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import os |
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from langchain.memory import ConversationBufferMemory |
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from langchain.utilities import GoogleSearchAPIWrapper |
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from langchain.agents import AgentType, initialize_agent, Tool |
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from lang import G4F |
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from fastapi import FastAPI, Request |
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from pydantic import BaseModel |
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from fastapi.middleware.cors import CORSMiddleware |
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from ImageCreator import generate_image_prodia |
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app = FastAPI() |
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app.add_middleware( |
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CORSMiddleware, |
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allow_credentials=True, |
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allow_origins=["*"], |
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allow_methods=["*"], |
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allow_headers=["*"], |
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) |
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google_api_key = os.environ["GOOGLE_API_KEY"] |
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cse_id = os.environ["GOOGLE_CSE_ID"] |
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model = os.environ['default_model'] |
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search = GoogleSearchAPIWrapper() |
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tools = [ |
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Tool( |
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name ="Search" , |
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func=search.run, |
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description="useful when you need to answer questions about current events" |
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), |
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] |
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llm = G4F(model=model) |
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agent_chain = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True) |
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@app.get("/") |
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def gello(): |
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return "Hello! My name is Linlada." |
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@app.post('/linlada') |
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async def hello_post(request: Request): |
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llm = G4F(model=model) |
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data = await request.json() |
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prompt = data['prompt'] |
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chat = llm(prompt) |
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return chat |
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@app.post('/search') |
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async def searches(request: Request): |
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data = await request.json() |
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prompt = data['prompt'] |
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response = agent_chain.run(input=prompt) |
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return response |
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@app.route("/", methods=["POST"]) |
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def generate_image(): |
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data = request.get_json() |
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prompt = data.get("prompt") |
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model = data.get("model") |
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sampler = data.get("sampler") |
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seed = int(data.get("seed")) |
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neg = data.get("neg") |
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response = generate_image_prodia(prompt, model, sampler, seed, neg) |
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return jsonify({"image": response}) |
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