Update app.py

app.py

@@ -0,0 +1,57 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from huggingface_hub import InferenceClient
+import uvicorn
+
+app = FastAPI()
+
+# Initialize the InferenceClient with the specified model
+client = InferenceClient("nvidia/Llama-3.1-Nemotron-70B-Instruct-HF")
+
+# Define the structure of the request body
+class CourseRequest(BaseModel):
+    course_name: str
+    history: list = []  # Keeping history optional
+    temperature: float = 0.0
+    max_new_tokens: int = 1048
+    top_p: float = 0.15
+    repetition_penalty: float = 1.0
+
+# Format the prompt for the model
+def format_prompt(course_name, history):
+    prompt = "<s>"
+    for user_prompt, bot_response in history:
+        prompt += f"[INST] {user_prompt} [/INST] {bot_response} </s> "
+    prompt += f"[INST] Generate a roadmap for the course: {course_name} [/INST]"
+    return prompt
+
+# Generate text using the specified parameters
+def generate(course_request: CourseRequest):
+    temperature = max(float(course_request.temperature), 1e-2)
+    top_p = float(course_request.top_p)
+
+    generate_kwargs = {
+        'temperature': temperature,
+        'max_new_tokens': course_request.max_new_tokens,
+        'top_p': top_p,
+        'repetition_penalty': course_request.repetition_penalty,
+        'do_sample': True,
+        'seed': 42,
+    }
+
+    formatted_prompt = format_prompt(course_request.course_name, course_request.history)
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+    return output
+
+# Define the API endpoint for generating course roadmaps
+@app.post("/generate-roadmap/")
+async def generate_roadmap(course_request: CourseRequest):
+    return {"roadmap": generate(course_request)}
+
+# Run the application (uncomment the next two lines if running this as a standalone script)
+# if __name__ == "__main__":
+#     uvicorn.run(app, host="0.0.0.0", port=8000)