Update GPU performance tuning and documentation for context length

- Enhanced the `OllamaTune` class to include a new `context_length` attribute, improving the configuration for different GPU tiers.
- Updated performance tuning logic to set appropriate context lengths for low, mid, high, and ultra tiers, ensuring optimal resource allocation.
- Modified installation scripts to reflect the new context length settings, enhancing the installation process for Ollama.
- Revised documentation to include context length details in the GPU performance table, providing clearer guidance for users.
- Added tests to validate the correct context length settings in various scenarios, ensuring robustness in performance tuning.

tests/test_perf_tiers.py

@@ -41,6 +41,8 @@ def test_ollama_high_reserves_vram_for_swarm():
     env = "\n".join(ollama_env_lines(tune))
     assert "OLLAMA_FLASH_ATTENTION=1" in env
     assert "OLLAMA_GPU_OVERHEAD=" in env
+    assert "OLLAMA_CONTEXT_LENGTH=16384" in env
+    assert tune.context_length == 16384
 
 
 def test_swarm_sage_on_ampere_mid():
@@ -68,3 +70,16 @@ def test_swarm_no_sage_on_low():
     st = swarm_tune_for(info)
     assert not st.use_sage_attention
     assert st.comfy_extra_args == ""
+
+
+def test_ollama_mid_4090_context_16k():
+    info = GpuInfo(
+        name="NVIDIA GeForce RTX 4090",
+        vram_mib=24564,
+        compute_cap="8.9",
+        uuid="GPU-4",
+        tier="mid",
+    )
+    tune = ollama_tune_for(info)
+    assert tune.context_length == 16384
+    assert "OLLAMA_CONTEXT_LENGTH=16384" in "\n".join(ollama_env_lines(tune))