src/adapter.py

from __future__ import annotations

import base64
import json
import os
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union

import requests


import io
import re
import random
from dataclasses import dataclass
from typing import List, Dict, Callable, Optional, Tuple, Union

import streamlit as st
from PIL import Image, ImageDraw
import pandas as pd
from io import BytesIO

class BaseAdapterError(RuntimeError):
    pass

@dataclass
class BaseAdapter:
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    OPENAI = 'openai'
    ANTHROPIC = 'anthropic'
    GEMINI = 'gemini'
    MISTRAL = 'mistral'
    GROK = 'grok'
    COHERE = 'cohere'
    TOGETHER = 'together'
    providers = [OPENAI,
            ANTHROPIC, 
            GEMINI, 
            MISTRAL, 
            GROK,
            COHERE,
            TOGETHER  ]
    def __post_init__(self) -> None:
        self.provider = self.provider.lower().strip()
        if self.api_key is None:
            env_keys = {
                "openai": "OPENAI_API_KEY",
                "anthropic": "ANTHROPIC_API_KEY",
                "gemini": "GEMINI_API_KEY",
                "mistral": "MISTRAL_API_KEY",
                "grok" : "XAI_API_KEY",
                "cohere": "COHERE_API_KEY",
                "together": "TOGETHER_API_KEY",
            }
            env_var = env_keys.get(self.provider)
            if env_var:
                self.api_key = os.getenv(env_var)
        if not self.api_key and self.provider not in ("gemini",):
            raise BaseAdapterError(f"Missing api_key for {self.provider}. Set via environment.")

    @staticmethod
    def list_models(provider: str, api_key: Optional[str] = None, base_url: Optional[str] = None, timeout: float = 60.0) -> List[str]:
        p = provider.lower().strip()
        if p == "openai":
            url = (base_url or "https://api.openai.com") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('OPENAI_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        if p == "anthropic":
            return [
                "claude-3-5-sonnet-latest",
                "claude-3-5-haiku-latest",
                "claude-3-opus-latest",
            ]
        if p == "gemini":
            key = api_key or os.getenv("GEMINI_API_KEY")
            if not key:
                raise BaseAdapterError("Missing GEMINI_API_KEY.")
            url = (base_url or "https://generativelanguage.googleapis.com") + f"/v1beta/models?key={key}"
            r = requests.get(url, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["name"] for m in r.json().get("models", [])]
        if p == "grok":
            key = api_key or os.getenv("XAI_API_KEY")
            url = (base_url or "https://api.x.ai") + "/v1/models"
            headers = {"Authorization": f"Bearer {key}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]        
        if p == "mistral":
            url = (base_url or "https://api.mistral.ai") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('MISTRAL_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        if p == "cohere":
            url = (base_url or "https://api.cohere.ai") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('COHERE_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["name"] for m in r.json().get("models", [])]
        if p == "together":
            url = (base_url or "https://api.together.xyz") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('TOGETHER_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            BaseAdapter._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        raise BaseAdapterError(f"Unsupported provider: {p}")

    # ---------- Utilities ---------- #

    @staticmethod
    def _raise_for_status_static(response: requests.Response) -> None:
        if 200 <= response.status_code < 300:
            return
        try:
            detail = response.json()
            msg = json.dumps(detail)
        except Exception:
            msg = response.text
        raise BaseAdapterError(f"HTTP {response.status_code}: {msg}")

    def _raise_for_status(self, response: requests.Response) -> None:
        return self._raise_for_status_static(response)

    @staticmethod
    def _detect_mime(b: bytes) -> str:
        if len(b) >= 8 and b[:8] == b"\x89PNG\r\n\x1a\n":
            return "image/png"
        if len(b) >= 3 and b[:3] == b"\xff\xd8\xff":
            return "image/jpeg"
        if len(b) >= 6 and b[:6] in (b"GIF87a", b"GIF89a"):
            return "image/gif"
        if len(b) >= 12 and b[8:12] == b"WEBP":
            return "image/webp"
        return "application/octet-stream"

    @staticmethod
    def _normalize_image(image: Union[str, bytes], default_mime: str = "image/png") -> tuple[str, str, str]:
        """Return (data_url, base64_str, mime_type) for the given image input.
        Accepts bytes, base64 string, data URL, or local file path.
        """
        if isinstance(image, bytes):
            b64 = base64.b64encode(image).decode()
            mime = BaseAdapter._detect_mime(image)
            if mime == "application/octet-stream":
                mime = default_mime
            return f"data:{mime};base64,{b64}", b64, mime
        if isinstance(image, str):
            if image.startswith("data:"):
                header, b64 = image.split(",", 1)
                # data:image/png;base64,XXXX
                mime = header.split(";")[0].split(":", 1)[1] or default_mime
                return image, b64, mime
            if os.path.exists(image):
                with open(image, "rb") as f:
                    raw = f.read()
                b64 = base64.b64encode(raw).decode()
                mime = BaseAdapter._detect_mime(raw)
                if mime == "application/octet-stream":
                    mime = default_mime
                return f"data:{mime};base64,{b64}", b64, mime
            # assume bare base64 string
            b64 = image
            mime = default_mime
            return f"data:{mime};base64,{b64}", b64, mime
        raise BaseAdapterError("Unsupported image type; pass bytes, path, base64 string, or data URL.")



class OpenaiAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.OPENAI, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.openai.com") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content = [{"type": "text", "text": prompt}]
        data_url = None
        if image is not None:
            if not isinstance(image, list):
                image = [image]
            
            for img in image:
                data_url, _b64, _mime = self._normalize_image(img, default_mime="image/png")
                content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()


class AnthropicAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.ANTHROPIC, model_name)
        
    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.anthropic.com") + "/v1/messages"
        headers = {
            "x-api-key": self.api_key or "",
            "anthropic-version": "2023-06-01",
            "content-type": "application/json",
            **self.extra_headers,
        }
        content_items: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            if not isinstance(image, list):
                image = [image]
            for img in image:
                _data_url, b64, mime = self._normalize_image(img, default_mime="image/png")
                content_items.append({
                    "type": "image",
                    "source": {
                        "type": "base64",
                        "media_type": mime,
                        "data": b64,
                    },
                })
        payload: Dict[str, Any] = {
            "model": self.model,
            "max_tokens": kwargs.get("max_tokens", 1024),
            "messages": [{"role": "user", "content": content_items}],
        }
        if system:
            payload["system"] = system
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        parts = data.get("content", [])
        return "".join(p.get("text", "") for p in parts if p.get("type") == "text").strip()




class GeminiAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.GEMINI, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        key = self.api_key or os.getenv("GEMINI_API_KEY")
        if not key:
            raise BaseAdapterError("Missing GEMINI_API_KEY.")
        base = self.base_url or "https://generativelanguage.googleapis.com"
        url = f"{base}/v1beta/models/{self.model}:generateContent?key={key}"
        headers = {"Content-Type": "application/json", **self.extra_headers}
        parts = [{"text": prompt}]
        if image is not None:
            if not isinstance(image,list):
                image = [image]
            for img in image:
                _data_url, b64, mime = self._normalize_image(img, default_mime="image/png")
                parts.append({"inline_data": {"mime_type": mime, "data": b64}})
        contents = [{"role": "user", "parts": parts}]
        if system:
            contents.insert(0, {"role": "system", "parts": [{"text": system}]})
        payload: Dict[str, Any] = {"contents": contents}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["candidates"][0]["content"]["parts"][0]["text"].strip()


class MistralAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.MISTRAL, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.mistral.ai") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            if not isinstance(image, list):
                image = [image]
            for img in image:
                data_url, _b64, _mime = self._normalize_image(img, default_mime="image/png")
                content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()

class GrokAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.GROK, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.x.ai") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content = [{"type": "text", "text": prompt}]
        data_url = None
        if image is not None:
            if not isinstance(image, list):
                image = [image]
            for img in image:
                data_url, _b64, _mime = self._normalize_image(img, default_mime="image/png")
                content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()





class TogetherAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.TOGETHER, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.together.xyz") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            if not isinstance(image, list):
                image = [image]
            for img in image:
                data_url, _b64, _mime = self._normalize_image(img, default_mime="image/png")
                content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()



class CohereAdapter(BaseAdapter):
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __init__(self, model_name):
        super().__init__(BaseAdapter.COHERE, model_name)

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[List[Union[str, bytes, Image]] ] = None, **kwargs: Any) -> str:
        url = (self.base_url or "https://api.cohere.ai") + "/v1/chat"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        payload: Dict[str, Any] = {"model": self.model, "message": prompt}
        if system:
            payload["preamble"] = system
        if image is not None:
            if not isinstane(image, list):
                image = [image]
            for img in image:
                data_url, _b64, mime = self._normalize_image(img, default_mime="image/png")
                # Cohere chat supports attachments; we send a data URL to keep it dependency-light
                payload["attachments"] = [
                    {
                        "type": "image",
                        "image_url": data_url,
                        "mime_type": mime,
                    }
                ]
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        # Cohere responses can be under 'text' or 'message.content'
        return (data.get("text") or data.get("message", {}).get("content", [{}])[0].get("text", "")).strip()

























































'''

@dataclass
class UniLLM:
    provider: str
    model: str
    api_key: Optional[str] = None
    timeout: float = 60.0
    base_url: Optional[str] = None
    extra_headers: Dict[str, str] = field(default_factory=dict)

    def __post_init__(self) -> None:
        self.provider = self.provider.lower().strip()
        if self.api_key is None:
            env_keys = {
                "openai": "OPENAI_API_KEY",
                "anthropic": "ANTHROPIC_API_KEY",
                "gemini": "GEMINI_API_KEY",
                "mistral": "MISTRAL_API_KEY",
                "cohere": "COHERE_API_KEY",
                "together": "TOGETHER_API_KEY",
            }
            env_var = env_keys.get(self.provider)
            if env_var:
                self.api_key = os.getenv(env_var)
        if not self.api_key and self.provider not in ("gemini",):
            raise UniLLMError(f"Missing api_key for {self.provider}. Set via environment.")

    # ---------- Public API ---------- #

    def generate(self, prompt: str, system: Optional[str] = None, image: Optional[Union[str, bytes]] = None, **kwargs: Any) -> str:
        p = self.provider
        if p == "openai":
            return self._openai_chat(prompt, system, image, **kwargs)
        if p == "anthropic":
            return self._anthropic_messages(prompt, system, image, **kwargs)
        if p == "gemini":
            return self._gemini_generate_content(prompt, system, image, **kwargs)
        if p == "mistral":
            return self._mistral_chat(prompt, system, image, **kwargs)
        if p == "cohere":
            return self._cohere_chat(prompt, system, image, **kwargs)
        if p == "together":
            return self._together_chat(prompt, system, image, **kwargs)
        raise UniLLMError(f"Unsupported provider: {p}")

    @staticmethod
    def list_models(provider: str, api_key: Optional[str] = None, base_url: Optional[str] = None, timeout: float = 60.0) -> List[str]:
        p = provider.lower().strip()
        if p == "openai":
            url = (base_url or "https://api.openai.com") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('OPENAI_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            UniLLM._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        if p == "anthropic":
            return [
                "claude-3-5-sonnet-latest",
                "claude-3-5-haiku-latest",
                "claude-3-opus-latest",
            ]
        if p == "gemini":
            key = api_key or os.getenv("GEMINI_API_KEY")
            if not key:
                raise UniLLMError("Missing GEMINI_API_KEY.")
            url = (base_url or "https://generativelanguage.googleapis.com") + f"/v1beta/models?key={key}"
            r = requests.get(url, timeout=timeout)
            UniLLM._raise_for_status_static(r)
            return [m["name"] for m in r.json().get("models", [])]
        if p == "mistral":
            url = (base_url or "https://api.mistral.ai") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('MISTRAL_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            UniLLM._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        if p == "cohere":
            url = (base_url or "https://api.cohere.ai") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('COHERE_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            UniLLM._raise_for_status_static(r)
            return [m["name"] for m in r.json().get("models", [])]
        if p == "together":
            url = (base_url or "https://api.together.xyz") + "/v1/models"
            headers = {"Authorization": f"Bearer {api_key or os.getenv('TOGETHER_API_KEY')}"}
            r = requests.get(url, headers=headers, timeout=timeout)
            UniLLM._raise_for_status_static(r)
            return [m["id"] for m in r.json().get("data", [])]
        raise UniLLMError(f"Unsupported provider: {p}")

    # ---------- Provider helpers ---------- #

    def _openai_chat(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        url = (self.base_url or "https://api.openai.com") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content = [{"type": "text", "text": prompt}]
        data_url = None
        if image is not None:
            data_url, _b64, _mime = self._normalize_image(image, default_mime="image/png")
            content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()

    def _anthropic_messages(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        url = (self.base_url or "https://api.anthropic.com") + "/v1/messages"
        headers = {
            "x-api-key": self.api_key or "",
            "anthropic-version": "2023-06-01",
            "content-type": "application/json",
            **self.extra_headers,
        }
        content_items: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            _data_url, b64, mime = self._normalize_image(image, default_mime="image/png")
            content_items.append({
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": mime,
                    "data": b64,
                },
            })
        payload: Dict[str, Any] = {
            "model": self.model,
            "max_tokens": kwargs.get("max_tokens", 1024),
            "messages": [{"role": "user", "content": content_items}],
        }
        if system:
            payload["system"] = system
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        parts = data.get("content", [])
        return "".join(p.get("text", "") for p in parts if p.get("type") == "text").strip()

    def _gemini_generate_content(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        key = self.api_key or os.getenv("GEMINI_API_KEY")
        if not key:
            raise UniLLMError("Missing GEMINI_API_KEY.")
        base = self.base_url or "https://generativelanguage.googleapis.com"
        url = f"{base}/v1beta/models/{self.model}:generateContent?key={key}"
        headers = {"Content-Type": "application/json", **self.extra_headers}
        parts = [{"text": prompt}]
        if image is not None:
            _data_url, b64, mime = self._normalize_image(image, default_mime="image/png")
            parts.append({"inline_data": {"mime_type": mime, "data": b64}})
        contents = [{"role": "user", "parts": parts}]
        if system:
            contents.insert(0, {"role": "system", "parts": [{"text": system}]})
        payload: Dict[str, Any] = {"contents": contents}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["candidates"][0]["content"]["parts"][0]["text"].strip()

    def _mistral_chat(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        url = (self.base_url or "https://api.mistral.ai") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            data_url, _b64, _mime = self._normalize_image(image, default_mime="image/png")
            content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()

    def _cohere_chat(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        url = (self.base_url or "https://api.cohere.ai") + "/v1/chat"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        payload: Dict[str, Any] = {"model": self.model, "message": prompt}
        if system:
            payload["preamble"] = system
        if image is not None:
            data_url, _b64, mime = self._normalize_image(image, default_mime="image/png")
            # Cohere chat supports attachments; we send a data URL to keep it dependency-light
            payload["attachments"] = [
                {
                    "type": "image",
                    "image_url": data_url,
                    "mime_type": mime,
                }
            ]
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        # Cohere responses can be under 'text' or 'message.content'
        return (data.get("text") or data.get("message", {}).get("content", [{}])[0].get("text", "")).strip()

    def _together_chat(self, prompt: str, system: Optional[str], image: Optional[Union[str, bytes]], **kwargs: Any) -> str:
        url = (self.base_url or "https://api.together.xyz") + "/v1/chat/completions"
        headers = {"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", **self.extra_headers}
        messages = []
        if system:
            messages.append({"role": "system", "content": system})
        content: List[Dict[str, Any]] = [{"type": "text", "text": prompt}]
        if image is not None:
            data_url, _b64, _mime = self._normalize_image(image, default_mime="image/png")
            content.append({"type": "image_url", "image_url": {"url": data_url}})
        messages.append({"role": "user", "content": content})
        payload = {"model": self.model, "messages": messages}
        r = requests.post(url, headers=headers, json=payload, timeout=self.timeout)
        self._raise_for_status(r)
        data = r.json()
        return data["choices"][0]["message"]["content"].strip()

    # ---------- Utilities ---------- #

    @staticmethod
    def _raise_for_status_static(response: requests.Response) -> None:
        if 200 <= response.status_code < 300:
            return
        try:
            detail = response.json()
            msg = json.dumps(detail)
        except Exception:
            msg = response.text
        raise UniLLMError(f"HTTP {response.status_code}: {msg}")

    def _raise_for_status(self, response: requests.Response) -> None:
        return self._raise_for_status_static(response)

    @staticmethod
    def _detect_mime(b: bytes) -> str:
        if len(b) >= 8 and b[:8] == b"\x89PNG\r\n\x1a\n":
            return "image/png"
        if len(b) >= 3 and b[:3] == b"\xff\xd8\xff":
            return "image/jpeg"
        if len(b) >= 6 and b[:6] in (b"GIF87a", b"GIF89a"):
            return "image/gif"
        if len(b) >= 12 and b[8:12] == b"WEBP":
            return "image/webp"
        return "application/octet-stream"

    @staticmethod
    def _normalize_image(image: Union[str, bytes], default_mime: str = "image/png") -> tuple[str, str, str]:
        """Return (data_url, base64_str, mime_type) for the given image input.
        Accepts bytes, base64 string, data URL, or local file path.
        """
        if isinstance(image, bytes):
            b64 = base64.b64encode(image).decode()
            mime = UniLLM._detect_mime(image)
            if mime == "application/octet-stream":
                mime = default_mime
            return f"data:{mime};base64,{b64}", b64, mime
        if isinstance(image, str):
            if image.startswith("data:"):
                header, b64 = image.split(",", 1)
                # data:image/png;base64,XXXX
                mime = header.split(";")[0].split(":", 1)[1] or default_mime
                return image, b64, mime
            if os.path.exists(image):
                with open(image, "rb") as f:
                    raw = f.read()
                b64 = base64.b64encode(raw).decode()
                mime = BaseAdapter._detect_mime(raw)
                if mime == "application/octet-stream":
                    mime = default_mime
                return f"data:{mime};base64,{b64}", b64, mime
            # assume bare base64 string
            b64 = image
            mime = default_mime
            return f"data:{mime};base64,{b64}", b64, mime
        raise BaseAdapter("Unsupported image type; pass bytes, path, base64 string, or data URL.")

'''