import os
import json
import gradio as gr
from huggingface_hub import InferenceClient

HF_TOKEN = os.getenv("HF_TOKEN")

client = InferenceClient(
    provider="hf-inference",
    api_key=HF_TOKEN
)

MODEL = "Qwen/Qwen2.5-3B-Instruct"

SYSTEM_PROMPT = """
You are Human Dynamics AI.

Analyze conversations objectively.

Return ONLY valid JSON.

Schema:

{
    "summary":"",
    "communication_style":"",
    "positive_patterns":[],
    "negative_patterns":[],
    "possible_risks":[],
    "coaching":[],
    "follow_up_message":""
}

Rules:

- Never diagnose people.
- Never claim certainty.
- Express risks as possibilities.
- Give practical coaching.
- Return JSON only.
"""


def analyze(conversation):

    try:

        response = client.chat_completion(
            model=MODEL,
            messages=[
                {
                    "role": "system",
                    "content": SYSTEM_PROMPT
                },
                {
                    "role": "user",
                    "content": conversation
                }
            ],
            max_tokens=700,
            temperature=0.4
        )

        result = response.choices[0].message.content

        try:
            parsed = json.loads(result)
            return json.dumps(parsed, indent=4)

        except Exception:
            return result

    except Exception as e:
        return f"Error:\n\n{e}"


demo = gr.Interface(
    fn=analyze,
    title="Human Dynamics AI",
    description="""
Paste any conversation.

The AI will return

• Summary

• Communication Style

• Positive Patterns

• Negative Patterns

• Possible Risks

• Coaching Suggestions

• Follow-up Message
""",
    inputs=gr.Textbox(
        lines=20,
        placeholder="Paste conversation here..."
    ),
    outputs=gr.Code(language="json")
)

demo.launch()