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+---
+layout: integration
+name: Comet API
+description: Use the Comet API for text generation models.
+authors:
+    - name: deepset 
+      socials:
+        github: deepset-ai
+        twitter: deepset_ai
+        linkedin: https://www.linkedin.com/company/deepset-ai/
+    - name: Gary Badwal
+      socials:
+        website: garybadwal.com
+        github: garybadwal
+        twitter: garybadwal_
+        linkedin: https://www.linkedin.com/in/garybadwal/
+pypi: https://pypi.org/project/cometapi-haystack
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/cometapi
+type: Model Provider
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/cometapi.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+- [License](#license)
+
+## Overview
+
+`CometAPIChatGenerator` lets you call any LLMs available on [Comet API](https://cometapi.com), including:
+
+- OpenAI variants such as `gpt-5`
+- Anthropic’s `claude-4.5-haiku`
+- Community-hosted open-source models (Llama 2, Mixtral, etc.)
+
+For more information on models available via the Comet API API, see [the Comet API docs](https://www.cometapi.com/model/).
+
+
+In order to follow along with this guide, you'll need a Comet API key. Add it as an environment variable, `COMET_API_KEY`.
+
+## Installation
+
+```bash
+pip install cometapi-haystack
+```
+
+## Usage
+You can use [CometAPIChatGenerator](https://docs.haystack.deepset.ai/docs/cometapichatgenerator) as standalone, within a [pipeline](https://docs.haystack.deepset.ai/docs/pipelines) or with the [Agent component](https://docs.haystack.deepset.ai/docs/agent).
+
+Here's an example of using it as a standalone component:
+
+```python
+import os
+from haystack.dataclasses import ChatMessage
+from haystack_integrations.components.generators.cometapi import CometAPIChatGenerator
+
+os.environ["COMET_API_KEY"] = "YOUR_COMET_API_KEY"
+
+client = CometAPIChatGenerator() # defaults to gpt-4o-mini
+response = client.run(
+    [ChatMessage.from_user("What are Agentic Pipelines? Be brief.")]
+)
+print(response["replies"])
+
+```
+```bash
+{'replies': [ChatMessage(_role=<ChatRole.ASSISTANT: 'assistant'>, _content=[TextContent(text='Agentic Pipelines refer to processes or frameworks that enable individuals or groups to take proactive control over their learning, decision-making, or actions in a systematic way. They emphasize agency, allowing participants to navigate pathways that reflect their interests, goals, and capabilities, often leveraging technology and resources to facilitate this empowerment. In various contexts, such as education or organizational development, Agentic Pipelines can foster greater engagement, autonomy, and outcomes.')], _name=None, _meta={'model': 'gpt-4o-mini-2024-07-18', 'index': 0, 'finish_reason': 'stop', 'usage': {'completion_tokens': 87, 'prompt_tokens': 17, 'total_tokens': 104, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}})]}
+```
+`CometAPIChatGenerator` also support streaming responses if you pass a streaming callback:
+
+```python
+import os
+from haystack.dataclasses import ChatMessage
+from haystack_integrations.components.generators.cometapi import CometAPIChatGenerator
+
+os.environ["COMET_API_KEY"] = "YOUR_COMET_API_KEY"
+
+def show(chunk):                              # simple streaming callback
+    print(chunk.content, end="", flush=True)
+
+client = CometAPIChatGenerator(
+    model="grok-3-mini",
+    streaming_callback=show,
+)
+
+response = client.run([ChatMessage.from_user("Summarize RAG in two lines.")])
+
+print(response)
+
+```
+
+### License
+
+`cometapi-haystack` is distributed under the terms of the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license.
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