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Browse files- app.py +77 -0
- requirements.txt +2 -0
app.py
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import os
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from huggingface_hub import InferenceClient
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import gradio as gr
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token = os.environ["HF_TOKEN"]
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client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct", token=token)
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SYSTEM_PROMPT = """Answer the following questions as best you can. You have access to the following tools:
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get_weather: Get the current weather in a given location
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The way you use the tools is by specifying a json blob.
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Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here).
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The only values that should be in the "action" field are:
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get_weather: Get the current weather in a given location, args: {"location": {"type": "string"}}
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example use :
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```
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{{
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"action": "get_weather",
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"action_input": {"location": "New York"}
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}}
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ALWAYS use the following format:
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Question: the input question you must answer
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Thought: you should always think about one action to take. Only one action at a time in this format:
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Action:
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```
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$JSON_BLOB
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```
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Observation: the result of the action. This Observation is unique, complete, and the source of truth.
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... (this Thought/Action/Observation can repeat N times, you should take several steps when needed. The $JSON_BLOB must be formatted as markdown and only use a SINGLE action at a time.)
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You must always end your output with the following format:
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Thought: I now know the final answer
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Final Answer: the final answer to the original input question
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Now begin! Reminder to ALWAYS use the exact characters `Final Answer:` when you provide a definitive answer. """
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prompt=f"""<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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{SYSTEM_PROMPT}
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<|eot_id|><|start_header_id|>user<|end_header_id|>
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What's the weather in London ?
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<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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"""
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output = client.text_generation(
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prompt,
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max_new_tokens=200,
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stop=["Observation:"]
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)
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# Dummy function
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def get_weather(location):
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return f"the weather in {location} is sunny with low temperatures. \n"
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new_prompt=prompt+output+get_weather('London')
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final_output = client.text_generation(
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new_prompt,
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max_new_tokens=200,
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)
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def llm():
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return final_output
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app = gr.Interface(
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title="Simple Agent",
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description="A simple agent that completes the text.",
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fn=llm,
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inputs=None,
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outputs="text"
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)
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app.launch()
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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gradio
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huggingface_hub
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