Updates for environment file proper use with docker command

.env.example

@@ -1,25 +1,36 @@
 # This is an example .env file for the Trading Agent project.
 # Copy this file to .env and fill in your API keys and environment configurations.
+"NOTE: When using for `docker` command do not use quotes around the values, otherwiser environment variables will not be set."
 
 # API Keys
-OPENAI_API_KEY="<your-openai-key>" # Replace with your OpenAI API key, for OpenAI, Ollama or other OpenAI-compatible models
-FINNHUB_API_KEY="<your_finnhub_api_key_here>" # Replace with your Finnhub API key
+# Set your OpenAI API key, for OpenAI, Ollama or other OpenAI-compatible models
+OPENAI_API_KEY=<your-openai-key> 
+# Set your  Finnhub API key
+FINNHUB_API_KEY=<your_finnhub_api_key_here>
 
 #LLM Configuration for OpenAI
-LLM_PROVIDER="openai" # Set to one of: openai, anthropic, google, openrouter or ollama,
-LLM_BACKEND_URL="https://api.openai.com/v1" # API URL
+# Set LLM_Provider to one of: openai, anthropic, google, openrouter or ollama,
+LLM_PROVIDER=openai 
+# Set the API URL for the LLM backend
+LLM_BACKEND_URL=https://api.openai.com/v1
 
 
 # Uncomment for LLM Configuration for loacl ollama
-#LLM_PROVIDER="ollama" # Set to one of: openai, anthropic, google, openrouter or ollama,
-#LLM_BACKEND_URL="http://localhost:11434/v1" # For Ollama running in the same container, /v1 added for OpenAI compatibility
-#LLM_DEEP_THINK_MODEL="qwen3:0.6b"  # name of the Deep think model for the main
-#LLM_QUICK_THINK_MODEL="qwen3:0.6b" # name of the quick think model for the main
-#LLM_EMBEDDING_MODEL="nomic-embed-text" # name of the embedding model
+#LLM_PROVIDER=ollama
+## For Ollama running in the same container, /v1 added for OpenAI compatibility
+#LLM_BACKEND_URL=http://localhost:11434/v1
+# Set name of the Deep think model for the main
+#LLM_DEEP_THINK_MODEL=qwen3:0.6b
+## Setname of the quick think model for the main
+#LLM_QUICK_THINK_MODEL=qwen3:0.6b
+# Set the name of the embedding model
+#LLM_EMBEDDING_MODEL=nomic-embed-text
 
 # Agent Configuration
-MAX_DEBATE_ROUNDS="1" # Maximum number of debate rounds for the agent to engage in choose from 1, 3, 5
-ONLINE_TOOLS="True" # Set to False if you want to disable tools that access the internet
+# Maximum number of debate rounds for the agent to engage in choose from 1, 3, 5
+MAX_DEBATE_ROUNDS=1
+# Set to False if you want to disable tools that access the internet
+ONLINE_TOOLS=True
 
 
 

Docker-readme.md

@@ -11,13 +11,16 @@ This project uses a `.env` file to manage environment-specific configurations fo
     cp .env.example .env
     ```
 2.  **Customize your `.env` file:**
-    Open the `.env` file in a text editor and modify the variables as needed for your local setup. For example, you might want to change LLM models or API keys (if applicable in the future).
+    Open the `.env` file in a text editor and modify the variables as needed for your local setup. For example, you might want to change LLM models or API keys. 
 
 ### How it Works with Docker Compose
 When you run `docker-compose up` or `docker-compose run`, Docker Compose automatically looks for a `.env` file in the project root directory (where `docker-compose.yml` is located) and loads the environment variables defined in it. These variables are then passed into the container environment for the `app` service.
 
 The `.env` file itself is ignored by Git (as specified in `.gitignore`), so your local configurations will not be committed to the repository.
 
+For streamlined experience, it is recommended to use docker compose as it simplifies experience eg handles mounting of directories for caching. Skip to [Docker Compose](#Using Docker Compose) section for this.
+
+
 ## Running with Docker
 
 This project supports running within a Docker container, which ensures a consistent environment for development and testing. 
@@ -34,27 +37,49 @@ docker build -t tradingagents .
 ### Test local ollama setup
 To test ollama connectivity and local model:
 ```bash
-docker run --rm \
+docker run -it --env-file .env tradingagents python test_ollama_connection.py
+```
+for picking environment settings from .env file. You can pass values directly using: 
+```bash
+docker run -it \
   -e LLM_PROVIDER="ollama" \
   -e LLM_BACKEND_URL="http://localhost:11434/v1" \
   -e LLM_DEEP_THINK_MODEL="qwen3:0.6b" \
-  -e LLM_QUICK_THINK_MODEL="qwen3:0.6b" \
-  -e MAX_DEBATE_ROUNDS="1" \
-  -e ONLINE_TOOLS="False" \
+  -e LLM_EMBEDDING_MODEL="nomic-embed-text"\ 
   tradingagents \
   python test_ollama_connection.py
 ```
-**Note on Ollama for Local Docker:**
-The `LLM_BACKEND_URL` is set to `http://localhost:11434/v1`. This assumes you have Ollama running on your host machine and accessible at port 11434. '/v1' is added to url at the end for OpenAI api compatibility. 
+For prevent re-downloading of Ollama models, mount folder from your host and run as
+```bash
+docker run -it \
+  -e LLM_PROVIDER="ollama" \
+  -e LLM_BACKEND_URL="http://localhost:11434/v1" \
+  -e LLM_DEEP_THINK_MODEL="qwen3:0.6b" \
+  -e LLM_EMBEDDING_MODEL="nomic-embed-text"\ 
+  -v ./ollama_cache:/app/.ollma \
+  tradingagents \
+  python test_ollama_connection.py
+```
+
+**Notes on Ollama for Local Docker:**
+When `LLM_PROVIDER` is set to `ollama` the ollama server is automatically started in the docker conatiner. The `LLM_BACKEND_URL` is set to `http://localhost:11434/v1`. This assumes you have Ollama running on your host machine and accessible at port 11434. '/v1' is added to url at the end for OpenAI api compatibility. 
 
 
 ### Run the Main Application
 To run the `main.py` script:
 ```bash
-docker run --rm \
+docker run -it --env-file .env tradingagents python -m main
+```
+or 
+```bash
   -e LLM_PROVIDER="ollama" \
   -e LLM_BACKEND_URL="http://localhost:11434/v1" \
-  # Add other necessary environment variables for main.py
+  -e LLM_DEEP_THINK_MODEL="qwen3:0.6b" \
+  -e LLM_QUICK_THINK_MODEL="qwen3:0.6b" \
+  -e LLM_EMBEDDING_MODEL="nomic-embed-text"\ 
+  -e MAX_DEBATE_ROUNDS="1" \
+  -e ONLINE_TOOLS="False" \
+  -v ./ollama_cache:/app/.ollama \
   tradingagents python -m main
 ```
 Adjust environment variables as needed for your local setup.
@@ -62,17 +87,21 @@ Adjust environment variables as needed for your local setup.
 ### Run the TradingAgents CLI
 To run the cli interface (default in the container)
 ```bash
-docker run --it \
+docker run -it --env-file .env tradingagents 
+```
+or 
+or 
+```bash
   -e LLM_PROVIDER="ollama" \
   -e LLM_BACKEND_URL="http://localhost:11434/v1" \
-  # Add other necessary environment variables for main.py
+  -v ./ollama_cache:/app/.ollma \
   tradingagents python -m cli.main
 ```
 Adjust environment variables as needed for your local setup.
 
 ### Using Docker Compose
 
-For a more streamlined local development experience, you can use Docker Compose. The `docker-compose.yml` file in the project root is configured to use the existing `Dockerfile`.
+For a more streamlined local development experience, it is recommended to use Docker Compose. The `docker-compose.yml` file in the project root is configured to use the existing `Dockerfile`.
 
 **Build and Run Tests:**
 
@@ -105,10 +134,14 @@ docker-compose run --it app python -m cli.main
 ```
 
 **Environment Variables:**
-The necessary environment variables (like `LLM_PROVIDER`, `LLM_BACKEND_URL`, model names, etc.) are pre-configured in the `docker-compose.yml` for the `app` service. Ollama is started by the entrypoint script within the same container, so `LLM_BACKEND_URL` is set to `http://localhost:11434/v1`.
+The necessary environment variables (like `LLM_PROVIDER`, `LLM_BACKEND_URL`, model names, etc.) are configured in the `docker-compose.yml` for the `app` service. Ollama is started by the entrypoint script within the same container when LLM_PROVIDER is set to `ollama`, and `LLM_BACKEND_URL` is set to `http://localhost:11434/v1`.
+
+When using enviroment file for `docker` command, please do not put extra quotes around the values, or any extra comments at the end otherwise docker will not pick the values. 
 
 **Live Code Reloading:**
 The current directory is mounted as a volume into the container at `/app`. This means changes you make to your local code will be reflected inside the container, which is useful for development. You might need to rebuild the image with `docker-compose build` or `docker-compose up --build` if you change dependencies in `requirements.txt` or modify the `Dockerfile` itself.
 
 **Ollama Model Caching:**
 To prevent re-downloading Ollama models, `docker-compose.yml` now mounts `./.ollama` on your host to `/app/.ollama` in the container. Models pulled by Ollama will be stored in `./.ollama/models` locally and persist across runs. Ensure this directory is in your `.gitignore`. If Docker has permission issues creating this directory, you might need to create it manually (`mkdir .ollama`).
+
+

Dockerfile

@@ -74,9 +74,10 @@ RUN chown -R appuser:appuser /app
 USER appuser
 
 # Set the entrypoint
-ENTRYPOINT ["docker-entrypoint.sh"]
+ENTRYPOINT ["/bin/sh", "-c", "if [ \"$LLM_PROVIDER\" = \"ollama\" ]; then ./docker-entrypoint.sh; else exec \"$@\"; fi", "--"]
+
 
 # Default command (can be overridden, e.g., by pytest command in CI)
-CMD ["python", "main.py"]
+CMD ["python", "-m", "cli.main"]
 
 EXPOSE 11434

docker-compose.yml

@@ -12,6 +12,7 @@ services:
     #  - LLM_BACKEND_URL=http://localhost:11434/v1
     #  - LLM_DEEP_THINK_MODEL=qwen3:0.6b
     #  - LLM_QUICK_THINK_MODEL=qwen3:0.6b
+    #  - LLM_EMBEDDING_MODEL=nomic-embed-text
     #  - MAX_DEBATE_ROUNDS=1
     #  - ONLINE_TOOLS=False
     # The default command in the Dockerfile is `python main.py`.