summarize-topic: Add a tool to summarize topic.

Author: amanagr

zulip/integrations/litelllm/README.md

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+# Summarize topic
+
+Generate a short summary of the last 100 messages in the provided topic URL.
+
+
+### API Keys
+
+For testing you need access token from https://huggingface.co/settings/tokens (or set the correct env variable with the access token if using a different model)
+
+In `~/.zuliprc` add a section named `LITELLM_API_KEYS` and set the api key for the model you are trying to use.
+For example:
+```
+[LITELLM_API_KEYS]
+HUGGINGFACE_API_KEY=YOUR_API_KEY
+```
+
+### Setup
+
+```bash
+$ pip install -r zulip/integrations/litelllm/requirements.txt
+```
+
+Just run `zulip/integrations/litelllm/summarize-topic` to generate sample summary.
+
+```bash
+$ zulip/integrations/litelllm/summarize-topic --help
+usage: summarize-topic [-h] [--url URL] [--model MODEL]
+
+options:
+  -h, --help     show this help message and exit
+  --url URL      The URL to fetch content from
+  --model MODEL  The model name to use for summarization
+```

zulip/integrations/litelllm/requirements.txt

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+zulip
+litellm

zulip/integrations/litelllm/summarize-topic

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+#!/usr/bin/env python3
+
+import argparse
+import os
+import sys
+import urllib.parse
+from configparser import ConfigParser
+
+from litellm import completion
+
+import zulip
+
+config_file = zulip.get_default_config_filename()
+if not config_file:
+    print("Could not find the Zulip configuration file. Please read the provided README.")
+    sys.exit()
+
+client = zulip.Client(config_file=config_file)
+
+config = ConfigParser()
+# Make config parser case sensitive otherwise API keys will be lowercased
+# which is not supported by litellm.
+# https://docs.python.org/3/library/configparser.html#configparser.ConfigParser.optionxform
+config.optionxform = str  # type: ignore[assignment, method-assign]
+
+with open(config_file) as f:
+    config.read_file(f, config_file)
+
+# Set all the keys in `LITELLM_API_KEYS` as environment variables.
+for key in config["LITELLM_API_KEYS"]:
+    print("Setting key:", key)
+    os.environ[key] = config["LITELLM_API_KEYS"][key]
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--url",
+        type=str,
+        help="The URL to fetch content from",
+        default="https://chat.zulip.org/#narrow/stream/101-design/topic/more.20user.20indicators",
+    )
+    parser.add_argument(
+        "--model",
+        type=str,
+        help="The model name to use for summarization",
+        default="huggingface/meta-llama/Meta-Llama-3-8B-Instruct",
+    )
+    args = parser.parse_args()
+
+    url = args.url
+    model = args.model
+
+    base_url, narrow_hash = url.split("#")
+    narrow_hash_terms = narrow_hash.split("/")
+    channel = narrow_hash_terms[2].split("-")[1]
+    topic = narrow_hash_terms[4]
+    channel = urllib.parse.unquote(channel.replace(".", "%"))
+    topic = urllib.parse.unquote(topic.replace(".", "%"))
+
+    narrow = [
+        {"operator": "channel", "operand": channel},
+        {"operator": "topic", "operand": topic},
+    ]
+
+    request = {
+        "anchor": "newest",
+        "num_before": 100,
+        "num_after": 0,
+        "narrow": narrow,
+        "apply_markdown": False,
+    }
+    result = client.get_messages(request)
+    messages = result["messages"]
+
+    formatted_messages = [
+        {"content": f"{message['sender_full_name']}: {message['content']}", "role": "user"}
+        for message in messages
+    ]
+
+    # Provide a instruction if using an `Instruct` model.
+    # There is a 100 token output limit by hugging face.
+    if "Instruct" in model:
+        formatted_messages.append(
+            {"content": "Summarize the above content within 90 words.", "role": "user"}
+        )
+
+    # Send formatted messages to the LLM model for summarization
+    response = completion(
+        model=model,
+        messages=formatted_messages,
+    )
+
+    print("Server response:\n", response)
+    print("\n\nGenerated summary for URL:", url)
+    print("Summary:")
+    print(response["choices"][0]["message"]["content"])