Add cohere vision

cookbook/models/aws/bedrock/image_agent_bytes.py

@@ -4,6 +4,7 @@
 from agno.media import Image
 from agno.models.aws import AwsBedrock
 from agno.tools.duckduckgo import DuckDuckGoTools
+from agno.utils.media import download_image
 
 agent = Agent(
     model=AwsBedrock(id="amazon.nova-pro-v1:0"),
@@ -13,9 +14,10 @@
 
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image and give me the latest news about it.",

cookbook/models/azure/ai_foundry/image_agent_bytes.py

@@ -3,6 +3,7 @@
 from agno.agent import Agent
 from agno.media import Image
 from agno.models.azure import AzureAIFoundry
+from agno.utils.media import download_image
 
 agent = Agent(
     model=AzureAIFoundry(id="Llama-3.2-11B-Vision-Instruct"),
@@ -11,9 +12,10 @@
 
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image.",

cookbook/models/cohere/image_agent.py

@@ -0,0 +1,18 @@
+from agno.agent import Agent
+from agno.media import Image
+from agno.models.cohere import Cohere
+
+agent = Agent(
+    model=Cohere(id="c4ai-aya-vision-8b"),
+    markdown=True,
+)
+
+agent.print_response(
+    "Tell me about this image.",
+    images=[
+        Image(
+            url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg"
+        )
+    ],
+    stream=True,
+)

cookbook/models/cohere/image_agent_bytes.py

@@ -0,0 +1,26 @@
+from pathlib import Path
+
+from agno.agent import Agent
+from agno.media import Image
+from agno.models.cohere.chat import Cohere
+from agno.utils.media import download_image
+
+agent = Agent(
+    model=Cohere(id="c4ai-aya-vision-8b"),
+    markdown=True,
+)
+
+image_path = Path(__file__).parent.joinpath("sample.jpg")
+
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
+# Read the image file content as bytes
+image_bytes = image_path.read_bytes()
+
+agent.print_response(
+    "Tell me about this image.",
+    images=[
+        Image(content=image_bytes),
+    ],
+    stream=True,
+)

cookbook/models/cohere/image_agent_local_file.py

@@ -0,0 +1,23 @@
+from pathlib import Path
+
+from agno.agent import Agent
+from agno.media import Image
+from agno.models.cohere.chat import Cohere
+from agno.utils.media import download_image
+
+agent = Agent(
+    model=Cohere(id="c4ai-aya-vision-8b"),
+    markdown=True,
+)
+
+image_path = Path(__file__).parent.joinpath("sample.jpg")
+
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
+agent.print_response(
+    "Tell me about this image.",
+    images=[
+        Image(filepath=image_path),
+    ],
+    stream=True,
+)

cookbook/models/ibm/watsonx/image_agent_bytes.py

@@ -3,7 +3,6 @@
 from agno.agent import Agent
 from agno.media import Image
 from agno.models.ibm import WatsonX
-from agno.tools.duckduckgo import DuckDuckGoTools
 
 agent = Agent(
     model=WatsonX(id="meta-llama/llama-3-2-11b-vision-instruct"),
@@ -13,8 +12,7 @@
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image and and give me the latest news about it.",

cookbook/models/openai/image_agent_bytes.py

@@ -4,6 +4,7 @@
 from agno.media import Image
 from agno.models.openai import OpenAIChat
 from agno.tools.duckduckgo import DuckDuckGoTools
+from agno.utils.media import download_image
 
 agent = Agent(
     model=OpenAIChat(id="gpt-4o"),
@@ -13,9 +14,10 @@
 
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image and give me the latest news about it.",

cookbook/models/together/image_agent_bytes.py

@@ -12,8 +12,7 @@
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image",

cookbook/models/xai/image_agent_bytes.py

@@ -4,6 +4,7 @@
 from agno.media import Image
 from agno.models.xai import xAI
 from agno.tools.duckduckgo import DuckDuckGoTools
+from agno.utils.media import download_image
 
 agent = Agent(
     model=xAI(id="grok-2-vision-latest"),
@@ -13,9 +14,10 @@
 
 image_path = Path(__file__).parent.joinpath("sample.jpg")
 
+download_image(url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg", save_path=str(image_path))
+
 # Read the image file content as bytes
-with open(image_path, "rb") as img_file:
-    image_bytes = img_file.read()
+image_bytes = image_path.read_bytes()
 
 agent.print_response(
     "Tell me about this image and give me the latest news about it.",

libs/agno/agno/models/cohere/chat.py

@@ -1,8 +1,10 @@
 from dataclasses import dataclass
 from os import getenv
-from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Tuple
+from pathlib import Path
+from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Sequence, Tuple
 
 from agno.exceptions import ModelProviderError
+from agno.media import Image
 from agno.models.base import MessageData, Model
 from agno.models.message import Message
 from agno.models.response import ModelResponse
@@ -17,6 +19,78 @@
     raise ImportError("`cohere` not installed. Please install using `pip install cohere`")
 
 
+def _format_images_for_message(message: Message, images: Sequence[Image]) -> List[Dict[str, Any]]:
+    """
+    Format an image into the format expected by WatsonX.
+    """
+
+    # Create a default message content with text
+    message_content_with_image: List[Dict[str, Any]] = [{"type": "text", "text": message.content}]
+
+    # Add images to the message content
+    for image in images:
+        try:
+            if image.content is not None:
+                image_content = image.content
+            elif image.url is not None:
+                image_content = image.image_url_content
+            elif image.filepath is not None:
+                if isinstance(image.filepath, Path):
+                    image_content = image.filepath.read_bytes()
+                else:
+                    with open(image.filepath, "rb") as f:
+                        image_content = f.read()
+            else:
+                logger.warning(f"Unsupported image format: {image}")
+                continue
+
+            if image_content is not None:
+                import base64
+
+                base64_image = base64.b64encode(image_content).decode("utf-8")
+                image_url = f"data:image/jpeg;base64,{base64_image}"
+                image_payload = {"type": "image_url", "image_url": {"url": image_url}}
+                message_content_with_image.append(image_payload)
+
+        except Exception as e:
+            logger.error(f"Failed to process image: {str(e)}")
+
+    # Update the message content with the images
+    return message_content_with_image
+
+
+def _format_messages(messages: List[Message]) -> List[Dict[str, Any]]:
+    """
+    Format messages for the Cohere API.
+
+    Args:
+        messages (List[Message]): The list of messages.
+
+    Returns:
+        List[Dict[str, Any]]: The formatted messages.
+    """
+    formatted_messages = []
+    for message in messages:
+        message_dict = {
+            "role": message.role,
+            "content": message.content,
+            "name": message.name,
+            "tool_call_id": message.tool_call_id,
+            "tool_calls": message.tool_calls,
+        }
+
+        if message.images is not None and len(message.images) > 0:
+            # Ignore non-string message content
+            if isinstance(message.content, str):
+                message_content_with_image = _format_images_for_message(message=message, images=message.images)
+                if len(message_content_with_image) > 1:
+                    message_dict["content"] = message_content_with_image
+
+        message_dict = {k: v for k, v in message_dict.items() if v is not None}
+        formatted_messages.append(message_dict)
+    return formatted_messages
+
+
 @dataclass
 class Cohere(Model):
     id: str = "command-r-plus"
@@ -116,29 +190,6 @@ def request_kwargs(self) -> Dict[str, Any]:
             _request_params.update(self.request_params)
         return _request_params
 
-    def _format_messages(self, messages: List[Message]) -> List[Dict[str, Any]]:
-        """
-        Format messages for the Cohere API.
-
-        Args:
-            messages (List[Message]): The list of messages.
-
-        Returns:
-            List[Dict[str, Any]]: The formatted messages.
-        """
-        formatted_messages = []
-        for message in messages:
-            message_dict = {
-                "role": message.role,
-                "content": message.content,
-                "name": message.name,
-                "tool_call_id": message.tool_call_id,
-                "tool_calls": message.tool_calls,
-            }
-            message_dict = {k: v for k, v in message_dict.items() if v is not None}
-            formatted_messages.append(message_dict)
-        return formatted_messages
-
     def invoke(self, messages: List[Message]) -> ChatResponse:
         """
         Invoke a non-streamed chat response from the Cohere API.
@@ -153,7 +204,7 @@ def invoke(self, messages: List[Message]) -> ChatResponse:
         request_kwargs = self.request_kwargs
 
         try:
-            return self.get_client().chat(model=self.id, messages=self._format_messages(messages), **request_kwargs)  # type: ignore
+            return self.get_client().chat(model=self.id, messages=_format_messages(messages), **request_kwargs)  # type: ignore
         except Exception as e:
             logger.error(f"Unexpected error calling Cohere API: {str(e)}")
             raise ModelProviderError(message=str(e), model_name=self.name, model_id=self.id) from e
@@ -173,7 +224,7 @@ def invoke_stream(self, messages: List[Message]) -> Iterator[StreamedChatRespons
         try:
             return self.get_client().chat_stream(
                 model=self.id,
-                messages=self._format_messages(messages),  # type: ignore
+                messages=_format_messages(messages),  # type: ignore
                 **request_kwargs,
             )
         except Exception as e:
@@ -195,7 +246,7 @@ async def ainvoke(self, messages: List[Message]) -> ChatResponse:
         try:
             return await self.get_async_client().chat(
                 model=self.id,
-                messages=self._format_messages(messages),  # type: ignore
+                messages=_format_messages(messages),  # type: ignore
                 **request_kwargs,
             )
         except Exception as e:
@@ -217,7 +268,7 @@ async def ainvoke_stream(self, messages: List[Message]) -> AsyncIterator[Streame
         try:
             async for response in self.get_async_client().chat_stream(
                 model=self.id,
-                messages=self._format_messages(messages),  # type: ignore
+                messages=_format_messages(messages),  # type: ignore
                 **request_kwargs,
             ):
                 yield response

libs/agno/agno/utils/media.py

@@ -3,7 +3,7 @@
 import requests
 
 
-def download_image(url, save_path):
+def download_image(url: str, save_path: str) -> bool:
     """
     Downloads an image from the specified URL and saves it to the given local path.
     Parameters:

libs/agno/pyproject.toml

@@ -75,7 +75,7 @@ postgres = ["psycopg-binary", "psycopg"]
 # Dependencies for Vector databases
 pgvector = ["pgvector"]
 chromadb = ["chromadb"]
-lancedb = ["lancedb", "tantivy"]
+lancedb = ["lancedb==0.20.0", "tantivy"]
 qdrant = ["qdrant-client"]
 cassandra = ["cassio"]
 mongodb = ["pymongo[srv]"]

libs/agno/tests/integration/models/aws/bedrock/test_multimodal.py

@@ -11,11 +11,10 @@ def test_image_input_bytes():
     """
     agent = Agent(model=AwsBedrock(id="amazon.nova-pro-v1:0"), markdown=True, telemetry=False, monitoring=False)
 
-    image_path = Path(__file__).parent.joinpath("../../sample_image.jpg")
+    image_path = Path(__file__).parent.parent.parent.joinpath("sample_image.jpg")
 
     # Read the image file content as bytes
-    with open(image_path, "rb") as img_file:
-        image_bytes = img_file.read()
+    image_bytes = image_path.read_bytes()
 
     response = agent.run(
         "Tell me about this image.",