initial commit

.gitignore

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+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.env
+*.env
+.env.*
+*.sqlite3
+*.db
+.DS_Store
+.vscode/
+.ipynb_checkpoints/
+.cache/
+*.log
+*.egg-info/
+dist/
+build/

requirements.txt

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+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: win-64
+accelerate=1.6.0=pypi_0
+aiohappyeyeballs=2.6.1=pypi_0
+aiohttp=3.11.18=pypi_0
+aiosignal=1.3.2=pypi_0
+annotated-types=0.7.0=pypi_0
+anyio=4.9.0=pypi_0
+asttokens=3.0.0=pyhd8ed1ab_1
+attrs=25.3.0=pypi_0
+bitsandbytes=0.45.5=pypi_0
+bzip2=1.0.8=h2bbff1b_6
+ca-certificates=2025.4.26=h4c7d964_0
+certifi=2025.4.26=pypi_0
+charset-normalizer=3.4.2=pypi_0
+click=8.2.1=pypi_0
+colorama=0.4.6=pyhd8ed1ab_1
+comm=0.2.2=pyhd8ed1ab_1
+contourpy=1.3.2=pypi_0
+cycler=0.12.1=pypi_0
+datasets=3.5.1=pypi_0
+debugpy=1.8.11=py311h5da7b33_0
+decorator=5.2.1=pyhd8ed1ab_0
+dill=0.3.7=pypi_0
+einops=0.7.0=pypi_0
+exceptiongroup=1.2.2=pyhd8ed1ab_1
+executing=2.2.0=pyhd8ed1ab_0
+fastapi=0.116.0=pypi_0
+filelock=3.18.0=pypi_0
+fonttools=4.57.0=pypi_0
+frozenlist=1.6.0=pypi_0
+fsspec=2023.10.0=pypi_0
+h11=0.16.0=pypi_0
+huggingface-hub=0.30.2=pypi_0
+idna=3.10=pypi_0
+importlib-metadata=8.6.1=pyha770c72_0
+ipykernel=6.29.5=pyh4bbf305_0
+ipython=9.2.0=pyhca29cf9_0
+ipython_pygments_lexers=1.1.1=pyhd8ed1ab_0
+ipywidgets=8.1.7=pypi_0
+jedi=0.19.2=pyhd8ed1ab_1
+jinja2=3.1.6=pypi_0
+jupyter_client=8.6.3=pyhd8ed1ab_1
+jupyter_core=5.7.2=py311h1ea47a8_0
+jupyterlab-widgets=3.0.15=pypi_0
+kiwisolver=1.4.8=pypi_0
+libffi=3.4.4=hd77b12b_1
+libsodium=1.0.18=h8d14728_1
+markupsafe=3.0.2=pypi_0
+matplotlib=3.10.1=pypi_0
+matplotlib-inline=0.1.7=pyhd8ed1ab_1
+mpmath=1.3.0=pypi_0
+multidict=6.4.3=pypi_0
+multiprocess=0.70.15=pypi_0
+nest-asyncio=1.6.0=pyhd8ed1ab_1
+networkx=3.4.2=pypi_0
+numpy=2.2.5=pypi_0
+openssl=3.0.16=h3f729d1_0
+packaging=25.0=pyh29332c3_1
+pandas=2.2.3=pypi_0
+parso=0.8.4=pyhd8ed1ab_1
+peft=0.15.2=pypi_0
+pickleshare=0.7.5=pyhd8ed1ab_1004
+pillow=11.2.1=pypi_0
+pip=25.1=pyhc872135_1
+platformdirs=4.3.7=pyh29332c3_0
+prompt-toolkit=3.0.51=pyha770c72_0
+propcache=0.3.1=pypi_0
+psutil=7.0.0=pypi_0
+pure_eval=0.2.3=pyhd8ed1ab_1
+pyarrow=20.0.0=pypi_0
+pyarrow-hotfix=0.7=pypi_0
+pydantic=2.11.7=pypi_0
+pydantic-core=2.33.2=pypi_0
+pygments=2.19.1=pyhd8ed1ab_0
+pyparsing=3.2.3=pypi_0
+python=3.11.11=h4607a30_0
+python-dateutil=2.9.0.post0=pyhff2d567_1
+python_abi=3.11=2_cp311
+pytz=2025.2=pypi_0
+pywin32=308=py311h5da7b33_0
+pyyaml=6.0.2=pypi_0
+pyzmq=24.0.1=py311h7b3f143_1
+regex=2024.11.6=pypi_0
+requests=2.32.3=pypi_0
+safetensors=0.5.3=pypi_0
+scipy=1.15.2=pypi_0
+seaborn=0.13.2=pypi_0
+setuptools=78.1.1=py311haa95532_0
+six=1.17.0=pyhd8ed1ab_0
+sniffio=1.3.1=pypi_0
+sqlite=3.45.3=h2bbff1b_0
+stack_data=0.6.3=pyhd8ed1ab_1
+starlette=0.46.2=pypi_0
+sympy=1.14.0=pypi_0
+tk=8.6.14=h0416ee5_0
+tokenizers=0.21.1=pypi_0
+torch=2.7.0+cu128=pypi_0
+torchaudio=2.7.0+cu128=pypi_0
+torchvision=0.22.0+cu128=pypi_0
+tornado=6.2=py311ha68e1ae_1
+tqdm=4.67.1=pypi_0
+traitlets=5.14.3=pyhd8ed1ab_1
+transformers=4.51.3=pypi_0
+typing-inspection=0.4.1=pypi_0
+typing_extensions=4.13.2=pyh29332c3_0
+tzdata=2025.2=pypi_0
+ucrt=10.0.22621.0=h57928b3_1
+urllib3=2.4.0=pypi_0
+uvicorn=0.35.0=pypi_0
+vc=14.42=haa95532_5
+vs2015_runtime=14.42.34433=hbfb602d_5
+wcwidth=0.2.13=pyhd8ed1ab_1
+wheel=0.45.1=py311haa95532_0
+widgetsnbextension=4.0.14=pypi_0
+xxhash=3.5.0=pypi_0
+xz=5.6.4=h4754444_1
+yarl=1.20.0=pypi_0
+zeromq=4.3.4=h0e60522_1
+zipp=3.21.0=pyhd8ed1ab_1
+zlib=1.2.13=h8cc25b3_1

server.py

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+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+from transformers import AutoTokenizer, T5ForConditionalGeneration, AutoModelForSeq2SeqLM
+import torch
+
+## Start the server with this command: uvicorn server:app --reload
+
+app = FastAPI()
+
+use_base_model = False
+
+
+if use_base_model:
+    # Load tokenizer and model (you can set torch_dtype=torch.float16 if on GPU)
+    tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
+    model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-small").to("cuda" if torch.cuda.is_available() else "cpu")
+else:
+    # Load custom model from Hugging Face Hub
+    model_name = "Cailean/macbeth"
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name).to("cuda" if torch.cuda.is_available() else "cpu")
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+class Query(BaseModel):
+    speaker: str
+    sentence: str
+    emotion: str
+    temp: float = 0.7
+
+@app.post("/test")
+def send_text(query: Query):
+    output = "hi!"
+    return {"response": output}
+
+@app.post("/generate")
+def generate_text(query: Query):
+    
+    speaker = query.speaker
+    sentence = query.sentence
+    emotion = query.emotion
+    temp = query.temp
+    
+    prompt = f"""Given the following dialogue from {speaker}: "{sentence}". Generate the next line of dialogue with the approriate speaker that expresses this specific emotion ({emotion}):"""
+    
+    print(prompt)
+    
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    if use_base_model:
+        outputs = model.generate(**inputs, temperature=temp, do_sample=True)
+    else:
+        outputs = model.generate(input_ids=inputs["input_ids"], max_length=64, num_beams=1, early_stopping=True, do_sample=True, temperature=0.8, eos_token_id=tokenizer.eos_token_id)
+        
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    print(response)
+    return {"response": response}