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Dockerfile

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+FROM python:latest
+
+WORKDIR /
+
+COPY ./requirements.txt .
+
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, HTTPException
+
+from fastapi.middleware.cors import CORSMiddleware
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+import logging
+
+app = FastAPI()
+
+# Add logging
+
+logging.basicConfig(level=logging.INFO)
+
+logger = logging.getLogger(__name__)
+
+formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
+
+handler = logging.StreamHandler()
+
+handler.setFormatter(formatter)
+
+logger.addHandler(handler)
+
+# Add CORS
+
+origins = ["*"]
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins,
+    allow_credentials=True,
+    allow_methods=["GET", "POST", "PUT", "DELETE"],
+    allow_headers=["*"],
+)
+
+intent_model = AutoModelForCausalLM.from_pretrained("llmware/slim-intent")
+intent_tokenizer = AutoTokenizer.from_pretrained("llmware/slim-intent")
+
+sentiment_model = AutoModelForCausalLM.from_pretrained("llmware/slim-sentiment")
+sentiment_tokenizer = AutoTokenizer.from_pretrained("llmware/slim-sentiment")
+
+def getResponse(model, tokenizer, text, params):
+  function = "classify"
+
+  prompt = "<human>: " + text + "\n" + f"<{function}> {params} </{function}>\n<bot>:"
+
+  inputs = tokenizer(prompt, return_tensors="pt")
+  start_of_input = len(inputs.input_ids[0])
+
+  outputs = model.generate(
+      inputs.input_ids.to('cpu'),
+      eos_token_id=tokenizer.eos_token_id,
+      pad_token_id=tokenizer.eos_token_id,
+      do_sample=True,
+      temperature=0.3,
+      max_new_tokens=100
+  )
+
+  output = tokenizer.decode(outputs[0][start_of_input:], skip_special_tokens=True)
+
+  return output
+
+@app.get("/")
+def read_root():
+    return {
+        "message": "API running successfully",
+        "endpoints": [
+            "/api/sentiment/",
+            "/api/intent/"
+        ]
+    }
+
+@app.post("/api/intent/")
+def intentResponse(text: str):
+  params = "intent"
+  try:
+    responses = getResponse(intent_model, intent_tokenizer, text, params)
+    return responses
+  except Exception as e:
+    logger.exception(e)
+    return {"API Error": str(e)}
+
+@app.post("/api/sentiment/")
+def sentimentResponse(text: str):
+  params = "sentiment"
+  try:
+    responses = getResponse(sentiment_model, sentiment_tokenizer, text, params)
+    return responses
+  except Exception as e:
+    logger.exception(e)
+    return {"API Error": str(e)}

requirements.txt

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+torch
+transformers
+fastapi
+uvicorn