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https://github.com/PlatypusPus/MushroomEmpire.git
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62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
import ollama
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import chromadb
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from pypdf import PdfReader
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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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import uvicorn
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client = chromadb.Client()
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collection = client.create_collection(name="docs")
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reader = PdfReader('../../GDPRArticles.pdf')
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chunks = [page.extract_text().strip() for page in reader.pages if page.extract_text().strip()]
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print("Done reading pages!")
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for i, chunk in enumerate(chunks):
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response = ollama.embed(model="nomic-embed-text", input=chunk)
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embedding = response["embeddings"][0]
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collection.add(
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ids=[str(i)],
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embeddings=[embedding],
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documents=[chunk]
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)
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print("Embeddings done!")
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app = FastAPI()
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# Allow browser calls from the frontend
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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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 ChatRequest(BaseModel):
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prompt: str
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@app.post("/chat")
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async def chat_bot(prompt: str | None = None, body: ChatRequest | None = None):
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# Accept prompt from either query (?prompt=) or JSON body {"prompt": "..."}
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query = prompt or (body.prompt if body else None)
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if not query:
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raise HTTPException(status_code=400, detail="Missing prompt")
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response = ollama.embed(model="nomic-embed-text", input=query)
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query_embedding = response["embeddings"][0]
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results = collection.query(
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query_embeddings=[query_embedding],
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n_results=1
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)
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data = results['documents'][0][0]
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output = ollama.generate(
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model="llama3.2",
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prompt=f"Context: {data}\n\nQuestion: {query}\n\nAnswer:"
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)
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return {"response": output["response"]}
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if __name__ == '__main__':
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uvicorn.run(app, port=8080, host='0.0.0.0') |