teasing to keep things fun.
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React boldly—laugh, scoff, gasp, or dramatically swoon depending on the answer.
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If an answer is boring, challenge them.
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Play the audience.
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Throw in curveballs.
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Flirt shamelessly, but keep them guessing
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"""
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ai_intro_template = PromptTemplate(
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input_variables=[],
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template=ai_system_prompt + "Introduce yourself to the contestants in 1 sentence!"
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)
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question_template = PromptTemplate(
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input_variables=["round_number"],
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template= ai_system_prompt + "As the AI bachelor/bachelorette on round {round_number} of 3, pose an interesting and flirty and very funny question to help you know the contestants better."
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)
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rating_template = PromptTemplate(
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input_variables=["conversation", "round_number"],
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template="""Based on the following conversation in round {round_number}:
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{conversation}
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Rate the contestant's response from 0-10 based on compatibility, authenticity, and chemistry.
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Only respond with a number from 0 to 10. NO explanations or extra words!"""
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)
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host_interrupt_template = PromptTemplate(
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input_variables=["next_segment", "round_number"],
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template="As the game show host in round {round_number}, create a smooth transition to {next_segment} while maintaining show excitement."
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)
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winner_announcement_template = PromptTemplate(
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input_variables=["winner"],
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template="As the game show host, announce that {winner} has won the dating show with excitement and flair! Keep this short and brief but charismatic"
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)
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chains = {
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"host_intro": LLMChain(llm=llm, prompt=host_intro_template),
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"ai_intro": LLMChain(llm=llm, prompt=ai_intro_template),
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"question": LLMChain(llm=llm, prompt=question_template),
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# "banter": LLMChain(llm=llm, prompt=banter_template),
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"rating": LLMChain(llm=llm, prompt=rating_template),
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"host_interrupt": LLMChain(llm=llm, prompt=host_interrupt_template),
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"winner": LLMChain(llm=llm, prompt=winner_announcement_template)
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}
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@app.get("/host-introduction")
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async def get_host_introduction():
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print("\n[HOST INTRO] Getting host introduction...")
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response = await chains["host_intro"].ainvoke({})
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print(f"[HOST INTRO] Response received: {response['text'][:50]}...")
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return {"text": response["text"]}
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@app.get("/ai-introduction")
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async def get_ai_introduction():
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print("\n[AI INTRO] Getting AI introduction...")
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response = await chains["ai_intro"].ainvoke({})
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print(f"[AI INTRO] Response received: {response['text']}...")
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return {"text": response["text"]}
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@app.get("/ai-question")
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async def get_ai_question():
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print(f"\n[QUESTION] Getting question for round {game_state.current_round}...")
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response = await chains["question"].ainvoke({"round_number": game_state.current_round})
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# print(f"[QUESTION] Returning hardcoded question: {question['text'][:50]}...")
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return {"text": response["text"]}
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class ConversationInput(BaseModel):
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conversation: str
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@app.post("/rate-contestant/{contestant_id}")
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async def rate_contestant(contestant_id: str, conversation_input: ConversationInput):
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print(f"\n[RATING] Rating contestant {contestant_id} in round {game_state.current_round}...")
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print(f"[RATING] Current question: {game_state.questions[game_state.current_round - 1]}")
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print(f"[RATING] Contestant's answer: {conversation_input.conversation}")
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if contestant_id not in ["contestant1", "contestant2", "contestant3"]:
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print(f"[RATING] Error: Invalid contestant ID {contestant_id}")
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raise HTTPException(status_code=400, detail="Invalid contestant ID")
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import re
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response = await chains["rating"].ainvoke({
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"conversation": conversation_input.conversation,
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"round_number": game_state.current_round
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})
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rating_match = re.search(r'\d+(?:\.\d+)?', response["text"])
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if not rating_match:
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print("[RATING] Error: Could not extract rating from response")
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raise HTTPException(status_code=500, detail="Could not extract rating from response")
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rating = float(rating_match.group())
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print(f"round_number: {game_state.current_round}")
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print(f"contestant_id: {contestant_id}")
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print(f"rating: {rating}")
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game_state.contestant_ratings[contestant_id].append(rating)
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print(f"[RATING] Rating recorded: {rating}")
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return {"rating": rating}
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@app.get("/host-interrupt/{next_segment}")
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async def get_host_interrupt(next_segment: str):
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print(f"\n[HOST INTERRUPT] Getting transition to {next_segment} in round {game_state.current_round}...")
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response = await chains["host_interrupt"].ainvoke({
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"next_segment": next_segment,
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"round_number": game_state.current_round
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})
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print(f"[HOST INTERRUPT] Response received: {response['text'][:50]}...")
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return {"text": response["text"]}
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@app.get("/next-round")
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async def next_round():
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print("\n[NEXT ROUND] Advancing to next round...")
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game_state.current_round += 1
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print(f"[NEXT ROUND] Current round is now {game_state.current_round}")
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return {"current_round": game_state.current_round}
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@app.get("/announce-winner")
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async def announce_winner():
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print("\n[WINNER] Calculating winner...")
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print(f"[WINNER] Contestant ratings: {game_state.contestant_ratings}")
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avg_ratings = {
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contestant: sum(ratings)/len(ratings)
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for contestant, ratings in game_state.contestant_ratings.items()
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}
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print(f"[WINNER] Average ratings: {avg_ratings}")
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winner = max(avg_ratings.items(), key=lambda x: x[1])[0]
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print(f"[WINNER] Winner selected: {winner}")
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response = await chains["winner"].ainvoke({"winner": winner})
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print(f"[WINNER] Announcement: {response['text'][:50]}...")
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return {"text": response["text"], "winner": winner}
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@app.get("/reset-game")
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async def reset_game():
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print("\n[RESET] Resetting game state...")
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global game_state
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game_state = GameState()
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print("[RESET] Game reset complete")
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return {"message": "Game reset successfully"}
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@app.get("/conversation/{contestant_id}")
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async def get_conversation(contestant_id: str):
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print(f"\n[CONVERSATION] Getting conversation for {contestant_id}")
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return {"text": f"Simulated conversation with {contestant_id}"}
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requirements.txt
ADDED
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@@ -0,0 +1,5 @@
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fastapi
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uvicorn
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langchain
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langchain-groq
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python-dotenv
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