feat: rename to lobsterx

.github/workflows/docker-image.yaml

@@ -2,12 +2,12 @@ name: Build and Publish Docker Image
 
 on:
   push:
-    tags: ["llamagram@v*.*.*"]
-    branches: [main]
+    # tags: ["lobsterx@v*.*.*"]
+    branches: [master] # avoid publishing for the first time
 
 env:
   REGISTRY: ghcr.io
-  IMAGE_NAME: astrabert/llamagram
+  IMAGE_NAME: astrabert/lobsterx
 
 jobs:
   build-and-publish-docker-image:
@@ -48,7 +48,7 @@ jobs:
         id: build-and-push
         uses: docker/build-push-action@0565240e2d4ab88bba5387d719585280857ece09 # v5.0.0
         with:
-          context: packages/llamagram
+          context: packages/lobsterx
           push: ${{ github.event_name != 'pull_request' }}
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}

.github/workflows/lint.yaml

@@ -23,7 +23,7 @@ jobs:
         shell: bash
         run: make lint-check
 
-  lint-llamagram:
+  lint-lobsterx:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
@@ -37,9 +37,9 @@ jobs:
       - name: Run formatter
         shell: bash
         run: make format-check
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx
 
       - name: Run linter
         shell: bash
         run: make lint-check
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx

.github/workflows/release_llamagram.yaml → .github/workflows/release_lobsterx.yaml

@@ -1,9 +1,9 @@
-name: GitHub Release LlamaGram
+name: GitHub Release LobsterX
 
 on:
   push:
     tags:
-      - "llamagram@v[0-9].[0-9]+.[0-9]+*"
+      - "lobsterx@v[0-9].[0-9]+.[0-9]+*"
 
 jobs:
   release-mcp:
@@ -20,14 +20,14 @@ jobs:
 
       - name: Build
         run: uv build -o dist
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx
 
       - name: Publish to PyPI
         run: uv publish --token ${{ secrets.PYPI_TOKEN }}
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx
 
       - name: Create GitHub Release
         uses: ncipollo/release-action@v1
         with:
-          artifacts: "packages/llamagram/dist/*"
+          artifacts: "packages/lobsterx/dist/*"
           generateReleaseNotes: true

.github/workflows/test.yaml

@@ -23,7 +23,7 @@ jobs:
       - name: Run Tests on Main Package
         run: make test
 
-  testing_pr_llamagram:
+  testing_pr_lobsterx:
     runs-on: ubuntu-latest
     strategy:
       matrix:
@@ -41,4 +41,4 @@ jobs:
 
       - name: Run Tests on Main Package
         run: make test
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx

.github/workflows/typecheck.yaml

@@ -20,7 +20,7 @@ jobs:
       - name: Run ty
         run: make typecheck
 
-  core-typecheck-llamagram:
+  core-typecheck-lobsterx:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
@@ -35,4 +35,4 @@ jobs:
 
       - name: Run ty
         run: make typecheck
-        working-directory: packages/llamagram
+        working-directory: packages/lobsterx

.gitignore

@@ -14,7 +14,7 @@ wheels/
 
 # caches
 *_cache/
-.llamagram/
+.lobsterx/
 # memory jsonl file
 .agent_memory.jsonl
 

CONTRIBUTING.md

@@ -1,4 +1,4 @@
-# Contributing to `workflows-acp` and `llamagram`
+# Contributing to `workflows-acp` and `lobsterx`
 
 Thank you for your interest in contributing to this project! Please review these guidelines before getting started.
 

README.md

@@ -320,11 +320,11 @@ def main() -> None:
     )
 ```
 
-## LlamaGram
+## LobsterX
 
-[LlamaGram](./packages/llamagram) is the [OpenClaw](https://openclaw.ai)-like AI agent (working as a Telegram bot) for document processing based on the `workflows-acp` harness and on [LlamaCloud](https://cloud.llamaindex.ai).
+[LobsterX](./packages/lobsterx) is the [OpenClaw](https://openclaw.ai)-like AI agent (working as a Telegram bot) for document processing based on the `workflows-acp` harness and on [LlamaCloud](https://cloud.llamaindex.ai).
 
-Find more in the [dedicated README](./packages/llamagram/README.md)
+Find more in the [dedicated README](./packages/lobsterx/README.md)
 
 ## License
 

packages/llamagram/Dockerfile → packages/lobsterx/Dockerfile

@@ -16,7 +16,7 @@ USER user
 ENV PATH=/home/user/.local/bin:$PATH
 WORKDIR /home/user/workspace
 
-# Install llamagram
-RUN uv tool install llamagram --prerelease=allow
+# Install lobsterx
+RUN uv tool install lobsterx --prerelease=allow
 
-CMD [ "llamagram", "run" ]
+CMD [ "lobsterx", "run" ]

packages/llamagram/Makefile → packages/lobsterx/Makefile

@@ -26,7 +26,7 @@ format-check:
 
 typecheck:
 	$(info ****************** type checking ******************)
-	uv run ty check src/llamagram/
+	uv run ty check src/lobsterx/
 
 build:
 	$(info ****************** building ******************)

packages/llamagram/README.md → packages/lobsterx/README.md

@@ -1,14 +1,14 @@
-# LlamaGram
+# LobsterX
 
-LlamaGram is an AI agent inspired by [OpenClaw](https://openclaw.ai) (formerly known as MoltBot or ClawdBot), which focuses on document-related tasks.
+LobsterX is an AI agent inspired by [OpenClaw](https://openclaw.ai) (formerly known as MoltBot or ClawdBot), which focuses on document-related tasks.
 
 It runs as a Telegram bot as comes with a CLI interface to set up the necessary environment variables.
 
 ## Prerequisites
 
 - Python (if setting up the bot natively, preferably with `uv`) or Docker (if deploying with Docker)
 - A Telegram Bot Token, in order to connect to Telegram. Follow [this guide](https://core.telegram.org/bots/tutorial) on how to create your Telegram bot with BotFather.
-- A LlamaCloud API key, in order to give LlamaGram document-processing capabilities. Sign up on LlamaCloud [here](https://cloud.llamaindex.ai/signup).
+- A LlamaCloud API key, in order to give LobsterX document-processing capabilities. Sign up on LlamaCloud [here](https://cloud.llamaindex.ai/signup).
 - An API key for Google, OpenAI or Anthropic (you can choose one among the three or swap between different providers)
 
 ## Installation
@@ -17,71 +17,71 @@ Install the bot natively:
 
 ```bash
 # uv (recommended)
-uv tool install llamagram --prerelease=allow
+uv tool install lobsterx --prerelease=allow
 # pip
-pip install llamagram
+pip install lobsterx
 ```
 
 Pull the docker image (only works for AMD64-compatible platforms):
 
 ```bash
-docker pull ghcr.io/astrabert/llamagram:main
+docker pull ghcr.io/astrabert/lobsterx:main
 ```
 
 ## Setup
 
-Through environment variables, you can customize the setup of LlamaGram:
+Through environment variables, you can customize the setup of LobsterX:
 
-- `LLAMAGRAM_LLM_PROVIDER`: LLM provider (choose between `google`, `anthropic` and `openai`). Default is `openai`
-- `LLAMAGRAM_LLM_MODEL`: LLM model (choose among [available models](../../README.md#available-llm-models)). Default is `gpt-4.1`
+- `LOBSTERX_LLM_PROVIDER`: LLM provider (choose between `google`, `anthropic` and `openai`). Default is `openai`
+- `LOBSTERX_LLM_MODEL`: LLM model (choose among [available models](../../README.md#available-llm-models)). Default is `gpt-4.1`
 
 You then need to set three required env variables:
 
-- `LLAMAGRAM_LLM_API_KEY`: API key for the LLM (you can also use `OPENAI_API_KEY`, `GOOGLE_API_KEY` or `ANTHROPIC_API_KEY`, depending on the provider).
+- `LOBSTERX_LLM_API_KEY`: API key for the LLM (you can also use `OPENAI_API_KEY`, `GOOGLE_API_KEY` or `ANTHROPIC_API_KEY`, depending on the provider).
 - `TELEGRAM_BOT_TOKEN`: token for the Telegram bot
 - `LLAMA_CLOUD_API_KEY`: API key for LlamaCloud
 
-You can use the setup wizard to configure LlamaGram interactively on the terminal:
+You can use the setup wizard to configure LobsterX interactively on the terminal:
 
 ```bash
-llamagram setup --interactive
+lobsterx setup --interactive
 ```
 
 Or pass options from CLI:
 
 ```bash
-llamagram setup --provider google \
+lobsterx setup --provider google \
     --model gemini-3-flash-preview \
     --api-key $GOOGLE_API_KEY \
     --llama-cloud-key $LLAMA_CLOUD_API_KEY \
     --telegram-token $TELEGRAM_BOT_TOKEN
 ```
 
-This will create a `.env` file with the necessary variables, which will be loaded by LlamaGram at runtime (make sure not to share it with anyone).
+This will create a `.env` file with the necessary variables, which will be loaded by LobsterX at runtime (make sure not to share it with anyone).
 
 ## Run
 
-Run LlamaGram as a CLI app:
+Run LobsterX as a CLI app:
 
 ```bash
-llamagram run 
+lobsterx run 
 ```
 
 You can set the `--log-level` option, if you wish to have more or less logging.
 
-Run LlamaGram in a Docker container referencing a `.env` file:
+Run LobsterX in a Docker container referencing a `.env` file:
 
 ```bash
-docker run ghcr.io/astrabert/llamagram:main --env-file=".env"
+docker run ghcr.io/astrabert/lobsterx:main --env-file=".env"
 ```
 
 Or, setting env varaibles directly (not recommended):
 
 ```bash
-docker run ghcr.io/astrabert/llamagram:main \
-    --env="LLAMAGRAM_LLM_PROVIDER=openai" \
-    --env="LLAMAGRAM_LLM_MODEL=gpt-4.1"\
-    --env="LLAMAGRAM_LLM_API_KEY=sk-xxx" \
+docker run ghcr.io/astrabert/lobsterx:main \
+    --env="LOBSTERX_LLM_PROVIDER=openai" \
+    --env="LOBSTERX_LLM_MODEL=gpt-4.1"\
+    --env="LOBSTERX_LLM_API_KEY=sk-xxx" \
     --env="LLAMA_CLOUD_API_KEY=llx-xxx" \
     --env="TELEGRAM_BOT_TOKEN=tok-xxx"
 ```
@@ -95,17 +95,17 @@ When on Telegram, you can perform two actions:
 
 > _With `/start` command, you will have a welcome message explaining how to use the bot_
 
-## How LlamaGram Works
+## How LobsterX Works
 
-LlamaGram is a generalist AI agent based on three main principles:
+LobsterX is a generalist AI agent based on three main principles:
 
-- [LlamaIndex Agent Workflows](https://github.com/run-llama/workflows-py): a powerful workflow engine that allows event-driven, stepwise execution of specific tasks and functions. LlamaGram uses a cyclic workflow to go through thinking, tool-calling and observing repeatedly until it produces its final output.
+- [LlamaIndex Agent Workflows](https://github.com/run-llama/workflows-py): a powerful workflow engine that allows event-driven, stepwise execution of specific tasks and functions. LobsterX uses a cyclic workflow to go through thinking, tool-calling and observing repeatedly until it produces its final output.
 - Structured outputs: the LLM underlying the agent is forced to produce JSON outputs that comply with certain schemas (a tool call, a thought, an observation...): outputs are produced informed by the previous chat history, and based on context about available tools and specific tasks the agent has to perform.
 - Security by design: the agent does not have access to your real filesystem, but it does have access to a virtualized copy of it provided through [AgentFS](https://github.com/tursodatabase/agentfs). PDFs sent over Telegram are also not downloaded into your real filesystem, but written within AgentFS. Files such as `.env`s or other popular credential files (`.npmrc`, `.pypirc`, `.netrc`) are excluded from the virtual filesystem, and thus unaccessible to the agent. The agent cannot use bash commands (it has access to filesystem-based tools like read/write/edit/grep/glob for AgentFS) to avoid it being able to perform destructive or vulnerable operations.
 
-Here is what happens when you send a prompt to LlamaGram:
+Here is what happens when you send a prompt to LobsterX:
 
-![Flowchart LlamaGram](./assets/flowchart_llamagram.png)
+![Flowchart LobsterX](./assets/flowchart_lobsterx.png)
 
 Along with the final response, the agent will also send you a report of everything it did during its session as a markdown file (namedd `session-<random-id>-report.md`).
 

packages/llamagram/pyproject.toml → packages/lobsterx/pyproject.toml

@@ -3,7 +3,7 @@ requires = ["uv_build>=0.9.10,<0.10.0"]
 build-backend = "uv_build"
 
 [project]
-name = "llamagram"
+name = "lobsterx"
 version = "0.1.0-beta"
 description = "Background AI assistant working as a Telegram bot, built specifically for document-related use cases"
 readme = "README.md"
@@ -31,4 +31,4 @@ dev = [
 ]
 
 [project.scripts]
-llamagram = "llamagram.cli:app"
+lobsterx = "lobsterx.cli:app"

packages/llamagram/src/llamagram/cli.py → packages/lobsterx/src/lobsterx/cli.py

@@ -71,12 +71,12 @@ def setup_wizard(
 ) -> None:
     if interactive:
         llm_provider = Prompt().ask(
-            "LLM Provider for LlamaGram",
+            "LLM Provider for LobsterX",
             choices=["openai", "google", "anthropic"],
             show_choices=True,
         )  # type: ignore
         llm_model = Prompt().ask(
-            "LLM Model for LlamaGram",
+            "LLM Model for LobsterX",
             choices=[
                 m
                 for m in list(AVAILABLE_MODELS.keys())
@@ -102,8 +102,8 @@ def setup_wizard(
     dot_env = Path(".env")
     if not dot_env.exists():
         dot_env.touch()
-    set_key(".env", key_to_set="LLAMAGRAM_LLM_PROVIDER", value_to_set=llm_provider)
-    set_key(".env", key_to_set="LLAMAGRAM_LLM_MODEL", value_to_set=llm_model)
-    set_key(".env", key_to_set="LLAMAGRAM_LLM_API_KEY", value_to_set=api_key)
+    set_key(".env", key_to_set="LOBSTERX_LLM_PROVIDER", value_to_set=llm_provider)
+    set_key(".env", key_to_set="LOBSTERX_LLM_MODEL", value_to_set=llm_model)
+    set_key(".env", key_to_set="LOBSTERX_LLM_API_KEY", value_to_set=api_key)
     set_key(".env", key_to_set="LLAMA_CLOUD_API_KEY", value_to_set=llama_cloud_api_key)
     set_key(".env", key_to_set="TELEGRAM_BOT_TOKEN", value_to_set=telegram_token)

packages/llamagram/src/llamagram/tools/caching.py → packages/lobsterx/src/lobsterx/tools/caching.py

@@ -8,7 +8,7 @@
 
 class FileContentCache:
     def __init__(self) -> None:
-        self._cache = DiskCache(directory=".llamagram/cache")
+        self._cache = DiskCache(directory=".lobsterx/cache")
         self._ttl: float = 60 * 60 * 24  # one day
 
     async def set(

packages/llamagram/src/llamagram/utils.py → packages/lobsterx/src/lobsterx/utils.py

@@ -36,7 +36,7 @@
 
 
 def start(user: User | None) -> str:
-    greetings = "Hello there, Llama Enthusiast!"
+    greetings = "Hello there, Lobster Enthusiast!"
     if user is not None and user.username is not None:
         username = user.username
         if not username.startswith("@"):
@@ -45,7 +45,7 @@ def start(user: User | None) -> str:
 
     return f"""
 {greetings}
-I am LlamaGram, your personal assistant for whatever concerns documents.
+I am LobsterX, your personal assistant for whatever concerns documents.
 I can navigate the filesystem from the directory where you deployed me, and perform operations based on your text messages.
 You can also upload PDF documents from this chat, that I will download and will be able to use afterwards.
 With this being said, please, ask any questions you like!
@@ -55,13 +55,13 @@ def start(user: User | None) -> str:
 @functools.lru_cache(maxsize=1)
 def get_llm() -> LLMWrapper:
     load_dotenv()
-    llm_provider = os.getenv("LLAMAGRAM_LLM_PROVIDER", "openai")
+    llm_provider = os.getenv("LOBSTERX_LLM_PROVIDER", "openai")
     if llm_provider not in ("openai", "google", "anthropic"):
         raise ValueError(f"Unsupported model provider: {llm_provider}")
-    model = os.getenv("LLAMAGRAM_LLM_MODEL", DEFAULT_MODEL[llm_provider])
+    model = os.getenv("LOBSTERX_LLM_MODEL", DEFAULT_MODEL[llm_provider])
     if AVAILABLE_MODELS.get(model) != llm_provider:
         raise ValueError(f"Unsupported model for provider {llm_provider}: {model}")
-    api_key = os.getenv("LLAMAGRAM_LLM_API_KEY") or os.getenv(
+    api_key = os.getenv("LOBSTERX_LLM_API_KEY") or os.getenv(
         f"{llm_provider.upper()}_API_KEY"
     )
     if api_key is not None:

packages/llamagram/tests/test_caching.py → packages/lobsterx/tests/test_caching.py

@@ -2,15 +2,14 @@
 from pathlib import Path
 
 import pytest
-
-from llamagram.tools.caching import FileContentCache
+from lobsterx.tools.caching import FileContentCache
 
 
 def test_cache_setup(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.chdir(tmp_path)
     cache = FileContentCache()
     assert cache._ttl == 60 * 60 * 24
-    assert (tmp_path / ".llamagram" / "cache").is_dir()
+    assert (tmp_path / ".lobsterx" / "cache").is_dir()
 
 
 @pytest.mark.asyncio